The Pennsylvania State University

The Graduate School

Department of Crop and Soil Sciences

RESPONSES OF AMMONIA-OXIDIZING BACTERIA AND ARCHAEA TO SOIL

MULCHING AND INTERACTIONS WITH SOIL TEMPERATURE AND

MOISTURE REGIMES

A Dissertation in

Soil Science and Biogeochemistry

by

Maina Cristina Mártir-Torres

2010 Maina Cristina Mártir-Torres

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

August 2010

ii

The dissertation of Maina Cristina Mártir-Torres was reviewed and approved* by the following:

Mary Ann Bruns

Associate Professor of Soil Microbiology

Dissertation Advisor

Chair of Committee

Carmen E. Martínez

Assistant Professor of Soil Science

David R. Huff

Associate Professor of Turfgrass Breeding and Genetics

John M. Regan

Associate Professor of Environmental Engineering

Curtis J. Dell

Soil Scientist and Adjunct Professor of Soil Science

John E. Watson

Professor of Crop and Soil Sciences

Graduate Program Head for the Department of Crop and Soil Sciences

*Signatures are on file in the Graduate School

iii

Abstract

Urban areas are increasing worldwide, but little is known about the effects of

urbanization on soil microbial communities and the biogeochemical cycles they mediate.

Urban soils surrounding residences and commercial structures are commonly landscaped

by removing native vegetation and covering the soil with mulch. The most widespread

mulching materials are bark and gravel, used to exclude undesired vegetation and

promote landscaped plant growth. Mulching involves a high degree of soil disturbance

and has strong potential for altering soil nitrogen (N) transformations. Nitrification, the

microbially mediated oxidation of exchangeable ammonium to mobile nitrate, is arguably

the most critical N transformation process occurring in soils because it has such a

significant effect on N species mobility. Soil microorganisms responsible for nitrification

are also expected to be affected by mulching. The ammonia oxidizers are an especially

important group of nitrifiers because they carry out the first and rate-limiting step of

nitrification. Two distinctive groups of ammonia-oxidizing prokaryotes (AOP) co-exist in

soils: ammonia-oxidizing archaea (AOA) and bacteria (AOB). For this dissertation, three

studies were conducted to investigate the effects of mulches on AOP abundance and

diversity: 1) an observational study in which AOA diversity and AOP abundance were

determined in soils from mulched and unmown experimental plots; 2) a controlled

greenhouse study in which the abundance of AOP, potential nitrification and other soil

variables were measured over time in mulched, grass-sown, and fallow soils at two

temperatures; and 3) a microcosm study of whole soils and clay/silt fractions comparing

abundances of AOB, AOA, and a rare lineage of AOA in the presence and absence of

iv

added ammonium. Diversity of AOA was determined after generating clone libraries of

genes encoding ammonia monooxygenase subunit A (amoA), while abundance of AOP

was determined using quantitative PCR. In the first study, AOA community structure in

gravel-mulched soils was significantly different from that in the unmowed ―parent‖ soil,

and AOA abundance was lower under bark mulch than under all other treatments. The

abundance of AOB was similar in all treatments. In the second study, soil cover and

temperature significantly affected the abundance of AOP over time. At both

temperatures (18 and 28°C) AOA abundance was greater than AOB in all treatments.

Whereas AOA abundance declined in all soils, AOB increased in mulched soils at 18˚C

while remaining similar in fallow and grass-sown soils. Due to overall lower abundance

of AOB relative to AOA, transcriptional activity of AOB was not detectable, compared to

AOA transcript levels, which were higher at 18˚C than at 28˚C. Further, a correlation

was found between AOA abundance and potential nitrification at 18˚C. In study 3,

incubation of whole soils and silt/clay fractions resulted in the enrichment of a lineage of

AOA sequences that had not been detected in previous clone libraries. Abundance of

these sequences, which were more closely related to 1.1a crenarchaea than to the

commonly recovered 1.1b and 1.3 sequences representative of soils, increased during

incubation as pH decreased. These studies demonstrate different responses by AOA and

AOB to mulching in urban environments and increase our knowledge of the

environmental factors influencing their abundance and activity.

v

TABLE OF CONTENTS

List of Figures ........................................................................................................................... vii

List of Tables .............................................................................................................................. ix

Acknowledgements ..................................................................................................................... x

Chapter 1 Introduction ........................................................................................................... 1

The role and nature of ammonia oxidizers ............................................................................. 1

Urbanization, landscaping practices, and the soil habitat ...................................................... 6

Thesis objectives .................................................................................................................. 10

Thesis structure .................................................................................................................... 11

References ............................................................................................................................ 12

Chapter 2 Molecular Analysis of Ammonia Oxidizer Communities in Vegetated

and Mulched Soils………………… ......................................................................................... 18

Abstract ................................................................................................................................ 18

Introduction .......................................................................................................................... 19

Methods ................................................................................................................................ 22

Results .................................................................................................................................. 29

Discussion ............................................................................................................................ 33

Acknowledgments ................................................................................................................ 37

References ............................................................................................................................ 38

Chapter 3 Responses of archaeal and bacterial ammonia oxidizers in mulched and

vegetated soils at different temperatures ................................................................................... 51

Abstract ................................................................................................................................ 51

Introduction .......................................................................................................................... 52

Methods ................................................................................................................................ 55

Results .................................................................................................................................. 60

Discussion ............................................................................................................................ 63

vi

Acknowledgements .............................................................................................................. 69

References ............................................................................................................................ 69

Chapter 4 Tracking the abundance of a groundwater-like ammonia oxidizing

archaeon in soil microcosms ..................................................................................................... 79

Abstract ................................................................................................................................ 79

Introduction .......................................................................................................................... 80

Methods ................................................................................................................................ 83

Results and Discussion ......................................................................................................... 88

Conclusion ............................................................................................................................ 95

Acknowledgements .............................................................................................................. 95

References ............................................................................................................................ 96

Chapter 5 General Conclusions ......................................................................................... 111

Appendix A Layout of experimental plots at urbanized field site in

Rock Springs, PA .................................................................................................................... 114

Appendix B Comparison of archaeal amoA gene copy numbers per gram soil

obtained using two cell lysis procedures ................................................................................. 115

Appendix C Archaeal amoA sequence alignment used to design primers

and the Taq Man probe used for quantitative PCR ................................................................. 116

Appendix D Calculations used to create a standard curve for bacterial

amoA quantification ................................................................................................................ 117

Appendix E ANOVA tables for Repeated Measures Analysis used for

the analysis of AOP and soil variables evaluated in Chapter 3 ............................................... 118

vii

List of Figures

1-1 The terrestrial N

cycle……………………………………………………………………….…….2

1-2 Reactions and enzymes involved in nitrification…………………….………….3

2-1 Neighbor Joining phylogenetic tree and distribution of crenarchaeal amoA

sequences representing each of the 31 OTUs obtained at 94% genetic

similarity.............................................................................................................44

2-2 Expected (A) and estimated (B) number of OTUs for each urbanized soil

treatment as a function of amino acid genetic distance…………………….….45

2-3 Number of synonymous (gray) or non-synonymous (black) substitutions per

codon site estimated using HyPhy in MEGA5 and sequences representing

each of the 31 OTUs found at 94% DNA similarity……..………..…..………46

2-4 Rarefaction curves based on 0.0 amino acid genetic distance using the

BLOSUM 32 weight matrix…………………………………………….…….47

2-5 Community structure analysis of archaeal amoA clone libraries recovered from

urbanized soils and soils under the original unmanaged vegetation at 100% amino

acid similarity…………………………………………………………………48

2-5 Abundance of archaeal (AOA) and bacterial (AOB) amoA per gram of

dry soil in urbanized soils…………………………………………………….49

2-6 Secondary structure predictions for amoA protein of the most

common OTUs found in the urbanized soils and corresponding

alignment……………………………………………………………………..50

3-1 Changes in abundance of AOP under the different urban land covers.……...74

3-2 Changes in AOA/AOB in all urbanized soils after incubation for three

months at 18˚C and 28˚C…………………..……………………………...…75

3-3 Transcriptional activity of amoA measured after 102 days for AOA………..76

3-4 Effects of urban land cover and temperature on (A) potential nitrification,

viii

(B) pH, (C) soil moisture, and (D) in situ soil temperature……….…………77

3-5 Correlation between AOA abundance and potential nitrification in soils

incubated at 18˚C……………………………………………………….…....78

4-1 Alignment of archaeal amoA sequences used for the development of

primers and a probe targeting groundwater AOA (GW-AOA)………....….103

4-2 Neighbor Joining phylogenetic trees of a) 16S rRNA and b) amoA of

clones recovered from the different microcosms……………………..…….104

4-3 Hydropathy profiles for selected amoA sequences………………………...107

4-4 Abundance of AOP in soil urban soil microcosms over a period of 13

months…………………………………………………………………...….108

4-5 Correlation between GW-AOA abundance and solution pH in two

microcosms……………………………………………………………..…..109

4-6 Correlation between GW-AOA and nitrate concentration in microcosm

with bulk soil under unmanaged vegetation enriched with ammonium

chloride……………………………………………………………………..110

ix

List of Tables

2-1 Characteristic pH, N and C of urbanized soils at Rock Springs, PA……..…22

2-2 Primers, probes, and PCR thermal profiles used for the detection and

quantification of archaeal amoA………………………………………....…..28

2-3 Number of OTUs shared among urbanized soil treatments…………….…...36

3-1 Chemical characteristics of soil at the beginning of the experiment

and after 102 days of incubation under different urban covers at two

temperatures……………………...…………………………………………..71

3-2 Primers and thermal profiles used for quantitative PCR targeting

AOP amoA genes in soils incubated under different urban covers at two

temperatures……………………………………………………………….…71

4-1 Primers, probe and PCR thermal profiles used for the detection and

quantification of ammonia oxidizing prokaryotes in urban soil

microcosms…………………………………………………………………107

4-2 Chemical properties of incubation solutions for all urban soil

microcosms……………………………………………………………..…..108

4-3 Response of AOP abundance, nitrate concentration, pH and EC

to ammonium chloride addition to microcosm solution…………..…….….108

x

Acknowledgements

This thesis could not have been completed without the help of many people. First

I want to thank my advisor Dr. Mary Ann Bruns for welcoming me into her lab and

giving me the opportunity to pursue my doctoral degree at Penn State. I thank Mary Ann

for her guidance, patience, and sound advice throughout these years. I also want to thank

Mary Ann for sharing her passion for science, teaching and microorganisms. Her

enthusiasm really kept me motivated about my research.

I would also like to thank all the wonderful professors and scientists I met at Penn

State. I particular, I want to thank Dr. Enid Martinez, Dr. Dave Huff, Dr. Jay Regan, and

Dr. Curt Dell, my dissertation committee members, for their support and motivation. I

also want to thank Dr. Loren Byrne, whose research inspired the questions addressed in

this thesis.

I extend my deepest gratitude to my labmates and friends: Morgan, Pauline,

Yonghua, Matt, Emily, and Claudia. You made labwork a lot more enjoyable. I am very

lucky to have had such great labmates!

I want to thank the Alfred P. Sloan Foundation Minority PhD Program, for

providing me financial support. Receiving this fellowship was like getting a life vest

throughout my doctoral program.

A standing ovation and my eternal gratitude go to my family. This thesis has

been the result of a team effort in which both my Puerto Rican family and my Peruvian

xi

in-laws have gone the extra mile to help me complete my doctoral degree. I was

fortunate to have family members helping me both in the lab and at home.

I can‘t thank enough my wonderful husband Fernando. Gracias mi vida por tu

amor, por siempre decir las palabras correctas para tranquilizarme, por ayudarme a

mantenerme enfocada en mis metas, y por apoyarme en todos mis inventos.

Finally, I want to thank a little person, who is still too young to read this, but

hopefully one day will: my daughter Micaela. Your coming into this world has made me

a stronger person and gave me the inspiration I needed to complete my dissertation. It is

for you that I want to make this world a better place. I want you to be able to breath

clean air, drink clean water, and see all of the beautiful species that live in this wonderful

planet.

1

Chapter 1. Introduction

The role and nature of ammonia oxidizers

The development of sophisticated molecular techniques has challenged our

understanding of the microbial life that inhabits our planet. The increased capability

for analyzing genetic composition of microbial communities in environmental

samples has led to better understanding of the microorganisms that drive

biogeochemical cycles. The N cycle has been no exception. Nitrogen is typically the

most limiting nutrient in terrestrial ecosystems. As a result, the N cycle has received

great attention, mainly due to its importance in agriculture, and the environmental

damage caused when poorly managed. Although the key reactions involved in N

cycling are well known, the organisms responsible for these reactions are still being

described (Klotz and Stein, 2007). In 2004, the possible existence of autotrophic

ammonia-oxidizing archaea was reported, challenging the widely held belief that

bacteria were the only autotrophs capable of oxidizing ammonia (Treusch et al., 2004;

Venter et al., 2004). Ammonia oxidizers carry out the rate-limiting step of

nitrification. Thus, their abundance, activity and diversity in soil can affect the fate of

different nitrogen forms, like ammonium and nitrate.

In soil, ammonium has various fates: it can be taken up by plants, adsorbed

onto clay particles, volatilized or nitrified (Fig. 1). Both volatilization and

nitrification contribute to direct loss of N from the soil system. The oxidation of

ammonia is the first and rate-limiting step of nitrification. In a two-step, energy-

2

yielding process, ammonia oxidizers convert ammonia to nitrite (Fig. 2). The nitrite

produced is then converted to nitrate by another group of microorganisms, the nitrite

oxidizers, completing the nitrification process. Nitrate can then be taken up by plants

or lost from the system through leaching or denitrification, and the latter process is

enhanced when soil oxygen levels are low (Fig. 1). Thus, the activity of ammonia

oxidizers greatly influences the fate of N in terrestrial and aquatic ecosystems by

helping mobilize N in the form of nitrate.

Figure 1-1. The terrestrial N cycle. Picture by Maina Mártir Torres

Fossil fuel

combustionPrecipitation

Eutrophication

Atmospheric

N storage

Organic N

R-NH2

N2 fixationLightning

Runoff

Fertilizer

Leaching

AmmoniumMineralization

Nitrites

Nitrates

Leac

hing

Nitrification

Nitrification

Denitrification

Plant/microbial

consumption

N2

N2O

NH3

VolatilizationFossil fuel

combustionPrecipitation

Eutrophication

Atmospheric

N storage

Organic N

R-NH2

N2 fixationLightning

Runoff

Fertilizer

Leaching

AmmoniumMineralization

Nitrites

Nitrates

Leac

hing

Nitrification

Nitrification

Denitrification

Plant/microbial

consumption

N2

N2O

NH3

Volatilization

3

Figure 1-2. Reactions and enzymes involved in nitrification. The first two steps of nitrification are

carried out by ammonia oxidizers, while the last step is performed by nitrite oxidizers. Dotted arrows

indicate by-products of the reactions. Picture modified from Wrage et al., 2001.

The by-products produced by the nitrification reactions can have

environmental consequences. Hydrogen ions are released by the three processes

involved in nitrification, thereby acidifying the environment (Myrold, 2005). In

addition, other by-products may be produced by nitrifier denitrification, including the

greenhouse gases nitric oxide and nitrous oxide (Avrahami et al., 2002) (Fig. 1-2).

As a result, the processes that regulate ammonia oxidation and the organisms

involved are critical for our understanding of the nitrogen cycle and the production of

N-based greenhouse gases.

NH3

NH2OH NO

2- NO

3-

O2+ 2H+ H

2O H

2O 5H+ + 4e- H

2O 5H+ + 4e-

N2O N

2O

?

Hydroxylamine

oxidoreductase

Ammonia

monooxygenase

Nitrite

oxidoreductase

Ammonia oxidation Nitrite oxidation

NH3

NH2OH NO

2- NO

3-

O2+ 2H+ H

2O H

2O 5H+ + 4e- H

2O 5H+ + 4e-

N2O N

2O

?

Hydroxylamine

oxidoreductase

Ammonia

monooxygenase

Nitrite

oxidoreductase

Ammonia oxidation Nitrite oxidation

4

For almost a century it was believed that autotrophic ammonia oxidation

could be carried out only by bacteria (Kowalchuk and Stephen, 2001). The best

characterized ammonia oxidizers are in the β-Proteobacteria family, but γ-

Proteobacteria ammonia oxidizers have been found in marine environments.

Nitrosomonas europea, belonging to β -Proteobacteria, has been the most studied

ammonia oxidizer and long thought to be the predominant oxidizer in soil

(Kowalchuk, et al. 2001). Nevertheless, studies have shown that species of the

genera Nitrosospira are the dominant ammonia oxidizers in soil (Stephen et al., 1996;

Bruns, et al., 1999). Ammonia-oxidizing bacteria (AOB) of the β-Proteobacteria, in

general, are slow growers and are found in comparatively low numbers in soil relative

to heterotrophic microorganisms. Consequently, the numbers of ammonia oxidizers

can affect nitrification rates. About 3×105 cells g

-1 are needed to achieve a

nitrification rate of 1 mg N kg-1

day-1

, and unfertilized soils typically have only about

103 cells g

-1 (Myrold, 2005).

With the discovery of putative archaeal ammonia oxidizers, a new window in

ammonia oxidation research has been opened. These archaea belong to the

Crenarchaeota, a group know to be ubiquitous in soils (Nicol and Schleper, 2006).

Given their recent discovery, the taxonomy of ammonia-oxidizing archaea remains

ambiguous. Based on DNA sequence diversity of the gene encoding subunit A of

ammonia monooxygenase (amoA), Francis et al. (2005) found terrestrial and aquatic

clones to be clustered separately. Further research has supported this dichotomy.

Data on 16S rRNA genes has shown that AOA from marine environments are

5

classified in group 1.1a crenarchaea, while AOA from soils and sediments are

classified in group 1.1b (Schleper, et al., 2005). Mesophilic crenarchaeota, including

ammonia-oxidizing lineages, have been found to be distinct enough from

thermophilic crenarchaeota that Brochier-Armanet, et al. (2008a) have proposed a

new archaeal phylum, the Thaumarchaeota. The creation of this phylum of

mesophilic crenarchaeota was based on phylogenetic analysis of ribosomal genes and

a type I topoisomerase (Brochier-Armanet, et al, 2008b). Given the ambiguous

taxonomy of these archaeons the term AOA will be used throughout this dissertation.

Just how significant the contribution of AOA is to ammonia oxidation in soil,

relative to AOB, is still to be determined. Studies have found putative soil AOA to be

very diverse based on amoA sequences (Hansel et al., 2008) and to be more abundant

than AOB in many soils and aquatic ecosystems (Francis, et al., 2005; Leininger et

al., 2006; Mincer et al., 2007). A cultured marine ammonia-oxidizing archaeon,

‗Candidatus Nitrosopumilus maritimus‘ strain SCM1, has been demonstrated to

oxidize ammonia to nitrite almost stoichiometrically, and at rates similar to those of

AOB (Könneke, et al., 2005). Further, this archaeon has shown a very high specific

affinity for reduced nitrogen, suggesting adaptation to oligotrophic conditions

(Martens-Habbena, et al., 2009). Although a soil AOA has yet to be isolated,

Leininger et al. (2006) showed that copy numbers of archaeal amoA are 3,000-fold

larger than those of AOB in a variety of soils. Further, Uric et al. (2008) found active

transcription of AOA genes for ammonia oxidation in soil. Significant increases in

6

AOA abundance have been found in the rhizosphere of rice plants, pointing out the

potential of this group to use organic nitrogen (Chen et al., 2008).

In soil, AOB diversity has been found to be affected by several factors

including N availability, pH, and soil organic matter (Bruns et al., 1996; Koops,

2006). Changes in soil pH (Nicol et al., 2008) and temperature (Tourna, et al., 2009)

have also been shown to affect AOA abundance and diversity. Land use practices

that affect soil pH, N availability, temperature and SOM can be expected to alter the

ammonia oxidizer community.

Urbanization, Landscaping Practices and the Soil Habitat

Urban areas are expanding worldwide. It has been estimated that over 81% of

Americans live in urban areas (United Nations, 2008). With the expansion in

residential, commercial, and industrial areas comes an increase in land used for

landscaping. For aesthetic purposes, barren or unmanaged urban lands may be

converted to lawns and gardens. In fact, the nursery and greenhouse industry is one

of the fastest growing segments of US agriculture, with nursery production valued at

4.6 billion in 2006 (USDA, 2007). Urban landscaping practices can create conditions

that alter soil processes like N cycling and thus impact the soil habitat and its

residents.

A common landscaping practice is the use of mulches. In the words of

Bennett (1982), ―mulch is any soil covering meant to enhance the growth of some

plants and discourage the growth of others.‖ Thus, mulch can be organic, such as

7

wood chips, bark or leaves, or inorganic, such as sand or gravel. Besides weed

suppression, mulch has other benefits that include increased water infiltration,

moisture retention and soil insulation, and reduced soil erosion and compaction

(Borland, 1990; Kemper et al., 1994; Kratsch, 2007). Mulching can also alter soil

conditions such as nutrient content and pH, but the extent of these changes depends

on the nature of the mulch and the soil.

Organic mulches can alter soil nutrient content more directly than inorganic

mulches. Soil potassium (K) content has been shown to increase under organic

mulching, potentially due to high K levels in wood (Fraedrich and Ham, 1982;

Pickering and Shepherd, 2000). Reports on the effects of organic mulching on soil N

content are variable. N immobilization can be expected to occur when a mulch with a

large C:N (>30) is added to the soil. However, since mulch is typically applied on the

soil surface, N immobilization may only occur at the mulch-soil interface and not

affect deeply-rooted plants (Borland, 1990). Billeaud and Zajicek (1989) found a

reduction in soil N content after six months of mulch addition, while Pickering and

Shepherd (2000) found no change after one year. Further, Valenzuela-Solano et al.

(2005) found an increase in soil N content after 3 years of annual chipped eucalyptus

mulching around avocado trees. Thus, the degree to which organic mulch can affect a

soil‘s N content may not only depend on the type of mulch used and the nature of the

soil, but also on the mulch application and soil sampling methods and the degree of

mulch decomposition.

8

Similar to soil N content, reports on the effects of organic mulches on soil pH

are variable. Billeaud and Zajicek (1989) found a reduction in soil pH due to

mulching, while Pickering and Shepherd (2000) found the opposite. Both studies,

nonetheless, were done using soils with contrasting buffering capacities and sampled

at different times following mulch application.

Though generalizations cannot be made regarding the effects of organic

mulches on soil conditions, both organic and inorganic mulches can be expected to

affect soil N dynamics differently. While organic mulches may in the long term help

increase or keep soil organic C levels constant, the opposite may be true for inorganic

mulches. As a result, relatively higher N mineralization rates are expected under

inorganic mulches. The lack of an extra C addition may prevent N from being

immobilized in microbial cells. Further, if no plants are present, the N released from

decomposition of organic matter can be available for nitrification and denitrification.

A study conducted by Byrne (2006) showed greater nitrous oxide emissions, a

product of denitrification, in gravel-mulched plots than in bark-mulched plots. How

these different types of mulch affect the soil community is only beginning to be

understood.

The impact of mulching on the soil habitat has received little attention (Byrne,

2007; Lorenz and Lal, 2008). Studies conducted by Byrne are among the few that

have described the effects of urban landscapes on soil biodiversity. These studies

have shown that microarthropods, earthworms, and spiders are affected by different

lawn management and mulches (Byrne and Bruns, 2004; Byrne, 2006). Certain

9

collembolans were more abundant in lawns than in unmanaged old fields (Byrne and

Bruns, 2004). Further, while earthworms were more abundant in bark-mulched soils,

spiders were more abundant in unmanaged old fields (Byrne, 2006). Other urban soil

studies have found variable impacts on the communities of ants and mites (Byrne,

2007).

Little is known about the impact of mulching and landscaping practices on

soil microbial diversity. Tiquia et al. (2002) described the effects of various types of

mulching, including composted yard waste and ground wood pellets, on rhizosphere

bacterial communities. In their study, diversity was assessed based on fingerprint

patterns obtained from terminal restriction fragment length polymorphisms (TRFLP)

of bacterial 16S rRNA genes. By using this technique, the authors were able to detect

at a coarse taxonomic level diversity changes in the bacterial community resulting

from mulching. So far, this has been the only study where the impact of wood chip

mulching on soil microbial diversity has been addressed.

The effect of mulching on specific microbial groups has not been determined.

Studies evaluating the effects of urbanization on soil processes often focus on N

mineralization, nitrification and denitrification (Scharenbroch et al., 2005; Lorenz and

Kandeler, 2006). It has been shown that urbanization (Kaye, et al., 2005) and

landscaping practices like mulching (Scharenbroch et al., 2005; Byrne, 2006) can

alter N cycling. It can then be expected that the community of ammonia oxidizers,

which are a key group involved in nitrification, will be affected by changes in soil

conditions resulting from urbanization and landscaping.

10

In April 2003 an urban soil habitat study was established at the Russell E.

Larson Agricultural Research Farm in Rocksprings, PA (Byrne, 2006). The

experimental set-up was a complete randomized block design with four blocks and

treatments that included: lawn, gravel mulching, bark mulching, and an unmowed

old field as control. From this study, Byrne and coworkers (Byrne, 2006; Byrne et

al., 2008) were able to identify changes in N cycling, C dynamics, and

microarthropod community composition following soil conversion to different urban

soil habitat. The studies presented in this thesis build on the data of Byrne and

coworkers and extend their findings by describing how a specific keystone population

of soil organisms, the ammonia oxidizers, responds to urban landscaping practices

such as bark and gravel mulching.

Thesis objectives

Research conducted in this thesis contributes to the goal of understanding how

anthropogenic activity impacts nitrogen biogeochemistry. The focus of this research

is on urban soils and how urban landscaping practices affect the community of

ammonia-oxidizing prokaryotes. Particular emphasis is placed on the effects of bark

and gravel mulch, two common landscaping practices in temperate regions that have

been shown to alter nitrogen cycling.

Hypothesis: Diversity and abundance of AOA and AOB can be affected by

landscaping practices, such as application of bark and gravel mulch.

11

Specific objectives of this thesis:

1. Create a clone library of AOA amoA gene sequences to assess the effects of

mulching practices on the diversity of this group.

2. Identify soil variables that may affect the abundance and diversity of AOP,

with particular emphasis placed on soil temperature, pH, moisture, carbon and

nitrogen content.

3. Develop quantitative PCR assays to determine the effects of urban soil

habitats on the abundance of soil AOA and AOB, and a relatively rare lineage

of AOA related to 1.1a crenarchaea.

Structure of this thesis

Experimental study chapters in this thesis (chapters 2-4) have been written in

manuscript formats suitable for submission to peer-reviewed journals. Chapter 2

describes the effects of mulching and lawn treatments on the abundance of ammonia

oxidizing prokaryotes, and the diversity of AOA in particular. This manuscript will

be submitted to the journal Applied and Environmental Microbiology. Chapter 3

expands on the results obtained in Chapter 2, and presents an investigation of the

effects of soil cover and temperature on the abundance and transcriptional activity of

AOP. More emphasis in this chapter is placed on evaluating relationships between

AOP and soil variables, and it will be submitted to the journal Soil Biology and

Biochemistry. The last data chapter, Chapter 4, provides a more in-depth look into

relative abundances of ammonia-oxidizing bacteria and archaea, specifically a

12

relatively rare AOA lineage more closely related to marine than to soil amoA

sequences. AOP abundances are followed over time during incubations of whole soils

and silt/clay fractions. Data in this chapter will be prepared for submission to the

journal Microbial Ecology. Key findings of this thesis and main conclusions have

been summarized in Chapter 5.

References

Avrahami, S., Conrad, R., and Braker, G. 2002. Effect of soil ammonium

concentration on N2O release and on the community structure of ammonia oxidizers

and denitrifiers. Appl. Environ. Microbiol.68: 5685-5692.

Bennett, J. 1982. Mulches to retain moisture and cool the soil. Horticulture 60:55–56.

Billeaud, L.A. and Zajicek, J.M. 1989. Influence of mulches on weed control, soil pH,

soil nitrogen content, and growth of Ligustrum japonicum. J. Environ. Hort. 7:155-

157.

Borland, J. 1990. Mulch: Examining the facts and fallacies behind the uses and

benefits of mulch. Am. Nurseryman 172:132-143.

Brochier-Armanet, C., Boussau, B., Gribaldo, S., and Forterre, P. 2008a. Mesophilic

Crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota. Nat. Rev.

Microbiol. 6:245-252.

Brochier-Armanet, C., Gribaldo, S., and Forterre, P. 2008b. A DNA topoisomerase

IB in Thaumarchaeota testifies for the presence of this enzyme in the last common

13

ancestor of Archaea and Eucarya. Biology Direct, December 23. doi: 10.1186/1745-

6150-3-54.

Bruns, M.A., Stephen, J.R., Kowalchuk, G.A., Prosser, J.I., and Paul, E.A. 1999.

Comparative Diversity of Ammonia Oxidizer 16S rRNA Gene Sequences in Native,

Tilled, and Successional Soils. Appl. Environ. Microbiol. 65: 2994-3000.

Byrne, L.B. and Bruns, M.A. 2004. The effects of lawn management on soil

microarthropods. J. Ag. Urban Ent. 21:150-156.

Byrne, L.B. 2006. Effects of urban habitat types and landscape patterns on ecological

variables at the aboveground-belowground interface. PhD dissertation. The

Pennsylvania State University. University Park, PA.

Byrne, L.B. 2007. Habitat structure: A fundamental concept and framework for

urban soil ecology. Urban Ecosyst. 10:225-274.

Byrne L.B., Bruns, M.A., and Kim, K.C. 2008. Ecosystem properties of urban land

covers at the aboveground-belowground interface. Ecosystems 11:1065-1077.

Fraedrich S. W., and Ham D. L. 1982. Wood chip mulching around maples: Effect on

tree growth and soil characteristics. J. Arboric. 8:85-89.

Chen, X.P., Zhu, Y.G., Xia, Y., Shen, J.P., and He, J.Z. 2008. Ammonia-oxidizing

archaea: important players in paddy rhizosphere soil? Environ. Microbiol. 10:1978-

1987.

14

Francis, C.A., Roberts, K.J., Beman, J.M., Santoro, A.E., Oakley, B.B. 2005.

Ubiquity and diversity of ammonia-oxidizing archaea in water columns and

sediments of the ocean. Proc. Natl.Acad. Sci. USA 102:14683–88

Francis, C.A., Beman, J.M., and Kuypers, M.M.M. 2007. New Processes and Players

in the Nitrogen Cycle: the Microbial Ecology of Anaerobic and Archaeal Ammonia

Oxidizers. ISME J. 1: 19027.

Hansel, C. M., S. Fendorf, P. M. Jardine, and C. A. Francis. 2008. Changes in

bacterial and archaeal community structure and functional diversity along a

geochemically variable soil profile. Appl. Environ. Microbiol. 74:1620-1633.

Kaye, J.P., McCulley, R.L., Burke, I.C. (2005) Carbon fluxes, nitrogen cycling and

soil microbial communities in adjacent urban, native and agricultural ecosystems.

Global Change Biol 11:575–587

Kemper, W.D., Nicks, A.D. and Corey, A.T. 1994. Accumulation of water in soils

under gravel and sand mulches. Soil Sci. Am. J. 58: 56-63.

Klotz, M.G. and Stein, L.Y. 2007. Nitrifier genomics and evolution of the nitrogen

cycle. FEMS Microbiol Lett. 278: 146–156

Könneke, M., Bernhard, A.E., de la Torre, J.R., Walker, C.B., Waterbury, J.B. and

Stahl, D.A. 2005. Isolation of an Autotrophic Ammonia-Oxidizing Marine Archaeon.

Nature 473: 543-546.

Koops, HP., Purkhold, U., Pommerening-Röser, A., Timmermann, G., and Wagner,

M. 2006. The Lithoautotrophic Ammonia-Oxidizing Bacteria. Prokaryotes 5: 778-

811

15

Kowalchuk, G.A. and Stephen J.R. 2001. Ammonia-Oxidizing Bacteria: A Model for

Molecular Microbial Ecology. Annu. Rev. Microbiol. 55:485–529.\

Kratsch, H.A. 2007. Water-wise landscaping: Mulch. Utah State University

Cooperative Extension. HG/Landscaping/2007-01pr.

Leininger, S., Urich, T., Schloter, M., Schwark, L., Qi, J., Nicol, G.W., Prosser, J.I.,

Schuster, S.C. and Schleper, C. 2006. Archaea predominate among ammonia-

oxidizing prokaryotes in soils. Nature 442, 806-809.

Lorenz, K. and Kandeler, E. 2005. Biochemical characterization of urban soil profiles

from Stuttgart, Germany. Soil Biol. Biochem. 37:1373–1385.

Lorenz, K. and Lal, R. 2008. Biogeochemical C and N cycles in urban soils. Environ

Int. In Press. doi:10.1016/j.envint.2008.05.006

Martens-Habbena, W., Berube, P.M., Urakawa, H., de la Torre, J.R., and Stahl, D.A.

2009. Ammonia oxidation kinetics determine niche separation of nitrifying Archaea

and Bacteria. Nature 461:976-979.

Mincer, T.J., Church, M.J., Taylor, L. T., Preston, C., Karl, D.M., and DeLong, E.F.

2007. Quantitative distribution of presumptive archaeal and bacterial nitrifiers in

Monterey Bay and the North Pacific Subtropical Gyre. Environ. Microbiol. 9: 1162–

1175

Myrold, D.D. 2005. Transformations of Nitrogen. In: Principles and Applications of

Soil Microbiology 2nd Ed.(Sylvia et al., Eds) . Pearson Education Inc., Upper Saddle

River, New Jersey, USA.

16

Nicol, G.W. and Schleper, C. 2005. Ammonia-oxidising Crenarchaeota: important

players in the nitrogen cycle? TRENDS in Microbiology 14: 207-212.

Nicol, G.W., Leininger, S., Schleper, C., and Prosser, J.I. 2008. The influence of soil

pH on the diversity, abundance and transcriptional activity of ammonia oxidizing

archaea and bacteria. Environ Microbiol 10:2966-2978.

Pickering, J.S. and Shepherd, A. 2000. Evaluation of organic landscape mulches:

composition and nutrient release characteristics. Arboricultural J. 24:175-187.

Scharenbroch B.C., Lloyd, J.E. and Johnson-Maynard, J.L. 2005. Distinguishing

urban soils with physical, chemical, and biological properties. Pedobiologia 49:283–

296.

Stephen, J.R., McCaig, A.E., Smith, Z, Prosser J.I., and Embley T.M. 1996.

Molecular Diversity of Soil and Marine 16S rRNA Gene Sequences Related to b-

Subgroup Ammonia-Oxidizing Bacteria. Appl. Environ. Microbiol. 62: 4147-4154.

Tiquia, S.M., Lloyd, J., Hermsb, D.A., Hoitink, H.A.J., and Michel, F.C. Jr. 2002.

Effects of mulching and fertilization on soil nutrients, microbial activity and

rhizosphere bacterial community structure determined by analysis of TRFLPs of

PCR-amplified 16S rRNA genes. Appl. Soil Ecol. 21:31-48.

Treusch, A.H., Kletzin, A., Raddatz, G., Ochsenreiter, T., Quaiser, A., Meurer, G.,

Schuster, S.C., and Schleper, C. 2004. Characterization of Large-Insert DNA

Libraries from Soil for Environmental Genomic Studies of Archaea. Environ.

Microbiol 6: 970-980.

17

Treusch, A.H., Leininger, S., Kletzin, A., Schuster, S.C., Klenk, H.P., and Schleper,

C. 2005. Novel Genes for Nitrite Reductase and Amo-Related Proteins Indicate a

Role of Uncultivated Mesophilic Crenarchaeota in Nitrogen Cycling. Environ.

Microbiol.7: 1985-1995.

United Nations (2008) World Urbanization Prospects: The 2007 Revision, Highlights

(United Nations, New York).

Urich, T., Lanzén, A., Qi, J., Huson, D.H., Schleper, C., Schuster, S.C. (2008)

Simultaneous Assessment of Soil Microbial Community Structure and Function

through Analysis of the Meta-Transcriptome. PLoS ONE 3: e2527

USDA, 2007. Nursery Crops 2006 Summary. Agricultural Statistics Board. NASS.

Sp Cr 6-3 (07)

Valenzuela-Solano, C., Crohn, D.M., and Downer, J.A. 2005. Nitrogen

mineralization from eucalyptus yardwaste mulch applied to young avocado trees.

Biol. Fertil. Soils (2005) 41: 38-45.

Venter, J. C., K. Remington, J. F. Heidelberg, A. L. Halpern, D. Rusch, J. A.

Eisen, D. Y. Wu, I. Paulsen, K. E. Nelson, W. Nelson, D. E. Fouts, S. Levy,

A. H. Knap, M. W. Lomas, K. Nealson, O. White, J. Peterson, J. Hoffman, R.

Parsons, H. Baden-Tillson, C. Pfannkoch, Y. H. Rogers, and H. O. Smith. 2004.

Environmental genome shotgun sequencing of the Sargasso Sea. Science 304:66–74.

Wrage, N., Velthof, G.L., van Beusichem, M.L. and Oenema, O. 2001. Role of

Nitrifer Denitrification in the Production of Nitrous Oxide. Soil Biol. Biochem. 33:

1723-1732.

18

Chapter 2. Molecular Analysis of Ammonia Oxidizer Communities in Vegetated

and Mulched Soils

Maina C. Martir, Mary Ann Bruns

Abstract

Land areas converted to urban uses are increasing worldwide. As with most

soil management practices, landscaping associated with urbanization can alter soil

habitats and their resident microbial communities. Mulching is one of the most

commonplace landscaping practices in urban areas, and it offers a familiar system for

investigating human impacts on soil microorganisms. Here we compared

communities in mulched and unconverted soils by focusing on the ammonia

oxidizers, an important keystone group involved in nitrogen (N) cycling. Our central

hypothesis was that soils under mulches would exhibit different ammonia oxidizer

communities than soils under vegetation. In the third year after mulching conversion,

we investigated the abundance of archaeal and bacterial amoA genes, and the spatial

diversity of archaeal genes, in community DNA extracts of vegetated (unconverted),

gravel-mulched, and bark-mulched soils. Clone libraries of archaeal amoA genes

from three individual soil cores per plot were obtained from replicate experimental

plots at Penn State University‘s Rock Springs Research Station. Whereas mulching

treatment or mulch type did not affect the richness of operational taxonomic units

(OTUs) richness, it did affect community composition. Gravel-mulched soils

harbored different AOA communities compared to bark-mulched soils and soils under

19

unconverted vegetation. At 100% amino acid (AA) similarity, a total of 252 OTUs

were recovered, of which four OTUs contained 40% of the sequences. Representative

sequences from these four OTUs had distinct hydropathy profiles, suggesting

differences in protein function. High spatial variability at the field scale was

demonstrated by the observation that many OTUs (8 out of 31 at the 94% DNA

similarity level) were detected in single cores. Mulching treatment or mulch type did

not affect AOB abundance but did affect abundance of AOA genes, which were lower

in bark-mulched soils. Consistent with other studies showing that AOA are more

sensitive than AOB to soil alteration, our results indicated that AOA abundance and

diversity were affected when soils were converted by mulching and that gravel and

bark mulches affect AOA communities in different ways. Further, this study provides

insights into the genetic diversity and spatial variability of ammonia-oxidizing

archaea in soils.

Introduction

Global N cycles have been greatly altered by anthropogenic increases in

reactive N due to the use of N fertilizers and fossil fuel combustion (Vitousek et al.,

1997; Schlesinger, 2008). What is less obvious and possibly as important are

anthropogenic alterations of microbial communities responsible for nitrogen (N)

cycling in soils. Soil areas affected by urbanization are increasing worldwide. While

more than half of the world‘s population lives in urban areas today, urban residents

are projected to make up 70% of the world‘s population by the year 2050 (United

20

Nations, 2008). Like many soil management practices, landscaping associated with

urbanization can alter soil habitats, thereby affecting resident microorganisms.

Mulching is one of the most commonplace landscaping practices in urban areas, and

it offers a familiar system for investigating less obvious, human impacts on soil N

cycling (Lorenz and Lal, 2008; Kaye et al., 2005).

Mulching involves selective removal of vegetation followed by application of

materials to soil surfaces to suppress weeds, increase moisture retention, and reduce

erosion (Borland, 1990; Kemper et al., 1994; Kratsch, 2007). Removal of vegetative

cover results in altered soil conditions and a shift to microbially-driven

biogeochemical cycling in the absence of live plants. Studies comparing N cycle

processes in vegetated and mulched soils have reported differences in organic matter

mineralization and N2O fluxes (Scharenbroch et al., 2005; Byrne et al., 2006). Since

N2O fluxes from oxic soils are thought to be influenced to a greater extent by

nitrification than denitrification, the effect of mulching on nitrifier populations is of

specific interest (Wrage et al., 2001). Mulch composition, which ranges from

organic materials (e.g., wood chips, bark) to inorganic materials (e.g., gravel, sand,

plastic sheeting), provide different substrates for fueling microbial activity in soils.

In the present study we expand on observations made during the process-

based experiment of Byrne et al. (2006) by investigating spatial variability and

differences in ammonia oxidizers in mulched and vegetated soils. In the study by

Byrne et al. (2006), N dynamics differed in soils covered by organic and inorganic

21

mulches. Gravel-mulched soils showed higher nitrous oxide (N2O) fluxes than bark-

mulched soils and the native soils under unmown vegetation prior to mulching.

Ammonia oxidizers, found within bacterial as well as archaeal domains, are

recognized as carrying out the first step in nitrification. While the effects of soil

management on ammonia oxidizer activity and diversity have been relatively well

studied in agricultural systems, little is known about how this keystone microbial

group responds to soil management practices associated with urbanization. Further,

most of what is known about the effects of land use change on nitrification has been

focused on ammonia-oxidizing bacteria (AOB). More recent studies have shown that

ammonia-oxidizing archaea (AOA) are also widespread and active in soils (Nicol and

Schleper, 2005; Treusch et al., 2004, 2005; Leininger et al., 2006; Francis et al., 2007;

Schauss et al., 2009).

The objective of this study was to investigate abundance, diversity, and spatial

variability of ammonia-oxidizing archaea and bacteria in experimentally mulched and

adjacent vegetated plots. The abundance and activity of both groups of ammonia

oxidizers have been shown to be affected by N availability (He et al., 2008; Di et al.,

2009) and the amount of soil organic matter (Leininger et al., 2006; Chen et al.,

2008). We hypothesized that ammonia oxidizer populations would respond to

organic and inorganic mulches in different ways and that this response would be

reflected in changes in the abundance of AOA and AOB. This hypothesis was tested

using the gene ammonia monooxygenase subunit A (amoA). We also compared

22

molecular diversity of AOA in these soils, since much less is known about this

recently discovered group.

Methods

Study site and soil sampling

Soils collected for this study were obtained from urban land cover experimental plots

established in 2003, and located at the Russell E. Larson Agricultural Research

Station in Rock Springs, PA (40° 43'N, 77° 55'W, 350 m elevation). Soils at the

study site have a silty clay loam texture and are classified in the Opequon series

(Clayey, mixed, active, mesic Lithic Hapludalfs) (Soil Survey Staff, NRCS). The

experimental plots were created following a complete randomized block design with

four replications and included the following urban land-cover treatments: unmanaged

vegetation (unmowed lawn), mowed lawn, and bark- and gravel mulch (Byrne, 2006).

For the purpose of this study, only two plots of the unmanaged vegetation, bark- and

gravel-mulched treatments were evaluated. Three 4-cm deep and 2.7-cm wide soil

cores were aseptically collected per plot in September of 2006. Cores were stored in

a cooler until transported to the laboratory, where they were kept at 4 ºC. Each core

was subdivided into aliquots and stored at -80 ºC until further processing. Additional

composite samples of soils collected per treatment from each block were used to

measure total C and N, and pH (Table 2-1). Total C and N were measured by

combustion at the Agricultural Analytical Services Laboratory at Penn State

University. Soil pH in water was measured twice for each sample using a pH

23

electrode and a 1:1 ratio of soil to water. Gravimetric soil moisture was determined

after drying a known amount of soil for 24 hrs at 105 ºC.

Soil DNA extraction

Genomic DNA for standard PCR amplification and archaeal amoA clone

library construction was extracted from 0.5 g of moist soil using the MoBio Ultra

Clean Soil DNA extraction kit (MoBio Laboratories, Inc., Carlsbad, CA).

Manufacturer‘s instructions were followed except for differences in physical lysis

methods, since preliminary trials indicated that DNA in gravel-mulched soils was

more readily sheared by bead-beating than by vortexing. Thus, soil samples from the

unmanaged vegetation and bark-mulched plots were extracted by bead-beating the

sample for 30s, while those from the gravel plots were extracted by vortexing the soil

for 10 min.

Further testing in our laboratory indicated that better soil genomic DNA yields

were obtained using the MoBio PowerTM

Soil DNA Isolation Kit. As a result, DNA

used for quantitative PCR (qPCR) was extracted from 0.3 g of moist soil from a

second set of aliquots. Since different lysis methods have been reported to affect

amoA quantification (Leininger et al., 2006), manufacturer‘s instructions were

followed with the exception that two lysis methods were tested, vortexing the soil for

10 min and bead beating for 30 s. The qPCR results in this study are reported only

for the genomic DNA extracted from vortexing (Appendix B). Due to sample

limitations, DNA for qPCR was extracted from only two of the three cores initially

24

collected from the second block of each treatment. DNA concentration of all samples

was determined using a NanoDrop 1000 Spectrophotometer (Thermo Fishes

Scientific Inc.).

PCR amplification and clone library construction of putative Crenarchaeal amoA

The ammonia monooxygenase subunit A gene (amoA) was amplified using

the primers 19F and 643R (Leininger et al., 2006; Table 2-2), with positive

amplification verified by gel electrophoresis. Duplicate PCR reactions were pooled

and cloned using the TOPO-TA cloning kit (Invitrogen). Plasmids containing amoA

inserts were either extracted using the Qiagen Plasmid Miniprep Kit or amplified

using the ilustraTM

TempliPhi Amplification Kit (GE Heathcare) following

manufacturer‘s instructions. Sequencing was performed on an ABI Hitachi 3730XL

capillary DNA analyzer using primers M13U and M13R. The software SeqMan was

used to manually edit and verify sequence quality. Clone libraries containing about

30 clones were obtained from each soil core.

A total of 524 sequences were analyzed, using a 606 bp (202 amino acids)

region of the amoA gene which excluded primer regions. Nucleotide sequences were

translated to amino acids using the ExPaSy (Expert Protein Analysis System)

Translate Tool. Sequence alignment was performed using the program ClustalX

version 1.83 (Thompson et al., 1997) with default parameters. Analysis of translated

sequences indicated that 42 sequences were non-coding (had stop codons). These

sequences were omitted from further diversity and phylogenetic analyses.

25

241 DNA sequences representing the OTUs obtained at 99% DNA similarity

will be deposited in GenBank database.

Crenarchaeal amoA diversity and phylogenetic analyses

For richness and diversity comparisons, sequences were classified into

operational taxonomic units (OTU) based on DNA and amino acid genetic distance.

Distance matrices for DNA, based on the Kimura 2-parameter weight matrix, and

translated sequences, based on the BLOSUM32 weight matrix, were calculated using

the programs DNAdist and PROTdist from the PHYLIP package, respectively

(Felsenstein, 2004). The program DOTUR (Schloss, 2005) was used to conduct

rarefaction analysis to calculate expected OTU richness (Sobs) and estimated OTU

richness based on the non-parametric estimator Chao1.

Community structure, based on DNA and amino acid genetic distance was

evaluated for each treatment using OTU-based and hypothesis testing approaches.

The number of shared OTUs among treatments was obtained using the program

MOTHUR (Schloss, 2009). Shared OTUs were evaluated at genetic distances

ranging from 0.0 to 0.09 (100% to 91% similarity). The program WebLibshuff

(Henriksen, 2004) was used to test the hypothesis of whether the clone libraries

recovered from each treatment belonged to similar communities. Distance matrices

for each comparison were generated using PROTdist with the Jones-Taylor-Thorton

weight matrix. WebLibshuff constructs random communities from the two libraries

being compared at a time, compares the coverage of the random community with the

26

coverage of each library, and calculates a Cramér-von Mise statistic (Singleton et al.,

2001). Two libraries can be said to belong to different communities when the

coverage of the homologous library is significantly different from that of the

randomly constructed heterologous library. Critical p-values were determined after a

Bonferroni correction for multiple comparisons.

Phylogenetic reconstruction was done using MEGA5 and sequences

representing each of the 31 OTUs found at DNA similarity of 94%. Using Model test

in MEGA 5, the model T92+G (Tamura, 1992), was identified as a suitable model for

genetic evolution for this set of sequences A neighbor joining tree was generated

using the model T92, with gamma equal to 0.28, transitions and transversions were

included in the analysis, and homogeneous patterns were assumed among lineages. A

bootstrap value of 100 was used for the interior branch test of phylogeny. HyPhy in

MEGA 5 was used to determine the number of synonymous and nonsynonymous

substitutions in 31 sequences representing the OTUs found at 94% DNA similarity.

Quantitative PCR

Copy numbers of putative crenarchaeal amoA were quantified using an ABI 7300

Sequence Detection System. Optimization of a SYBR Green assay for the detection

of archaeal amoA using primers ArchamoF and ArchamoR (Francis et al., 2006)

proved to be challenging after melting curve analysis repeatedly indicated unspecific

amplification. As a result, the software Primer Express® v3.0 (Applied Biosystems)

was used to design primers and a TaqMan®

probe specific for crenarchaeal amoA

27

(Table 2-2, Appendix C). Only one degenerate position was included in each primer

and probe to allow annealing to a wider range of amoA sequences without

compromising efficiency and specificity. When compared against our clone library,

the forward primer anneals to 90 % of sequences, while the reverse primer anneals to

95%. Given the high diversity of the archaeal amoA gene, limiting the number of

degenerate positions in a TaqMan® probe reduces the number of sequences

potentially detected. The probe designed here, anneals to 77% of the sequences in

our clone library including all sequences similar to published sequences recovered

from soil environments. Nevertheless, this probe anneals to a wider range of our

clone library than would other published probes with multiple degenerate positions

(Treusch et al., 2005). Duplicate samples and a standard curve spanning from 104 to

108 were used for the assays. Each reaction had a final volume of 25 μL and

contained 9 ng of DNA, 0.4 μM of each primer, 0.2 μM of probe and 12.5 μL of

TaqMan® Universal PCR Master Mix, No AmpErase® UNG (Applied Biosystems).

The standard curve used for amoA quantification was constructed using a dilution

series of a 1:1 mix of DNA from two transformed plasmids containing the different

degenerate nucleotides. A slope of -3.42 and an R2>0.99 was obtained for amoA

quantification.

Relative quantification of bacterial amoA was done using SYBR Green

chemistry, primers 1F and 2R (Table 2-2), and an ABI 7500 Sequence Detection

System. Each reaction had a final volume of 10 μL, and contained 9 ng of DNA, 0.2

μM of each primer and 5 μL of Maxima™ SYBR Green qPCR Master Mix

28

(Fermentas Inc., Glen Burnie, MD, USA). The specificity of the products was

assessed using melting curve analysis and gel electrophoresis. A ten-fold dilution

series of a known concentration of plasmid DNA containing a bacterial amoA insert

recovered from soil was used to create a standard curve over seven orders of

magnitude (3 ×102 to 3 × 10

8) (Appendix D). Slopes of -4.90 and R

2>0.99 were

obtained for bacterial amoA quantification. Thermal profiles for both assays are

shown in Table 2-2.

Analysis of variance (Generalized Linear Model) was used to compare

abundance of archaeal and bacterial amoA among treatments. All statistical analyses

were performed using SPSS 17.0 (SPSS, Chicago, IL). If main effects were

significant at the 0.05 level, means were compared using Tukey‘s Test.

Prediction of amoA secondary structure

The hydropathy index of Kyte and Doolittle was used to predict protein secondary

structure or topology (Kyte and Doolittle, 1982). The four most common OTUs

based on 100% amino acid similarity and two reference amino sequences

(Nitrosopumilus maritimus and the fosmid Cren54d9) were included as references for

analysis.

29

Results

Phylogenetic analysis

At 100% amino acid (AA) and DNA similarity, a total of 252 and 241 OTUs were

recovered, respectively. Four OTUs clustered 40% of the AA sequences at this level

of genetic similarity. Further, the most common OTU based on 100% AA similarity

consisted of two OTUs based on 94% DNA similarity (OTU1 and OTU2), indicating

convergence of amino acid composition. A total of 31 OTUs were identified based

on a 94% DNA similarity level (Figs 2-1 and 2-2). High spatial variability at the field

scale was demonstrated by the observation that many OTUs (8 out of 31 at the 94%

DNA similarity level) were detected in single cores (Fig. 2-1). Phylogenetic analyses

using representative sequences from these 31 OTUs showed that all sequences fell

within three main clusters, all associated with amoA sequences recovered from soils

and sediments, potentially belonging to the Crenarchaeota 1.1b lineage (Fig. 2-1).

One cluster, designated as Rock Springs Dominant (RSD), contained 93% of

all OTUs and included the sequence of the soil fosmid 54d9. Sequences from the

other two clusters were located in the more basal portion of the phylogenetic tree,

closer to the outgroup sequence of Nitrosopumilis maritimus. The second cluster,

comprised of OTU9 and OTU20, was designated as Rock Springs Rare (RSR). The

third cluster consisting of OTU28, found in only one soil core, grouped with the

sequence of the thermophilic AOA Nitrososphaera gargensis and was designated

Rock Springs Nitrososphaera-like (RSN).

30

As shown in Fig 1, each soil core contained a diverse AOA community, with

each library consisting of 5-13 OTUs at the 94% DNA similarity level. Overall,

OTUs 1 and 2 were most abundant, accounting for 25-85% of the sequences in each

clone library. These two OTUs merge at genetic distances greater than 0.09 and code

for amino acid sequences that differ only by 0-2 residues. A few other OTUs

dominated in one core, such as OTU7 in core B-2-2, OTU10 in core G-2-3, and

OTU4 in core B-1-1. Of the rarer OTUs, OTU9 was found only in bark-mulched and

vegetated soils, and OTU20 found only in vegetated soils. Sequences in OTU28 were

closely related to N. gargensis and were found in a single core from vegetated soils.

Richness and diversity

The number of expected (Sobs) and estimated (Chao1) OTUs varied as a

function of genetic distance and also differed when comparing DNA and amino acid

sequences (Fig 2-2). In general, more OTUs were identified based on DNA

sequences than on amino acid sequences, suggesting sequence convergence (Fig 2-2).

The potential for amino acid sequence convergence is supported by a high number of

synonymous substitutions observed when values were plotted against

nonsynonymous substitutions (Fig 2-3).

The expected number of OTUs tended to be lower in gravel-mulched soils but

this difference was within the 95% confidence intervals of the other two treatments

(Fig 2-2A). DNA sequences from all treatments fell into one OTU at a genetic

distance of 0.32. Contrastingly, amino acid sequences from bark mulched, soils

31

under unmanaged vegetation and gravel mulched soils fell into one OTU at a distance

of 0.12, 0.10 and 0.09, respectively. Rarefaction analysis at 100% amino acid

similarity, showed no differences in the number of expected OTUs among treatments

and while the curve deviated from a 1:1 line, a plateau was not reached (Fig 2-4).

Based on the Chao1 richness estimator, DNA sequences from the unmanaged

vegetation soils differed only by a genetic distance of 0.12 (Fig 2-2B). In contrast,

DNA sequence libraries from mulched soils exhibited greater genetic distance, with

sequences differing by distances up to 0.32 (fig 2-2B).

Community composition analysis

OTU composition and hypothesis testing approaches were used to analyze the

structure of the crenarchaeal ammonia oxidizing community (Table 2-3). More

OTUs were generated based on DNA sequences vs. amino acid sequences. At

genetic similarities greater than 97%, shared richness was lower than the number of

unique OTUs in each treatment. At DNA sequence similarities lower than 97%, more

OTUs were shared between soils under the unmanaged vegetation and the bark mulch

than when compared to gravel mulched soils. The same result was obtained at all

amino acid genetic similarities evaluated. This pattern was supported by the

hypothesis testing approach using web-Libshuff. Significant p-values were obtained

when comparing the clone library recovered from the Gravel-mulched soils with the

other two treatments (Fig 2-5).

32

Abundance of ammonia oxidizers in mulched and vegetated soils

The numbers of archaeal amoA gene copies per gram of soil ranged from 9.1

× 105 to 1.0 × 10

8, while bacterial amoA ranged from 2.2 × 10

6 to 2.7 × 10

7 (Fig 2-6).

Abundance of archaeal and bacterial amoA was analyzed after a log transformation of

the data to satisfy the equal variance assumption for analysis of variance. The log-

transformed abundance of archaeal amoA was found to be significantly lower in bark

mulched soils when compared to soils under gravel mulch and unmanaged vegetation

(Fig 2-6). No difference in archaeal amoA abundance was found between soils under

gravel mulch and unmanaged vegetation. Further, no significant differences in

bacterial amoA abundance were found among treatments (Fig 2-6).

Prediction of amoA secondary structure

Five transmembrane domains have been predicted for amoA (Treusch et al., 2005).

The secondary structure predicted for the four most common OTUs (found at > 94%

DNA similarity) based on the Kyte-Doolittle hydropathy index depicts these

transmembrane domains (Fig 2-7). In general, the hydropathic character of archaeal

amoA was found to be conserved among the OTUs and the reference amino acid

sequences. Most of the variability in hydropathy index observed was located in

hydrophobic regions. When comparing the four OTUs, the sign of the hydropathy

score changed only in postion 89. In this position, sequences in OTU-4 have a

Methionine, while sequences in all other common OTUs have a Tyrosine (Fig 2-7).

Further, due to the residue in position 89, of the 202 residues evaluated, sequences in

33

OTU-4 have eight Methionine residues while most other sequences in our clone

library have seven. Changes in the hydropathic character of the amoA protein may

translate into differences in protein function.

Discussion

Little is known about the effects of mulching on the soil community (Byrne,

2007; Lorenz and Lal, 2008). Studies conducted by Byrne are among the few that

have described the effects of urban landscapes on soil biodiversity. These studies

have shown that macroorganisms like earthworms, spiders and arthropods are

affected by different lawn management practices and mulching (Byrne and Bruns,

2004; Byrne, 2006, 2007). Here we report for the first time how mulching, a

commonly used landscaping practice, affects a keystone soil microbial group: the

ammonia oxidizers. While OTU richness did not vary among treatments, the

composition of the AOA community did. Further, we found a reduction in the

abundance of AOA in soils under bark mulch, while the abundance of AOB was not

affected by mulch application.

The land covers evaluated here created soil environmental conditions capable

of supporting the same number of OTUs. However, the identity of these OTUs

differed. Similar results were observed for bacterial communities by Tiquia et al.

(2002) when evaluating the impacts of various types of mulching, including

composted yard waste and ground wood pellets. Mulching was found to alter the

composition of soil bacteria based on 16S rRNA terminal fragment length

34

polymorphism (TRFLP) patterns when compared to barren soil. In our study, three

years following mulch application, only the AOA community in gravel-mulched soils

was significantly different from that in soils under the original unmanaged vegetation.

Further, the community in gravel-mulched soils was also different from that in bark-

mulched soils. Gravel mulching may lead to a more extreme environmental change

than bark mulching when compared to the original soil conditions. Higher surface

temperatures were reported by Byrne 2006 in gravel mulched soils and temperature

has been found to be a major factor influencing the community structure of AOA

(Tourna et al., 2008). AOA diversity has also been found to be affected by soil pH

(Nicol et al., 2008). Our gravel-mulched soils had slightly higher pH, with values

close to 7.8 vs. the 6.4-6.8 and 6.8-7.1 found in unmanaged vegetation and bark

mulched soils, respectively. Gravel mulched soils also retained more moisture than

vegetated soils. Higher surface temperatures, increases in soil pH and moisture

retention are factors associated with gravel mulching that may contribute to the

formation of the distinct community composition present.

In this study a decrease in AOA abundance was observed in bark-mulched

soils when compared to soils covered by unmanaged vegetation and gravel-mulch.

The bark-mulched soils studied here have been found to contain a much higher

percent of organic matter (16.4 %) than either gravel-mulched (11.4 %) or vegetated

(13.8 %) soils (Byrne, 2006). Further, bark-mulched soils also had a higher C:N ratio

than the other two soils. Recent studies based on the marine ammonia oxidizing

crenarchaeon ‗Candidatus Nitrosopumilus maritimus‘ strain SCM1, suggest AOA

35

may be adapted to nitrification under oligotrophic conditions (Martens-Habbenea et

al., 2009). However, studies conducted in soils have found that either AOB or AOA

may respond to organic matter additions and increases in N availability. In various

soils, Leininger et al. (2006) found a decrease in bacterial amoA with increasing soil

depth, while the abundance of archaeal amoA did not change. One of the factors

associated with this increase in soil depth was a decrease in soil organic matter.

Further, Di et al. (2009) found an enrichment of AOB in relation to AOA with

increasing N availability in an agricultural soil. In contrast, increases in AOA

abundance in relation to AOB have been found in the rhizosphere of rice and aquatic

plants (Chen et al., 2008; Hermann et al., 2008). In addition, Schauss et al. (2009)

found increased growth of AOA after organic matter fertilization. The higher C:N in

bark mulched soils may have caused a decrease in N mineralization rates, potentially

explaining the decrease in AOA abundance at the time of sampling.

Gravel-mulched soils were able to support a community of autotrophic

ammonia oxidizers, both bacterial and archaeal, similar in size to the one present in

soils under unmanaged vegetation. When measured in 2004 and 2005 by Byrne

(2006), these soils exhibited higher levels of N2O flux than bark-mulched or

unmanaged vegetation soils. Gravel mulched soils received no constant inputs of

organic material like the soils under unmanaged vegetation, but at the same time,

available N was not being taken up by plants. As a result, more of the mineralized N

present may be available to support the ammonia-oxidizing community. The fact that

higher N2O fluxes were observed in gravel-mulched soils suggests that the

36

community of ammonia-oxidizers is active and that the nitrate was being denitrified

instead of being taken up by plants.

Given the nature of the molecular techniques used in this study, biases could

have been introduced in our observations. Since the same procedures were applied to

all samples, however, we are confident that the comparisons made among treatments

are valid. In the specific case of bacterial amoA quantification, a low efficiency was

obtained. Though low, the same efficiency was consistently obtained in several

assays. Further, since the data on AOB amoA abundance presented here was obtained

at the same efficiency level and with a high R2 we are confident that the low

efficiency of our assay does not compromise our conclusion that AOB abundance was

not affected by the mulching treatments evaluated here. The low efficiency of our

assay could have at worst led to a slight overestimation of AOB abundance.

Knowing the degree of the genetic and functional diversity of each microbial

group is an important aspect towards a better understanding of how ecosystems

respond to disturbances. Soils analyzed in this study were collected from a relatively

small area, but the degree of genetic diversity found among our clone library was

large. The distribution and proportional abundance of the OTUs identified at 94%

DNA similarity varied among soil cores. This data suggests a heterogeneous

distribution of the OTUs present in our soils, potentially driven by microniche

establishment (Nunan et al., 2002). Our analysis of the individual soil cores allowed

us to get insights into the spatial distribution of the individual OTUs. The two most

common OTUs were present in almost all soil cores and belonged to the same genetic

37

lineage. These two OTUs code for the same amino acid sequence, suggesting a

different evolutionary history but adaptation to the same niche. Other OTUs were

found to have limited distribution. For instance, OTU- 28, of the RSN cluster, was

found only in one soil core of the vegetated soils. Given the limited distribution of

this OTU, it is possible that had we analyzed a composite soil sample this OTU would

have been too rare to be detected using our methodology.

The fact that some OTUs varied in their predicted secondary structure also

points out potential differences in adaptation. For instance, if indeed OTU-4 has one

extra Methionine residue it might require slightly greater sulfur availability than other

OTUs, suggesting different niche adaptations. Further it was interesting to note that

the archaeal amoA sequences recovered from these Pennsylvanian soils were highly

similar to sequences recovered from different geographic areas. The most common

OTU found had 99% identity to the amoA sequence from the German soil fosmid

54d9 (Treusch et al., 2004). Several OTUs shared more than 99% similarity with

sequences recovered from Chinese soils. This pattern suggests a cosmopolitan

distribution for some OTUs. It is still to be determined whether these common OTUs

are also the most active ones in soils.

Acknowledgments

This study was supported with money provided by the Alfred P. Sloan Foundation

Minority PhD Program.

38

References

Borland, J. (1990) Mulch: Examining the facts and fallacies behind the uses and

benefits of mulch. Am. Nurseryman 172: 132-143.

Byrne, L.B. and Bruns, M.A. (2004) The effects of lawn management on soil

microarthropods. J Agr Urban Entomol 21: 150-156.

Byrne, L.B. (2006) Effects of urban habitat types and landscape patterns on

ecological variables at the aboveground-belowground interface. PhD dissertation.

The Pennsylvania State University. University Park, PA.

Byrne, L.B. (2007) Habitat structure: A fundamental concept and framework for

urban soil ecology. Urban Ecosyst 10: 225-274.

Chen, X.-P., Zhu, Y.-G., Xia, Y., Shen, J.-P., and He, J.-Z. (2008) Ammonia-

oxidizing archaea: important players in paddy rhizosphere soil? Environ Microbiol

10: 1978–1987.

Di, H.J., Cameron, K.C., Shen, J.Pl, Winefield, C.S., O‘Callaghan, M.O., Bowatte, S.,

and He, J.Z. (2009) Nitrification driven by bacteria and not archaea in nitrogen-rich

grassland soils. Nat Geosci 2: 621-624.

Felsenstein, J. (2004) PHYLIP (Phylogeny Inference Package), Version 3.6.

Distributed by the author. Seattle, WA, USA: Department of Genome Sciences,

University of Washington.

Francis, C.A., Roberts, K.J., Beman, J.M., Santoro, A.E., Oakley, B.B. (2005)

Ubiquity and diversity of ammonia-oxidizing archaea in water columns and

sediments of the ocean. Proc Natl Acad Sci USA 102: 14683-14688.

Francis, C.A., Beman, J.M., and Kuypers, M.M.M. (2007) New processes and

players in the nitrogen cycle: the microbial ecology of anaerobic and archaeal

ammonia oxidizers. ISME J 1: 19-27.

He, J.Z., Shen, J.P., Zhang, L.M., Zhu, Y.G., Zheng, Y.M., Xu, M.G. et al. (2007).

Quantitative analyses of the abundance and composition of ammonia-oxidizing

bacteria and ammonia-oxidizing archaea of a Chinese upland red soil under long-term

fertilization practices. Environ Microbiol 9: 2364–2374.

Henriksen, J. R. (2004) webLIBSHUFF (http://libshuff.mib.uga.edu)

39

Herrmann, M., Saunders, A.M., and Schramm, A. (2008) Archaea dominate the

ammonia-oxidizing community in the rhizosphere of the freshwater macrophyte

Littorella uniflora. Appl Environ Microbiol 74: 3279–3283.

Kaye, J.P., R.L. McCulley, and I.C. Burke. 2005. Carbon fluxes, nitrogen cycling,

and soil microbial communities in adjacent urban, native and agricultural ecosystems.

Global Change Biol. 11: 575-587, doi: 10.1111/j.1365-2486.s005.00921.x

Kemper, W.D., Nicks, A.D. and Corey, A.T. (1994) Accumulation of water in soils

under gravel and sand mulches. Soil Sci Am J 58: 56-63.

Kratsch, H.A. (2007) Water-wise landscaping: Mulch. Utah State University

Cooperative Extension. HG/Landscaping/2007-01pr.

Kyte,J. and Doolittle,R.F. (1982) A simple method for displaying the hydropathic

character of a protein. J Mol Biol 157: 105-132.

Leininger, S., Urich, T., Schloter, M., Schwark, L., Qi, J., Nicol, G.W. et al. (2006)

Archaea predominate among ammonia-oxidizing prokaryotes in soils. Nature 442:

806-809.

Lorenz, K. and Lal, R. (2009) Biogeochemical C and N cycles in urban soils.

Environ Int 35: 1-8.

Martens-Habbena, W., Berube, P.M., Urakawa, H., de la Torres, J.R., and Stahl, D.

(2009) Ammonia oxidation kinetics determine niche separation of nitrifying Archaea

and Bacteria. Nature 461: 976-981.

Nicol, G.W. and Schleper, C. (2005) Ammonia-oxidising Crenarchaeota: important

players in the nitrogen cycle? TRENDS Microbiology 14: 207-212.

Nicol, G.W., Leininger S., Schleper, C., and Prosser, J.I. (2008) The influence of soil

pH on the diversity, abundance and transcriptional activity of ammonia oxidizing

archaea and bacteria. Environ Microbiol 10: 2966-2978.

Nunan, N., Wu, K., Young, I.M., Crawford, J.W., and Ritz, K. (2008) In situ spatial

patterns of soil bacterial populations, mapped at multiple scales, in an arable soil.

Microb Ecol 44: 296-305.

Santoro, A.E., Francis, C.A., de Sieyes, N.R., Boehm, A.B., 2008. Shifts in the

relative abundance of ammonia-oxidizing bacteria and archaea across

physicochemical gradients in a subterranean estuary. Environ Microbiol 10, 1068-

1079.

40

Scharenbroch, B.C., Lloyd, J.E. and Johnson-Maynard, J.L. (2005) Distinguishing

urban soils with physical, chemical, and biological properties. Pedobiologia 49: 283-

296.

Schauss, K., Focks, A., Leininger, S., Kotzerke, A., Heurer, H., Thiele-Bruhn, S., et

al. (2009) Dynamics and functional relevance of ammonia-oxidizing archaea in two

agricultural soils. Environ Microbiol 11: 446-456.

Schlesinger, W.H. 2008. On the fate of anthropogenic nitrogen. Proc Natl Acad Sci

USA 106:203-208.

Schloss, P.D., and Handelsman, J. (2005) Introducing DOTUR, a computer program

for defining operational taxonomic units and estimating species richness. Appl

Environ Microbiol 71: 1501-1506.

Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., et

al. (2009) Introducing mothur: Open source, platform-independent, community-

supported software for describing and comparing microbial communities. Appl

Environ Microbiol doi:10.1128/AEM.01541-09

Singleton, D. R., Furlong, M. A., Rathbun, S. L. and Whitman, W. B. (2001)

Quantitative comparisons of 16S rDNA sequence libraries from environmental

samples. Appl Environ Microbiol 67:4373-4376.

Soil Survey Staff, Natural Resources Conservation Service, United States Department

of Agriculture. Web Soil Survey. Available online at

http://websoilsurvey.nrcs.usda.gov/

Thompson, J.D., Gibson, T.J., Plewniak, F., Jeanmougin, F., Higgins, D.G. (1997)

The CLUSTAL_X windows interface: flexible strategies for multiple sequence

alignment aided by quality analysis tools. Nucleic Acids Res 25: 4876-82.

Tiquia, S.M., Lloyd, J., Hermsb, D.A., Hoitink, H.A.J., and Michel, F.C. Jr. (2002)

Effects of mulching and fertilization on soil nutrients, microbial activity and

rhizosphere bacterial community structure determined by analysis of TRFLPs of

PCR-amplified 16S rRNA genes. Appl Soil Ecol 21: 31-48.

Tourna, M., Freitag, T.E., Nicol, G.W., and Prosser, J.I. (2008) Growth, activity and

temperature responses of ammonia-oxidizing archaea and bacteria in soil

microcosms. Environ Microbiol 10: 1357–1364.

Treusch, A.H., Kletzin, A., Raddatz, G., Ochsenreiter, T., Quaiser, A., Meurer, G., et

al. (2004) Characterization of Large-Insert DNA Libraries from Soil for

Environmental Genomic Studies of Archaea. Environ Microbiol 6: 970-980.

41

Treusch, A.H., Leininger, S., Kletzin, A., Schuster, S.C., Klenk, H.P., and Schleper,

C. (2005) Novel Genes for Nitrite Reductase and Amo-Related Proteins Indicate a

Role of Uncultivated Mesophilic Crenarchaeota in Nitrogen Cycling. Environ

Microbiol 7: 1985-1995.

United Nations World urbanization prospects: the 2007 revision. In United Nations

2007 New York, NY:United Nations

Urich, T., Lanzén, A., Qi, J., Huson, D.H., Schleper, C., Schuster, S.C. (2008)

Simultaneous Assessment of Soil Microbial Community Structure and Function

through Analysis of the Meta-Transcriptome. Plos one 3: e2527.

Venter, J. C., Remington, K., Heidelberg, J. F., Halpern, A. L., Rusch, D.,

Eisen, J. A., et al. (2004) Environmental genome shotgun sequencing of the Sargasso

Sea. Science 304: 66-74.

Vitousek, P.M., Aber, J.D. Howarth, R.W. Likens, G.E., Matson, P.A., Schindler,

D.W., et al. (1997) Human alteration of the global nitrogen cycle: sources and

consequences. Ecol Appl 7: 737-750.

Wrage, N., Velthof, G.L., van Beusichem, M.L. and Oenema, O. 2001. Role of

Nitrifer Denitrification in the Production of Nitrous Oxide. Soil Biol. Biochem. 33:

1723-1732.

42

Table 2-1. Characteristic pH, N and C content of urbanized soils at Rock

Springs, PA.

Soil Sample* pH** Moisture % N*** % C C:N

B1 6.84 0.67 0.35 4.12 11.93

B2 7.10 0.72 0.49 5.52 11.39

G1 7.76 0.66 0.32 2.84 8.97

G2 7.79 0.69 0.41 3.58 8.72

U1 6.82 0.42 0.40 3.59 9.06

U2 6.43 0.43 0.43 3.74 8.67

*B=bark mulch, G=gravel mulch, U=unmanaged vegetation; numbers indicate blocks

**In water 1:1 dilution value is average of two repeated measures of same moist soil

sample

***Total N and total C from combustion of composite soil sample from each block

soil samples were air dried

Table 2-2. Primers, probe and PCR thermal profiles used for the detection and

quantification of amoA

Target Primers/

Probe

Sequence (5‘-3‘) Amplicon

length

(bp)

Thermal profile Reference

Archaeal

amoA

Standard

PCR

19F

643R

ATGGTCTGGCTW

AGACG

TCCCACTTWGAC

CARGCGGCCATC

CA

648 94 oC 5 min, 40

cycles of 94 oC

30 sec, 55 o

C 30

sec, 68 oC 60

sec followed by

68 oC for 5 min

Leininger et

al., 2006

Archaeal

amoA

qPCR,

Taq Man

amoA508F

amoA610R

Probe 543

CCTCAGGTCGGW

AAGTTCTACA

CGGCCATCCATCT

RTATGTCCA

CGTRGCGCTAGG

ATCGGGAG

102 95 oC 10 min, 40

cycles of 95 oC

15 sec, 60 oC 1

min

This study

Bacterial

amoA

SYBR

Green

qPCR

1F

2R

GGGGTTTCTACTG

GTGGT

CCCCTCKGSAAA

GCCTTCTTC

490 95 oC 10 min, 35

cycles of 94 oC

45 sec, 56 o

C 30

sec, 72 oC 60

sec, 80.5 oC 30

sec

Santoro et

al., 2008

43

Table 2-3. Number of OTUs shared among urbanized soil treatments. Data

shown at various levels of genetic similarity.

Genetic similarity

100% 99% 97% 94% 91%

Bark

Gra

vel

Unm

anag

ed

Bark

Gra

vel

Unm

anag

ed

Bark

Gra

vel

Unm

anag

ed

Bark

Gra

vel

Unm

anag

ed

Bark

Gra

vel

Unm

anag

ed

Nucleotide

Unique OTUs 61 72 73 27 25 25 10 11 8 2 3 4 2 3 3 Shared with Gravel 9 - 6 8 - 7 6 - 4 4 - 3 1 - 1 Shared with Bark - - 8 - - 5 - - 10 - - 5 - - 4 Shared richness 12 15 10 10 9

Total richness 241 11

2 59 31 23

Amino Acid

Unique OTUs 68 64 76 21 22 31 3 3 2 0 0 0 0 0 0 Shared with Gravel 6 - 5 9 - 6 2 - 1 0 - 1 0 - 0 Shared with Bark - - 9 - - 11 - - 5 - - 2 - - 0 Shared richness 6 8 9 6 2

Total richness 234 10

8 25 9 2

44

Figure 2-1. Neighbor Joining phylogenetic tree and distribution of crenarchaeal

amoA DNA sequences representing each of the 31 OTUs obtained at 94% genetic

similarity. Environmental and cultivated amoA sequences recovered from soils, sediments

and marine environments are included as reference. Sequence labels include the clone

name|OTU#|number of sequences in OTU. Numbers in each node denote bootstrap values

for the interior branch test of phylogeny. Symbols denote the three main clusters:

square=Rock Springs Dominant; circle=Rock Springs Rare, triangle=Rock Springs

Nitrososphaera-like. Matrix next to tree shows the proportional distribution of each OTU

among soil cores. Letters denote treatment: B = bark mulch, G = gravel mulch, U =

unmanaged vegetation. Numbers after each letter indicate blocks (1 or 2), and each of the

three cores collected from each block.

U21a7ooo|12|21

EU590275_Chinese_soil

G21a30oo|18|6

G13dtp1o|10|30

DQ148868_OKR-C-4

G11dtp20|6|3

EU885662_DeepSea_Sediment

U23a47o|4|44

EF207227_FertChinese_red_soil

U22a15o|27|2

Soil_Fosmid_54d9

U21a18oo|16|13

G22atp2o|25|1

EU590527_Chinese_soil

U23atp12|22|4

U23atp33|13|4

B23d46oo|2|127

AB353450_Ag_soil

U13atp4o|1|132

G13dtp7o|5|3

B11catp8o|8|1

U12ctp17b|23|2

U13atp32|3|8

G21a50oo|11|4

G22atp33|15|9

U12ctp28|17|2

B23dtp60|21|3

U22tp25|30|2

G13dtp17|24|1

U23atp10|31|1

G22atp30|26|1

B22btp13|7|41

EU770846_Forest_soil

U12ctp32|14|2

U22tp14|19|6

U13atp6o|29|1

EU770835_CL1

DQ534815_KRO1

U22tp9o|9|4

B23dtp39|20|1

U11c9ooo|28|3

EU281319_Nitrososphaera

N.maritimus

52

99

99

99

99

99

88

75

99

94

99

84

81

99

55

99

77

22

99

94

2

96

84

90

31

99

60

95

99

98

99

92

99

49

99

4

98

B-1

-1

B-1

-2

B-1

-3

B-2

-1

B-2

-2

B-2

-3

G-1

-1

G-1

-2

G-1

-3

G-2

-1

G-2

-2

G-2

-3

U-1

-1

U-1

-2

U-1

-3

U-2

-1

U-2

-2

U-2

-3

0 0 4 0 0 4 0 0 0 24 8 4 4 4 4 16 8 4

0 0 0 0 4 12 0 0 0 8 0 0 0 0 0 0 0 0

0 4 4 10 8 8 0 0 20 0 8 36 0 0 0 12 4 4

4 0 0 0 0 0 4 0 0 0 0 0 4 0 0 0 0 0

36 4 28 0 0 0 24 8 0 20 16 4 8 12 0 0 4 8

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 4 0

0 0 0 3 0 0 0 4 0 0 16 12 0 0 0 4 4 8

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0

0 0 0 0 0 0 4 0 0 4 4 0 0 0 0 0 0 4

0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 4 0 8

29 40 48 0 12 8 36 24 20 16 16 0 64 52 88 16 20 16

14 44 16 57 12 16 16 32 32 24 12 24 24 28 36 28 56 44

4 0 0 3 0 0 0 0 4 0 0 0 0 0 0 0 0 0

4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 4 0 0 0 0 0 4 0 0 0 0

4 8 0 3 0 0 4 0 0 0 0 0 0 4 4 4 0 0

0 0 4 3 0 0 0 4 0 4 0 0 0 0 0 0 0 0

0 0 0 3 0 16 0 12 0 0 4 0 0 0 0 0 0 0

0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0

0 0 0 0 0 4 0 0 0 0 4 0 0 4 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0

0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0

4 0 0 7 60 16 4 12 16 0 16 8 0 0 0 12 0 8

0 0 4 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0

0 0 0 0 0 8 0 0 0 0 0 0 0 4 4 0 4 4

0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0

4 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 4 0

0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0

% of Sequences

0-10

11-20

21-30

31-40

41-50

>51

U21a7ooo|12|21

EU590275_Chinese_soil

G21a30oo|18|6

G13dtp1o|10|30

DQ148868_OKR-C-4

G11dtp20|6|3

EU885662_DeepSea_Sediment

U23a47o|4|44

EF207227_FertChinese_red_soil

U22a15o|27|2

Soil_Fosmid_54d9

U21a18oo|16|13

G22atp2o|25|1

EU590527_Chinese_soil

U23atp12|22|4

U23atp33|13|4

B23d46oo|2|127

AB353450_Ag_soil

U13atp4o|1|132

G13dtp7o|5|3

B11catp8o|8|1

U12ctp17b|23|2

U13atp32|3|8

G21a50oo|11|4

G22atp33|15|9

U12ctp28|17|2

B23dtp60|21|3

U22tp25|30|2

G13dtp17|24|1

U23atp10|31|1

G22atp30|26|1

B22btp13|7|41

EU770846_Forest_soil

U12ctp32|14|2

U22tp14|19|6

U13atp6o|29|1

EU770835_CL1

DQ534815_KRO1

U22tp9o|9|4

B23dtp39|20|1

U11c9ooo|28|3

EU281319_Nitrososphaera

N.maritimus

52

99

99

99

99

99

88

75

99

94

99

84

81

99

55

99

77

22

99

94

2

96

84

90

31

99

60

95

99

98

99

92

99

49

99

4

98

B-1

-1

B-1

-2

B-1

-3

B-2

-1

B-2

-2

B-2

-3

G-1

-1

G-1

-2

G-1

-3

G-2

-1

G-2

-2

G-2

-3

U-1

-1

U-1

-2

U-1

-3

U-2

-1

U-2

-2

U-2

-3

0 0 4 0 0 4 0 0 0 24 8 4 4 4 4 16 8 4

0 0 0 0 4 12 0 0 0 8 0 0 0 0 0 0 0 0

0 4 4 10 8 8 0 0 20 0 8 36 0 0 0 12 4 4

4 0 0 0 0 0 4 0 0 0 0 0 4 0 0 0 0 0

36 4 28 0 0 0 24 8 0 20 16 4 8 12 0 0 4 8

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 4 0

0 0 0 3 0 0 0 4 0 0 16 12 0 0 0 4 4 8

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0

0 0 0 0 0 0 4 0 0 4 4 0 0 0 0 0 0 4

0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 4 0 8

29 40 48 0 12 8 36 24 20 16 16 0 64 52 88 16 20 16

14 44 16 57 12 16 16 32 32 24 12 24 24 28 36 28 56 44

4 0 0 3 0 0 0 0 4 0 0 0 0 0 0 0 0 0

4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 4 0 0 0 0 0 4 0 0 0 0

4 8 0 3 0 0 4 0 0 0 0 0 0 4 4 4 0 0

0 0 4 3 0 0 0 4 0 4 0 0 0 0 0 0 0 0

0 0 0 3 0 16 0 12 0 0 4 0 0 0 0 0 0 0

0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0

0 0 0 0 0 4 0 0 0 0 4 0 0 4 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0

0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0

4 0 0 7 60 16 4 12 16 0 16 8 0 0 0 12 0 8

0 0 4 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0

0 0 0 0 0 8 0 0 0 0 0 0 0 4 4 0 4 4

0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0

4 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 4 0

0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0

% of Sequences

0-10

11-20

21-30

31-40

41-50

>51

U21a7ooo|12|21

EU590275_Chinese_soil

G21a30oo|18|6

G13dtp1o|10|30

DQ148868_OKR-C-4

G11dtp20|6|3

EU885662_DeepSea_Sediment

U23a47o|4|44

EF207227_FertChinese_red_soil

U22a15o|27|2

Soil_Fosmid_54d9

U21a18oo|16|13

G22atp2o|25|1

EU590527_Chinese_soil

U23atp12|22|4

U23atp33|13|4

B23d46oo|2|127

AB353450_Ag_soil

U13atp4o|1|132

G13dtp7o|5|3

B11catp8o|8|1

U12ctp17b|23|2

U13atp32|3|8

G21a50oo|11|4

G22atp33|15|9

U12ctp28|17|2

B23dtp60|21|3

U22tp25|30|2

G13dtp17|24|1

U23atp10|31|1

G22atp30|26|1

B22btp13|7|41

EU770846_Forest_soil

U12ctp32|14|2

U22tp14|19|6

U13atp6o|29|1

EU770835_CL1

DQ534815_KRO1

U22tp9o|9|4

B23dtp39|20|1

U11c9ooo|28|3

EU281319_Nitrososphaera

N.maritimus

52

99

99

99

99

99

88

75

99

94

99

84

81

99

55

99

77

22

99

94

2

96

84

90

31

99

60

95

99

98

99

92

99

49

99

4

98

B-1

-1

B-1

-2

B-1

-3

B-2

-1

B-2

-2

B-2

-3

G-1

-1

G-1

-2

G-1

-3

G-2

-1

G-2

-2

G-2

-3

U-1

-1

U-1

-2

U-1

-3

U-2

-1

U-2

-2

U-2

-3

0 0 4 0 0 4 0 0 0 24 8 4 4 4 4 16 8 4

0 0 0 0 4 12 0 0 0 8 0 0 0 0 0 0 0 0

0 4 4 10 8 8 0 0 20 0 8 36 0 0 0 12 4 4

4 0 0 0 0 0 4 0 0 0 0 0 4 0 0 0 0 0

36 4 28 0 0 0 24 8 0 20 16 4 8 12 0 0 4 8

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 4 0

0 0 0 3 0 0 0 4 0 0 16 12 0 0 0 4 4 8

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0

0 0 0 0 0 0 4 0 0 4 4 0 0 0 0 0 0 4

0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 4 0 8

29 40 48 0 12 8 36 24 20 16 16 0 64 52 88 16 20 16

14 44 16 57 12 16 16 32 32 24 12 24 24 28 36 28 56 44

4 0 0 3 0 0 0 0 4 0 0 0 0 0 0 0 0 0

4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 4 0 0 0 0 0 4 0 0 0 0

4 8 0 3 0 0 4 0 0 0 0 0 0 4 4 4 0 0

0 0 4 3 0 0 0 4 0 4 0 0 0 0 0 0 0 0

0 0 0 3 0 16 0 12 0 0 4 0 0 0 0 0 0 0

0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0

0 0 0 0 0 4 0 0 0 0 4 0 0 4 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0

0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4

0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0

4 0 0 7 60 16 4 12 16 0 16 8 0 0 0 12 0 8

0 0 4 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0

0 0 0 0 0 8 0 0 0 0 0 0 0 4 4 0 4 4

0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0

4 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 4 0

0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0

% of Sequences

0-10

11-20

21-30

31-40

41-50

>51

45

Estimated OTU richness based on Chao1 for amino acid and nucleotide data

1

10

100

1000

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Genetic distance

Est

ima

ted

nu

mb

er

of

OT

Us

Bark NT Gravel NT Unmanaged NT Bark AA Gravel AA Unmanaged AA

Figure 2-2. Expected (A) and estimated (B) number of OTUs for each urbanized soil

treatment as a function of amino acid genetic distance. Closed symbols represent values

obtained using DNA sequences, while open symbols represent values obtained using amino

acid sequences. Circles, squares, and triangles indicate sequences recovered from bark-

mulched soils, gravel mulched soils and soils under unmanaged vegetation, respectively.

A

B

Estimated number of OTUs for each treatment as a function of genetic distance

based on amino acid and nucleotide data

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Amino acid distance

Esti

mate

d n

um

ber

of

OT

U

Bark Gravel Unmanaged Bark NT Gravel NT Unmanaged NT

46

Figure 2-3. Number of synonymous (gray) or non-synonymous (black)

substitutions per codon site estimated using HyPhy in MEGA5 and sequences

representing each of the 31 OTUs found at 94% DNA similarity. The sites where

there are many non-synonymous substitutions correspond to the most variable sites.

0

2

4

6

8

10

12

14

16

18

20

1 9 17 25 33 41 49 57 65 73 81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201

Codon site

Num

be

r of

su

bstitu

tio

ns p

er

site

synonimous inferred nonsynonimous inferred

47

Figure 2-4. Rarefaction curves based on 0.0 amino acid genetic distance using

the BLOSUM 32 weight matrix. Overlapping 95% Confidence Intervals not shown

for clarity.

Rarefaction curves for all treatments

0

20

40

60

80

100

120

0 20 40 60 80 100 120 140 160 180 200

Number of sequences

Exp

ecte

d n

um

ber

of

OT

Us

Bark

Gravel

Unmowed

1:1 line

Linear (1:1 line)

48

Figure 2-5. Community structure analysis of archaeal amoA clone libraries

recovered from urbanized soils and soils under the original unmanaged

vegetation at 100% amino acid similarity. The number of unique OTUs found in

each clone library is shown under the labels. Numbers in italics indicate OTUs

shared between clone libraries. P-values obtained after analysis of homologous vs.

heterologous clone libraries using Web-Libshuff are shown in parenthesis.

Bark mulch Gravel mulch

Unmanaged

vegetation

6

6

68 64

9 5

76

(0.004,

0.847)

(0.123,

0.652)

(0.629,

0.007)

Bark mulch Gravel mulch

Unmanaged

vegetation

6

6

68 64

9 5

76

(0.004,

0.847)

(0.123,

0.652)

(0.629,

0.007)

49

Figure 2-6. Abundance of archaeal (AOA) and bacterial (AOB) amoA per gram of dry

soil in mulched and vegetated soils. Error bars indicate two standard error of the mean (n =

5), while similar letters indicate significance at the 0.05 level.

50

Figure 2-7. Secondary structure predictions for amoA protein of the most common

OTUs found in the urbanized soils and corresponding alignment. Positive values

indicate hydrophobic regions, most likely present in the interior of the membrane. Negative

values indicate hydrophilic regions. Scores for OTU-1, 4, 7 and 10 overlapped with the

scores of fosmid Cren54d9, except where the different lines are visible. Note that OTU-1 and

OTU-2 in Fig 1 code for the same amino acid sequence.

Hydropathicity plots for common OTUs

-3

-2

-1

0

1

2

3

4

5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 155 165 175 185 195

Amino acid position

Sco

re

OTU-1 OTU-10 OTU-4 OTU-7 Nitrosopumilus Cren54d9

OTU-1

Fosmid 54d9

OTU-4

OTU-7

OTU-10

Nitrosopumilus

ruler

OTU-1

Fosmid 54d9

OTU-4

OTU-7

OTU-10

Nitrosopumilus

ruler

OTU-1

Fosmid 54d9

OTU-4

OTU-7

OTU-10

Nitrosopumilus

ruler

OTU-1

Fosmid 54d9

OTU-4

OTU-7

OTU-10

Nitrosopumilus

ruler

51

Chapter 3. Responses of archaeal and bacterial ammonia oxidizers in mulched

and vegetated soils at different temperatures

Abstract

Urbanization is increasing worldwide. In developed countries, this increase is

accompanied by an increase in landscaped areas. Mulching is a common landscaping

practice which causes soil biogeochemical cycling to be microbially driven rather

than plant-driven. The effects of mulching on ammonia oxidizers, an important group

involved in nitrogen cycling, were investigated in this controlled greenhouse study.

The ammonia oxidizers carry out the first step in nitrification, the oxidation of

ammonia to nitrite. Changes in abundance of ammonia oxidizing prokaryotes (AOP),

including bacteria and archaea, were measured following application of bark and

limestone gravel mulch to soils and compared to grass-sown and bare soil (fallow).

Soil covers were evaluated at two temperatures, 18 and 28 °C, simulating spring and

summer day temperatures, respectively. AOP abundance was assessed based on

numbers of gene copies of ammonia monooxygenase subunit A (amoA) using

quantitative PCR, and evaluating soils after 34, 68, and 102 days of incubation.

Potential nitrification and soil variables such as pH, moisture, and ammonium and

nitrate concentration were measured. Abundance of AOP was affected by soil cover

and temperature of incubation and varied over time. In general, greater abundance of

AOP was observed in mulched soils than in bare soil. At 18 °C, the abundance of

ammonia-oxidizing bacteria (AOB) increased over time in mulched soils, while

abundance of ammonia-oxidizing archaea (AOA) decreased after 68 days in all soils.

52

Despite the AOA decline at 18 °C, potential nitrification was correlated with

abundance of AOA amoA gene copies. Further, at 102 days, transcriptional activity

of AOA amoA was greater at 18°C than at 28°C. Our results suggest that nitrification

was driven by AOA in these soils. Further, mulching may help increase AOP

abundance, a factor that can negatively impact N retention in soil and the

concentration of N in urban runoff.

Introduction

Projected increases in urbanization worldwide (United Nations, 2008) will likely

exacerbate global change. Extensive, vegetation-free areas covered by pavement and

other impermeable surfaces create heat island effects that increase energy demand for

cooling buildings. Higher temperatures in urban areas can be moderated by the

establishment of gardens, parks, and artificial landscapes which often incorporate the

use of mulches to retain moisture in soils. Organic mulches like bark chips or

composts promote lower soil temperatures than those of bare soil (Long et al., 2001).

Inorganic mulches like gravel or sand, on the other hand, may result in increased soil

temperatures (Byrne, 2006, Iles and Dosman, 1999).

In addition to affecting soil temperatures, the type of mulch applied to soils

can influence biogeochemical processes like N cycling (Byrne, 2007; Lorenz and Lal,

2008). Whereas inorganic mulches do not add organic matter to the soil, organic

mulches provide a source of organic carbon that can enhance soil microbial activity

53

and organic matter mineralization (Valenzuela-Solano, et al., 2005). Biogeochemical

processes in vegetation-free, mulched soils are driven mainly by microorganisms, and

the interaction between mulch treatment and temperature in urban areas is expected to

affect soil microbial community activity and composition. Soil microorganisms

responsible for nitrogen (N) cycling are of particular interest because they affect the

amounts of soil N lost through denitrification and runoff.

A key step for N cycling in soil is the oxidation of ammonia to nitrite, the first

and rate-limiting step of nitrification. Through the reactions involved in nitrification,

nitrate, a mobile form of nitrogen is produced. An excess of nitrate in soil can be lost

readily by leaching to groundwater, thus reducing its quality. Further, atmospheric

greenhouse gases can be affected since nitrous oxide is a potential byproduct of

nitrification. In soil, the oxidation of ammonia is carried out by specialized groups of

organisms which possess the enzyme ammonia monooxygenase. Ammonia-oxidizing

prokaryotes (AOP) comprise representatives of both bacteria and archaea. To date,

only cultures of ammonia-oxidizing bacteria (AOB) belonging to the beta-subdivision

of Proteobacteria have been recovered from soils, and the genus Nitrosospira is

typically detected more frequently than Nitrosomonas spp. (Fierer et al., 2009). The

newly recognized ammonia-oxidizing archaea (AOA), however, are reported to be

even more abundant than AOB in many soils (Leininger et al., 2006; Mincer et al.,

2007). The recent discovery that AOA are ubiquitous and abundant has generated

great interest in understanding which environmental factors affect this group and its

ammonia-oxidizing activities (Francis et al., 2007).

54

Temperature is known to affect biological processes and is associated with

changes in local biodiversity (Andrews et al., 2000). In a microcosm study conducted

by Tourna et al. (2008) a change in the community structure of active AOA was

observed in response to increasing soil temperature. Further, Avrahami et al. (2003)

found a relationship between increasing soil temperature and AOB community

composition, with sequences belonging to various Nitrosospira clusters dominating at

different temperatures. At a global scale, the biogeography of AOB was found to be

affected most strongly by temperature regime (Fierer, et al., 2009). As temperatures

increase under global climate change, there is a need to understand how processes

such as nitrification and the microorganisms responsible respond to changes in soil

temperature (Barnard et al., 2005).

Mulched and vegetated soils, which had been experimentally established by

Byrne et al. (2006), were found to differ in AOA abundance and community

composition (Martir and Bruns, 2010, i.e. Chapter 2). Three years following

vegetation removal and mulch application, AOA abundance was lower in soils under

bark mulch than in soils under gravel mulch or unmanaged vegetation, while AOB

abundance was not affected by treatment cover. Further, gravel-mulched soils

harbored a different AOA community than soils under bark mulch or unmanaged

vegetation. In this study, we investigated the combined effects of mulching and soil

temperature on the abundance and activity of AOP. Two soil temperatures were

evaluated, 18˚C and 28˚C, chosen to represent spring and summer day temperatures

in temperate regions, respectively. Based on the results obtained in the field study by

55

Martir and Bruns (2010), we hypothesized a reduction in AOA abundance in bark

mulched soils but no alteration in AOB abundance.

Methodology

Treatment establishment and sampling

Soils for this study were collected from two unmanaged vegetation plots

where both AOA and AOB had been detected previously (Martir and Bruns, 2010).

The study site used by Martir and Bruns (2010) had been an unmanaged oldfield prior

to the establishment of urbanized plots in 2003 by Byrne (2006). Thus, the Opequon

silty clay loam soil with unmanaged vegetation harbored the soil community in long-

term residence at the site and represented soil conditions prior mulching. Soil was

collected with an ethanol-treated shovel from four random locations in the old field

plots after digging up plants and separating soil from plant roots. The soil was

mixed, air dried, and passed through a sterile 2 mm sieve. One kilogram of re-mixed,

sieved soil was placed in each of the 32 pots used for this study (four replicated plots

per treatment). Each pot had a diameter of 15 cm and a volume of 1750 mL, and was

wiped cleaned with ethanol before use. Prior to treatment establishment soil in each

pot was wetted to 35% (w/v) water content by adding 35 g of water for every 100 g of

soil. All pots were pre-warmed for one day, after which time two soil samples were

collected for initial chemical analysis (as described below). Four soil covers were

evaluated: bark mulch (Timberline pine bark nuggets), gravel mulch (Vigoro

56

decorative stone marble chips), lawn and fallow. Both bark and gravel mulches were

autoclaved once prior to application, and were applied to a depth of 4 cm. A tall

fescue (Festuca arundinacea) seed mix (Pennington Seed, Madison, GA) was used

for lawn treatments. Lawn was maintained at a height of 4 cm by regular clipping of

the grass. The fallow treatment consisted of pots with bare soil. Treatments were

established in a randomized complete block design with four replications per

treatment at each temperature regime. The two day/night temperature regimes were

18/8˚C and 28/18˚C, with a day length of 14 hours. Full coverage of soil surfaces

with grass was established after two weeks for the 18˚C chamber and after four weeks

for the 28˚C chamber. Volunteer seedlings germinating in all other pots, but the lawn

treatment, were removed within 3 days of emergence.

To maximize aerobic conditions, all pots were maintained at 35% (w/v) water

content through the experiment. Soil moisture in the pots was monitored every 72 hrs

by weighing each pot. Sufficient sterile water was added to replace that lost by

evaporation or evapotranspiration. Changes in moisture content occurring over each

72-hour period were recorded.

At 34, 68 and 102 days since treatment establishment, all pots were sampled.

At each sampling time the following was measured: soil temperature, moisture, pH,

potential nitrification rate, and the abundance of bacterial and archaeal amoA genes.

Soil temperature was measured in situ using a soil thermometer (Cal-Temp Quick-

Reading Calibrateable Digital Thermometer) sterilized with ethanol between

measurements. Approximately 20 g of soil were aseptically collected per pot, and

57

stored in a cooler with ice until processing. Soil genomic DNA and RNA were

extracted immediately after sampling (see below). Soils used for potential

nitrification measurements and chemical analyses were stored at 4ºC for no longer

than three days.

One of the grass-sown pots incubated at 28˚C had an unidentified fungal

infection causing necrosis and stunting of the grass. This pot was removed from the

experiment after 86 days since treatment establishment to prevent the spread of the

fungus to other pots with grass.

Soil chemical analyses

Soil chemical analyses were conducted at the beginning and end of the experiment to

measure total C and N, organic matter content, CEC, ammonium, and nitrate (Table

3-1). Air dried, soil samples composited from the four pots per treatment were sent to

the Agricultural Analytical Services Laboratory at Penn State University, and

analyzed following standard procedures. Gravimetric soil moisture was determined

after drying soil for 24 hr at 105˚C. Soil pH was measured using dried samples in a

1:2 solution in water.

Potential nitrification assay

Potential nitrification was measured using the shaken soil slurry method as described

by Hart et al. (1994). This method is based on the incubation of soil in an ammonium

phosphate solution for about 24 hours. Sufficient ammonium (1 mM) is provided to

58

inhibit immobilization, while denitrification is inhibited by keeping the slurry aerobic.

Nitrate content was measured four times during the incubation period, at 2, 4, 22, and

24 hours. Nitrate concentration was determined colorimetrically after reduction to

nitrite using the nitrate reductase enzyme (Nitrate Elimination Company, Inc., Lake

Linden, MI) Manufacturer‘s instructions were followed and a standard curve was

created using ammonium phosphate solution with known nitrate concentrations

ranging from 1 to 10 ppm.

Nucleic acid extraction and quantitative RT-PCR

Nucleic acids were extracted from approximately 2 g of field-moist soil. The MoBio

RNA PowerSoil® Total RNA Isolation Kit was used following manufacturer‘s

instructions. DNA was extracted from the same sample using the RNA PowerSoil®

DNA Elution Accessory Kit. RNA and DNA concentration of all samples was

determined using a NanoDrop 1000 Spectrophotometer (Thermo Fisher Scientific

Inc.).

Due to technical limitations, only the RNA extracted at 102 days was reverse

transcribed to cDNA. For each sample, 1 μg of extracted RNA was treated with

DNase using the TURBO DNA-freeTM

Kit from Applied Biosystems. DNase

treatment was immediately followed by reverse transcription using the High Capacity

cDNA Reverse Transcription Kit from Applied Biosystems. Two negative controls

were included in the reaction. The first control contained all reagents except the

reverse transcriptase enzyme. This control was used to determine the presence of

59

contaminant DNA in the final cDNA. The second control contained all reagents and

no template.

Archaeal amoA gene abundance in soil genomic DNA and transcript

abundance in cDNA was determined using probe amoA543 from the study by Martir

and Bruns (2010, e.i, Chapter 2). Duplicate samples and a standard curve ranging

from 104 to 10

8 gene copies were used for the assays. Each reaction had a final

volume of 25 μL and contained 9 ng of DNA, 0.4 μM of each primer, 0.2 μM of

probe and 12.5 μL of TaqMan® Universal PCR Master Mix, No AmpErase® UNG

(Applied Biosystems). The standard curve used for amoA quantification was

constructed using a dilution series of a 1:1 mix of DNA from two transformed

plasmids. Slopes ranging from -3.35 to -3.51 and R2>0.99 were obtained for DNA

quantification. For cDNA obtained at 102 days, a slope of -3.90 and an R2>0.99 were

obtained.

Quantification of bacterial amoA was performed using SYBR Green

chemistry, primers 1F and 2R (Table 3-2), and an ABI 7500 Sequence Detection

System. Each reaction had a final volume of 10 μL, and contained 9 ng of DNA, 0.2

μM of each primer and 5 μL of Maxima™ SYBR Green qPCR Master Mix

(Fermentas Inc., Glen Burnie, MD, USA). The specificity of the products was

assessed using melting curve analysis and gel electrophoresis. A ten-fold dilution

series of a known concentration of plasmid DNA containing a bacterial amoA insert

recovered from soil was used to create a standard curve over seven orders of

magnitude of concentration (3 ×102 to 3 × 10

7 gene copies). Standard curve slopes

60

ranged from -3.75 to -3.78 and r2 was 0.99. AOB amoA was not detected in the cDNA

of samples collected at 102 days. Thermal profiles for both assays are shown in

Table 3-2.

Statistical analysis

Longitudinal data were analyzed using repeated measures analysis in SAS 9.1

(Appendix E). The goodness of fit of the covariance structure selected based on the

Akaike‘s information criterion (AIC). Other linear regressions and analyses of

variance were done using SPSS 17.0. An alpha of 0.05 was used for all tests.

Results

Abundance of prokaryotic ammonia oxidizers

Copy numbers of amoA genes from AOA and AOB exhibited contrasting temporal

patterns, and they were affected in different ways by soil cover (Fig 3-1). The

abundance of archaeal and bacterial amoA at the beginning of the experiment was 5.5

× 107 copies/g dry soil and 1.8 × 10

5 copies/g dry soil, respectively. On Day 34 at

18˚C, abundances of AOB and AOA were similar in all 4 treatments. On Days 68

and 102 at18˚C, AOB abundance had increased in mulched soils but declined in soils

under grass and fallow (Fig 3-1a). At the same temperature, AOA abundance was

similar in all treatments, decreasing between Day 34 and Day 68 and then increasing

again at Day 102 (Fig 3-1b). On Day 34 at 28˚C, both AOB (Fig 3-1c) and AOA (Fig

3-1d) showed higher gene abundance under bark mulch than the other 3 treatments.

61

On Day 68, however, AOA gene abundance had declined sharply at 28C and

remained at levels comparable to those in the other treatments (Fig 3-1d). The ratios

of AOA:AOB gene abundance were significantly affected by soil temperature but

response varied with sampling date (Fig 3-2). At Day 34 this ratio was slightly lower

at 28˚C compared to 18˚C. Compared to Day 34, soils incubated at both temperatures

showed decreased AOA:AOB ratios on Days 68 and 102.

In the cDNA of samples collected on Day 102, amoA transcripts were

detected from AOA but not from AOB. Log-transformed values of AOA amoA

transcripts were significantly lower in all soils incubated at 28˚C than at 18˚C (Fig 3-

3). Average numbers of transcripts per gram of dry soil across all treatments at 18˚C

and 28°C were 1.2×105 and 4.6×10

4, respectively. In contrast to temperature, soil

cover did not affect the abundance of AOA amoA transcripts.

Potential nitrification

Potential nitrification was relatively low, but detectable. It was affected by the

interaction between soil cover, temperature, and sampling date. Soils under fallow

had the lowest potential nitrification (Fig 3-4a). At 18˚C there was a sharp decline in

potential nitrification after 34 days, and values remained low until the completion of

the experiment. In contrast, at 28˚C there was a significant increase in potential

nitrification for soils under lawn and gravel mulch. A positive and significant

correlation was found between AOA gene copy abundance and potential nitrification

in soils incubated at 18ºC (Fig 3-5).

62

Soil pH

Soil pH values were highly variable and significantly affected by soil temperature.

The interaction between soil cover and sampling date was significant (Fig 3-4b). As

expected, soils under gravel mulch tended to have higher pH, while soils under fallow

had the lowest pH. There was a general tendency for pH to decrease with incubation

time. At Day 102 pH values for soils under bark mulch and fallow were lower at

28˚C than at 18˚C.

Soil moisture

Even when an effort was made to keep soil moisture constant throughout the

experiment, variations were observed, with a significant interaction observed between

soil cover, temperature and sampling date (Fig 3-4c). Moisture was generally higher

in mulched soils. At 18˚C mulched plots rarely needed watering (data not shown).

Soils under grass and fallow experienced greater fluctuations in soil moisture than

mulched soils. These results confirm the effectiveness of mulching in retaining soil

moisture.

In situ soil temperature

Data for in situ soil temperature was evaluated separately for both temperatures. At

18˚C in situ soil temperature was significantly affected by soil cover and sampling

date, while at 28˚C only an interaction between these two factors was observed for

63

soil temperature (Fig 3-4d). Cooler in situ temperatures were maintained under bark

mulch than under gravel mulch at both chamber temperatures and across sampling

dates. Soils incubated at 28˚C exhibited higher temperatures at Day 34 than on the

other two sampling dates.

Ammonium and nitrate concentration at Day 102

Soils in this study received no inorganic N amendment. The parent soil had an

ammonium concentration of 2.73 ppm at the beginning of the experiment. After 102

days, detectable ammonium dropped to values ranging from 0.48-0.50 and from 0.34-

0.36 in soils incubated at 18˚C and 28˚C, respectively (Table 3-1). Contrastingly,

nitrate concentrations varied among covers and temperatures. At the beginning of the

experiment, the nitrate concentration of the parent soil was 11.2 ppm. After 102 days,

nitrate concentrations ranged from 4.78-27.69 ppm and from 2.43-35.49 ppm in soils

incubated at 18˚C and 28˚C, respectively (Table 3-1). Soils under bark mulch and

fallow showed an increase in the amount of detectable nitrate compared to the other

treatments. In contrast, nitrate decreased sharply in soils under lawn, suggesting plant

uptake or microbial immobilization.

Discussion

Homeowners and commercial landscapers incorporate bark and gravel

mulching into their landscaping practices to create gardens that are both eye-pleasing

and low in maintenance. With an increase in urban areas worldwide, areas covered

64

by lawns and mulches are expected to expand. This study has shown for the first time

how AOP abundance responds to the combined effects of urban soil cover and

contrasting soil temperatures. Our results can be summarized as three key findings.

First, regardless of soil cover or temperature, AOP abundance had a tendency to be

higher in mulched soils compared to soils under lawn or fallow. Second, AOP

abundance was in general higher in soils incubated at 18ºC compared to 28ºC;

nevertheless, the drop in abundance at 28 ºC was delayed in bark-mulched soils.

Finally, AOA seemed to drive potential nitrification in soils incubated at 18 ºC.

In general, bark and gravel mulch created soil conditions that favored a

greater abundance of both AOA and AOB, in particular, when compared with soils

under fallow. The beneficial effects of mulching were more evident for AOB since a

constant increase was observed in soils incubated at 18ºC. In terms of AOA, our

results failed to support the hypothesis of a reduction in AOA abundance under bark

mulch when compared to gravel-mulched or vegetated soils. Nevertheless, in the

study conducted by Martir and Bruns (2010) the soils evaluated had been under bark

mulch for three years. Bark-mulched soils had a higher C:N ratio, ranging from 11.4

to 12.0, than soils under gravel or unmanaged vegetation, which ranged from 8.67-

9.06. Higher C:N ratios can have a negative effect on N mineralization, and

nitrification rates may depend strongly on N mineralization (Booth et al 2005). In

this study the soils were monitored for a short period of time, and a change in C:N

was not observed. Thus, bark mulch may be detrimental for ammonia oxidizer

65

abundance only after prolonged application, when sufficient decomposition of the

bark leads to a high C:N ratio.

While few studies have investigated mulching effects on soil microorganisms,

mulching has been found to promote the activity of soil macroinvertebrates.

Increased abundance of millipedes, centipedes, segmented worms, beetles, and

spiders has been found in mulched soils compared to bare soil (Jordan and Jones,

2006). Long et al. (2001) found greater termite activity under soils mulched with pea

gravel than bare soils. Further, Byrne (2006) noted greater abundance of earthworms

in bark-mulched soils compared to gravel-mulched soils, and soils under lawn and

unmanaged vegetation. Thus, mulching can be expected to affect soil communities at

different trophic levels.

In this study, greater AOP abundances were detected at 18 ºC, with the most

significant change observed for AOA. This finding was not surprising as the summer

temperatures for this soil were reported to fluctuate around 20 ºC (Byrne, 2006).

Therefore, the native AOP should be adapted to this temperature regime. Potential

nitrification rates were higher at 18 ºC after 34 days of incubation, indicating that

incubation at 28 ºC resulted in lower potential nitrification. In a meadow soil,

Avrahami et al. (2003) found potential nitrification rates to be higher at temperatures

ranging from 10 and 25˚C than at either 4˚C or 37˚C. Contrastingly, Tourna et al.

(2008), after incubating soil for 55 days, found greater nitrate production at 30 ºC.

Optimal nitrification rates have been predicted to be in the range of 20-37 ºC (Stark,

1996). In the present study, potential nitrification rates in soils incubated at 18 ºC

66

were significantly correlated with AOA abundance. After 34 days of incubation at 28

ºC, abundance of AOA dropped significantly as did potential nitrification. Therefore,

even when nitrification may be optimal at temperatures such as 28 ºC, it seems that at

this temperature the most abundant AOP population in our soil was not large enough

to support nitrification rates comparable to those of the soils incubated at 18 ºC.

Here, the beneficial effects of bark mulch were more pronounced at 28ºC, as

bark mulch appeared to delay the decrease in AOP abundance. The mechanisms by

which bark mulching helped mitigate the effects of high temperature on AOP

abundance are not clear from these data. However, at both temperature regimes, soils

under bark mulch tended to have slightly lower temperatures than soils under gravel

mulch. Further, mulched soils helped maintain a constant and higher soil moisture

level. Both temperature and moisture are known to affect AOB (Stark and Firestone,

1995). Avrahami and Bohannan (2007) found an overall increase in soil AOB with

increasing soil moisture and a decrease with increasing soil temperature. Further,

Hastings et al. (2000) found a significant reduction in AOB abundance under

moisture limitation. The slightly cooler temperatures and the constant moisture level

might have helped keep N mineralization constant, providing a more continuous

supply of substrate for AOP. An alternative explanation is that these factors may

have allowed a higher number of AOP to survive longer, even when inactive.

Our data suggested that AOA were driving potential nitrification in soils

incubated at 18 ºC. A correlation between potential nitrification and AOA abundance

is an indication that this group contributes more to nitrification than do AOB (He et

67

al., 2008). However, it is important to keep in mind that the amoA probe used here is

not expected to target all soil AOA. Rather, it targets the most commonly recovered

OTUs found in the Rock Springs soils evaluated here (Martir and Bruns, 2010).

Thus, the possibility remains that a stronger correlation or no correlation would have

been found had we been able to analyze the entire community of soil AOA.

Nonetheless, further evidence to support the active role of AOA in driving potential

nitrification rates comes from the lack of detection of AOB amoA transcripts in the

RNA recovered on Day 102. AOB may have been active in these soils, but at

transcript levels below our detection limit.

Active nitrification in our soils was also evidenced by the net ammonium

consumption and nitrate production data. After 102 days, ammonium concentration

dropped at both temperatures. Though AOA were found to be active in these soils,

this decrease in ammonium could have resulted from a combination of factors

including oxidation by AOP, immobilization by heterotrophs, or plant uptake in soils

planted with grass. Contrastingly, nitrate concentrations were highly variable. On

Day 102, bark mulched and fallow soils, which had lower pH than the other two

treatments, had the highest nitrate concentrations. Increased acidity in soils may have

resulted from a high rate of oxidative reactions such as those involved in nitrification.

Further, it is possible that the low pH could have caused an increase in the

protonation of amphoteric functional groups in soil particles (Toner et al. 1989). This

increase in protonated groups may have lead to greater nitrate adsorption and

retention in soil, thus allowing detection of higher nitrate concentrations. The lower

68

nitrate concentration found in gravel-mulched soils, suggests potential loss due to

denitrification. Byrne (2006) noted greater N2O flux in gravel mulched soils.

Gravel-mulched soils in this study had moisture and pH levels that are conducive to

denitrification, in particular nitrifier denitrification (Wrage et al., 2001). Plant uptake

may explain the low nitrate concentration found in soils planted with grass.

This study has shown that bark and gravel mulching not only affects N

cycling, as previously reported (Byrne, 2007), but also AOP abundance. In addition,

our results show that soil AOA abundance and transcriptional activity were lower at

28 ºC than at 18 ºC. Although the factors responsible for the effects of mulching on

AOA and AOB abundance could not be clearly identified, it is likely that mulching

helps support greater AOP abundance through maintaining more constant moisture

levels in soil. In urban soils, where temperatures are expected to be higher than in

forested land, the use of bark mulch may help mitigate temperature increases and

favor abundance of AOP. The increase in AOP in mulched soils coupled with active

nitrification point to the potential for greater nitrate production in these soils, in

particular during the spring time when temperatures are lower than during the

summer. Nitrogen from fertilized lawns and gardens has been found to be a

significant component of urban watershed budgets (Groffman et al 2004, Law et al

2004). Law et al (2004) estimated fertilizer application rates of 97.6 kg N/ha/yr with

a standard deviation of 88.3 kg N/ha/yr in residential areas of a suburban watershed in

Maryland, USA. Given that bark and gravel mulching typically accompany lawns in

common residential gardens the positive effects of mulching on AOP abundance may

69

contribute to N loss and degradation of groundwater quality. Further studies looking

at leachates from mulched soils are needed to determine the impact of mulching on

nitrate leaching and to make recommendations for homeowners and commercial

landscapers.

Acknowledgements

Funding for this research was obtained from the Alfred P. Sloan Foundation Minority

Ph.D. Program

References

Andrews, J.A., Matamala, R., Westover, K.M., Schlesinger, W.H., 2000.

Temperature effects on the diversity of soil heterotrophs and the delta C-13 of soil-

respired CO2. Soil Biology & Biochemistry 32, 699-706.

Avrahami, S., Bohannan, B.J.A., 2007. Response of Nitrosospira sp. strain AF-like

ammonia oxidizers to changes in temperature, soil moisture content, and fertilizer

concentration (vol 73, pg 1166, 2007). Applied and Environmental Microbiology 73,

3121-3121.

Avrahami, S., Conrad, R., 2003. Patterns of community change among ammonia

oxidizers in meadow soils upon long-term incubation at different temperatures.

Applied and Environmental Microbiology 69, 6152-6164.

Barnard, R., Leadley, P.W., Hungate, B.A., 2005. Global change, nitrification, and

denitrification: A review. Global Biogeochemical Cycles 19.

Byrne, L.B., 2006. Effects of urban habitat types and landscape patterns on ecological

variables at the aboveground-belowground interface Ecology. The Pennsylvania State

University.

Byrne, L.B., 2009. Habitat structure: A fundamental concept and framework for

urban soil ecology (vol 10, pg 225, 2007). Urban Ecosystems 12, 21.

Byrne, L.B., Bruns, M.A., Kim, K.C., 2008. Ecosystem Properties of Urban Land

Covers at the Aboveground-Belowground Interface. Ecosystems 11, 1065-1077.

70

Chen, X.P., Zhu, Y.G., Xia, Y., Shen, J.P., He, J.Z., 2008. Ammonia-oxidizing

archaea: important players in paddy rhizosphere soil? Environmental Microbiology

10, 1978-1987.

Fierer, N., Carney, K.M., Horner-Devine, M.C., Megonigal, J.P., 2009. The

Biogeography of Ammonia-Oxidizing Bacterial Communities in Soil. Microbial

Ecology 58, 435-445.

Francis, C.A., Beman, J.M., Kuypers, M.M.M., 2007. New processes and players in

the nitrogen cycle: the microbial ecology of anaerobic and archaeal ammonia

oxidation. Isme Journal 1, 19-27.

Groffman PM, Law NL, Belt KT, Band LE, Fisher GT (2004). Nitrogen fluxes and

retention in urban watershed ecosystems. Ecosystems 7: 393-403.

Hansel, C.M., Fendorf, S., Jardine, P.M., Francis, C.A., 2008. Changes in bacterial

and archaeal community structure and functional diversity along a geochemically

variable soil profile. Applied and Environmental Microbiology 74, 1620-1633.

Hart, S.C., Stark, J.M., Davidson, E.A., Firestone, M.K., 1994. Nitrogen

mineralization, immobilization and nitrification. , In: Weaver, R.W., Angle, S.,

Bottomley, P., Bezdicek, D., Smith, S., Tabatabai, A., Wollum, A. (Eds.), Methods of

Soil Analysis. Part III: Microbiological and Biochemical Properties. Soil Science

Society of America, Madison, pp. 985–1018.

Hastings, R.C., Butler, C., Singleton, I., Saunders, J.R., McCarthy, A.J., 2000.

Analysis of ammonia-oxidizing bacteria populations in acid forest soil during

conditions of moisture limitation. Letters in Applied Microbiology 30, 14-18.

He, J.Z., Shen, J.P., Zhang, L.M., Zhu, Y.G., Zheng, Y.M., Xu, M.G., Di, H.J., 2007.

Quantitative analyses of the abundance and composition of ammonia-oxidizing

bacteria and ammonia-oxidizing archaea of a Chinese upland red soil under long-term

fertilization practices (vol 9, pg 2364, 2007). Environmental Microbiology 9, 3152-

3152.

Iles, J.K., Dosmann, M.S., 1999. Effect of organic and mineral mulches on soil

properties and growth of Fairview Flame red maple trees. J. Arboricult. 25, 163-168.

Jordan, K.K., Jones, S.C., 2007. Invertebrate diversity in newly established mulch

habitats in a midwestern urban landscape. Urban Ecosystems 10, 87-95.

71

Law N, Band L, Grove M (2004). Nitrogen input from residential lawn care practices

in suburban watersheds in Baltimore county, MD Journal of Environmental Planning

and Management 47: 737 - 755

Lehtovirta, L.E., Prosser, J.I., Nicol, G.W., 2009. Soil pH regulates the abundance

and diversity of Group 1.1c Crenarchaeota. Fems Microbiology Ecology 70, 367-376.

Leininger, S., Urich, T., Schloter, M., Schwark, L., Qi, J., Nicol, G.W., Prosser, J.I.,

Schuster, S.C., Schleper, C., 2006. Archaea predominate among ammonia-oxidizing

prokaryotes in soils. Nature 442, 806-809.

Long, C.E., Thorne, B.L., Breisch, N.L., Douglass, L.W., 2001. Effect of organic and

inorganic landscape mulches on subterranean termite (Isoptera : Rhinotermitidae)

foraging activity. Environmental Entomology 30, 832-836.

Lorenz, K., Kandeler, E., 2006. Microbial biomass and activities in urban soils in two

consecutive years. Journal of Plant Nutrition and Soil Science-Zeitschrift Fur

Pflanzenernahrung Und Bodenkunde 169, 799-808.

Lorenz, K., Lal, R., 2009. Biogeochemical C and N cycles in urban soils.

Environment International 35, 1-8.

Mosier, A.C., Francis, C.A., 2008. Relative abundance and diversity of ammonia-

oxidizing archaea and bacteria in the San Francisco Bay estuary. Environmental

Microbiology 10, 3002-3016.

Nicol, G.W., Glover, L.A., Prosser, J.I., 2003. The impact of grassland management

on archaeal community structure in upland pasture rhizosphere soil. Environmental

Microbiology 5, 152-162.

Nicol, G.W., Leininger, S., Schleper, C., Prosser, J.I., 2008. The influence of soil pH

on the diversity, abundance and transcriptional activity of ammonia oxidizing archaea

and bacteria. Environmental Microbiology 10, 2966-2978.

Prosser, J.I., Nicol, G.W., 2008. Relative contributions of archaea and bacteria to

aerobic ammonia oxidation in the environment. Environmental Microbiology 10,

2931-2941.

Reed, D.W., Smith, J.M., Francis, C.A., Fujita, Y., 2010. Responses of Ammonia-

Oxidizing Bacterial and Archaeal Populations to Organic Nitrogen Amendments in

Low-Nutrient Groundwater. Applied and Environmental Microbiology 76, 2517-

2523.

72

Santoro, A.E., Francis, C.A., de Sieyes, N.R., Boehm, A.B., 2008. Shifts in the

relative abundance of ammonia-oxidizing bacteria and archaea across

physicochemical gradients in a subterranean estuary. Environmental Microbiology

10, 1068-1079.

Shaw, L.J., Nicol, G.W., Smith, Z., Fear, J., Prosser, J.I., Baggs, E.M., 2006.

Nitrosospira spp. can produce nitrous oxide via a nitrifier denitrification pathway.

Environmental Microbiology 8, 214-222.

Shen, J.P., Zhang, L.M., Zhu, Y.G., Zhang, J.B., He, J.Z., 2008. Abundance and

composition of ammonia-oxidizing bacteria and ammonia-oxidizing archaea

communities of an alkaline sandy loam. Environmental Microbiology 10, 1601-1611.

Stark, J.M., 1996. Modeling the temperature response of nitrification.

Biogeochemistry 35, 433-445.

Toner, C.V., Sparks, D.L., Carski, T.H., 1989. Anion-exchange chemistry of Middle

Atlantic soils—charge properties and nitrate retention kinetics. Soil Science Society

of America Journal 53, 1061-1067.

Tourna, M., Freitag, T.E., Nicol, G.W., Prosser, J.I., 2008. Growth, activity and

temperature responses of ammonia-oxidizing archaea and bacteria in soil

microcosms. Environmental Microbiology 10, 1357-1364.

Treusch, A.H., Leininger, S., Kletzin, A., Schuster, S.C., Klenk, H.P., Schleper, C.,

2005. Novel genes for nitrite reductase and Amo-related proteins indicate a role of

uncultivated mesophilic crenarchaeota in nitrogen cycling. Environmental

Microbiology 7, 1985-1995.

Valenzuela-Solano, C., Crohn, D.M., 2006. Are decomposition and N release from

organic mulches determined mainly by their chemical composition? Soil Biology &

Biochemistry 38, 377-384.

Wrage, N., Velthof, G.L., Laanbroek, H.J., Oenema, O., 2004. Nitrous oxide

production in grassland soils: assessing the contribution of nitrifier denitrification.

Soil Biology & Biochemistry 36, 229-236.

Yang, Y.J., Dungan, R.S., Ibekwe, A.M., Valenzuela-Solano, C., Crohn, D.M.,

Crowley, D.E., 2003. Effect of organic mulches on soil bacterial communities one

year after application. Biology and Fertility of Soils 38, 273-281.

Zhan, G., Wang, X., He, X., Tao, Y., Gao, P., Li, D., 2010. Autotrophic Nitrification-

Denitrification Process at High Temperature. Chinese Journal of Applied and

Environmental Biology 16, 122-125.

73

Table 3-1. Chemical characteristics of soil at the beginning of the experiment

and after 102 days of incubation under different urban covers at two temperatures.

Treatment Total N

(%)

Total C

(%)

C:N SOM

(%)

CEC

(meq/100g)

NO3-

(ppm)

NH4+

(ppm)

Initial 0.49 4.11 8.39 7.35 17.95 11.6 2.73

18 ºC

Bark 0.51 4.49 8.80 8.02 20.10 19.39 0.49

Gravel 0.46 3.90 8.48 7.27 20.10 8.35 0.50

Lawn 0.50 4.35 8.70 7.87 19.40 4.78 0.48

Fallow 0.49 4.14 8.45 7.15 19.60 27.69 0.50

28 ºC

Bark 0.53 4.46 8.42 8.30 20.20 24.26 0.36

Gravel 0.52 4.37 8.40 7.84 18.80 13.48 0.34

Lawn 0.50 4.33 8.66 8.02 19.30 2.43 0.34

Fallow 0.52 4.22 8.12 8.00 20.10 35.49 0.36

Table 3-2. Primers and thermal profiles used for quantitative PCR targeting AOP

amoA genes in soils incubated under different urban covers at two temperatures.

Target Primers/Probe Sequence (5‘-3‘) Amplicon

length

(bp)

Thermal profile Reference

AOA

amoA

amoA508F and

amoA610R

Probe amoA543

CCTCAGGTCGGW

AAGTTCTACA

CGGCCATCCATC

TRTATGTCCA

CGTRGCGCTAGG

ATCGGGAG

102 95 oC 10 min

and 40 cycles of

95 oC 15 sec, 60

oC 1 min

Martir and

Bruns, 2010

AOB

amoA

1F

2R

GGGGTTTCTACT

GGTGGT

CCCCTCKGSAAA

GCCTTCTTC

490 95 oC 10 min; 35

cycles of 94 oC

45 sec, 56 o

C 30

sec, 72 oC 60

sec, 80.5 oC 30

sec (plate read)

Santoro et

al., 2008

74

Figure 3-1. Changes in abundance of AOP under the different urban land covers. (a)

AOB at 18˚C , (b) AOA at 18˚C , (c) AOB at 28˚C , and (d) AOA at 28˚C . Note

differences in scale. Error bars denote one standard error.

75

Figure 3-2. Changes in AOA/AOB in all urbanized soils after incubation for three

months at 18˚C and 28˚C. Error bars denote one standard error.

0

5

10

15

20

25

30

35

40

34 68 102

Days

AO

A/A

OB

(am

oA

copie

s/g

dry

soil)

18 C

28 C

76

Figure 3-3. Transcriptional activity of amoA measured after 102 days for AOA. At

this sampling time transcriptional activity of AOB amoA was not detected. Error bars

denote one standard error.

Transcriptional abundance of AOA amoA at 102 days

0

1

2

3

4

5

6

Bark Gravel Lawn Fallow

Treatment

log a

moA

tra

nscripts

/ g

dry

soil

18C 28C

77

Figure 3-4. Effects of urban land cover and temperature on (A) potential

nitrification, (B) pH, (C) soil moisture, and (D) in situ soil temperature. Error bars

denote one standard error.

A

B

C D

AB

C D

78

Figure 3-5. Correlation between AOA abundance and potential nitrification in soils

incubated at 18˚C. Means of duplicate qPCR reactions for each sample were included

in the analysis.

79

Chapter 4. Differential responses of Group 1.1a and 1.1b ammonia-oxidizing

archaea in soil microcosms

Martir, MC and Bruns, MA

Abstract

Ammonia-oxidizing archaea (AOA) and bacteria (AOB) are widely

distributed in aquatic and terrestrial habitats. In a previous comparison of amoA gene

abundance and diversity in soils under different landscape covers, AOA communities

in gravel-mulched soils differed from those in vegetated and bark-mulched soils. In

microcosms established with the same soils, a preliminary clone library based on

amoA sequences revealed the presence of an AOA lineage related to 1.1a crenarchaea

and which had not been found in previous clone libraries from field soils. One

objective of the present study was to design specific primers to recover the ―1.1a-

related‖ amoA sequences to use in quantitative PCR assays. Another objective was to

determine the response of this group to added ammonium at a concentration of 1 mM.

To determine potential differences in spatial distribution or habitat preference of

AOA vs. AOB, microcosms were established using whole soils and silt/clay fractions.

Soil microbial community DNA was extracted from microcosm samples taken over

time. Phylogenetic analysis of PCR amplicons obtained with primers for archaeal 16S

rRNA and amoA genes indicated that the newly recovered AOA sequences were

affiliated with the 1.1a Crenarchaea. Measurement of amoA genes of AOA, AOB,

80

and the 1.1a-like group showed that abundance of the latter group was lower overall

and unaffected by the addition of ammonium to the incubation solution. However, a

steady increase in the abundance of the 1.1a-like group in two of the microcosms was

associated with decreasing pH, indicating a better ability of this group to tolerate

acidic conditions. Soil 1.1a-AOA amoA sequences were closely related to sequences

found in distant geographic locations, suggesting a global distribution. The qPCR

assay developed here can be used to further our understanding of AOA biogeography.

Introduction

Ammonia-oxidizing prokaryotes (AOP) carry out a critical step of nitrogen

cycling in terrestrial ecosystems--the oxidation of ammonia to nitrite. In turn, nitrite

is converted by nitrite oxidizers to the mobile anion nitrate, which is more susceptible

to losses from the environment. Thus, AOP play an important role in controlling N

residence time in soils. For almost a century it was believed that autotrophic ammonia

oxidation was carried out only by bacteria (Kowalchuk and Stephen 2001). However,

research conducted during the past decade has shown that mesophilic archaea can

also oxidize ammonia. Putative AOA appear to be very diverse based on their amoA

sequences, and they are often more abundant than AOB in many soil and aquatic

ecosystems (Angel et al 2010, Beman et al 2008, Bernhard et al 2010, Hansel et al

2008, He et al 2007, He et al 2008, Leininger et al 2006, Mincer et al 2007, Moin et al

2009, Prosser and Nicol 2008, Treusch et al 2005, Urakawa et al 2010, Venter et al

2004). Further, kinetic studies have shown that AOA may be responsible for most of

81

the ammonia oxidized in marine and oligotrophic habitats (Martens-Habbena et al

2009b). Despite their abundance, the main factors affecting the phylogeny and

ecology of AOA remain poorly understood.

Phylogenetic analysis of 16S rRNA genes from enrichment cultures and

cloned environmental sequences of ammonia-oxidizing archaea led to an initial

assignment of these organisms as members of the kingdom Crenarchaeota (Venter et

al 2004, Treusch et al 2005). Marine AOA were classified as 1.1a crenarchea, while

terrestrial sequences were classified as 1.1b. More recently, studies conducted by

Brochier-Armanet et al (2008a; 2008b) have led to the proposed creation of a new

archaeal kingdom, the Thaumarchaeota, to include the mesophilic archaea including

ammonia oxidizers. Regardless of their taxonomic classification, there seems to be a

clear distinction between AOA adapted to marine vs. terrestrial habitats. Based on

either 16S rRNA or the ammonia monooxygenase subunit A (amoA) gene, AOA

sequences recovered from marine habitats tend to cluster with sequences of known

marine AOA, such as Nitrosopumilus maritimus SCM1 (Brochier-Armanet et al

2008a). When compared to sequences from marine habitats, sequences recovered

from soils tend to group in distinct clusters with multiple lineages in 1.1b, 1.1c, and

1.3 (Brochier-Armanet et al 2008a, Nicol and Schleper 2006, Treusch et al 2005).

Soil management practices are known to affect the abundance and diversity of

AOP (Bruns et al 1999; Webster et al 2005). Factors such as fertilization, pH and

temperature can affect AOP populations (Angel et al 2010, Avrahami et al 2002,

Avrahami and Conrad 2003, Avrahami and Conrad 2005, Avrahami and Bohannan

82

2007, Avrahami and Bohannan 2009, Barnard et al 2006, Bernhard et al 2010, Bruns

et al 1999, Chen et al 2008, Ciudad et al 2007, Di et al 2009, Fierer et al 2009, Hansel

et al 2008, Kim et al 2006, Leininger et al 2006, Martens-Habbena et al 2009a,

Mosier and Francis 2008, Nicol et al 2008, Prosser and Nicol 2008, Tourna et al

2008). In urban areas, soil management practices can lead to changes in most of

these factors (Lorenz and Lal 2009). A common soil management practice used in

urban areas is mulching, the addition of an organic or inorganic material to bare soil

to retain moisture and prevent weed establishment. In a previous study of soils that

had received a mulch application three years before, a reduction in the abundance of

AOA was found in bark-mulched soils in comparison to soils that were either

mulched with limestone gravel or under unmanaged vegetation (Martir and Bruns,

2010, i.e. Chapter 2). No response to treatment cover was observed for AOB

abundance. Further, a distinct AOA community was found in gravel-mulched soils

when compared to bark-mulched soils and soils under unmown vegetation, and all of

these amoA sequences clustered with other soil sequences in group 1.1b.

In the present study, microcosms were established to determine the response

of AOP to prolonged incubation and ammonium addition. Soil collected from bark-

mulched, gravel-mulched and unmanaged vegetation plots was used for the

microcosms since these soils were found previously to harbor different AOA

communities (Martir and Bruns, 2010). In the previous study, clone libraries were

dominated by two highly similar OTUs associated with soil AOA. These OTUs were

expected to respond positively to microcosm conditions that favor ammonia

83

oxidation, like ammonium fertilization. Further, a comparison was made between

microcosms established with whole soil and only the fine mineral fraction (silt and

clay). The latter microcosms were expected to favor autotrophic growth because the

inocula contained less organic matter when compared to whole soil. The objectives of

this study were to track the abundance of AOP using quantitative PCR and determine

if microcosm conditions selected a specific group.

Methods

Microcosm set up

Soils collected for this study were obtained from urban land cover experimental plots

established in 2003 and located at the Russell E. Larson Agricultural Research Station

in Rock Springs, PA (40° 43'N, 77° 55'W, 350 m elevation). Soils at the study site

have a silty clay loam texture and are classified in the Opequon series (Clayey,

mixed, active, mesic Lithic Hapludalfs) (web Soil Survey). The experimental plots

were created following a complete randomized block design and included the

following urban land-cover treatments: unmanaged vegetation (original conditions),

and bark chips- and limestone gravel mulch (Byrne, 2006). For the purpose of this

study, three soil samples were collected on November 2007 from two plots of the

unmanaged vegetation, bark- and gravel-mulched treatments. Soils were kept at 4˚C

for four weeks until processing. Composite soil samples were created for each land

cover treatment.

84

Microcosms were established on December of 2007 using sterile wide mouth

mason jars (0.95 L). Four microcosms were created for each land cover treatment.

Two ―whole soil‖ microcosms consisted of 10 g of field moist bulk soil mixed in 50

mL of sterile distilled water with or without 1mM NH4Cl, pH 8. For the other two

microcosms, 10 g of bulk soil were mixed with 20 mL of sterile distilled water,

shaken by hand for 3 minutes, and allowed to settle for 30 s. Immediately, 10 mL of

the supernatant were added to 50 mL of sterile distilled water with or without 1mM

NH4Cl, pH 8. Soil solids suspended in the supernatant corresponded to

approximately 2 g of the silt/clay fraction of the field-moist soil. These microcosms

will henceforth be referred to as clay/silt (fine) fraction. The incubation solution was

replaced every two to three months for a period of 13 months. At each time, the

incubation solution was collected by decantation into a sterile 50 mL Falcon tube and

an aliquot of the incubated soil was collected using a sterile spatula. Solution and soil

samples were stored at -80 ˚C until further processing. Incubation solutions and soils

collected after 2, 7, and 13 months were analyzed.

The incubation solution was analyzed for EC, pH, ammonium and nitrate. EC

and pH were determined using electrodes. Ammonium and nitrate were measured

colorimetrically on a microplate spectrophotometer (Shand et al 2008), with nitrate

reduced to nitrite using Devarda‘s alloy (Purkhold et al 2000, Sims et al 1995).

85

DNA extraction and clone library construction

DNA was extracted using the MoBio Power Soil DNA extraction kit and

following manufacturer‘s instructions. DNA was extracted from 0.3 g of fresh soil

from the bulk soil microcosms that received ammonium chloride. The ammonia

monooxygenase subunit A gene (amoA) was amplified using the primers 19F and

643R (Leininger et al., 2006; Table 1), with positive amplification verified by gel

electrophoresis. Duplicate PCR reactions were pooled and cloned using the TOPO-

TA cloning kit (Invitrogen). Plasmids containing amoA inserts were amplified using

the ilustraTM

TempliPhi Amplification Kit (GE Heathcare) following manufacturer‘s

instructions. Sequencing was performed on an ABI Hitachi 3730XL capillary DNA

analyzer using primers M13U and M13R. The software SeqMan was used to

manually edit and verify sequence quality. The archaeal 16S rRNA clone library was

obtained using primers Arch 21F and Arch 958R, with the thermal profile as

described in Table 1 (Delong 1992). 16S rRNA sequences were aligned using

Greengenes, and a maximum likelihood phylogenetic tree was constructed using

Phylip 3.68 (Felsenstein 1993).

Quantification of AOP amoA genes

DNA used for qPCR was extracted as described above from 0.05 to 0.15 g of

soil collected after 2, 7 and 13 months since the establishment of the microcosms. To

remove excess incubation solution, each sample was centrifuged for 60 s at 10,000

rpm before DNA extraction, and the supernatant was discarded. Moisture content

86

was determined for each soil sample, and this value was used to calculate number of

amoA copies per gram of dry soil.

Quantification of soil AOA amoA copies was done using the primers designed

by Martir and Bruns (2010) (Table 1). These primers and the probe were found to

target 77% of the sequences recovered by these authors from soils from the same

study site as the soils used in this study. Although only 77% of the sequences were

targeted, this qPCR assay targets the most commonly recovered operational

taxonomic unit (OTU) recovered from the soils evaluated, presumed to belong to

group 1.1b. Thus, this qPCR assay should reflect the patterns of soil AOA

abundance. Duplicate samples and a standard curve spanning from 104 to 10

8 were

used for the assays. Each reaction had a final volume of 25 μL and contained 9 ng of

DNA, 0.4 μM of each primer, 0.2 μM of probe and 12.5 μL of TaqMan® Universal

PCR Master Mix, No AmpErase® UNG (Applied Biosystems). The standard curve

used for amoA quantification was constructed using a dilution series of a 1:1 mix of

DNA from two transformed plasmids containing the different degenerate nucleotides

in the primers. A slope of -3.52 and an R2>0.99 were obtained for soil AOA amoA

quantification.

Primers and a Taq Man probe were developed to target specifically the lineage

of AOA that was found to cluster with sequences recovered from groundwater (soil

1.1a-AOA). Sequences belonging to this lineage were found exclusively in the clone

library generated from soil in the microcosm with bulk gravel-mulched soil and added

ammonium chloride, and are not detected by the qPCR assay described above.

87

Primers 578F and 625R, and probe 598F were designed using the program Primer

Express and an alignment of representative sequences of the soil 1.1a-AOA lineage

(Fig. 1). PCR reactions were carried out as described above. The standard curve

used for amoA quantification was constructed using a dilution series of a 1:1 mix of

DNA from two transformed plasmids containing the different degenerate nucleotides

in the primers. Slopes of -3.55 to -3.69 and an R2>0.99 were obtained for GW-AOA

amoA quantification.

Relative quantification of bacterial amoA was done using SYBR Green

chemistry, primers 1F and 2R (Table 1), and an ABI 7500 Sequence Detection

System. Each reaction had a final volume of 10 μL, and contained 9 ng of DNA, 0.2

μM of each primer and 5 μL of Maxima™ SYBR Green qPCR Master Mix

(Fermentas Inc., Glen Burnie, MD, USA). The specificity of the products was

assessed using melting curve analysis and gel electrophoresis. A ten-fold dilution

series of a known concentration of plasmid DNA containing a bacterial amoA insert

recovered from soil was used to create a standard curve over seven orders of

magnitude (3 ×102 to 3 × 10

8). Slopes of -3.94 and -3.77 and R

2=0.99 were obtained

for bacterial amoA quantification. Thermal profiles for both assays are shown in

Table 2.

Statistical analysis

All statistical analyses were performed using SPSS 17.0. Statistical significance was

determined using an alpha of 0.05.

88

Results and Discussion

Phylogenetic analysis of AOA 16S rRNA and amoA

After 10 months of incubation 11 16S rRNA sequences were recovered from

the ammonium-enriched microcosms containing gravel-mulched whole soil, and 8

sequences from the bark-mulched whole soil. These sequences were classified as

representatives of either Crenarchaeota (Thaumarchaeota) or Euryarchaeota (Fig 4-

2a). A majority of the sequences clustered with known group 1.1b AOA including

Candidatus Nitrososphaera gargensis (Hatzenpichler et al 2008) and the German soil

fosmid 54d9 (Treusch et al 2005). Two ribosomal sequences, Gravel+NH4Cl-236

and Gravel+NH4Cl-611, were found to cluster with Nitrosopumilus maritimus

SCM1, a member of the Crenarchaeota group 1.1a (Konneke et al 2005). A close

relationship has been found between phylogenetic reconstruction based on amoA and

16S rRNA for AOB (Purkhold et al 2000). If this relationship is also true for AOA,

then the two 16S rRNA sequences found to cluster with N. maritimus may be

representatives of the 1.1a AOA lineage found in our microcosms. Sequence

Gravel+NH4Cl-611 shares 93% identity with N. maritimus suggesting that archaea

giving rise to these sequences are different species.

The archaeal amoA clone library generated after 10 months of incubation

revealed a clear distinction between soil-associated (potentially belonging to group

1.1b) and aquatic system-associated (potentially belonging to group 1.1a) AOA (Fig

4-2b). Most of the sequences recovered from the microcosm with gravel-mulched

bulk soil enriched with ammonium chloride fell in a separate cluster from other

89

sequences recovered from soil. The predicted secondary structure of the soil 1.1a-

AOA amoA protein shows a different hydropathy profile when compared to

structures of other soil AOA (Fig 4-3). The changes in secondary structure point to

potential changes in protein function. Phylogenetic analysis of amoA sequences

supports the close relationship between the Rock Springs 1.1a-like AOA and N.

maritimus SCM1 (Fig 4-2b). However, the Rock Springs 1.1a-like sequences are

even more similar to amoA sequences recently reported as being recovered from

groundwater systems in The Netherlands (van der Wielen et al 2009) (Fig 4-2b). The

distant geographic locations from which these sequences were recovered suggest

widespread distribution of this group.

Tracking the abundance of AOP in soil microcosms

After 13 months of incubation, during which the microcosm solution was

replaced four times, both AOA and AOB were found to co-exist. In general amoA

copy numbers of soil AOA were more abundant than AOB across microcosms and

sampling dates (Fig 4-4). The use of whole soil or fine fraction to inoculate

microcosms also affected the abundance of bacterial amoA genes. After two months

of incubation, AOB genes were more abundant in fine-fraction microcosms with

added ammonium than in microcosms inoculated with whole soil (t=-5.59, df=2,

p=0.03). In contrast, soil 1.1a-like AOA were more prevalent in whole soil

microcosms than in fine fraction microcosms regardless of ammonium addition (Fig

4-4).

90

The use of the fine soil fraction as inoculum and the addition of ammonium

were expected to favor growth of autotrophic ammonia oxidizers, because the whole

soil microcosms contained plant detritus while the fine-soil fraction microcosms did

not. Thus, fine-soil fraction microcosms were expected to support less heterotrophic

competition for ammonium. Further, the larger amounts of soil added as whole-soil

inocula may have helped buffer the incubation solution, since whole-soil microcosms

had higher pH values (t=3.73, df =16, p=0.002) than fine-soil fraction microcosms.

Abundance of AOA has been found to increase in the rhizosphere of aquatic plants

more than AOB abundance (Chen et al 2008, Herrmann et al 2008). These

observations suggest that certain AOA lineages may be favored in the presence of

mineralizable organic matter.

After repeated attempts, soil AOA were not detected after 7 months of

incubation in the microcosm with the fine fraction of gravel-mulched soil with

ammonium (Fig 4-4c) or after 13 months of incubation in the microcosm with whole

soil from unmown vegetation with ammonium (Fig 4-4e). It is not likely that soil

AOA abundance dropped to undetectable levels in the microcosms. Procedures used

during the extraction of community DNA from soil can affect the relative

representation of different soil microorganisms (Bruns and Buckley 2002).

(Leininger et al 2006) used different cell lysis methodologies for the quantification of

AOA and AOB. Nevertheless, in our case both AOB and soil 1.1a-like AOA were

detected in these samples. If extraction procedures did affect the recovery of soil

91

AOA and not soil 1.1a-like AOA, then these two groups could have very distinct

physiological characteristics.

The abundance of soil 1.1a-like AOA was orders of magnitude lower than that

of other soil AOA and AOB and varied among microcosms. The low initial

abundance of this group may be the reason why it was not detected in the clone

libraries generated by Martir and Bruns (2010) from soils obtained from the same

study site. Nevertheless, abundance increased in most microcosms after 7 months of

incubation (Fig 4-4), except in the microcosms with bark-mulched soil and

ammonium. The observation that amoA copies of soil 1.1a-like AOA had a tendency

to increase after 7 months suggests an initial low abundance in the incubated soils.

The increase in abundance was sustained in only three of the microcosms (Fig 4-4a

and e). In two of these microcosms, there was a correlation between abundance of

soil 1.1a-like AOA and pH (Spearman‘s Rho = -1.00, p<0.01) (Fig 4-5). The greatest

increase in abundance was observed in the incubation with soil from the unmanaged

vegetation. This incubation also exhibited an increase in nitrate content, which was

correlated with increasing abundance of soil 1.1a-like AOA (Spearman‘s Rho = -1.00,

p<0.01) (Fig 4-6).

The above mentioned correlations do not provide sufficient information to

explain the patterns of abundance of soil 1.1a-like AOA amoA copies in the

microcosms. The apparent ephemeral nature of this group suggests either true

negative effects of microcosm chemistry or insufficient sensitivity of our sampling

methods. It is possible that soil 1.1a-like AOA inhabited a very specific niche in the

92

microcosms. Correlations between the distribution of different AOB species and

spatial location were observed in a study by Kim et al (2006), which suggested

adaptation to different niches. Since microcosms in the present study were incubated

under static conditions, it is possible that the soil 1.1a-like AOA may have occupied

microsites, affecting our ability to detect them. Alternatively, the high genetic

similarity between the soil 1.1a-like AOA recovered from the microcosms and clones

obtained from groundwater systems in The Netherlands (van der Wielen et al 2009)

suggest that this group may prefer aquatic ecosystems. If the later is true, then it is

possible that the abundance of this group may have increased in the incubation

solution and not in the soils. Differences have been found in the diversity of AOP

when comparing communities in water vs. soil or sediment samples (Francis et al

2005, Kim et al 2006). Additional studies are needed to test this hypothesis.

Effects of ammonium addition

Ammonium was not detected in the microcosms, except at the 13-month

sampling of the microcosm with the fine fraction of soil from unmanaged vegetation

(Table 4-2). The constant addition of ammonium was associated with an increase in

nitrate concentration and a simultaneous decrease in pH after 7 months of incubation

(Table 4-3). Ammonium consumption and nitrate production indicate active

nitrification (Webster et al 2005). However, the long time lag between sampling

dates limited our ability to calculate a nitrification rate. The decrease in pH observed

here could have resulted from the active oxidative reactions taking place and our use

93

of an unbuffered incubation solution. Ammonium enrichment was associated with an

increase in EC at 7 months of incubation (Table 4-3). Although EC values varied

throughout sampling dates, incubation solutions never reached values associated with

saline soils (>2 dS/m) (Irshad et al 2005).

Ammonia-oxidizing bacteria were the only AOP group that showed a

significant response to ammonium addition (Table 4-3). After 2 months AOB amoA

copy numbers were greater in fine-soil fraction microcosms with added ammonium

than in microcosms with whole soil. As described above, the use of the fine soil

fraction as inoculum for the microcosms was expected to favor autotrophic growth.

Further, at 7 months of incubation, greater abundance of AOB was detected in

microcosms that received ammonium. Recent studies comparing the abundance of

AOB vs. AOA in soil have found that AOB play a greater role in nitrification in

fertilized soils than AOA (Di et al 2009). Contrastingly, AOA have been found to be

more dominant and active in oligotrophic ecosystems (Martens-Habbena et al 2009b).

It was surprising that the abundance of AOB did not seem to respond to

ammonium addition after 13 months of incubation. This observation could have

resulted from a response of AOB to changes in microcosm chemistry or from

limitations of our qPCR assay. After 13 months of incubation, pH decreased in

almost all of the microcosms (Table 4-2). Studies have shown that AOB populations

are affected by decreasing pH (Princic et al 1998). Low pH can decrease nitrification

rates and the abundance of certain AOB species (Subbarao et al 2006). Nevertheless,

no correlation was found between AOB abundance and pH. Alternatively, it is

94

possible that an AOB population which did respond to ammonium enrichment was

not detected by our assay. Kim et al (2006) found niche partitioning among AOB in

lake systems, with clear differences between AOB inhabiting sediments and those

inhabiting the water column. Our microcosms remained static for continuous periods

of two months or more, which may have been sufficient time to cause a stratified

distribution of AOB populations. In addition, by replacing the incubation solution at

every sampling day we may have caused a depletion of the AOB in solution. Further,

the primers used here were designed for the detection of β-Proteobacterial ammonia

oxidizers but not of those of the γ-Proteobacteria (Rotthauwe et al 1997). The latter,

are associated with marine ecosystems. A detailed analysis of AOB dynamics in the

microcosms was beyond the scope of this study. However, a more thorough

understanding of AOP dynamics in the microcosms could have been achieved by

analyzing the microcosm solutions and not just the incubated soils.

Although a constant increase in the abundance of soil 1.1a-like AOA was

found in two of the ammonium-enriched microcosms, our data are not sufficient to

conclude that this group responds positively to the addition of mineral nitrogen. The

sequence similar to soil 1.1a-like AOA amoA, which was recovered from

groundwater systems in The Netherlands, had undetectable ammonium

concentrations (van der Wielen et al 2009). These authors pointed out the potential

for this AOA group to use substrates other than ammonium and to have a

heterotrophic or facultative heterotrophic lifestyle. Much is still to be learned about

95

the physiological characteristics of soil AOA, and a heterotrophic lifestyle for these

organisms cannot be ruled out.

Conclusion

The qPCR assay developed here allowed us to track the abundance of a 1.1a-

like group of ammonia oxidizers found in soil microcosms. Compared to other soil

AOA, this group constituted a minor portion of the AOA found in the soils evaluated

here. Our observations showed no evidence for a positive response of this group to

the addition of ammonium to the incubation solution. However, a steady increase in

the abundance of this group in two of the microcosms was correlated with decreasing

pH, suggesting an ability to tolerate acidic conditions. The high genetic similarity of

the soil 1.1a–like AOA amoA sequences to those obtained from groundwater in The

Netherlands point to a potential global distribution for this group and a preference for

freshwater systems. The primers developed here can be used to increase our

understanding of the biogeography of this novel AOA lineage.

Acknowledgements

This study was supported by funding obtained from the Alfred P. Sloan Foundation

Minority Ph.D. Program.

96

References

Avrahami S, Conrad R, Braker G (2002). Effect of soil ammonium concentration on

N2O release and on the community structure of ammonia oxidizers and denitrifiers.

Applied and Environmental Microbiology 68: 5685-5692.

Avrahami S, Conrad R (2003). Patterns of community change among ammonia

oxidizers in meadow soils upon long-term incubation at different temperatures.

Applied and Environmental Microbiology 69: 6152-6164.

Avrahami S, Conrad R (2005). Cold-temperate climate: a factor for selection of

ammonia oxidizers in upland soil? Canadian Journal of Microbiology 51: 709-714.

Avrahami S, Bohannan BJA (2007). Response of Nitrosospira sp. strain AF-like

ammonia oxidizers to changes in temperature, soil moisture content, and fertilizer

concentration (vol 73, pg 1166, 2007). Applied and Environmental Microbiology 73:

3121-3121.

Avrahami S, Bohannan BJM (2009). N2O emission rates in a California meadow soil

are influenced by fertilizer level, soil moisture and the community structure of

ammonia-oxidizing bacteria. Global Change Biology 15: 643-655.

Barnard R, Le Roux X, Hungate BA, Cleland EE, Blankinship JC, Barthes L et al

(2006). Several components of global change alter nitrifying and denitrifying

activities in an annual grassland. Functional Ecology 20: 557-564.

Beman JM, Popp BN, Francis CA (2008). Molecular and biogeochemical evidence

for ammonia oxidation by marine Crenarchaeota in the Gulf of California. Isme

Journal 2: 429-441.

Bernhard AE, Landry ZC, Blevins A, de la Torre JR, Giblin AE, Stahl DA (2010).

Abundance of Ammonia-Oxidizing Archaea and Bacteria along an Estuarine Salinity

Gradient in Relation to Potential Nitrification Rates. Applied and Environmental

Microbiology 76: 1285-1289.

Brochier-Armanet C, Boussau B, Gribaldo S, Forterre P (2008a). Mesophilic

crenarchaeota: proposal for a third archaeal phylum, the Thaumarchaeota. Nature

Reviews Microbiology 6: 245-252.

Brochier-Armanet C, Gribaldo S, Forterre P (2008b). A DNA topoisomerase IB in

Thaumarchaeota testifies for the presence of this enzyme in the last common ancestor

of Archaea and Eucarya. Biology Direct 3.

97

Bruns MA, Stephen JR, Kowalchuk GA, Prosser JI, Paul EA (1999). Comparative

diversity of ammonia oxidizer 16S rRNA gene sequences in native, tilled, and

successional soils. Applied and Environmental Microbiology 65: 2994-3000.

Bruns MA, Buckley DH (2002). Isolation and purification of microbial community

nucleic acids from environmental samples. In: al. CJHe (ed). Manual of

environmental microbiology., 2nd edn. American Society for Microbiology Press:

Washington, DC. pp 564–572.

Chen XP, Zhu YG, Xia Y, Shen JP, He JZ (2008). Ammonia-oxidizing archaea:

important players in paddy rhizosphere soil? Environmental Microbiology 10: 1978-

1987.

Ciudad G, Gonzalez R, Bornhardt C, Antileo C (2007). Modes of operation and pH

control as enhancement factors for partial nitrification with oxygen transport

limitation. Water Research 41: 4621-4629.

Delong EF (1992). Archaea in coastal maarine environments. Proceedings of the

National Academy of Sciences of the United States of America 89: 5685-5689.

Di HJ, Cameron KC, Shen JP, Winefield CS, O'Callaghan M, Bowatte S et al (2009).

Nitrification driven by bacteria and not archaea in nitrogen-rich grassland soils.

Nature Geoscience 2: 621-624.

Felsenstein J (1993). PHYLIP (Phylogeny Inference Package) version 3.68.

Distributed by the author Department of Genetics, University of Washington, Seattle

Fierer N, Carney KM, Horner-Devine MC, Megonigal JP (2009). The Biogeography

of Ammonia-Oxidizing Bacterial Communities in Soil. Microbial Ecology 58: 435-

445.

Francis CA, Roberts KJ, Beman JM, Santoro AE, Oakley BB (2005). Ubiquity and

diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean.

Proceedings of the National Academy of Sciences of the United States of America

102: 14683-14688.

Hansel CM, Fendorf S, Jardine PM, Francis CA (2008). Changes in bacterial and

archaeal community structure and functional diversity along a geochemically variable

soil profile. Applied and Environmental Microbiology 74: 1620-1633.

Hatzenpichler R, Lebedeva EV, Spieck E, Stoecker K, Richter A, Daims H et al

(2008). A moderately thermophilic ammonia-oxidizing crenarchaeote from a hot

spring. Proceedings of the National Academy of Sciences of the United States of

America 105: 2134-2139.

98

He JZ, Shen JP, Zhang LM, Zhu YG, Zheng YM, Xu MG et al (2007). Quantitative

analyses of the abundance and composition of ammonia-oxidizing bacteria and

ammonia-oxidizing archaea of a Chinese upland red soil under long-term fertilization

practices (vol 9, pg 2364, 2007). Environmental Microbiology 9: 3152-3152.

He JZ, Zheng Y, Chen CR, He YQ, Zhang LM (2008). Microbial composition and

diversity of an upland red soil under long-term fertilization treatments as revealed by

culture-dependent and culture-independent approaches. Journal of Soils and

Sediments 8: 349-358.

Herrmann M, Saunders AM, Schramm A (2008). Archaea dominate the ammonia-

oxidizing community in the rhizosphere of the freshwater macrophyte Littorella

uniflora. Applied and Environmental Microbiology 74: 3279-3283.

Irshad M, Honna T, Yamamoto S, Eneji AE, Yamasaki N (2005). Nitrogen

mineralization under saline conditions. Communications in Soil Science and Plant

Analysis 36: 1681-1689.

Kim D-J, Lee D-I, Keller J (2006). Effect of temperature and free ammonia on

nitrification and nitrite accumulation in landfill leachate and analysis of its nitrifying

bacterial community by FISH. Bioresource Technology 97: 459-468.

Konneke M, Bernhard AE, de la Torre JR, Walker CB, Waterbury JB, Stahl DA

(2005). Isolation of an autotrophic ammonia-oxidizing marine archaeon. Nature

(London) 437: 543-546.

Kowalchuk GA, Stephen JR (2001). Ammonia-oxidizing bacteria: A model for

molecular microbial ecology. Annual Review of Microbiology 55: 485-529.

Kyte J, Doolittle RF (1982). A simple method for displaying the hydropathic

character of a protein. Journal of Molecular Biology 157: 105-132.

Leininger S, Urich T, Schloter M, Schwark L, Qi J, Nicol GW et al (2006). Archaea

predominate among ammonia-oxidizing prokaryotes in soils. Nature 442: 806-809.

Lorenz K, Lal R (2009). Biogeochemical C and N cycles in urban soils. Environment

International 35: 1-8.

Martens-Habbena W, Berube PM, Urakawa H, de la Torre JR, Stahl DA (2009a).

Ammonia oxidation kinetics determine niche separation of nitrifying Archaea and

Bacteria. Nature (London) 461: 976.

99

Martens-Habbena W, Berube PM, Urakawa H, de la Torre JR, Stahl DA (2009b).

Ammonia oxidation kinetics determine niche separation of nitrifying Archaea and

Bacteria. Nature 461: 976-U234.

Mincer TJ, Church MJ, Taylor LT, Preston C, Kar DM, DeLong EF (2007).

Quantitative distribution of presumptive archaeal and bacterial nitrifiers in Monterey

Bay and the North Pacific Subtropical Gyre. Environmental Microbiology 9: 1162-

1175.

Moin NS, Nelson KA, Bush A, Bernhard AE (2009). Distribution and Diversity of

Archaeal and Bacterial Ammonia Oxidizers in Salt Marsh Sediments. Applied and

Environmental Microbiology 75.

Mosier AC, Francis CA (2008). Relative abundance and diversity of ammonia-

oxidizing archaea and bacteria in the San Francisco Bay estuary. Environmental

Microbiology 10: 3002-3016.

Nicol GW, Schleper C (2006). Ammonia-oxidising Crenarchaeota: important players

in the nitrogen cycle? Trends in Microbiology 14: 207-212.

Nicol GW, Leininger S, Schleper C, Prosser JI (2008). The influence of soil pH on

the diversity, abundance and transcriptional activity of ammonia oxidizing archaea

and bacteria. Environmental Microbiology 10: 2966-2978.

Princic A, Mahne I, Megusar F, Paul EA, Tiedje JM (1998). Effects of pH and

oxygen and ammonium concentrations on the community structure of nitrifying

bacteria from wastewater. Applied and Environmental Microbiology 64: 3584-3590.

Prosser JI, Nicol GW (2008). Relative contributions of archaea and bacteria to

aerobic ammonia oxidation in the environment. Environmental Microbiology 10:

2931-2941.

Purkhold U, Pommerening-Roser A, Juretschko S, Schmid MC, Koops HP, Wagner

M (2000). Phylogeny of all recognized species of ammonia oxidizers based on

comparative 16S rRNA and amoA sequence analysis: Implications for molecular

diversity surveys. Applied and Environmental Microbiology 66: 5368-5382.

Rotthauwe JH, Witzel KP, Liesack W (1997). The ammonia monooxygenase

structural gene amoA as a functional marker: Molecular fine-scale analysis of natural

ammonia-oxidizing populations. Applied and Environmental Microbiology 63: 4704-

4712.

Shand CA, Williams BL, Coutts G (2008). Determination of N-species in soil extracts

using microplate techniques. Talanta 74: 648-654.

100

Sims GK, Ellsworth TR, Mulvaney RL (1995). Microscale determination of inorganic

nitrogen in water and soil extracts. Communications in Soil Science and Plant

Analysis 26: 303-316.

Subbarao GV, Ito O, Sahrawat KL, Berry WL, Nakahara K, Ishikawa T et al (2006).

Scope and strategies for regulation of nitrification in agricultural systems-challenges

and opportunities. Critical Reviews in Plant Sciences 25: 303-335.

Tourna M, Freitag TE, Nicol GW, Prosser JI (2008). Growth, activity and

temperature responses of ammonia-oxidizing archaea and bacteria in soil

microcosms. Environmental Microbiology 10: 1357-1364.

Treusch AH, Leininger S, Kletzin A, Schuster SC, Klenk HP, Schleper C (2005).

Novel genes for nitrite reductase and Amo-related proteins indicate a role of

uncultivated mesophilic crenarchaeota in nitrogen cycling. Environmental

Microbiology 7: 1985-1995.

Urakawa H, Martens-Habbena W, Stahl DA (2010). High Abundance of Ammonia-

Oxidizing Archaea in Coastal Waters, Determined Using a Modified DNA Extraction

Method. Applied and Environmental Microbiology 76: 2129-2135.

van der Wielen PWJJ, Voost S, van der Kooij D (2009). Ammonia-Oxidizing

Bacteria and Archaea in Groundwater Treatment and Drinking Water Distribution

Systems. Applied and Environmental Microbiology 75: 4687-4695.

Venter JC, Remington K, Heidelberg JF, Halpern AL, Rusch D, Eisen JA et al

(2004). Environmental genome shotgun sequencing of the Sargasso Sea. Science 304:

66-74.

Webster G, Embley TM, Freitag TE, Smith Z, Prosser JI (2005). Links between

ammonia oxidizer species composition, functional diversity and nitrification kinetics

in grassland soils. Environmental Microbiology 7: 676-684.

101

Table 4-1. Primers, probe and PCR thermal profiles used for the detection and

quantification of ammonia oxidizing prokaryotes in urban soil microcosms Target

gene

Primers/

Probe

Sequence (5‘-3‘) Amplicon

length (bp)

Thermal profile Reference

ArchaeaamoA 19F

643R

ATGGTCTGGCTWA

GACG

TCCCACTTWGACCA

RGCGGCCATC CA

648 94 oC 5 min, 40

cycles of 94 oC

30 sec, 55 o

C 30

sec, 68 oC 60

sec followed by

68 oC for 5 min

Leininger et

al., 2006

ArchaeaamoA amoA508F

amoA610R

Probe 543

CCTCAGGTCGGWA

AGTTCTACA

CGGCCATCCATCTR

TATGTCCA

CGTRGCGCTAGGAT

CGGGAG

102 95 oC 10 min, 40

cycles of 95 oC

15 sec, 60 oC 1

min

Martir and

Bruns, 2010

ArchaeaamoA amoA578F

amoA625R

Probe 598

CAGTAACCATGGCC

GCATT

CAGGCGGCCATCCA

YCT

ATGTCCACGTGTTC

AGTTTGCATCC

48 95 oC 10 min, 40

cycles of 95 oC

15 sec, 60 oC 1

min

This study

BacteriaamoA 1F

2R

GGGGTTTCTACTGG

TGGT

CCCCTCKGSAAAGC

CTTCTTC

490 95 oC 10 min, 35

cycles of 94 oC

45 sec, 56 o

C 30

sec, 72 oC 60

sec, 80.5 oC 30

sec

Rotthauwe

et al., 1997

Archaea

16S rRNA

Arch 21F

Arch 958R

TTCCGGTTGATCCY

GCCGGA

YCCGGCGTTGAMT

CCAATT

Ranged

from 903 to

915

94 oC 5 min, 35

cycles of 95 oC

1 min, 55 o

C 1

min, 72 oC 1.5

min; followed by

72 oC 7 min

De Long,

1992

102

Table 4-2. Chemical properties of incubation solutions for all urban soil microcosms.

Table 4-3. Response of AOP abundance, nitrate concentration, pH and EC to ammonium chloride addition to microcosm

solution. Means ± 1SE. Means were compared using a paired t-test. Values in bold are significant at an alpha of 0.05.

Treatment 2 7 13 2 7 13 2 7 13 2 7 13

Bark-N 7.0 6.7 N/A 0.30 0.16 N/A 1.93 11.91 N/A 0.00 0.00 N/A

Bark+N 6.8 6.5 6.0 0.28 0.21 0.20 0.00 7.14 22.42 0.00 0.00 0.00

Bark silt/clay-N 6.9 6.5 6.3 0.15 0.06 0.07 9.22 15.34 9.26 0.00 0.00 0.00

Bark silt/clay+N 6.5 5.3 4.6 0.28 0.27 0.20 38.31 37.93 15.66 0.00 0.00 0.00

Gravel-N 7.1 7.2 6.8 0.33 0.31 0.38 2.07 12.50 13.50 0.00 0.00 0.00

Gravel+N 7.1 7.0 6.6 0.32 0.47 0.28 23.39 35.11 28.73 0.00 0.00 0.00

Gravel silt/clay-N 7.3 6.6 6.7 0.18 0.08 0.08 13.02 7.79 10.71 0.00 0.00 0.00

Gravel silt/clay+N 7.2 5.6 5.2 0.46 0.27 0.26 24.76 34.10 35.87 0.00 0.00 0.00

Unmown-N 7.1 6.4 6.1 0.23 0.11 0.23 1.58 15.08 38.49 0.00 0.00 0.00

Unmown+N 6.9 6.0 5.5 0.32 0.27 0.22 0.00 29.95 48.74 0.00 0.00 0.00

Unmown silt/clay-N 6.3 6.0 6.1 0.20 0.05 0.06 23.75 21.32 6.26 0.00 0.00 0.00

Unmown silt/clay+N 6.7 4.8 5.6 0.13 0.30 0.32 30.16 34.67 37.35 0.00 0.00 6.54

pH EC (dS/m) Nitrate (ppm) Ammonium (ppm)

Months Months Months Months

Months +NH4Cl -NH4Cl +NH4Cl -NH4Cl +NH4Cl -NH4Cl +NH4Cl -NH4Cl +NH4Cl -NH4Cl +NH4Cl -NH4Cl

2 2.3E8±1.2E8 1.9E8±7.3E7 4.8E2±4.8E2 1.4E2±1.4E2 4.2E7±2.3E7 1.2E7±7.5E6 19.8±7.9 9.50±2.2 6.9±0.1 7.0±0.1 0.30±0.04 0.23±0.03

7 4.2E7±2.2E7 1.5E8±7.8E7 3.3E4±2.0E4 1.2E4±5.9E3 6.8E6±1.8E6 2.7E6±1.2E6 30.3±2.2 9.90±1.8 5.9±0.3 6.6±0.2 0.30±0.04 0.13±0.04

13 6.9E7±3.6E7 2.2E8±1.5E8 1.1E5±6.3E4 1.7E4±1.7E4 4.1E6±2.8E6 3.4E6±9.2E5 30.1±6.7 17.7±5.4 5.6±0.3 6.4±0.2 0.25±0.02 0.17±0.06

EC (dS/m)pHsoil-AOA GW-AOA AOB Nitrate (ppm)

103

Figure 4-1. Alignment of archaeal amoA sequences used for the development of

primers and a probe targeting groundwater AOA (GW-AOA).

104

Figure 4-2. Neighbor Joining phylogenetic trees of a) 16S rRNA and b) amoA of

clones recovered from the different microcosms. The Tamura-Nei (1992) model of

genetic evolution, with a gamma of 0.38 and 0.31 were used for the amoA and 16S

rRNA trees, respectively. Bootstrap values are shown on each node.

105

a) Archaeal 16S rRNA

106

b) AOA amoA

107

Figure 4-3. Hydropathy profiles for selected AOA. Values are based on the Kyte-

Doolittle hydropathy index (Kyte and Doolittle 1982). Profiles shown are from OTU-

4, most common operational taxonomic unit found by Martir and Bruns (2010) in the

urbanized soils; Nitrosopumilus maritimus SCM1 (Konneke et al 2005); German soil

fosmid with amoA (Treusch et al 2005); and a representative sequence of the novel

GW-AOA recovered from the gravel soil microcosms in this study.

Hydropathicity plots for common OTUs

-3

-2

-1

0

1

2

3

4

5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 155 165 175 185 195

Amino acid position

Sco

re

OTU-4 Nitrosopumilus Cren54d9 novelAOA

108

Figure 4-4. Abundance of AOP in soil urban soil microcosms over a period of 13

months.

2 months +NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark

fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

s/g

dry

so

il

AOB soilAOA 1.1aAOA

2 months -NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark

fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

s/g

dry

so

il

AOB soilAOA 1.1aAOA

7 months +NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

/g d

ry s

oil

7 months -NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark

fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

s/g

dry

so

il

13 months +NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

Microcosm

log

am

oA

co

pie

s/g

dry

so

il

13 months -NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

Microcosm

log

am

oA

co

pie

s/g

dry

so

il

A B

C D

E F

2 months +NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark

fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

s/g

dry

so

il

AOB soilAOA 1.1aAOA

2 months -NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark

fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

s/g

dry

so

il

AOB soilAOA 1.1aAOA

7 months +NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

/g d

ry s

oil

7 months -NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark

fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

log

am

oA

co

pie

s/g

dry

so

il

13 months +NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

Microcosm

log

am

oA

co

pie

s/g

dry

so

il

13 months -NH4Cl

0

2

4

6

8

10

Gravel

whole

soil

Gravel

fine

fraction

Bark

whole

soil

Bark fine

fraction

Unmown

whole

soil

Unmown

fine

fraction

Microcosm

log

am

oA

co

pie

s/g

dry

so

il

A B

C D

E F

109

Figure 4-5. Correlation between GW-AOA abundance and solution pH in two

microcosms.

y = -3.9665x + 27.78

R2 = 0.9341

y = -6.4379x + 47.274

R2 = 0.5315

0

1

2

3

4

5

6

7

5 5.5 6 6.5 7 7.5

pH

GW

-AO

A c

op

ies/g

dry

soil

Gravel+NH4Cl Unmown+NH4ClLinear (Unmown+NH4Cl) Linear (Gravel+NH4Cl)

110

Figure 4-6. Correlation between GW-AOA and nitrate concentration in microcosm

with bulk soil under unmanaged vegetation enriched with ammonium chloride.

y = 0.0002x - 1.008

R2 = 0.9969

-10

0

10

20

30

40

50

60

0.0E+00 5.0E+04 1.0E+05 1.5E+05 2.0E+05 2.5E+05 3.0E+05

GW-AOA copies/g dry soil

Nitra

te-N

(pp

m)

111

Chapter 5. General Conclusions

―For in the end we will conserve only what we love. We will love only what we

understand. And we will understand only what we are taught.‖

Baba Dioum—African Conservationist

This thesis has shown that subtle changes in soil management like using bark

instead of gravel mulch can affect populations of ammonia-oxidizing prokaryotes

(AOP). Evaluating soils collected from an experimental site in central Pennsylvania,

it was possible to show that gravel mulching supports a community of ammonia-

oxidizing archaea (AOA) that is distinct from the one supported by soils under the

original unmanaged vegetation. Further, the AOA community found in gravel-

mulched soils was also distinct from that found in bark-mulched soils. Mulching can

not only affect community structure, but also abundance of AOA. This thesis showed

that AOA abundance was reduced in bark-mulched soils, which had the highest C:N

ratio of the three cover treatments and potentially more limited nitrogen availability.

Given the threat of global climatic change it is important to understand how

soil microbial communities respond to environmental shifts and how that affects their

activity. Abundance of AOP was shown to be affected not only by soil cover but also

by its interaction with soil temperature. AOA and AOB responded differently to the

combined effects of soil cover and temperature. At 18˚C AOB abundance had a

tendency to increase in mulched soils, while AOA abundance declined. Increased

temperature negatively impacted ammonia oxidizer abundance, but this negative

effect might be temporarily mitigated by bark mulching. Urban areas often experience

warmer temperatures than rural areas given the warming effects of pollution and

112

cement. Bark mulching may help protect soil communities from daily changes in

temperature, most likely through its moisture retention capabilities. Prolonged

changes in soil temperature and moisture regime are expected to affect AOP.

Whether negative effects are permanent is still to be determined.

Harboring a high biological diversity ensures that an ecosystem can continue

to function and provide critical services even under changing conditions. Our

extensive clone library demonstrated a high diversity of AOA found in the Rock

Springs, PA, soils evaluated in this thesis. The usefulness of a diverse AOA

community was demonstrated in the microcosms evaluated, where a lineage not

detected in field samples increased in abundance after prolonged incubation under

saturated conditions. This lineage was presumed to be too rare under field conditions,

which would explain why it was not initially detected. Nevertheless under suitable

conditions, it increased in abundance and potentially in activity.

Much is still to be learned about the ecology of AOP, in particular of AOA.

Work conducted here suggests that AOA and AOB populations are impacted

differently by changing soil conditions. As more information is obtained about AOA

diversity, based on both amoA and 16S rRNA, more light will be shed on the

evolution, phylogeny, and biogeography of these microorganisms. Further, isolation

of a soil AOA will assist in gaining more understanding of their physiological

characteristics and whether are significant contributors to nitrous oxide production in

soil through nitrifier denitrification.

113

Soils are a critical component of our ecosystem. Nutrient cycling, an

important ecosystem service provided by soil, is driven by the soil microbial

community. Yet, very little is known about soil microorganisms and how the services

they provide can be affected by human activity. As the quote above states,

understanding soil and its inhabitants is the key to its conservation. Studies

conducted in this thesis have advanced our understanding of how landscaping

practices can affect a keystone group of soil organisms, the ammonia oxidizers.

114

Appendix A. Layout of experimental plots at urbanized field site in Rock

Springs, PA

G = gravel; B = bark; U = unmanaged vegetation

Figure A-1. Layout of experimental plots at urbanized field site in Rock Springs, PA.

Treatments are designed by labels and were organized in four plots. Soils used in this

dissertation were collected from the gravel mulched soils (G), bark mulched soils (B)

and unmanaged vegetation (U) in blocks 1 and 2, highlighted in the figure with a

black box. For the study presented in Chapter 2, three cores were collected from each

plot. Soils used in Chapter 3 were collected from the unmanaged vegetation plots in

blocks 1 and 2. For the microcosms study described in Chapter 4, composite soil

samples were prepared using soil collected from the B, G, and U plots in blocks 1 and

2. Image modified from Byrne (2006). Not to scale.

115

Appendix B. Comparison of archaeal amoA gene copy numbers per gram soil

obtained using two cell lysis procedures

Soil samples were collected from bark-mulched (B), gravel-mulched (G) and

unmanaged vegetation soils (U). Legend for soil sample is as follows: Treatment-

block number-core number lysis method (vtx=vortexing, bb=bead beating). Bars

denote the average of two analytical samples analyzed per soil core. In general,

greater abundance was obtained using the vortexing for 10 minutes method when

compared to the bead beating for 60 s method.

0.0E+00

5.0E+04

1.0E+05

1.5E+05

2.0E+05

2.5E+05

3.0E+05

3.5E+05

4.0E+05

4.5E+05

5.0E+05

amo

A c

op

ies/

g d

ry s

oil

Soil Sample

Average archaeal amoA copy number per g of dry soil

116

Appendix C. Archaeal amoA sequence alignment used to design primers and the

Taq Man probe used for quantitative PCR.

117

Appendix D. Calculations used to create a standard curve for bacterial amoA

quantification

Step 1. Calculate mass of plasmid molecule

mass = size of plasmid + insert in bp (1.096 E-21 g/bp)

plasmid size 3956

insert size 490

n=plasmid+insert

n= 4446

m = n (1.096E-21 g/bp)

m= 4.873E-18 in g/bp

Thus one copy # has a mass of 4.873 E-18 g

Step 2. Calculate the mass of plasmid containing the copy # of interest

Formula: Copy# of interest * mass of one plasmid molecule = mass of plasmid DNA needed

Copy # of

interest

plasmid

mass

plasmid DNA

needed (g)

3.0.E+08 4.873E-18 1.462E-09

3.0.E+07 4.873E-18 1.462E-10

3.0.E+06 4.873E-18 1.462E-11

3.0.E+05 4.873E-18 1.462E-12

3.0.E+04 4.873E-18 1.462E-13

3.0.E+03 4.873E-18 1.462E-14

3.0.E+02 4.873E-18 1.462E-15

Step 3. Calculate concentration needed to achieve the copy # of interest

Here 2 uL will be used per PCR rxn, therefore per each uL we will have Xg of plasmid DNA

Copy # of

interest

plasmid

DNA

needed (g) uL to be used

final

[plasmid

DNA in PCR

rxn] g/uL

3.0.E+08 1.462E-09 1 1.46E-09

3.0.E+07 1.462E-10 1 1.46E-10

3.0.E+06 1.462E-11 1 1.46E-11

3.0.E+05 1.462E-12 1 1.46E-12

3.0.E+04 1.462E-13 1 1.46E-13

3.0.E+03 1.462E-14 1 1.46E-14

3.0.E+02 1.462E-15 1 1.46E-15

Step 4. Serial dilution

Initial concentration of my non-linearized new plasmid (AOB-3) = 2.47E-07 g/uL

Dilution#

Source

plasmid

DNA

Initial conc.

(g/uL) =Ci

Volume

plasmid

DNA =Vi

Final Volume=

Vf

Final conc. =

Cf

Volume of

diluent

Copy # / 1uL

that go to

PCR rxn

dilution-1 stock 2.47E-07 3.55 600 1.46E-09 596.45 3.00E+08

dilution-2 dilution 1 1.46E-09 20.00 200 1.46E-10 180.00 3.00E+07

dilution-3 dilution 2 1.46E-10 20.00 200 1.46E-11 180.00 3.00E+06

dilution-4 dilution 3 1.46E-11 20.00 200 1.46E-12 180.00 3.00E+05

dilution-5 dilution 4 1.46E-12 20.00 200 1.46E-13 180.00 3.00E+04

dilution-6 dilution 5 1.46E-13 20.00 200 1.46E-14 180.00 3.00E+03

dilution-7 dilution 6 1.46E-14 20.00 200 1.46E-15 180.00 3.00E+02

118

Appendix E. ANOVA tables for Repeated Measures Analysis used for the

analysis of AOP and soil variables evaluated in Chapter 3.

List of tables

Table 1. Potential nitrification pooled data

Table 2. Potential nitrification 18 degrees C

Table 3. Potential nitrification 28 degrees C

Table 4. Soil pH pooled data

Table 5. Soil pH 18 degrees C

Table 6. Soil pH 28 degrees C

Table 7. Soil moisture pooled data

Table 8. Soil moisture 18 degrees C

Table 9. Soil moisture 28 degrees C

Table 10. In situ soil temperature pooled data

Table 11. In situ soil temperature 18 degrees C

Table 12. In situ soil temperature 28 degrees C

Table 13. Ammonium concentration pooled data

Table 14. Ammonium concentration 18 degrees C

Table 15. Ammonium concentration 28 degrees C

Table 16. Nitrate concentration pooled data

Table 17. Nitrate concentration 18 degrees C

Table 18. Nitrate concentration 28 degrees C

Table 19. AOA amoA gene copies/g dry soil pooled data

Table 20. AOB amoA gene copies/g dry soil pooled data

Table 21. log AOA/AOB amoA gene copies/g dry soil pooled data

119

Table 1. Potential nitrification pooled data Num Den Effect DF DF F Value Pr > F cover 3 24.2 36.52 <.0001 Temp 1 24.3 307.82 <.0001 Time 2 47.7 84.43 <.0001 cover*Time 6 47.7 3.67 0.0045 cover*Temp 3 24.2 3.81 0.0228 Temp*Time 2 47.7 267.33 <.0001 cover*Temp*Time 6 47.7 4.85 0.0006

Table 2. Potential nitrification 18 degrees C Effect DF DF F Value Pr > F Cover 3 12 13.69 0.0004 Time 2 12 217.42 <.0001 Cover*Time 6 12 3.84 0.0225

Table 3. Potential nitrification 28 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12.1 57.08 <.0001 Time 2 23.7 69.04 <.0001

Cover*Time 6 23.7 7.70 0.0001

Table 4. Soil pH pooled data Num Den Effect DF DF F Value Pr > F cover 3 24.3 44.16 <.0001 Temp 1 24.3 7.23 0.0128 Time 2 47.8 33.31 <.0001 cover*Time 6 47.8 3.35 0.0078 cover*Temp 3 24.3 0.23 0.8746 Temp*Time 2 47.8 0.24 0.7877 cover*Temp*Time 6 47.8 1.37 0.2462

Table 5. Soil pH 18 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 13.3 19.16 <.0001 Time 2 14.9 13.47 0.0005 Cover*Time 6 14.9 0.49 0.8043

Table 6. Soil pH 28 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12.3 30.56 <.0001 Time 2 12.7 43.87 <.0001 Cover*Time 6 12.7 9.58 0.0004

120

Table 7. Soil moisture pooled data Num Den Effect DF DF F Value Pr > F cover 3 24.2 38.76 <.0001 Temp 1 24.2 10.72 0.0032 Time 2 47.7 1.35 0.2689 cover*Time 6 47.7 3.87 0.0032 cover*Temp 3 24.2 0.29 0.8298 Temp*Time 2 47.7 27.58 <.0001 cover*Temp*Time 6 47.7 6.24 <.0001

Table 8. Soil moisture 18 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12 22.26 <.0001 Time 2 12 10.09 0.0027 Cover*Time 6 12 2.73 0.0655

Table 9. Soil moisture 28 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12.1 18.00 <.0001 Time 2 13.2 33.10 <.0001

Cover*Time 6 13.2 14.41 <.0001

Table 10. In situ soil temperature pooled data Effect DF DF F Value Pr > F cover 3 24.1 13.43 <.0001 Temp 1 24.1 2613.40 <.0001 Time 2 47.3 94.72 <.0001 cover*Time 6 47.2 4.10 0.0021 cover*Temp 3 24.1 5.58 0.0047 Temp*Time 2 47.3 88.58 <.0001 cover*Temp*Time 6 47.2 1.95 0.0919

Table 11. In situ soil temperature 18 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12 10.69 0.0010 Time 2 24 15.53 <.0001 Cover*Time 6 24 1.42 0.2484

Table 12. In situ soil temperature 28 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12.1 6.60 0.0069 Time 2 23.2 316.54 <.0001 Cover*Time 6 23.2 7.84 0.0001

121

Table 13. Ammonium concentration pooled data Num Den Effect DF DF F Value Pr > F cover 3 24.2 0.85 0.4797 Temp 1 24.2 0.34 0.5633 Time 2 47.8 1418.26 <.0001 cover*Time 6 47.8 0.51 0.7970 cover*Temp 3 24.2 2.08 0.1290 Temp*Time 2 47.8 30.85 <.0001 cover*Temp*Time 6 47.8 2.45 0.0378

Table 14. Ammonium concentration 18 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12 0.41 0.7519 Time 2 12.2 1389.77 <.0001

Cover*Time 6 12.2 1.64 0.2181 Table 15. Ammonium concentration 28 degrees C

Num Den Effect DF DF F Value Pr > F Cover 3 12 3.27 0.0588 Time 2 12.3 1596.39 <.0001 Cover*Time 6 12.3 1.77 0.1874

Table 16. Nitrate concentration pooled data Num Den Effect DF DF F Value Pr > F cover 3 23.8 13.69 <.0001 Temp 1 23.8 14.09 0.0010 Time 2 47.5 0.35 0.7053 cover*Time 6 47.4 3.53 0.0057 cover*Temp 3 23.8 0.42 0.7381 Temp*Time 2 47.5 3.61 0.0348 cover*Temp*Time 6 47.4 0.45 0.8391

Table 17. Nitrate concentration 18 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12.1 4.94 0.0183 Time 2 14.6 3.32 0.0646 Cover*Time 6 14.6 4.22 0.0115

Table 18. Nitrate concentration 28 degrees C Num Den Effect DF DF F Value Pr > F Cover 3 12 9.24 0.0019 Time 2 11.9 3.17 0.0789 Cover*Time 6 11.9 11.34 0.0003

122

Table 19. AOA amoA gene copies/g dry soil pooled data Num Den Effect DF DF F Value Pr > F Cover 3 17.8 7.15 0.0024 Temperature 1 18.4 11.01 0.0037 Date 2 39.3 13.10 <.0001 Date*Temperature 2 39.3 2.81 0.0724 Date*Cover 6 38.6 2.73 0.0264 Temperature*Cover 3 17.8 1.15 0.3579 Date*Temperatu*Cover 6 38.6 1.53 0.1929

Table 20. AOB amoA gene copies/g dry soil pooled data Num Den Effect DF DF F Value Pr > F Cover 3 22.3 4.73 0.0107 Temperature 1 23 0.94 0.3412 Date 2 40.8 1.10 0.3425 Date*Temperature 2 40.8 4.13 0.0232 Date*Cover 6 40.1 0.58 0.7445 Temperature*Cover 3 22.3 0.16 0.9228 Date*Temperatu*Cover 6 40.1 2.01 0.0874

Table 21. log AOA/AOB amoA gene copies/g dry soil pooled data Num Den Effect DF DF F Value Pr > F Date 2 40.5 25.18 <.0001 Temperature 1 23.8 2.94 0.0996 Cover 3 23.1 1.27 0.3093 Date*Temperature 2 40.5 3.77 0.0314 Date*Cover 6 39.8 1.20 0.3258 Temperature*Cover 3 23.1 1.20 0.3303 Date*Temperatu*Cover 6 39.8 0.73 0.6247

Vita

Maina Cristina Mártir Torres

EDUCATION 1999-2003, B.S. Biology, University of Puerto Rico

2003-2006, M.S. Soil Science, University of Minnesota

2006-2010, Ph.D. Soil Science and Biogeochemistry, Penn State

University

PUBLICATIONS Mártir, M.C., Tlusty, B., van Berkum, P., and Graham, P.H. (2007)

The genetic diversity of rhizobia associated with Dalea purpurea

Vent. in fragmented grasslands of West-Central Minnesota. Canadian

Journal of Microbiology 53: 351-363.

Bruns, M.A., Mártir-Torres, M.C., and Minyard, M. (2009)

SOILS412W: Soil Ecology Fall 2009 Laboratory Manual.

RESEARCH

EXPERIENCE

2001-2003, Tropical Community Ecology Laboratory, UPR

2003-2006, Rhizobium Research Laboratory, U of MN

2006-2010, Soil Microbiology Laboratory, PSU

TEACHING

EXPERIENCE

SOILS 101 (Introduction to Soils) Teaching Assistant, PSU Spring

2007 and 2008.

SOILS 412W (Soil Ecology) Teaching Assistant, PSU Fall 2008 and

2009.

DISTINCTIONS Fellowships

2001-2003, Fellowship, Minority Access to Research Careers, UPR

2006-2010, Bunton-Waller Fellowship, PSU

2008, Scholarship, Alfred P. Sloan Foundation Minority PhD

Program, PSU

Grants Uncovering Nitrifier Interactions in Urbanized Soils, CAS/DCSS, PSU,

$2000, 2009.

Awards

Diversity of Crenarchaeal Genes for Ammonia Monooxygenase in

Simulated Urban Soils. March 2008. Poster. Environmental

Chemistry Student Symposium, University Park, PA. Second Prize.

Other

President Boricua Grads@PSU 2008-2009.