algae for conversion of manure nutrients to animal feed: evaluation of advanced nutritional value,...

Algae for Conversion of Manure Nutrients to Animal Feed:

Evaluation of advanced nutritional value, toxicity, and zoonotic pathogens

1Shelton Murinda, 2Marcia Murry, 3Gregory Schwartz, 4Trygve Lundquist, 5A. Mark Ibekwe

1Animal and Veterinary Sciences Department, California State Polytechnic University, Pomona, CA.2Biological Sciences Department, California State Polytechnic University, Pomona, CA.

3BioResource and Agricultural Engineering Department, California Polytechnic State University, San Luis Obispo, CA.4Civil & Environmental Engineering Department, California Polytechnic State University, San Luis Obispo, CA.

5USDA Agricultural Research Service, U. S. Salinity Laboratory, Riverside, CA.

INTRODUCTION

Manure disposal is a major concern in concentrated feeding operations (CAFOs), e.g., dairy industry

Microalgae offer great potential for sustainable bioremediation of manure nutrients and wastewaters for production of biofuel, feedstock and bio-products (e.g., nutritional supplements).

GOALS OF PROJECT Collect field data to calibrate growth models for the culture of algae

Maximize the nutritional value of produced algae for animal feed

Optimize pathogen inactivation methods, and

Quantify and control any cyanobacterial (“blue-green algae”) toxins

OVERALL GOAL: Benefit agriculture and the environment by introducing microalgae, as a fast-growing safe, livestock feed crop.

LAGOON LAGOON

Shade Shade

Algae ponds/bio-reactors

(in red rectangle)

BIOREACTORS then

WEEKLY DAILYSecchi disk visibilityAfternoon oxygen and pHWater temperatureSolar radiation Pond colorDLE additionExchange

Dairy Lagoon Effluent (DLE)Total suspended solids (TSS) Volatile suspended solids (VSS) Nitrogen (N): soluble and particulate

Total N, Total Insoluble N Phosphorus (P)Chemical oxygen demand (COD)Algal species identification

Ponds are operated as a semi-continuous culture. Data will be used to develop a predictive model.

DAIRY LAGOON EFFLUENT (DLE) NUTRIENT CHARACTERISTICS

MONITORING NUTRIENT UPTAKE (N & P)

Seasonal Nitrogen Uptake Rates

SOLAR RADIATION DATA

DAILY TEMPERATURE DATA

WEEKLY PRODUCTIVITY

Photobioreactors Used to Simulate Seasonal Light and Temperature Regimes in the lab

SYMBIOTIC NUTRIENT RECOVERY (BACTERIA & ALGAE)

COMPOSITION OF HARVESTED BIOMASS: Feb vs. Sep 2016

% C

hlor

ophy

ll/Bi

omas

s

BIO-REACTOR UNIT OPERATION

• Units were exchanged daily and fed nutrients from DLE

• Controls have no DLE: synthetic fertilizer

• Units with nutrients supplied 100% by DLE, brown in color, have lower overall oxygen concentrations, and lower pH

Identification of Algal Strains: Microscopy and Sequencing

>100 strains isolated from seasonal samples (2014-2016)

Sequenced ITS 4-5 intergenic region of several isolates.

Identified seasonally dominant spp.: Scenedesmus Desmodesmus Chlorella variety of small, unspeciated Chlorophyta

Eustigmatos sp.

Microactinium NannochloropsisMarine Isolate

TetraselminisMarine Isolate Scenedesmus sp.

Sequence Comparisons of ITS 4-5 region of

Ribosomal Genes to identify Pond Isolates

ADVANCED NUTRITION ANALYSIS

Pond isolates cultured to optimize growth rate while also attempting to have the highest value algae composition for feed (i.e.):

DigestibilityCarbohydrates, Lipids, Proteins Fatty acid & amino acid profiles

Sampled in exponential phase and stored (-80ᵒC) for proximate analysis

Fatty Acid Profiles of 9 Algae StrainsFAME Composition FAME Standard PBR1 CP71 PBR2 CP71

PBRa

CP24 PBRb PBR1&2 PBRR PBR1 PBR2a PBR3

C6:0 - - - - - - - - - -

C7:0 - - - - - - - - - -

C8:0 + - - - - - - - - -

C9:0 + - - - - - - - - -

C10:0 + + - + - - + + - -

C11:0 + - - - - - - - - -

C12:0 + + + + + + + + + +

C13:0 + + + + + + + + + +

C14:0 + + + + + + + + + +

C14:1 + - - - - - - - - -

C15:0 + + + + + + + + + +

C16:0 + + + + + + + + + +

C16:1 + - - + - - - - - -

C17:0 + + + + + + + + + +

C17:1 + + + + - - - - - -

C18:0 + + + + + + + + + +

C18:1(Z) + + - + + + + + + -

C18:1 € + + - + - - - - - -

C18:2 + + + - + - + + + -

C18:3 + - - - - + - - - -

C19:0 - - - - - - - - - -

C20:0 + + - - - - + - - +

C20:1 + - - - - - - - - -

C20:2 + - - - - - - - - -

C20:3 + - - - - - - - - -

C20:3 + - - - - - - - - -

C21:0 + - - - - - - - - -

C22:0 + - - - - - - - - -

C22:1 + - - - - - - - - -

C22:2 + - - - - - - - - -

C22:6 + - - - - - - - - -

C23:0 + - - - - - - - - -

C24:0 + - - - - - - - - -

C24:1 + - - - - - - - - -

FAMEs analysis: GC-MS; C6-C24

Quantitation

CYANOBACTERIA DETECTION

Important in monitoring of algae ponds and safety of algae-based feeds

CYANOBACTERIA DETECTION PROTOCOLS

Universal detection of cyanobacteria targeting 16s RNA and rpoC1 gene sequences

Universal detection of cyanobacteria targeting the rpoC1 gene sequence

Gels stained with Midori green

16s RNArpoC1

CELL TOXICITY AND CYANOTOXIN TESTS

• Cell Counters (Abaxis & TC 20 cell counter)

TC 20 >>> Total, Live vs. dead cell countsAbaxis >>> blood cell counts (WBCs/RBCs/Platelets)

• ELISA toxin detection (Abraxis & Beacon kits)

Evaluation of Different DNA Extraction Kits On Bio-reactor Bacterial Community Structures

Mo Bio Power water extraction kitZymo fungi/bacterial extraction kitMP Biomedicals FastDNA spin kit DNA

DNA was extracted from samples for analysis of total bacteria, cyanobacteria and other microalgae (targeting V4 16s rDNA)

Used Illumina MiSeq’s next generating sequencing (NGS) platform [Second Genome - The Microbiome Co., San Francisco, CA].

.

OTU; operational taxonomic unit

Phylum Extraction Kit (%) MP MoBio Zymo

Cyanobacteria 3.78 2.5 2.5 Proteobacteria 38.2 40.9 28.7 ---Beta 6.4 9.5 4.6 ---Alpha 12.6 16.3 11.7 ---Gamma 7.6 9.3 5.8 ---Epsilon 1.01 2.7 1.5 ---Delta 8.4 2.5 4.4 Actinobacteria 3.7 4.9 4.9 Bacteroidetes 15.83 20.1 18.9 Verrucomicrobia 7.8 8.8 8.3 Chloroflexi 1.32 1.6 2.5 Firmicutes 7.76 4.5 9.3 Tenericutes 0.3 0.6 1.1 SR1 0.6 0 0 Acidobacteria 1.7 0.2 0 Chlorobi 0.7 0.6 0.4 Planctomycetes 5.82 1.8 3.7 OD1 2.65 2.2 5.2 Fibrobacteres 0.03 0 0 Gemmatimonadetes 0.1 0.2 0.4 Chlamydiae 0.1 0.2 0.1 Spirochaetes 0.8 0.4 1.1 TM7 0.7 0.2 0.2 GN02 0.1 0.6 0.7 Caldithrix 0.1 0.2 0.1 Thermi 0.1 0 0 NKB19 0.3 0 0.2 Armatimonadetes 0.1 0 0 TM6 0.1 0 0.1 Fusobacteria 0.4 6 0.5 BRC1 1.2 0 0 OP3 0.3 2 1.6 WPS-2 0.3 0 0 LD1 0.1 0.2 0.1 Elusimicrobia 0.1 0.2 0 WWE1 0 1.1 0.8 Lentisphaerae 0 0.6 1.5 Spirochaetes 0 0.4 1.1

Detection of significantly different *OTUs from each DNA extraction kit

*OUT; operational taxonomic unit

CONCLUSIONS

• Good nutrient (N&P) uptake rates were measured. Removal of 75-85% N; greater removal efficiency of P.

• Recommended seasonal HRT‘s: Summer/Fall 2.5-3 days; Spring 4 days, and Winter 6 days

• Confidence to narrow the scope of model parameters that optimize nutrient uptake and productivity to: Temperature, HRT, and DLE addition.

• Isolated, characterized and identified seasonally dominant algae strains for final productivity model development.

FUTURE STUDIES

• Well characterized seasonally dominant algae strains will be cultured in ponds, optimized for biomass productivity, and monitored for safety

• Refine technics for toxin detection to improve reliability of ELISA tests.

• Pathogens will be identified and quantified using PCR (real-time or digital droplet), employing optimized DNA extraction technics.

• Computer software and bioinformatics analyses will facilitate identification of pathogens and non-pathogens (Quantitation and relative abundance).

DISSEMINATION

• Presented at least 20 local, regional and national conferences

• Presented at 3 international conferences (ASM, ABO, ABBB)

• Published 2 book chapters

• Authored 2 book manuscripts (in review)

• Authored 1 journal manuscript (in review)

ACKNOWLEDGEMENTS

• This project was supported by USDA Award # 2013-67019-21374

• Thanks to all the student research assistants, volunteers and interns