who you are? or what you do? 0$#8psltipq · group models for representing evolutionary processes...
TRANSCRIPT
Who you are? or
What you do? Evolution of metabolic function shapes ocean
biogeochemistry in a gene based model
Victoria ColesUniversity of Maryland Center for Environmental
Science, Horn Point Laboratory
2018 OCB Workshop
Some key limitations of (many) functional group models for representing evolutionary processes
Diatoms CalcifiersN2-Fixers
Detritus Dissolved Nitrogen
Mixotrophs
2018 OCB Workshop
Will the taxa in each functional grouprespond similarly to changes in pH, temp, nutrient ratios and concentrations?
Doney et al. (2012)
2018 OCB Workshop
Follows, Dutkiewicz, Grant, Chisholm, Science 2007
Coles and Hood, 2015
Mismatch between observational “omics” and models
2018 OCB Workshop
Self-organizing communities of microbes - with randomly assembled genomes from a shared pool of metabolic functions - will establish realistic ocean biogeochemistry
Tish Yager, Adrian Burd, Byron Crump, Patricia Medeiros, Mary Ann Moran, John Paul, Jeff Richey, Maureen Brooks, Raleigh Hood, Mary Doherty, Caroline Fortunato, Brandon Satinsky, Shalabh Sharma, Christa Smith, Mike Stukel, Nick Ward, Brian Zielinski
2018 OCB Workshop
Adjacent Seawater
Leaf blades of Ulva Australis
MDS Plot of functional similarity
Burke et al, PNAS 2011
Adjacent surfaces are colonized by different microbial species with similar metabolic function
2018 OCB Workshop
Animator: Rainier Hood
2018 OCB Workshop
A library of “genes” coding for functions relevant to nitrogen cycling
Satinsky, Smith, Sharma, Landa, Medeiros, Coles,Yager, Crump, Moran, ISME J. 2016
Normalized expression ratio
Salinity
2018 OCB Workshop
Broad gene potential is maintained by ongoing insertion of new organisms to replace those that never become successful.
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Organism
s
1980 1985 1990 1995
Year
2018 OCB Workshop
The emergent model community develops realistic size structure patterns – a key requirement for evaluating export
Satellite fields from Kostadinov et al, 2010
micro
pico+nano
pico+nano
micro
Satellite ModelEstimates
Satellite ModelEstimates
2018 OCB Workshop
The emergent community occupies diverse spatial niches
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
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1995_167_00_2db_euphsum_v10
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
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1995_167_00_2db_euphsum_v15
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
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1995_167_00_2db_euphsum_v14
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_euphsum_v180.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_euphsum_v37
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
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1995_167_00_2db_euphsum_v46
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
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1995_167_00_2db_euphsum_v200.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
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1995_167_00_2db_euphsum_v50
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_euphsum_v420.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_euphsum_v59
0.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_euphsum_v210.10.20.51.02.05.0
10.020.050.0
100.0200.0500.0
mmol N/m^2
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_euphsum_v63
12
2018 OCB Workshop
Emergent patterns in metagenomes and metatranscriptomes can be mapped in relation to substrates
0.00010.00020.00050.00100.00200.00500.01000.02000.05000.10000.20000.50001.00002.00005.000010.0000
vanA
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_layer_1_gene_vanA
0.0010.0020.0050.0100.0200.0500.1000.2000.5001.0002.0005.000
10.000mmol DON/m^3
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_1_v6
0.00010.00020.00050.00100.00200.00500.01000.02000.05000.10000.20000.50001.00002.00005.000010.0000
vanA
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_1_v86
Terrestrial DOM (e.g. lignins)
Metagenomes for aromatic compound metabolism pcaH(community potential)
Metatranscripts of pcaH (community activity)
pcaH genes
pcaH transcripts
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2018 OCB Workshop
Emergent metagenomic patterns can be compared with observations and cost-benefit choices reviewed.
Terrestrial DOM (e.g. lignins)
Metagenomes for aromatic compound metabolism pcaH (community potential)
Metatranscripts of pcaH (community activity)
pcaH genes
pcaH transcripts
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2018 OCB Workshop
Emergent metagenomic patterns can be compared with observations and cost-benefit choices reviewed.
0.00010.00020.00050.00100.00200.00500.01000.02000.05000.10000.20000.50001.00002.00005.000010.0000
vanA
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_layer_1_gene_vanA
0.0010.0020.0050.0100.0200.0500.1000.2000.5001.0002.0005.000
10.000mmol DON/m^3
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_1_v6
0.00010.00020.00050.00100.00200.00500.01000.02000.05000.10000.20000.50001.00002.00005.000010.0000
vanA
−80˚ −40˚ 0˚
0˚
20˚
1995_167_00_2db_1_v86
Terrestrial DOM (e.g. lignins)
Metagenomes for aromatic compound metabolism pcaH (community potential)
Metatranscripts of pcaH (community activity)
pcaH genes
pcaH transcripts
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2018 OCB Workshop
Direct comparison of model with omics observations are reasonable
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2018 OCB Workshop
All conversion of DON, PON and NH4 to NO3occurs through the emergent community and the genetic potential of each organism
Model Model
Model Ammonium
Model NitrateAMT Nitrate (uM)
AMT Ammonium (uM) Model Ammonium
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2018 OCB Workshop
Gene counts from Agogué et al 2008, Nutrients from the Atlantic Meridional Transect Program
AMT Run 1 Run 2 Run 3 Run 4
Nitrate
Ammonium
Nitrite / amoAtranscripts
amoA Gene copy #
Model simulations with different organisms but common gene functions show similar biogeochemical gradients
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2018 OCB Workshop
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1980 1982 1984 1986 1988 1990 1992 1994 1996Nitrate
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Primary production
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600
Autotroph growth rate
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4
Nitrification rate
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200
Total biomass
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1980 1982 1984 1986 1988 1990 1992 1994 1996
Species introductions (evolution) can strongly reshape the model properties over the short term
New species introduction rate
2018 OCB Workshop
0.000.050.100.150.200.250.300.350.400.450.50
1980 1982 1984 1986 1988 1990 1992 1994 1996
expt_12.0_atl_sum_v98mot_transcripts/m^2day
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1980 1982 1984 1986 1988 1990 1992 1994 1996
expt_12.0_atl_sum_v99
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expt_12.0_atl_sum_v99
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1980 1982 1984 1986 1988 1990 1992 1994 1996
expt_12.0_atl_sum_v98mot_transcripts/m^2day
Changes in organism’s ability to nitrify at low ammonium concentrations appears to be a key model sensitivity Basin averaged amoAtranscript concentration
Basin averaged transcript concentration
2018 OCB Workshop
Species environmental niche is more flexible for temp. and light than for nitrate
Irwin et al, PNAS 2015
2018 OCB Workshop
pcb−hl
pcb−ll
pbs−hl
pbs−ll
nrt−HA
nrt−LA
amtB−H
Aam
tB−LA
rhod
pcaH
AMA
AMA−
det
amoA
−Aam
oA−B nif
motG
mot−P sil
cheA
Chi−syn
Run=1
Run=2
Run=3
Run=4
10 20 30
Salinity
−4 −3 −2 −1 0 1
A
B
C
D
pcb−hl
pcb−ll
pbs−hl
pbs−ll
nrt−HA
nrt−LA
amtB−H
Aam
tB−LA
rhod
pcaH
AMA
AMA−
det
amoA
−Aam
oA−B nif
motG
mot−P sil
cheA
Chi−syn
Run=1
Run=2
Run=3
Run=4
10 20 30
Salinity
−1 0 1 2 3 4
Model simulations with different organisms have dissimilar metagenomes
2018 OCB Workshop
Type
Size
BioM
pcb.hl
nrt.H
Anrt.LA
amt.H
Aam
t.LA
amoA.A
amoA.B nif
pcaH
AMA
AMA.det
rhod mot
mot.P
cheA
Chi.syn sil
1340
1128
1371
325
860
1671
1166
1485
134
516
591
474
1084
1309
1503
629
1489
1791
1679
1507
1771
691
512
1629
1436
1328
346
78
0 0.4 1Value
Color Key
Type
Size
BioM
pcb.hl
nrt.H
Anrt.LA
amt.H
Aam
t.LA
amoA.A
amoA.B nif
pcaH
AMA
AMA.det
rhod mot
mot.P
cheA
Chi.syn sil
731
619
190
1074
599
871
997
214
752
122
483
36
265
406
207
638
144
459
722
1063
903
979
506
325
919
0 0.4 1Value
Color Key
Type
Size
BioM
pcb.hl
nrt.H
Anrt.LA
amt.H
Aam
t.LA
amoA.A
amoA.B nif
pcaH
AMA
AMA.det
rhod mot
mot.P
cheA
Chi.syn sil
1020
1501
303
602
416
661
980
1443
569
1244
638
550
995
79
669
176
210
757
195
192
1152
1455
118
1241
834
0 0.4 1Value
Color Key
Type
Size
BioM
pcb.hl
nrt.H
Anrt.LA
amt.H
Aam
t.LA
amoA.A
amoA.B nif
pcaH
AMA
AMA.det
rhod mot
mot.P
cheA
Chi.syn sil
1074
1280
89
1052
549
350
2009
106
467
1610
931
800
775
155
893
1623
927
970
1073
1062
440
1590
330
1891
1097
1505
750
1176
2005
1659
0 0.4 1Value
Color Key
Model communities differ, but share prochlorococchus and SAR analogs
Prochloroccocus analog
SAR
Run 1
Run 2
Run 3
Run 4
Organism #
Organism #
2018 OCB Workshop
The metatranscriptomes – reflecting realized function – are similar across runs in similar physical environments
1176 893
494
pcb−hl
pcb−ll
pbs−hl
pbs−ll
nrt−HA
nrt−LA
amtB−H
Aam
tB−LA
rhod
pcaH
AMA
AMA−
det
amoA
−Aam
oA−B nif
motG
mot−P sil
cheA
Chi−syn
Run=1
Run=2
Run=3
Run=4
10 20 30
Salinity
−4 −3 −2 −1 0 1
A
B
C
Dpcb−hl
pcb−ll
pbs−hl
pbs−ll
nrt−HA
nrt−LA
amtB−H
Aam
tB−LA
rhod
pcaH
AMA
AMA−
det
amoA
−Aam
oA−B nif
motG
mot−P sil
cheA
Chi−syn
Run=1
Run=2
Run=3
Run=4
10 20 30
Salinity
−1 0 1 2 3 4
Salinity
2018 OCB Workshop
Its not who you are underneath but what you do that defines you
1176 893
494
pcb−hl
pcb−ll
pbs−hl
pbs−ll
nrt−HA
nrt−LA
amtB−H
Aam
tB−LA
rhod
pcaH
AMA
AMA−
det
amoA
−Aam
oA−B nif
motG
mot−P sil
cheA
Chi−syn
Run=1
Run=2
Run=3
Run=4
10 20 30
Salinity
−4 −3 −2 −1 0 1
A
B
C
Dpcb−hl
pcb−ll
pbs−hl
pbs−ll
nrt−HA
nrt−LA
amtB−H
Aam
tB−LA
rhod
pcaH
AMA
AMA−
det
amoA
−Aam
oA−B nif
motG
mot−P sil
cheA
Chi−syn
Run=1
Run=2
Run=3
Run=4
10 20 30
Salinity
−1 0 1 2 3 4
Salinity
2018 OCB Workshop
Hellweger et al. Science 2014
Neutral evolution is fast enough to generate biogeographic provinces in marine microbes
2018 OCB Workshop
Dispersion timescales are too short to generate distinct biogeographic provinces in abundant marine microbes
Jonsson and Watson Nat. Comm 2015
2018 OCB Workshop
In the model:evolution of key metabolic functions sets basin biogeochemical gradients
Thus, the evolution of specific lineages could potentially be non-deterministic.
Many different trees of life could produce the present day ocean
2018 OCB Workshop
Discussion questions• If experimental evolution experiments are not terribly realistic, what are they
good for in the first place?
• How many traits are enough traits? How much effort should we put into phenotypic characterisations?
• Is it correct to assume that today's organisms are in their optimum environment / strongly locally adapted to their environment/ at a peak of the fitness landscape in their current environment?
• How often are interspecies interactions other than competition and exploitation important for ocean ecosystem functioning, and does evolution tend to preserve or disrupt them?
• When can we ignore contemporary evolution?• Do we need to pay attention to evolution if it isn't changing populations in ways
that we care or that we can measure?• What kinds of long term observations need to be put into place to measure
evolutionary change?• Can evolution reshape carbon export (over decadal timescales) or does physics
reign supreme?
2018 OCB Workshop