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2-21-2021 Synergistic Epistasis Enhances the Co-Operativity of Mutualistic Interspecies Interactions.

Serdar Turkarslan Institute for Systems Biology

Nejc Stopnisek University of Washington

Anne W. Thompson Portland State University

Christina E. Arens Institute for Systems Biology

Jacob J. Valenzuela Institute for Systems Biology

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Citation Details Turkarslan, S., Stopnisek, N., Thompson, A. W., Arens, C. E., Valenzuela, J. J., Wilson, J., Hunt, K. A., Hardwicke, J., de Lomana, A. L. G., Lim, S., Seah, Y. M., Fu, Y., Wu, L., Zhou, J., Hillesland, K. L., Stahl, D. A., & Baliga, N. S. (2021). Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions. The ISME Journal. https://doi.org/10.1038/s41396-021-00919-9

This Article is brought to you for free and open access. It has been accepted for inclusion in Biology Faculty Publications and Presentations by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. Authors Serdar Turkarslan, Nejc Stopnisek, Anne W. Thompson, Christina E. Arens, Jacob J. Valenzuela, James Wilson, Kristopher A. Hunt, Jessica Hardwicke, Adrián López García de Lomana, Sujung Lim, Yee Mey Seah, Ying Fu, Liyou Wu, Jizhong Zhou, Kristina L. Hillesland, David A. Stahl, and Nitin S. Baliga

This article is available at PDXScholar: https://pdxscholar.library.pdx.edu/bio_fac/331 The ISME Journal https://doi.org/10.1038/s41396-021-00919-9

ARTICLE

Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

1 2 3 1 1 Serdar Turkarslan ● Nejc Stopnisek ● Anne W. Thompson ● Christina E. Arens ● Jacob J. Valenzuela ● 1 2 2 4 5 James Wilson ● Kristopher A. Hunt ● Jessica Hardwicke ● Adrián López García de Lomana ● Sujung Lim ● 6 7 7 7 6 2 Yee Mey Seah ● Ying Fu ● Liyou Wu ● Jizhong Zhou ● Kristina L. Hillesland ● David A. Stahl ● Nitin S. Baliga 1

Received: 26 July 2020 / Revised: 18 December 2020 / Accepted: 29 January 2021 © The Author(s) 2021. This article is published with open access

Abstract Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of

1234567890();,: 1234567890();,: Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR− and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.

Introduction

Syntrophic interactions between bacteria and archaea are a major driver of anaerobic transformations of >1 gigaton/ year of C into methane, which is ~30 times more potent These authors contributed equally: Serdar Turkarslan, Nejc Stopnisek than CO2 as a greenhouse gas [1]. Across diverse anoxic environments, including anaerobic reactors, animal guts, Supplementary information The online version contains ocean and lake sediments and soils, in the absence of supplementary material available at https://doi.org/10.1038/s41396- 021-00919-9. respirable electron acceptors, such as nitrate and sulfate,

* Kristina L. Hillesland 3 Department of Biology, Portland State University, Portland, OR [email protected] 97201, USA * David A. Stahl 4 University of Iceland, Reykjavík, Iceland [email protected] 5 Division of Geological and Planetary Sciences, California Institute * Nitin S. Baliga of Technology, Pasadena, CA 91125, USA [email protected] 6 Biological Sciences, University of Washington Bothell, Bothell, WA 98011, USA 1 Institute for Systems Biology, Seattle, WA 98109, USA 7 Institute for Environmental Genomics and Department of 2 Civil and Environmental Engineering, University of Washington, Microbiology & Plant Biology, University of Oklahoma, Seattle, WA 98195, USA Norman, OK 73072, USA S. Turkarslan et al. diverse syntrophs partner with methanogens to oxidize fitness contributions of each interacting organism. Prior organic material. Syntrophy can be either obligate or work using synthetic communities of yeast, E. coli and facultative, for example, although oxidation via sulfate Salmonella enterica have demonstrated the potential for respiration (SR) is energetically favorable compared to synergistic epistasis to improve interspecies cooperation syntrophy, many sulfate-reducing bacteria are facultative [14–16]. Here, we have investigated whether intergenomic syntrophs that conditionally engage in syntrophy with synergistic epistasis can indeed emerge during evolution to methanogens in the absence of sulfate [2]. enhance cooperativity (combined metabolic activity of Conditional switching between syntrophy and SR is interacting microorganisms for efficient cross-feeding) and energetically expensive, requiring the differential regulation productivity of a mutualism that plays a central role in of thousands of genes [3]. Not surprisingly, frequent fluc- biogeochemical C cycling across diverse environments. tuations between SR and syntrophy was demonstrated to be Further, we have also investigated whether intergenomic energetically unsustainable for a coculture of Desulfovibrio epistasis might also contribute to the coexistence of vulgaris Hildenborough (Dv) and Methanococcus mar- assemblages of a generalist and their specialized variants ipaludis S2 (Mm)[3]. By contrast, prolonged laboratory within the same evolution line. Briefly, we tracked the evolution of the same community under obligate syntrophy longitudinal patterns in which mutations accumulated in Dv conditions resulted in significantly improved growth and and Mm across 1000 generations of nine independent evo- stability within 300 generations, but at the expense of loss lution lines. From the 1 K generation of two lines, we of independence through the erosion of SR [4, 5]. Another generated simplified communities through serial end-point striking discovery was that a subpopulation of cells capable dilutions (EPDs). Bulk sequencing of the simplified com- of respiring sulfate (SR+) persisted in low frequency within munities revealed how parental mutations were segregated the dominant non-sulfate respiring (SR−) populations for into each EPD, and discovered evidence for the existence of most evolved lines [5]. Persistence of SR+ cells during interactions among specific evolved lineages of Dv and Mm, syntrophy suggested that they may be adapted to a narrow within the same evolution line. Through single-cell niche that the dominant SR− population is unable to exploit sequencing, we then inferred and characterized interac- effectively. One hypothesis is that SR+ and SR− have tions within a SR+ and a SR− EPD derived from the same specialized growth dynamics, allowing for their coex- parental population. Finally, we quantified growth rate, istence, e.g., as r- and K-strategists in a seasonal environ- yield, and cooperativity of each EPD, and pairings of ment [6–8]. Another consideration is that the Black Queen evolved and ancestral clonal isolates of Dv and Mm. These Hypothesis (BQH) can explain the persistence of the SR+ analyses uncovered synergistic epistasis as a plausible population [9]. In this hypothesis, the SR+ population mechanism for the increased cooperativity of mutualistic subsists by producing a costly metabolite that SR− cells interactions within EPDs, giving likely mechanistic expla- cannot. Dependency of SR− cells on the metabolite pre- nation for coexistence of SR+ and SR− assemblages in the vents them from completely excluding SR+ cells even same community (Fig. 1). though the SR+ cells pay the cost for the metabolite. Given that mutations in many pathways in the two organisms could have improved the mutualism, this also raised the Results possibility that distinct interactions between SR− and SR+ populations and different subpopulations of evolved Mm Distribution, frequency, and functional implications (partner choice [10]) could have independently increased of mutations during laboratory evolution of the productivity of syntrophy in each of the two sub- obligate syntrophy populations. Notably, naturally occurring polymorphisms in ion-translocating CooK subunit of the membrane-bound We evaluated whether the selection of mutations in the COO hydrogenase of Dv are known to be essential same genes (i.e., “parallel evolution” [17]) had contributed for mutualism with Mm, demonstrating that partner choice to improvements in syntrophic growth of Dv and Mm across is important in promoting facultative syntrophic independent evolution lines, all of which started with the interactions [11]. same ancestral clone of each organism. The goal of this In coevolved microbial interactions, the fitness of indi- analysis was to focus on generalized strategies for adapta- vidual organisms may depend on the genotypes of both tion to syntrophy, irrespective of the culturing condition so partners [12]. These epistatic interactions between two we investigated parallelism across both U and H lines. genomes of different species can be described as a form of Based on the number of mutations (normalized to gene “intergenomic interaction” [13]. Intergenomic interactions length and genome size) in Dv and Mm across 13 evolved can manifest in overall fitness of the community that is lines (six lines designated U for “uniform” conditions with greater (synergistic) or less (antagonistic) than the sum of continuous shaking and seven H lines for “heterogenous” Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Clonal Dv Isolates Growth rate UE3.03 (x96) End Point pairings Growth yield Dv HA2,HA3,HE2, Dilutions Mm FACS single cell not shaking HE3,HR1,HR2,HS3 sequencing sorting UE3.03 (x96) transfer # EPD.UE3-03 Mm Dv 1015 45 76 118 152 x7 UE3 100 300 500 780 1000 generation # Dv Mm Ancestor EPD.UE3-09 FACS UE3.09 (x96) Clonal single cell shaking Dv sorting UA2,UA3,UE2, Isolates sequencing x6 UE3,UR1,US1 End Point pairings Growth rate Mm Growth yield UE3.09 (x96) Dilutions Mm

Sequencing Early-Generations 1K EPDs Clonal-isolates Single Cells (4 generations x 9 lines) (13 Lines) (UE3: 3 EPDs, (UE3: 3 EPDs, 8 clones of Dv and Mm, (UE3 line, 2 EPDs, HR2: 3 EPDs) HR2: 3 EPDs, 9 clones of Dv and Mm) 96 cells of Dv & Mm) Fig. 1 Overview of directed laboratory evolution to probe evolu- isolates, and single cells to identify genomic alterations. In addition, tionary signatures for syntrophic cocultures of Dv and Mm. Thir- clonal isolates were paired in varied combinations in order to deter- teen independent cocultures were subjected to laboratory evolution mine growth rate and yield for cocultures. Number of samples with and without shaking as described before [5]. DNA samples were sequenced are indicated at the bottom. collected across generations, end-point-dilutions (EPDs), clonal conditions without shaking), we calculated a G-score [18] two missense mutations in UE3 (S223Y) and UA3 (T242P). (“goodness-of-fit”, see “Methods” section [18]) to assess if Notably, the regulator of the archaellum operon the observed parallel evolution rate was higher than (MMP1718) had the highest G-score with frameshift (11 expected by chance. The “observed G-score” was calculated lines) and nonsynonymous coding (2 lines) mutations [23]. as the sum of G-scores for all genes in the genome of each Similarly, two motility-associated genes of Dv (DVU1862 organism; mean and standard deviation of “expected and DVU3227) also accumulated frameshift, nonsense and G-scores” were calculated through 1000 simulations of nonsynonymous mutations across 4 H and 3 U lines. randomizing locations of observed numbers of mutations Together, these observations were consistent with other across the genome of each organism. The observed total laboratory evolution experiments performed in liquid media G-score for Dv (1092.617) and Mm (805.02) was sig- [24], suggesting that retaining motility has a fitness cost nificantly larger than the expected mean G-score (Dv: during syntrophy [25, 26]. 798.19 ± 14.99, Z = 19.63 and Mm: 564.83 ± 15.95, Z = Consistent with our previous observation that obligate 15.06), demonstrating significant parallel evolution mutual interdependence drove the erosion of metabolic across lines. independence of Dv [5, 27], mutations in SR genes were With the exception of five high G-score genes among the top contributors to the total G-score in Dv (DVU0597, DVU1862, DVU0436, DVU0013, and (DVU2776 (74.7), DVU1295 (46.5), DVU0846 (42.9), and DVU2394), which were mutated during long term salt DVU0847 (22.3)). However, it was intriguing that DVU2776 adaptation of Dv [19], mutations in other high G-score (DsrC), which catalyzes the conversion of sulfite to sulfide, genes appeared to be putatively specific to syntrophic the final step in SR, accumulated function modulating but not interactions. Altogether, 24 genes in Dv and 16 genes in loss-of-function mutations across six lines. The functional Mm associated with core processes had accumulated func- impact of these mutations is not clear but it is possible that tion modulating mutations across at least 2 or more evolu- these changes might alter previously suggested alternative tion lines (Fig. 2 and Supplementary Table S1). Signal roles for this gene, including electron confurcation for the transduction and regulatory gene mutations (seven in Dv oxidation of lactate [28], sulfite reduction, 2-thiouridine bio- and six in Mm) represented 19.9% and 27.2% of all muta- synthesis and possibly gene regulation [29]. tions in Dv and Mm, respectively, similar to long term laboratory evolution of E. coli [18], potentially because Analysis of temporal appearance and combinations their influence on the functions of many genes [20, 21]. We of mutations across evolution lines also observed missense and nonsense mutations in outer membrane and transport functions (four genes in Dv and Growth characteristics of all evolution lines improved by three genes in Mm). For example, the highest G-score gene the 300th generation [4], and in some lines even before the in Dv, DVU0799—an abundant outer membrane porin for appearance of SR− mutations, indicating that mutations in the uptake of sulfate and other solutes in low-sulfate con- other genes had also contributed to improvements in syn- ditions [22], was mutated early across all lines, with at least trophy. Each evolution line had at least 8 and up to 13 out of S. Turkarslan et al.

ABDesulfovibrio vulgaris Methanococcus maripaludis DVU0799 DVU0013 1654660 MMP1718 1340400 MMP1361 885600 14 156.6 18000 4 32.8 1654640 13 166.4 2 12.3 885300 Transport/OM 1654620 1340200 Transcription 17000 Regulation/Signal trans. 1654600 Regulation/Motility 885000 conserved hypothetical 1340000 DNA−directed RNA hypothetical protein 16000 sensory box histidine kinase 1654580 archeal protein polymerase subunit B 1339800 D DVU1283 MMP0327 2883900 1376040 422000 MMP0419 VU2776 324700 2883800 6 74.7 1376020 3 27.1 12 115.5 2 12.2 2883700 1376000 421500 324650 2883600 Sulfate respiration 1375980 421000 Transport/OM 324600 2883500 dissimilatory sulfite reductase 1375960 UTP−glucose−1−phosphate Sodium:neurotransmitter Metabolic/Nucleotide 2883400 subunit gamma uridylyltransferase 420500 1375940 symporter 324550 Thymidine phosphorylase D D 1348500 MMP1511 MMP0694 VU1260 VU0001 684500 1348000 6 58 1500 3 24.8 1470500 8 72.3 684000 2 11.4 1470000 1347500 1000 Regulation/Signal trans. 683500 1347000 Transport/OM 1469500 Transport/OM 683000 500 chromosomal replication Nucleotide-binding 1346500 1469000 Sodium:alanine symporter 682500 outer membrane protein P1 0 initiator protein DnaA 682000 Beta−lactamase−like DVU1862 D MMP1227 1930400 934050 MMP1363 5 49.1 934000 3 22.3 VU0847 6 58 1343800 2 10.1 1930200 933950 1217250 1930000 Sulfate Respiration 1217000 1343700 Motility 933900 Metabolic/Porphyrin Transcription 1929800 933850 adenylylsulfate reductase 1216750 Uroporphyrin−III C/tetrapyrrole 1343600 RNA polymerase diguanylate cyclase 933800 subunit alpha 1929600 1216500 methyltransferase 1343500 alpha subunit DVU2894 DVU3227 3396250 MMP0335 Mutation 5 48.5 3396200 2 17.5 5 52.3 G-score

332700 A2 2991500 3396150 count U HE3 HS3 HA3 HE2 UE3 UE2 US1 HR1 HR2 Regulation/Signal trans. 3396100 Motility UR1 2991000 sigma−54 dependent flagellar basal body− 332650 conserved hypothetical Gene Function transcriptional regulator 3396050 associated protein Evolution Line 3396000 332600 protein DVU1295 DVU0436 490200 1290500 MMP1303 1389000 5 46.5 2 17.1 6 46.7 490100 1290250 Mutation Frequency 1388600 490000 Regulation/Signal trans. Sulfate respiration 1290000 Regulation/Signal trans. 1388200 489900 TetR family Sensory transduction 1387800 sulfate adenylyltransferase 489800 transcriptional regulator 1289750 histidine kinase D DVU2395 MMP1362

2498000 VU2394 1343000 5 45.7 2 15.1 4060 80 100 2499000 1342500 5 37.6 2497500 Regulation/Signal trans. 1342000 Transcription 2498500 Regulation/Signal trans. 2497000 sigma−54 dependent transcriptional 1341500 DNA−directed RNA regulator/response regulator sensor histidine kinase 1341000 polymerase, beta subunit

D Predicted Impact DVU2451 14992.50 MMP0209 V

Genomic Coordinates 217200 2557000 5 43.7 14992.25 2 14.7 U 3 26.6 2556500 A0011 217100 HIGH 2556000 14992.00 Nitrogen metabolism 217000 2555500 Transport/OM Metabolic/A. acid 2555000 14991.75 nitrogenase molybdenum 216900 Conserved hypothetical L−lactate permease iron protein subunit beta 216800 protein MODERATE 2554500 14991.50 216700 DVU0846 DVU0797 933300 MMP0166 4 42.9 883500 2 14.6 176000 3 21.2 933200 175500 Sulfate respiration 883400 Transport/OM 933100 adenylylsulfate 883300 175000 MatE family member reductase subunit beta hypothetical protein 174500 (drug/sodium antiporters) D D 968220.5 MMP0357

1306000 VU1214 VU0876 1305500 5 41.3 968220.2 2 14 354600 2 13.6 1305000 968220.0 1304500 354400 Metabolic/Carbohydrate. dolichyl−phosphate−mannose 968219.8 UDP−N−acetylglucosamine 1304000 protein mannosyltransferase metallo−beta−lactamase 354200 1303500 968219.5 2−epimerase D D 1199000 MMP0033 VU2210 VU1092 51400 4 35 2306000 2 13.9 1198500 51200 2 13 1198000 2305900 Transport/OM 51000 1197500 sodium−dependent 2305800 Regulation/Signal trans. 50800 1197000 symporter family protein 2305700 hypothetical protein LysR family member D DVU0597 1116000 MMP1077 666750 VU1012 4 33.2 1114000 2 7.7 1068400 2 12.7 666500 1112000 Biofilm 1068000 Metabolic/Carbohydrate. 666250 Regulation/Signal trans. 1110000 Hemolysin type Ca-binding 1067600 Phosphoglucomutase 666000 regulatory protein LytS repeat-containing protein phosphomannomutase 1067200 Mutation Mutation Mutation A2 A3 G-score G-score count count G-score U U UE3 HA3 US1 UE2 HS3 HA2 HE2 HE3 HR2 UR1 HR1 count UA2 UA2 UA3 UE2 UE3 HA2 HA3 HE2 HE3 HS3 US1 HS3 HE2 HA2 HA3 HE3 UE2 UE3 US1 HR2 UR1 HR1 HR2 UR1 Gene Function Gene Function Evolution Line Evolution Line Evolution Line Gene Function Fig. 2 Frequency and location of high G-score mutations in Dv (A) indicated inside each panel. Mutations for each gene are plotted along and Mm (B) across 13 independent evolution lines. SnpEff predicted their genomic coordinates (vertical axes) across 13 evolution lines impact of mutations* are indicated as moderate (orange circles) or high (horizontal axes). Total number of mutations for a given gene is shown (red circles) with the frequency of mutations indicated by node size. as horizontal bar plots. [*HIGH impact mutations: gain or loss of start Expected number of mutations for each gene was calculated based on and stop codons and frameshift mutations; MODERATE impact the gene length and the total number of mutations in a given evolution mutations: codon deletion, nonsynonymous in coding sequence, line. Genes with parallel changes were ranked by calculating a G change or insertion of codon; low impact mutations: synonymous (goodness of fit) score between observed and expected values and coding and nonsynonymous start codon].

24 high G-score mutations in Dv, while Mm had mutations generation of HA2, they appeared much later in HR2 and in at least 5 and up to 10 out of 16 high G-score genes. We HA3) (Fig. 3A). Similar temporal patterns of appearance interrogated the temporal order in which high G-score and co-occurrence of mutations were observed in Mm mutations were selected and the combinations in which they (Fig. 3B). We also discovered evidence for temporally co-existed in each evolution line to uncover evidence for nested fixations, wherein prior to fixation of a mutation epistatic interactions in improving obligate syntrophy. from an earlier generation, another mutation selected in a Indeed, missense mutations in DsrC (DVU2776) were fixed later generation gradually increased in frequency towards simultaneously with the appearance of loss of function fixation e.g., DVU0799, DVU0001, and DVU1283 in HA3 mutations in one of two sigma 54 type regulators (P = 1.19 × 10−3); and MMP1718 and MMP0335 in UA3 (DVU2894, DVU2394) in lines HA2, and UR1 (P = 5.40 × (P = 1.81 × 10−4). Moreover, there were many cases of 10−5). In rare instances, we also observed that some high G- simultaneous fixation of mutations in multiple genes (e.g., score mutations co-occurred across evolution lines, e.g., two DVU0799 and DVU1214 in HE3; MMP0378, MMP0705, U- and one H-line consistently showed for at least two time MMP0986, and MMP1170 in HA2) suggesting that hitch- points a mutation in DVU1283 (GalU) coexisting with hiking may be common [30, 31]. However, given that mutations in DVU2394 (P = 5.04 × 10−3). More com- samples were only sequenced every 250 generations, we monly, the combinations of high G-score gene mutations cannot rule out the possibility of each mutation sweeping varied across multiple lines. In fact, no two lines possessed separately during that time interval. These observations lead identical combination of high G-score gene mutations us to conclude that mutations that were commonly selected (Fig. 3A, B), and many high-frequency mutations were may simply have additive effects on fitness, arising at dif- uniquely present or absent in different lines (Fig. 3C, D). ferent times in different populations because of chance (i.e., Mutations in high G-score genes appeared consistently in they became available for selection at different times in all evolution lines (P < 1.82 × 10−2), although in a different different populations). temporal order in each line. Mutations in the same high The longitudinal analysis revealed a cross-species G-score genes appeared at different times (e.g., whereas selection event that resulted in the replacement of the mutations in SR gene DVU0847 first appeared in the 300th dominant clones of both species with new clones containing Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

ABDesulfovibrio vulgaris Hildenborough (Dv) Methanococcus maripaludis S2 (Mm) HA2 HA3 HE3 HR2 HS3 UA3 UE3 UR1 US1 HA2 HA3 HE3 HR2 HS3 UA3 UE3 UR1 US1 15 10 G-score 5 G-score 5 Mutation Count Rank Rank Mutation Count 0 1 DVU0799 2 MMP0419 3 DVU1260

12 DVU0597 1 MMP1718 2 DVU2776 7 DVU2394 7 MMP1362

8 DVU2451 5 MMP0335 4 DVU1862 DVU0013 13 3 MMP1511 6 DVU1295 5 DVU2894 6 MMP1303 10 DVU1214 4 MMP1227 15 DVU0001 Mutated Locus 14 DVU1283 9 MMP0166 IG_184033

21 DVU0797 8 MMP0209 16 DVU0847 DVU1632 10 MMP0357

9 DVU0846 MMP1255 11 DVU1092 20 DVUA0011 MMP1611 17 DVU3227

22 DVU0876 MMP1314 DVU2405 IG_1429948 DVU1012

Generations Generations Frequency (%) Mutation Impact Frequency (%) Mutation Impact 1K 1K low rate low 500 high 100 300 780 high 100 500 780 40 60 80 100 300 40 60 80 100 modifier modifier mode moderate

Desulfovibrio vulgaris Methanococcus CDEHildenborough (Dv) maripaludis S2 (Mm) HA3 HE3 HR2 HS3 UE3 UR1 HA2 HA3 HE3 HR2 HS3 UR1 US1 HS3 MMP1186 1 DVU0799 DVU2210 MMP0378 12 DVU0597 DVU0150 MMP0705 21 DVU0797 MMP0986 13 DVU0013 Selective DVU0796 MMP1170 15 DVU0001 MMP0033 MMP1511 sweep DVU1833 MMP0234 3 MMP0939 7 MMP1362 DVU1083 MMP0694 MMP1255 MMP0146 MMP1611 DVU2396 MMP0643 7 DVU2394 DVU2244 IG_1439720 8 DVU2451 MMP0026 4 DVU1862 DVU2609 MMP0466 IG_184033 MMP1557 MMP0466 DVU0845 MMP0952 MMP1077 MMP1557 HS3

Mutated Locus DVU0672 MMP1479 MMP0952 MMP1180 MMP1077 specific DVU0436 IG_646987 MMP1479 mutations MMP1363 DVU2609 DVU1788 MMP1720 DVU0845 Generations Generations 1K 300 500 780 Generations100 1K 1K 100 780 300 500 780 100 300 500 Fig. 3 Frequency and time of appearance of mutations through 1 mutations in each generation and the color indicates impact of muta- K generations of laboratory evolution lines of Dv and Mm cocul- tion. Use “Frequency”, “Generations”, and “Mutation impact” key tures. The heat maps display frequency of mutations in genes (rows) below the heat maps for interpretation. Mutations that were unique to in Dv (A) and Mm (B) in each evolution line, ordered from early to each evolution line is shown in (C, D) for Dv and Mm, respectively. E later generations (horizontal axis). High G-score genes are shown in The heatmap illustrates a selective sweep across both organisms in red font and their G-score rank is shown to the left in gray shaded box, line HS3. also in red font. Bar plots above heat maps indicate total number of different mutations. Between generations 500 and 780 of dominant mutations in MMP1255, MMP1611, MMP1362, HS3, the dominant Dv (harboring high G-score mutations and MMP1511) clones disappeared (Fig. 3E). At the same DVU0799, DVU0597, DVU0797) and Mm (harboring time a new Dv clone with mutations in DVU2394, S. Turkarslan et al.

DVU2451, DVU1862, and intergenic region IG_184033, represented minimal sets of genotypes with growth phe- and a new Mm clone with mutations in MMP0952, notypes comparable to the 1 K culture (see “Methods” MMP1077, and MMP1479 were selected (Fig. 3E). One section). While two EPDs from each line represented the explanation for this phenomenon is that, coincidentally, rare dominant SR− subpopulation of the 1 K evolved line, we clones in both Dv and Mm acquired beneficial mutations also recovered an SR+ subpopulation that co-existed and outcompeted dominant clones in the same 250 gen- within each line albeit at much lower abundance and eration interval of evolution. Another possibility is that below the detection limit of bulk mutation analysis of the selection of a new dominant clone in one species changed parental culture (Fig. 4). Finally, we isolated evolved the selection environment for the other, allowing its rare clones of each organism by streaking EPDs on agar plates clone to take over. Which species might have started this containing nalidixic acid and neomycin, taking advantage process is unclear because there are no samples available in of chromosomally integrated selection markers in Dv and the 250 generations during which the sweep occurred. Mm, respectively. Altogether, three clones of Dv and Mm However, information about the new mutations, their from each EPD were isolated and re-sequenced. The functions, and parallel evolution may provide hypotheses. distribution of unique mutations across EPDs and clonal The novel mutations in DVU2394 (a sigma 54-dependent isolates added evidence for coexistence of distinct linea- transcriptional regulator) and DVU2451 (a lactate per- ges of one or both organisms within each evolved line. mease) co-occurred in at least two lines including HS3 Logically, all high-frequency mutations in an asexual (P = 3.93 × 10−2) and appeared individually in only three population must be linked on the same genetic back- other lines, suggesting that the two genes might be bene- ground. As expected, all 15 high-frequency mutations ficial and also functionally coupled in the context of pro- detected in the 1 K generation of UE3 were present only in moting syntrophy. Notably, we demonstrate later through sub-communities with the SR− mutations (EPD-03 and single-cell analysis that mutations in DVU2394 occurred EPD-10). By contrast, at least 11 mutated loci (ten genic subsequent to mutations in DVU2451, but exclusively in and one intergenic) in the SR+ sub-community (EPD-09) the SR− lineage within UE3. Interestingly SR− mutations were not detected in the SR− sub-communities or in 1 K were never selected through 1000 generations in HS3 line. bulk sequencing of UE3, demonstrating that the EPD-09 Conversely, while mutations in DVU2394, DVU2451, and assemblage was made up of rare Dv lineages (Fig. 4Aand DVU1862, all co-occurred in UE3, they did not sweep Supplementary Table S2). Strikingly, both Dv and Mm through the population, underscoring how improvements to lineages in the SR+ assemblage of HR2 were distinct syntrophic interactions occurred through multiple distinct from lineages in the SR− EPDs, and below detection limit trajectories in terms of the order and combinations of in 1 K bulk sequencing (Fig. 4B, Supplementary Fig 1 and mutation selection. In other words, this cross-species Supplementary Table S2). Thus, the existence of geno- selective sweep occurred only in HS3, suggesting one of typically distinct subpopulations of Dv and Mm with the several features unique to this line was responsible, parental growth phenotype suggested that specificinter- including simultaneous selection of mutations in DVU2394, actions across multiple evolved genotypes of the two DVU2451, and DVU1862, the overall mutational landscape organisms could have emerged during their syntrophic of HS3 between generations 500 and 780, or mutations evolution. unique to HS3. Interestingly, fixed mutations that were We further investigated the evidence for specific observed only in HS3 were in Mm (MMP0952, MMP1077, interactions among evolved genotypes using single-cell MMP1479) and their appearance coincided with the selec- sequencing of SR− (EPD-03) and SR+ (EPD-09) tive sweep between 500 and 780 generations. Regardless of assemblages from UE3. We sorted, amplified, and re- the mechanism, it is interesting that a new mutation(s) in sequenced the genomes of single cells of Dv (94 from Mm appears to have selectively swept high G-score muta- EPD-03, and 94 from EPD-09) and Mm (87 from EPD-03, tions across both interacting organisms, strongly suggesting and 72 from EPD-09) to reconstruct lineages of both that the new Mm genotype conferred a fitness advantage to a organisms within each EPD ([32]and“Methods” section, specific lineage of genotypes in Dv that were in low Supplementary Table S3). Using stringent cutoffs (fold abundance prior to the sweep. coverage ≥ 8, number of cells with mutation ≥2, fre- quency ≥ 80%) and consensus mutation calling using Characterization of evolutionary lineages and varscan [33], GATK [34], and Samtools [35], we identi- interspecies interactions in minimal assemblages at fied across single cells of Dv 16 of 17 and 3 of 12 single-cell resolution mutations detected in bulk sequencing of EPD-03 and EPD-09, respectively. Similarly, we identified across Mm We performed EPDs from the 1 K generation of HR2 and single cells seven of seven and six of seven mutations UE3 lines to generate simplified sub-communities that from bulk EPD-03 and EPD-09, respectively. Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

A B UE3 HR2 SR- Desulfovibrio SR+ EPD-10 SR- EPD-10 SR+ Clone 02 1K Gen. EPD-09 1K Gen. EPD-10 EPD-01 EPD-10 EPD-03 EPD-05 Type Type Type DVU1838−1909758 DVU3277−3452476 DVU1453−1531779 IG−2053158 DVU1942−2016435 1K−gen. DVU2451−2556376 DVU3152−3305497 DVU0168−209232 DVU3227−3396071 Clonal DVU0184−229814 DVU2451−2555217 isolates DVU1483−1561378 DVU0151−185882 DVU0597−666775 DVU0597−666321 DVU1260−1346834 EPD DVU1862−1929822 DVU1295−1388181 DVU1283−1376015 DVU0799−885161 DVU0799−885112 DVU0001−412 DVU2776−2883762 DVU3227−3396063 DVU1092−1198488 DVU1083−1187319 DVU0847−933834 M DVU0846−933091 DVU2395−2498389

DVU1260−1346673 IG−495942 ut DVU1295−1388854 IG−1259554

DVU2394−2497733 DVUA0075−101865 a

DVU1349−1426765 tions DVU1862−1929873 DVUA0075−101864 DVU1214−1305196 DVU1337−1413556 DVU1632−1716114 DVU3152−3305221 DVU2210−2306515 DVU0670−743018 DVU0030−37335 IG−1010502 IG−495942 DVU1283−1375964 DVU2305−2398566 DVU1082−1186730 DVU0436−490134 DVU1283−1376222 DVU0799−885407 DVU1571−1653920 DVU1260−1346657 DVU0799−885257 DVU2253−2349370 DVU2395−2498730 DVU0916−1010155 100 DVU2394−2497015 DVU0145−180302 DVU2451−2555119 DVU1571−1654242 DVU3233−3402340 80 DVU1425−1499475 DVU3376−3549107 IG−2082600 DVU1017−1118479 IG−2082602 DVU1214−1305310 DVU0002−2473 DVU0671−744487 60 DVU0845−932922 IG−1555094 DVU0916−1010092 DVU3152−3305497 DVU0670−742697 40 DVU3152−3305221 DVU1283−1376331 DVU2083−2170335 DVU2894−2991137 IG−1297045 DVU2405−2510665 DVU0151−186541 20 IG−1297047 DVU1082−1186581 DVU1634−1716832 DVU0597−666321 DVU3152−3306280 DVU2305−2398628 0 Methanococcus Type Type MMP1591−1540747 MMP1303−1289826 MMP0669−658751 MMP1612−1558801 MMP1718−1654605 MMP0166−175754 MMP1362−1341204 MMP0419−420683 MMP0146−156264 MMP0419−421352

MMP1227−1216664 M IG−1439720

MMP0643−635006 ut MMP0209−216934 MMP1511−1469819 a

MMP1718−1654605 tions MMP1361−1340302 MMP1314−1298610 MMP0335−332700 MMP1511−1469519 MMP0419−421946 MMP1511−1469074 MMP1119−1108915 IG−308883 MMP0251−252299 MMP0111−120330 MMP0094−104053 IG−1627425 MMP1511−1469741 MMP1511−1469773 MMP0209−216924 MMP0762−753653 MMP1099−1092628 1K Generation EPD-01 Clone 01 EPD-01 Clone 02 EPD-01 Clone 03 EPD-05 EPD-05 Clone 01 EPD-05 Clone 02 EPD-05 Clone 03 EPD-10 EPD-10 Clone 01 EPD-10 Clone 02 EPD-10 Clone 03 EPD-01 EPD-09 Cl EPD-10 EPD-10 Clone 02 EPD-10 Clone 03 EPD-09 EPD-09 Clo 1K Generation EPD-03 EPD-09 Cl EPD-03 Clon EPD-03 Cl EPD-03 Clon o o one 02 n ne 02 ne 01 e 03 e 01 e 03

Samples Samples Fig. 4 Genotype mapping of 1 K generation, EPDs and clonal Dv and the lower panel for Mm. The hierarchical tree indicates a isolates for two evolution lines. Heatmap displays frequency for each simplified lineage map of mutations in Dv within each evolution line, mutation (rows) in UE3 (A) and HR2 (B) across 1 K generation, EPDs, with SR phenotypes indicated. and clonal isolates (columns). The upper panel shows genotype map of

Using a mutation lineage inference algorithm SCITE organisms. While the Mm lineages across EPDs had few [36] and cross-referencing with longitudinal sequencing differences, lineages of Dv were strikingly different data from 100, 300, 500, 780, and 1000 generations, bulk across the SR− and SR+ communities. The SR− muta- sequencing of EPDs, single-cell sequencing, and tions in the EPD-03 lineage were followed by selection sequencing of clonal isolates, we reconstructed the line- of mutations in at least six regulators, and complex age and timeline of mutations that shaped the evolution of radiating branches with many coexisting sub-clones, syntrophyinSR− and SR+ communities within UE3 (see suggesting that loss of SR in the EPD-03 line might have “Methods” section) (Fig. 5 and Supplementary Figs. 2–3). promoted the selection of mutations in regulatory genes. As expected, the two EPDs shared a core lineage of Altogether, the observation that dominant lineages were events that included sequential accumulation of high excluded in the minimal community assemblages of G-score mutations in the early stages of evolution in both EPD-09, demonstrates the coexistence of distinct high S. Turkarslan et al.

A DVU1571−1654242 Clone 1

EPD-10 DVU1634−1716832 Clone 2 UE3_1K Mutations in Sulfate DVU1016 IG−2053158 Respiration Pathway 8 DVU2451−2556376 Single Cells 7 DVU2394−2497733 DVU1502 DVU2003 4 DVU1862−1929822 IG_3258643 IG_175901p DVU1483−1561378 DVU2078 IG_2687527 6 DVU1295−1388854 14DVU1283−1376015 3 DVU1260−1346673 DVU0145−180302 IG_1834332 IG_2356552 DVU2014 11DVU1092−1198488 DVU0598 IG_1739979 9 DVU0846−933091 1 DVU0799−885112 IG_2731367 DVU0184−229814 DVU1488 DVU0168−209232 11 7 DVU3106 780 2 DVU2776−2883762DVU2776−2883762 IG−49089 DVU1092 DVU2394 EPD-03 DVU0724 IG_1590370 DVU3277−3452476 IG_2211448 DVU3152−3305221 DVU3129−3276860 DVU0680 Single Cells DVU2815 Clone 1 DVU0606 IG_1761165 500 12DVU0597 DVU1788 DVU2662 DVU3152−3305497 IG_178760p Clone 2 14 DVU1283 300

DVUA0073−99977 (*) DVU3152−3306280 Clone 3 1 DVU0799 DVU2320 IG_3217507 100 IG−1297047 DVU1588 DVU0672 DVUA0025 IG−1297045 DVU2083−2170335 IG_46303 IG−882511 Clone 2 Single Cells IG−716874 DVU0279 IG−42867 EPD-09 IG_141105 IG−3457155 IG−3455727 IG−495942 IG−3066926 19 DVU2395−2498730 IG_2356552 IG−3056212 23 DVU2210−2306515 DVU0653 IG−1555094 IG−2982788 4 DVU1862−1929873 DVU0002−2473 IG−2502193 DVU1632−1716114 IG_2748309 IG−211389 DVU1571−1653920 Clone 3 IG−2083305 14 DVU1283−1376222 IG−1897096 10 DVU1214−1305196 IG−1313341 DVU1082−1186730 IG−1144620 IG−2082602 DVU3023−3142198 1 DVU0799−885257 Clone 1 DVU3022−3140594 DVU0030−37335 DVU3022−3140576 DVU2955−3064065 IG−2082600 DVU2955−3064064 DVU1425−1499475 DVU2664−2775672 DVU2287−2381877 DVU2078−2162235 DVU2023−2104739 DVU1842−1913197 Frequency Node size G-score rank DVU1698−1773344 DVU1698−1773256 # of single-cells DVU1349−1426830 1 DVU1087−1191166 100% with mutation Ancestor 260

B MMP1119−1108915 Single cells Clone 3 MMP1179 Ancestor UE3_1K 3 MMP1511−1469519 EPD-03 1 MMP1718−1654605 MMP0172 MMP1477−1438687 MMP0111−120330 MMP1511 MMP1361−1340302 MMP1169−1153734 Clone 2 6 MMP1303−1289826 MMP0697−687745 Clone 1 4 MMP1227−1216664 MMP0234−241892 2 MMP0419−420683 Clone 3 IG−1495457 8 MMP0209−216934 Clone 1 EPD-10 3 MMP1511−1469741 Clone 2 Frequency Node size # of single-cells 100% with mutation EPD-09 Clone 2 260 MMP0614 Single cells MMP0372 Clone 3 MMP1604 Clone 1 MMP0762−753653 Fig. 5 Lineage map of mutational events deciphered through orange shaded box. An asterisk indicates mutation in a plasmid gene sequencing of up to 96 single cells of (A) Dv and (B) Mm from that was not detected in single cells potentially due to loss of plasmid. EPD-03 and EPD-09, cross-referenced with longitudinal bulk Of the total 11 high G-score Dv genes in the 1 K generation of UE3, sequencing of UE3, EPDs and sequencing of clonal isolates. Tem- just three were observed in both EPDs. Note, the three high G-score poral ordering of mutations in the trunk is based on their order of genes DVU1862, DVU2394, and DVU0799 had mutations in different appearance in longitudinal sequencing data across generations. Unique locations in the two EPDs. High G-score genes that were only mutations within each lineage are shown together with frequency observed in EPD-03 were DVU2451, DVU1260, and DVU1092, and (length of bars). The single-cell lineage tree for each EPD was con- those unique to EPD-09 were DVU2395, DVU2210, and DVU1214. structed using the algorithm SCITE and shown in the context of the In addition, SR− mutations in DVU0846 and DVU1295 were unique parent EPD and linked to clonal isolates. (See Supplementary Figs. 2 to EPD-03, appearing after 780 generations, and were present across and 3 for details). Mutation names for regulatory or signal transduction single cells and all clonal isolates. genes are colored in blue and SR-related genes are indicated with an abundance (SR−) and low abundance (SR+) lineages subsequent to the evolution of SR− was not simply the within the same evolved population (Figs. 4 and 5 and dominant clone without the SR− mutation. Instead, it was Supplementary Figs. 1–3). A surprising observation is a rare genotype with different mutations from the domi- that the SR+ clone that remained in the population nant population. Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Fig. 6 Growth rate, yield and cooperativity of EPDs, and clonal 03 and EPD-09. C Excess-Over-Bliss analysis for estimating syner- isolate pairings. A A stacked barplot showing the number of repli- gistic and antagonistic interactions of Dv/Mm clonal isolate pairings. D cates exhibiting growth for each EPD and the ancestral cocultures Growth rate and yield for three evolved Dv/Mm pairings from across a dilution series. B Growth rate and carrying capacity of pair- each EPD. ings of ancestral and evolved clonal isolates of Dv and Mm from EPD-

Investigation of cooperativity and synergistic interspecies characteristics of the parental EPD, when both partners interactions in the interacting pair were evolved clonal isolates (DvEv × MmEv). This result demonstrated unequivocally We performed a density dilution assay to investigate the that increased cooperativity had emerged from synergistic evidence for improved cooperativity due to interactions interactions between the evolutionary changes in both among specific genotypes of Dv and Mm within microbial species within each EPD, with proportional antagonistic community assemblages of the two EPDs [37, 38]. Briefly, effect on growth yield [39](Fig.6C). The higher growth we generated a dilution series of both EPD and ancestral rate of EPD-03 and higher carrying capacity of EPD-09 cell lines in 96-well plates and determined growth rate, (both relative to the other EPD) gives mechanistic insight carrying capacity, and a minimal cell density that supported into coexistence of SR− and SR+ sub-communities as a syntrophic population growth (See “Methods” section, r-andK-strategists, respectively (Fig. 6D, Supplementary Supplementary Fig. 4). Both EPDs could initiate growth at Fig. 4). Notably, the few mutations that differentiate significantly lower cell density relative to the ancestral genotypes of each clonal isolate appear to manifest in coculture. EPD-03 initiated growth at a 1.5-fold lower cell variation in growth rate and yield, demonstrating that density with faster growth rate and lower carrying capacity productivity of DvEV × MmEV interactions are genotype- relative to EPD-09, explaining how the two EPDs co- specific, even within the same EPD (Fig. 6D, Supple- existed in vastly different proportions in UE3 (>80% EPD- mentary Fig. 5, Supplementary Table S2). 03 vs, <1% EPD-09, Fig. 6A). These data make a com- pelling case for the emergence of increased cooperativity among Dv and Mm lineages during the evolution of Discussion syntrophy. We investigated whether the increased cooperativity We sought to understand the evolutionary trajectories that could have emerged through synergistic interactions increase the productivity of interspecies interactions of Dv between Dv and Mm lineages by characterizing individual with Mm in an obligate syntrophic association, while and combined contributions of the two evolved partners retaining a small subpopulation that can respire sulfate. To towards improved growth characteristics. By comparing do so, we combined a broad survey of all the mutations pairs of evolved and ancestral clones (DvEV × MmEV, accumulated over the first 1000 generations of nine inde- DvAc × MmEv and DvEv × MmAc, DvAc × MmAc), we deter- pendently evolved communities with an in-depth study of mined that each evolved clonal isolate had contributed the genotypic structure of one community down to the individually to significant improvement in growth rate and single-cell level. These data showed a high level of paral- yield (Fig. 6B and Supplementary Table S4). The lelism across communities despite considerable variance improvements were maximal, and comparable to growth across populations in their evolutionary trajectories. A S. Turkarslan et al. detailed view of one community revealed the perseverance H lines suggests that substantial adaptation happened in and evolution of a rare lineage that maintained its ability to both environments. That being said, we also detected par- respire sulfate while the rest of the population did not. allelism, albeit with lower statistical significance, when the Growth experiments with clones and subpopulations analysis was repeated with either U or H lines, separately demonstrated that the SR+ and SR− Dv subpopulations (Supplementary Fig. 1). Genes associated with parallel both cooperate more efficiently with corresponding evolved evolution are usually under strong selection [48], and Mm partners, allowing them to grow at lower starting implicated as a major driver of evolution of bacteria [49], densities than the ancestors. The collective action of clones phages [50] and microbial communities [51–54]. To our within each subpopulation has a synergistic effect on knowledge, this is the first demonstration of a role for population growth rate and an antagonistic effect on yield. parallel evolution in driving mutualism across metabolically Finally, the different growth dynamics of SR− and SR+ coupled species. evolved communities is consistent with how the two com- While the high number of G-score mutations suggests munities might coexist in vastly different proportions, likely that parallel changes conferred fitness benefits across a as r- and K-strategists. range of genotypes [50], in some populations these high G- The evolutionary trajectory of a microbial population score mutations were selected in a different order, sug- depends on the order in which mutations occur (chance), gesting epistasis did not substantially constrain the timing of and the relative effects of the pool of mutations on fitness selection of a given high G-score mutation. Many differ- (selection) [40]. If the effects of each beneficial mutation are ences between populations in mutation order could have constant, meaning they do not vary in the presence of other occurred due to the chance occurrence of mutations at dif- polymorphisms or species, then all populations would ferent times in different populations [55]. However, we eventually acquire the same mutations, even if they occur cannot rule out the possibility that epistasis and evolu- and are, therefore, selected in a different order. However, tionary history caused some of the differences between the effect of an allele on fitness may depend on epistasis, populations [56, 57]. For example, it is possible that a where the effect of an allele changes depending on alleles at mutation unique to HS3 precluded or significantly delayed other loci in the same genome [41]. In this case, the order in erosion of SR in this coculture. which mutations occur in different populations could affect Intergenomic epistasis is a pre-requisite for coevolution their overall trajectories. This relationship between fitness and the synergistic epistasis observed in this study could and the possible combinations of genetic variants is called have caused or resulted from coevolution. There are a few an adaptive landscape, and has been the subject of intense reasons to believe that each species is not evolving inde- research [42–45]. pendently in a constant environment consisting of another In the present work, we investigated evolutionary tra- species, and that some evolutionary changes likely resulted jectories of not just one but two species that rely on one from genetic interactions between specific evolved geno- another for survival. One might expect the interaction to types of Dv and Mm. The most striking example was amplify the effects of chance if the adaptive landscape is observed in community HS3. In this community, it seems affected by genetic changes in the partner population that one or more new mutations in one partner affected the (coevolution; [46, 47]), and those partner genetic changes fitness of the dominant clone of the other partner, causing it depend on chance. In an extreme case, this situation could to decrease in frequency below the limits of detection, while send each population down completely different trajec- a new clone arose. A plausible hypothesis for this inter- tories, with very little parallelism. However, that is not the genomic epistasis is that the selective sweep likely occurred result that was observed here. The discovery of high G- due to the loss of function mutations in MMP1077, a score mutations in both Dv and Mm made a compelling case putative phosphomannomutase, which re-directed mono- that parallel evolution was a dominant driver of productive saccharides towards synthesis of exopolysaccharides to obligate syntrophy (Fig. 2). It is important to emphasize that promote intercellular interactions through clumping or in order to increase statistical power, our assessment of flocculation [58]. Regardless of the mechanism, the inter- parallelism was based on the analysis of all mutations esting observation is that both Dv and Mm clones that were pooled from two different evolution environments (U: in low frequency swept through the entire population, Uniform and H: Heterogenous). While the two treatments indicating preferential interactions among those clones. This were different in terms of mixing, there were also many two-population selective sweep suggests epistasis between similarities, including the chemical composition of the specific genotypes of the two interacting species. This media, the incubation temperature, and the fact that the hypothesis of partner choice was also supported by the species were forced to rely on syntrophy for survival instead observation that growth rates and yields differed between of growing alone with different metabolism. In fact, some pairings of clones within a population, demonstrating observation of similar numbers of mutations in both U and variation in effectiveness of cooperation. Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

While most adaptive mutations rose to fixation, SR It was significant that each of the two EPDs segregated a mutations did not show complete penetrance. In fact, pre- subset of high G-score mutations into simplified assem- viously we reported that SR+ populations were readily blages but retained growth rate and carrying capacity of the obtained from every evolved coculture even after 1300 parental evolved population. This result demonstrated that generations [5] and through characterization of EPDs and multiple independent evolutionary strategies can coexist in single cells we have re-confirmed the presence of rare SR+ the same population, albeit in vastly different proportions. subpopulations in most evolved populations. One explana- Whether the distinct sets of Dv and Mm mutations within tion could be that SR+ cells persist because the main- each EPD reflect coevolution will require additional tenance of SR machinery allows them to produce a costly experiments, including pairing with evolved populations but essential metabolite. Leaking of this metabolite could from preceding generations [47]. Notwithstanding that allow SR− cells to survive without paying the cost of caveat, the ability of evolved isolates of Dv and Mm to production, allowing them to flourish as long as SR+ cells synergistically improve growth characteristics lends cred- and the leaked resource do not become scarce. In other ibility to the claim that complementary genetic changes words, these SR+ cells might act as “helpers” for the (e.g., in transport, regulation, and motility) enhanced “beneficiary” SR− cells as stated by BQH [9]. High metabolic coupling and cross-feeding between the two expression of SR genes even under syntrophic conditions interacting organisms, significantly increasing their [59] supports this hypothesis. However, a minimal assem- cooperativity. blage that is entirely composed of SR− cells (EPD-03 of The nature of cooperation in this syntrophic mutualism is UE3 line) does better than assemblage of SR+ cells (EPD- unclear. On the surface, it seems like the fitness of Dv and 09 of the same line) in cooperativity assays with no Mm would be aligned and exploitation unlikely [61–63] apparent growth defect indicating that SR+ cells do not because the production of hydrogen is a necessary bypro- play an essential role in supporting syntrophic growth of the duct of metabolism for Dv and the only energy source population. In fact, the poor performance of EPD-09 rela- available for Mm.Efficient transfer of electrons through tive to EPD-03 suggests that SR is too expensive to main- hydrogen is in the best interests of both species [64]. tain and, therefore, undesirable during syntrophy. However, evolution could hypothetically change this Moreover, individual SR− clonal isolates synergistically situation by altering mechanisms of electron transfer, or improved growth characteristics of cocultures upon pairing through the evolution of new dependencies that are costly with evolved Mm further demonstrating that coexistence of [47, 65]. One high G-score mutation in Mm (MMP1511) SR+ and SR− populations cannot be explained solely by could reflect the evolution of a new costly dependency. the BQH. Alanine was earlier shown to be exchanged between the two Alternatively, SR+ and SR− cells may be adapted to interacting partners during syntrophic growth, likely at a different niches that arise as a result of the seasonal changes cost to the producer (Dv) and of energetic advantage to Mm in resources that recur in each transfer-cycle of the evolu- [66]. Alanine production by Dv provides a mechanism to re- tion experiment [8]. Specifically, growth dynamics of the oxidize reduced internal cofactors during syntrophic two EPDs [higher growth rate (r) of EPD-03 and higher growth, but at the cost of a high-energy phosphate bond. In carrying capacity (K) of EPD-09] suggest that the faster- turn, alanine taken up and converted to pyruvate and growing SR− lineages (r-strategists) can initiate growth at ammonia by Mm serves as both a carbon and a nitrogen lower cell density and are, therefore, favored in early source, alleviating complete dependency on energetically growth phase when resources are plentiful but fluctuating. costly autotrophic growth with hydrogen. A cheater popu- The slower growing SR+ lineages (K-strategists) are lation, e.g., one with a loss of function mutation in favored in later stages of growth when the resources are MMP1511, might consume additional alanine through limited but stable, and cell density is high [6]. Hence, these passive transport and therefore consume less hydrogen to growth dynamics based on r/K tradeoffs might explain why maintain lactate consumption by Dv. Indeed, mutations in SR+ populations are retained in the absence of sulfate. In MMP1511 rose to fixation in six out of nine lines, and we the natural world, where sulfate availability varies over cannot rule out if minor MMP1511 mutant populations also time, persistence of SR+ genotypes in the absence of sul- exist in low frequency in the other lines, including UE3. fate may stabilize sulfate-reducing populations overall. In The observation that interactions among some genotypes other words, it may be a bet-hedging strategy (similar to were more productive than other pairings suggests that the maintenance of subpopulations with COO hydrogenase enhanced cooperativity of evolved communities could have polymorphisms [11, 60]) that might contribute to the suc- occurred through the selection of complementary mutations cess of Dv as a generalist that can conditionally switch across Dv and Mm, invoking the possibility of partner between SR and syntrophy without the need for expensive choice and partner fidelity feedback [67]. Furthermore, each gene regulatory changes [3]. EPD had significantly better growth characteristics than any S. Turkarslan et al. of the pairings of their member clonal isolates, demon- concentrations were determined using Quant-iT PicoGreen strating the emergence of increased cooperativity from dsDNA assay kit (Thermofisher, MA, USA). Sequencing guilds or “collections of genotypes” of Dv and Mm.In was performed as described above. conclusion, the multiscale dissection of independent laboratory evolution lines has demonstrated that selection of Single-cell lineage tree building complementary mutations across Dv and Mm synergistically increased the cooperativity and productivity of syntrophic Variants detected in at least two cells at >80% frequency interactions within both SR− and SR+ communities, while were converted into a matrix (1 = mutation present, 0 = supporting their coexistence in vastly different proportions mutation absent, or 3 = not enough reads) with unique as r- and K-strategists, respectively. mutation in rows and single cells in columns. Mutation his- tories of single cells were determined using the SCITE algorithm [36] with parameters -r 1 -l 90,0000 -fd 6.04e-5 -ad Methods 0.21545 0.21545 -cc 1.299164e-05. Temporal ordering of mutations was cross-referenced with longitudinal sequencing Strains and culture conditions data for the UE3 line, especially when there was ambiguity due to noisy and missing data. All the strains, culture conditions, and the setup of the laboratory evolution experiment were the same as described Calculation of G-scores before [4, 5]. (See Supplementary Methods for details). G-score (“goodness-of-fit”) for each gene was calculated Sequencing of evolved cocultures based on the frequency of observed nonsynonymous mutations (normalized to gene length and genome size) DNA was extracted with Masterpure Kit (Epicentre, WI, across 13 evolved lines, as described before [18]. G-scores USA), processed for sequencing using Nextera DNA library for all genes in the genome of each organism were summed preparation kit (Illumina, CA, USA) and sequenced on to get the “total observed G-statistic” and compared to the Illumina Hiseq with 100 bp paired-end sequencing or on simulated “total expected G-statistic” by calculating a Z- Illumina MiSeq in the paired-end mode producing 2 × 250 score as described in Supplementary Methods and in [18]. bp long reads as described before [5]. Density dilution assay Identification of mutations in evolved cocultures Ancestral cocultures and EPDs were grown anaerobically in Mutations in populations were determined using a custom balch tubes containing coculture medium A (CCMA) [64] sequence alignment and variant calling pipeline (https:// with 80%:20% N2:CO2 headspace at 30 °C without shaking. github.com/sturkarslan/evolution-of-syntrophy) (Supple- All stationary phase cultures were diluted to the same OD600 mentary Methods). Variant calling was performed with value and subjected to a 1.5-fold dilution series in 96-well GATK UnifiedGenotyper [34], Varscan [33] (version 2.3.9) plates. Blank media were included in the first column of and bcftools from Samtools [68] package. Variants identi- each 96-well plate to rule out contamination. All steps were fied by each caller were collated and filtered for variant performed in a Coy Anaerobic Chamber with 95%:5% N2: frequency ≥20%. Variants called by at least two algorithms H2. Growth measurements were performed in a plate reader were included for further analysis, including annotation (BioTek, VT, USA). See Supplementary Methods for more using SnpEff (version 4.3) [69]. details.

Single-cell sequencing Clonal isolate pairings and measurement of growth rate and yield Single cells of Dv and Mm from mid-log phase EPD cul- tures were sorted into wells of a 96-well plate and lysed by All Dv clonal isolates were revived anaerobically in balch using a freeze-and-thaw cycle. Whole Genome Amplifica- tubes containing CCMA flushed with 80%:20% N2:CO2. tion from single cells was performed using REPLI-G Sin- Mm isolates were revived in balch tubes pressurized to 30 gle-Cell kit (Qiagen, MD, USA). We screened single psig with 80%:20% H2:CO2. Aliquots (0.1–0.2 ml) of sta- amplified genomes (SAGs) with 16S universal primers for tionary phase cultures (after two transfers) of Dv and Mm Dv and Mm, and used AmpPure XP magnetic beads were combined in 20 ml of CCMA containing 30 mM (Beckman-Coulter, CA, USA) to clean and purify con- sodium lactate in balch tubes flushed with 80%:20% N2: firmed SAGs; QC was performed with Bioanalyzer. DNA CO2, and incubated at 37 °C with shaking at 300 rpm. Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Growth parameters were estimated by analyzing changes in and regulatory genome information can be explored through cell density (OD600nm) using grofit[70]. Syntrophy Portal (http://networks.systemsbiology.net/ syntrophy/). Excess over Bliss analysis for measuring synergy Acknowledgements This material by Ecosystems and Networks Synergistic, additive, and antagonistic effects of clonal Integrated with Genes and Molecular Assemblies (ENIGMA) (http:// enigma.lbl.gov), a Science Focus Area Program at Lawrence Berkeley isolate pairings was determined using the Bliss Indepen- National Laboratory is based upon work supported by the US dence model [71]. The experimentally measured fractional Department of Energy, Office of Science, Office of Biological, and Environmental Research under contract number DE-AC02- growth rate and yield for Dv (fDv) and Mm (fMm) was determined by pairing evolved clonal isolates with ancestral 05CH11231. Sequencing of ancestral and early generation cocultures was supported by the National Science Foundation grant no. DEB- clones. The expected fractional effect on growth rate and 1453205 and DEB-1257525 to KLH. Development of the sequencing yield fDvMm, induced by the combined effect of evolved analysis pipeline was funded by the National Institute of Health under isolates was calculated as: grant number R01AI141953 to NSB. Authors thank to Nicholas Elliott for his help with growth analysis, and Joseph Hellerstein for discussion fDvMm ¼ 1 À ðÞÂ1 À fDv ðÞ¼1 À fMm fDv þ fMm À fDv  fMm on data analysis.

Excess over Bliss (EOB) was determined by computing Compliance with ethical standards the difference in fractional improvement of growth rate or yield induced by combination, fz, and the expected frac- Conflict of interest The authors declare no competing interests. tional inhibition, fDvMm. ’ ¼ ðÞÂÀ Publisher s note Springer Nature remains neutral with regard to EOB fz fDvMm 100 jurisdictional claims in published maps and institutional affiliations. A clonal isolate pair combination for which EOB ≈ 0 has Open Access This article is licensed under a Creative Commons an additive behavior, whereas a pair with positive or Attribution 4.0 International License, which permits use, sharing, negative EOB values has synergistic or antagonistic beha- adaptation, distribution and reproduction in any medium or format, as vior, respectively. Error was computed by propagating the long as you give appropriate credit to the original author(s) and the standard deviation of fractional effects. source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless Statistical analysis of mutation emergence across indicated otherwise in a credit line to the material. If material is not evolutionary trajectories included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright To quantify the likelihood of observing a mutated gene holder. To view a copy of this license, visit http://creativecommons. given another one mutated, we generated a background org/licenses/by/4.0/. distribution assuming a mutation in a particular gene as an independent event. We simulated a large random set of References mutational trajectory experiments maintaining the number of mutations per evolutionary line and the mutational fre- 1. Thauer RK. Anaerobic oxidation of methane with sulfate: on the quency observed for each gene. We computed an empirical reversibility of the reactions that are catalyzed by enzymes also P value of an experimental observation as P = (s + 1)/(n + involved in methanogenesis from CO2. Curr Opin Microbiol. 2011;14:292–9. https://doi.org/10.1016/j.mib.2011.03.003. 1), where s is the number of the simulation instances with 2. Oude Elferink SJWH, Visser A, Hulshoff Pol LW, Stams AJM. equal or stronger association as observed experimentally Sulfate reduction in methanogenic bioreactors. FEMS Microbiol and n is the number of simulated mutational trajectory Rev. 1994;15:119–36. https://doi.org/10.1111/j.1574-6976.1994. experiments (n = 1×106). tb00130.x. 3. Turkarslan S, Raman AV, Thompson AW, Arens CE, Gillespie MA, von Netzer F, et al. Mechanism for microbial population Data availability collapse in a fluctuating resource environment. Mol Syst Biol. 2017;13:919 https://doi.org/10.15252/msb.20167058. All sequencing data are available in NCBI Bioproject 4. Hillesland KL, Stahl DA. Rapid evolution of stability and pro- ductivity at the origin of a microbial mutualism. Proc Natl Acad database (accession number: PRJNA248017). Sci USA. 2010;107:2124–9. https://doi.org/10.1073/pnas. 0908456107. Code availability 5. Hillesland KL, Lim S, Flowers JJ, Turkarslan S, Pinel N, Zane GM, et al. Erosion of functional independence early in the evo- lution of a microbial mutualism. Proc Natl Acad Sci USA. Custom R and Python codes are available on GitHub 2014;111:14822–7. https://doi.org/10.1073/pnas.1407986111. (https://github.com/sturkarslan/evolution-of-syntrophy). 6. Wei X, Zhang J. Environment-dependent pleiotropic effects of Annotated mutations within the context of other functional mutations on the maximum growth rate r and carrying capacity K S. Turkarslan et al.

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