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Open Access

Peer-reviewed

Research Article

Identifying microbial functional guilds performing cryptic organotrophic and lithotrophic redox cycles in anaerobic granular biofilms

  • Zachary Flinkstrom ,

    Contributed equally to this work with: Zachary Flinkstrom, Samuel J. Bryson

    Roles Conceptualization, Investigation, Project administration, Software, Writing – original draft, Writing – review & editing

    zflink@uw.edu

    Affiliation Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America

    ⨯
  • Samuel J. Bryson ,

    Contributed equally to this work with: Zachary Flinkstrom, Samuel J. Bryson

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America, Phase Genomics, Seattle, Washington, United States of America

    ⨯
  • Bojan Pelivano,

    Roles Conceptualization, Data curation, Writing – original draft, Writing – review & editing

    Affiliation Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America

    ⨯
  • Pieter Candry,

    Roles Conceptualization, Investigation, Writing – original draft, Writing – review & editing

    Affiliations Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America, Laboratory of Systems and Synthetic Biology, Wageningen University & Research WE, Wageningen, The Netherlands

    ⨯
  • Kristopher A. Hunt,

    Roles Conceptualization, Investigation, Writing – original draft, Writing – review & editing

    Affiliation Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America

    ⨯
  • Mari-Karoliina H. Winkler

    Roles Conceptualization, Funding acquisition, Investigation, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America

    ⨯

Abstract

Granular biofilms used in anaerobic digester systems contain diverse microbial populations that interact to hydrolyze organic matter and produce methane within controlled environments. Prior research investigated the feasibility of utilizing granular biofilms obtained from an anaerobic digester to remove nitrate without the addition of exogenous electron donors. These granules possessed a unique structure of alternating light and dark iron sulfide and pyrite rich layers that potentially served as both an electron source and sink, linking carbon, nitrogen, sulfur, and iron cycles. To characterize the functional roles of diverse microbial populations enriched within these layered biofilms, we analyzed metagenomes obtained from three different granules. Comparisons between the functional gene content of forty metagenome assembled genomes (MAGs) identified phylogenetically cohesive functional guilds. Each of these functional MAG clusters was assigned to specific steps in anaerobic digestion (hydrolysis, acidogenesis, acetogenesis, and methanogenesis) and anaerobic respiration (denitrification and sulfate reduction). Comparisons with metagenomes derived from a variety of natural and engineered ecosystems confirmed that the enriched denitrifying bacteria were similar to populations typically found in wetlands and biological nitrogen removal systems. Analysis of read alignments to individual genes within the forty MAGs identified conserved genomic features that were representative of the functions that distinguished functional guilds. Overall, this research illustrates the utility of functional based classification of microorganisms for characterizing ecosystem functions and highlights the potential application of engineered ecosystems to serve as experimental models for complex natural ecosystems.

Citation: Flinkstrom Z, Bryson SJ, Pelivano B, Candry P, Hunt KA, Winkler M-KH (2025) Identifying microbial functional guilds performing cryptic organotrophic and lithotrophic redox cycles in anaerobic granular biofilms. PLoS One 20(8): e0330380. https://doi.org/10.1371/journal.pone.0330380

Editor: Erika Kothe, Friedrich Schiller University, GERMANY

Received: January 15, 2025; Accepted: July 30, 2025; Published: August 18, 2025

Copyright: © 2025 Flinkstrom et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Sequences and assemblies are deposited under the NCBI BioProject ID PRJNA743349. Additional metagenome libraries used for comparisons can be retrieved from the NCBI SRA using the ascension numbers listed in Table S5. Project code is available from figshare (https://doi.org/10.6084/m9.figshare.28179476) or github (https://github.com/brysons7919/metagenome_analysis). Annotation and binning data files have been uploaded to figshare (https://doi.org/10.6084/m9.figshare.28179449).

Funding: ZF, PC and MW were supported by a grant from the DOE (DOE Award: DE-SC0020356) and MW also by DARPA (Contract Number: HR0011-17-2-0064). PC also acknowledges support by the Dutch Research Council (NWO) Veni Talent Programme (File no. 21027). SB was supported by postdoctoral fellowships from the Washington Research Foundation and the Momental Foundation. BP was supported by WTE Wassertechnik. KH was supported by ENIGMA - Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Science Focus Area Program at Lawrence Berkeley National Laboratory that is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research under contract number DE-AC02-05CH11231.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Granular biofilms cultivated within engineered ecosystems have been harnessed for several applications; first in anaerobic digesters that treat organic rich waste streams and produce biogas [1–3], and later for biological nitrogen removal from wastewater [4–6]. Anaerobic digester systems employ microbial populations that carry out sequential and interacting processes that govern the degradation of organic matter: hydrolysis, acidogenesis, acetogenesis, and methanogenesis [1]. Beyond engineering applications, the microbial processes that anaerobically degrade organic matter and produce methane are found in diverse anoxic environments, such as the rumen [7] and wetland soils [8], suggesting that engineered ecosystems may serve as experimentally tractable models to better understand microbial processes occurring in natural ecosystems.

Much of the research into anaerobic digester microbial communities has focused on improved process engineering [9] and the development of predictive mathematical models [10–12]. More recently, the application of molecular methods to study the microbial communities of anaerobic digesters has focused on characterizing the community composition and identifying functional roles of specific taxa [13,14]. Studies have utilized metagenomic sequencing and analysis of recovered genomes to identify core microbial functional guilds, which are sets of organisms with similar metabolic capacities, and understand the contributions of individual taxa to the anaerobic digester metabolic networks [15,16]. Furthermore, molecular approaches have been harnessed to examine impacts of operational controls such as temperature [17], granule size [18], and substrate dynamics [19] – linking performance and microbial community composition.

Different types of waste streams derived from agricultural, municipal, or more specialized waste products impose strong selective pressures [20] that result in reduced taxonomic diversity compared to natural ecosystems [21,22]. Additionally, bioreactors and individual biofilm granules represent defined system boundaries, whereas natural ecosystems can be investigated at different scales ranging from individual soil aggregates [23] to more broadly defined regions such as forests, wetlands, agricultural soils, and sediments [24]. These attributes make engineered ecosystems tractable model systems to investigate more generalized questions in microbial ecology and evolution.

Investigations of anaerobic digesters have been useful for understanding the mechanisms and microbial interactions that facilitate organic matter degradation and methanogenesis. Studying how fermentative and methanogenic microorganisms interact with nitrate-, sulfate-, or iron-respiring microbes found in terrestrial and aquatic ecosystems requires the development of engineered systems that support these ecological processes. An example of this can be found in previous research that investigated the feasibility of utilizing granular biofilms obtained from a full-scale upflow anaerobic sludge blanket reactor to treat nitrate polluted water [25]. Dissection of these granules revealed a surprisingly well differentiated layered structure, consisting of alternating light and dark zones (Fig 1). Batch tests performed on these granules demonstrated active methanogens, sulfate reducers, and nitrate reducers that competed for acetate, and revealed a biofilm community that was powered by electron donors generated through hydrolysis and fermentation of endogenous organic matter [25]. Additionally, the observation of iron sulfide (FeS) and pyrite (FeS₂) in the biofilm indicated the potential role of cryptic iron and sulfur redox cycles—closed loops of rapid oxidation and reduction reactions that leave little net change in measurable redox species but can strongly influence microbial metabolism and mineral formation. Such cryptic cycles have been documented in marine sediments, where they drive coupled biotic and abiotic transformations that shape sediment geochemistry [26]. Taken together, these characteristics suggest that anaerobic granular biofilms cultured with the addition of alternative electron acceptors (e.g., nitrate, sulfate, or iron) may serve as a model experimental system for investigating the responses of natural ecosystems to perturbations in redox state.

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Fig 1. Layered structure of granular biofilms.

Anaerobic granule sliced showing alternating light and dark layers. Granule sizes were typically in the 3 to 5 mm diameter range.

https://doi.org/10.1371/journal.pone.0330380.g001

This study addressed the research gap of whether clustering metagenome assembled genomes (MAGs) by functional gene content could be used to define meaningful functional guilds within complex anaerobic communities, and whether these guilds—and the taxa that comprise them—are relevant beyond a single engineered system to other anaerobic ecosystems. To fill this gap, we performed short (Illumina) and long-read (Oxford Nanopore) sequencing, assembly, genome reconstruction, annotation, and functional analysis. The functional repertoire of MAGs was clustered to identify functional guilds performing specific redox functions. We then compared the metagenomes and recovered MAGs to publicly available metagenomes derived from different environments including anaerobic digesters, activated sludge, bovine rumen, landfill leachate, wetland sediments, and groundwater which revealed the organisms and functions conserved across these disparate ecosystems.

Results

Methanogens are the most abundant granule community members

The hybridSPAdes assembly of the three short-read (Illumina) and one long-read (Oxford Nanopore) libraries totaled 458,545,694 bases, with an N50 of 15,505 bases, and the longest scaffold at 1,311,200 bases in length – an overall improvement over the short-read (metaSPAdes) assembly (S1 Table in S1 File). An average of 83.8% (± 0.2% SD, n = 3) of the three short-read libraries aligned to the assembly. MaxBin2 binning resulted in 108 bins (S2 Table in S1 File) that were 333,583,683 bases in length (72.7% of the total assembly) and included 68.5% of all assembled scaffolds. Read mapping to the 108 bins and un-binned scaffolds from each short-read library indicated significantly correlated abundance patterns (p < 4e-52, Avg. Pearson’s rho = 0.95 ± 0.02 SD, n = 3) among pairwise comparisons of the three granules. Taxonomic assignment to the 108 bins (S3 Table in S1 File) revealed a diverse microbial community with 18 bins assigned to methanogenic Archaea that accounted for 43% (± 1.1% SD, n = 3) of the metagenomes based on the relative proportion of summed RPKM values. These bins included populations of Thermoplasmata (2 bins), Methanobacteria (6 bins), and Methanomicrobia (10 bins) (Fig 2B). The second and third most abundant taxonomic groups included 13 bins assigned to Betaproteobacteria that represented 16% (±3.7% SD, n = 3) of the community, followed by 7 Desulfobacterota bins (avg. 8.0% ± 1.2% SD, n = 3). Remaining taxa with greater than 1% relative abundance included Ca. Aminicenantes (1 bin, avg. 4.2% ± 1.5% SD), Bacteroidia (4 bins, avg. 4.1% ± 0.5% SD), Anaerolinea (6 bins, avg. 2.9% ± 0.54% SD), Krumholzibacteriota (1 bin, avg. 2.0% ± 1.1% SD), Ca. WOR-3 (1 bin, avg. 1.7% ± 0.76% SD), Gammaproteobacteria (1 bin, avg. 1.3% ± 1.3% SD), and Ca. Fermentibacteria (1 bin, avg. 1.1% ± 0.2% SD) (Fig 2B).

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Fig 2. Functional and taxonomic characterization of granular biofilms.

(A left to right) The dendrogram presents clustering based on Pearson correlation of normalized KEGG ortholog (KO) annotation counts for 40 MAGs followed by genomic characteristics and taxonomic assignments. The heatmap depicts CAZyme counts (log transformed, normalized, and scaled to a range of −2 to 2) for each category: AA-auxiliary activities, GT-glycosyl transferase, CBM-carbohydrate binding motif, PL-polysaccharide lyase, GH-glycoside hydrolase, and CE-carbohydrate esterase. The grid indicates the presence of specific functional genes, hydrogenase (hydAB), methyl coenzyme M reductase (mcrA), dissimilatory sulfite reductase (dsrAB), formate dependent nitrite reductase (nrfAH), periplasmic nitrate reductase complex (napAB), dissimilatory nitrate reductase (narGH), nitrite reductases (nirK and nirS), nitric oxide reductase (norB), and nitrous oxide reductase (nosZ). The color of each gene column corresponds to the redox processes (i-vii) in panel C. The taxonomic assignment for each MAG is designated by the same colors as in panel B. (B) Stacked bar-chart representing the microbial community structure based on RPKM values assessed for each recovered bin for each of the three Illumina sequence libraries obtained for each granule, columns A, B, and C. Each bar includes the summed RPKM values for all bins for each assigned taxonomy. “Other” includes bins assigned to low abundance taxa, taxa without a representative high-quality MAG, and all un-binned contigs. (C) Diagram of potential biologically mediated redox processes (i-vii) occurring within the granules.

https://doi.org/10.1371/journal.pone.0330380.g002

Functional guilds are phylogenetically cohesive

Of the 108 bins produced by the hybrid assembly, 40 of them (representing an average of 45.7% ± 4.3% of the total assembly RPKM) were of sufficient high quality for further analysis (CheckM completeness ≥ 80% and contamination ≤ 20%) (S2 Table in S1 File) to identify genomic features that differentiate individual taxa and predict their functional roles within the granule consortia. Clustering of these 40 MAGs based on KEGG Orthology (KO) annotations resulted in one singleton cluster plus eight clusters that exhibited significant within group correlation (PERMANOVA, 999 permutations, 9 groups, pseudo-F = 2.48, p ≤ 0.001) and generally contained phylogenetically related taxa within each cluster (Fig 2A). Functional differences between each cluster are highlighted by gene annotations for CAZymes and specific redox genes (Fig 2A). The one singleton cluster (Bin.081 – Alphaproteobacteria), was assigned to the genus Pleomorphomonas. This MAG had a relatively low abundance (avg. 0.18% ± .05% SD), limited numbers of genes assigned to CAZymes, and no identified genes indicating a role in nitrogen or sulfur respiration. Bin.081 did contain aldehyde and alcohol dehydrogenases, e.g., the fermentative acetaldehyde-alcohol dehydrogenase, adhE [27]. Pleomorphomonas isolates have exhibited diverse physiologies, including carboxydotrophs, capable of anaerobic carbon monoxide (CO) oxidation [28]. The CO dehydrogenase complex genes cool and cooH were identified in Bin.081, but not cooS and cooF [28]. The remaining eight clusters corresponded to the primary functional roles within the granules that include the conventional anaerobic digestion processes (Fig 2C; hydrolysis, acidogenesis, acetogenesis or syntrophic fermentation, and methanogenesis), as well as anaerobic respiration processes (Fig 2C; sulfur transformation, nitrogen transformation, and potentially some roles in iron transformations).

Bacteroidia are the primary hydrolyzers

Cluster 6 included three MAGs assigned to Bacteroidia plus two Planctomycetota MAGs, Bin.054 assigned to class Phycisphaerae and Bin.071 assigned to class Planctomycetia. In general, cluster 6 MAGs had the highest content of genes assigned to CAZyme classifications for carbohydrate esterases (CE), glycosyl hydrolases (GH), polysaccharide lyases (PL), and carbohydrate binding motifs (CBM), indicating a principal role in degradation of polymers and thus supplying organic reductant to the biofilm community. The 45 KOs significantly enriched in this cluster (S4 Table in S1 File) support this functional role; these enriched genes included alpha-L-rhamnosidase (ramA), beta-galactosidase (bgaB, lacA), and alpha-L-fucosidase (fucA). These findings are in line with prior research indicating that Bacteroidetes populations in anaerobic digesters potentially degrade polymers and ferment carbohydrates [29]. Additionally, the taxa represented by the two Planctomycetota MAGs have been identified as anaerobic fermenters and genomic analysis of members of the Phycisphaerae lineage has indicated a strictly fermentative saccharolytic lifestyle [30,31].

Acidogenic and acetogenic fermenters formed separate clusters

Five MAGs assigned to Anaerolinea comprised cluster 5 (Fig 2A) which had 43 KOs that were significantly enriched (S4 Table in S1 File). Many of these genes were indicative of a general functional role as chemoorganoheterotrophic facultative anaerobic fermenters, using predominantly carbohydrate oligomers as substrates. Among these genes were multiple transporters including ABC multiple sugar transporter, ribose transporter (rbs), raffinose, stachyose, melibiose transporter (msm), arabinogalactan oligomer/maltooligosaccharide transport system (cyc, gan, mdx), acarbose 7IV-phosphotransferase system (acb), nucleoside transporter (nup), as well as the lac/gal regulator system. Although these Anaerolinea populations may share a common general niche, deeper analysis of the transporters encoded within each genome suggested finer scale diversity in terms of the types of carbon sources used (Table 1). For example, most of the transporters listed in Table 1 were typically only present in two of the five genomes and specific transporters for glycine, glutamate, N-acetylglucosamine, glycerol, glucitol/sorbitol, and phospholipids were only identified in one of the MAGs. Three of the Anaerolinea MAGs harbored the nrf gene needed for dissimilatory nitrate reduction to ammonia (DNRA) suggesting some additional roles in nitrogen cycling within the granules.

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Table 1. Transporter diversity among Anaerolinea MAGs.

https://doi.org/10.1371/journal.pone.0330380.t001

MAGs assigned to four candidate phyla (Bin.077 – Ca. FCPU427, Bin.004 – Ca. Aminicenantes formerly OP8, Bin.008 Ca. WOR-3, and Bin.024 Ca. Fermentibacteria formerly Hyd24−12) and one MAG assigned to Krumholzibacteriota (Bin.007) formed cluster 8. This cluster had the lowest number of significantly enriched KOs, only 11, likely due to the higher level of phylogenetic diversity within the cluster. All four MAGs were assigned to different phyla and this diversity led to greater within-cluster distances than for the other clusters. Two significantly enriched genes were related to nucleotide sugar synthesis (rmd - GDP-4-dehydro-6-deoxy-D-mannose reductase) and polymer transport (exbB - biopolymer transport protein) suggesting a role in biofilm formation. Previous research has identified Ca. Aminicenantes (OP8) in methane producing environments, such as anaerobic digesters [32] and hydraulic fractured coal beds [33]. Ca. Aminicenantes have been linked to cellulose degradation and a putative fermentative saccharolytic lifestyle in deep subsurface aquifers [34,35]. Ca. WOR-3 bacteria have been linked to cellulose degradation in estuarine sediments [24]. Analysis of Ca. Fermentibacteria genomes suggests a functional role in fermentation and acidogenesis and are commonly reported in anaerobic digesters [36] and anoxic sediments [37]. Krumholzibacteria have been identified as slow-growing fermenters [38] with potential roles in iron cycling [39].

Cluster 7 included three MAGs, a Flavobacteria (Bin.061) and two Ignavibacteria MAGs (Bin.036 and Bin.093) (Fig 2A). Among the 17 KOs identified as enriched in this cluster were a proton dependent oligopeptide transporter and a hemoglobin/transferrin/lactoferrin receptor protein (S4 Table in S1 File). The Flavobacteria MAG contained genes annotated as nirK and nirS. While this might indicate contamination, recent reports have shown both types of nir genes can be present in a single organism [40]. The two Ignavibacteria MAGs harbored the nrf gene for DNRA, consistent with analysis of Ignavibacteria MAGs from partial-nitritation anammox reactors [41]. The only Ignavibacteria isolate was characterized as an obligately anerobic fermenter [42], but genomic analysis expanded this view identifying nitrite and nitrous oxide reductases, as well as hydrogenase genes that may either generate H2 during fermentation or be used to oxidize H2 [43].

Cluster 4 consisted of three MAGs assigned to the order Clostridiales which are often observed as abundant syntrophic acetogenic fermenters within anaerobic digester systems [44]. Twenty-seven KOs were significantly enriched in this cluster (S4 Table in S1 File), including genes related to sporulation, fatty acid metabolism (fatty acid kinase - fakB), lipid metabolism (3-hydroxybutyryl-CoA dehydrogenase -mmgB), and fermentation (enoyl-CoA hydratase – crt). Two of the MAGs (Bin.056 and Bin.069) were assigned to the family Syntrophomonadaceae and possessed one or both subunits for hydAB which may function in the proton reduction direction, suggesting these members may drive syntrophic fermentation in association with hydrogenotrophic methanogens.

The most abundant methanogens were acetoclastic

Cluster 2 included nine MAGs assigned to methanogenic taxa. Of the KOs identified among all these MAGs, 151 were significantly enriched (S4 Table in S1 File). Among these KOs were many archaeal specific genes, including the genes involved in methanogenesis. Among the methanogenic taxa Bin.021 was assigned to Methanothrix, of which the first isolate was obtained from an anaerobic digester and characterized as an obligately acetoclastic methanogen [45]. Although Bin.021 was the only high-quality bin representing acetoclastic methanogens in the assembly, two lower quality bins, Bin.001 and Bin.002 assigned to genus Methanothrix (S2 Table in S1 File), had the highest average relative abundances (relative to total RPKM) in the three granule libraries, 14.8% ± 1.53% and 7.7% ± 0.89% respectively. The methanogenic taxa also included two MAGs, Bin.045 and Bin.057, assigned to the class Thermoplasmata and the genus Methanomassiliicoccus, which have been characterized as methane producers that are dependent on H2 to reduce methyl compounds [46]. Four MAGs (Bin.055, Bin.018, Bin.005, and Bin.025) in cluster 2 were assigned to the genus Methanobacterium within the class Methanobacteria. This lineage is generally obligately hydrogenotrophic [47], reducing CO2 with H2, however, some isolates can utilize formate [48], methanol [49], or secondary alcohols [50]. The remaining three Archaeal MAGs were assigned to class Methanomicrobia, with two MAGs (Bin.003 and Bin.048) assigned to the genus Methanoregula that can utilize formate [51] or H2 for methane production [52].

Desulfobacterota were the primary sulfate reducers

Cluster 3 included 4 MAGs assigned to the phylum Desulfobacterota. These MAGs had 53 KOs significantly enriched (S4 Table in S1 File), including genes for sulfite reduction (dissimilatory sulfite reductase – dsr and heterodisulfide reductase - hdrA2) plus amino acid transporters (liv – BCAA transporter and ABC – polar amino acid transporters), genes for anaerobic metabolism (frd – fumarate reductase and acsA - anaerobic carbon-monoxide dehydrogenase), and the Wood–Ljungdahl pathway (S4 Table in S1 File). All four MAGs also contained hydrogenases (hydAB). Three of the Desulfobacterota MAGs (Bin.034, Bin.006, and Bin.033) were assigned to the family Syntrophaceae which are described as strict anaerobes that may respire (e.g., sulfite reduction) or ferment in syntrophic association with H2 oxidizers [53]. These three MAGs also contained the nitrite reductase (nrf) utilized in DNRA, indicating a potential role in nitrogen cycling. Bin.059 was assigned to the family Desulfovibrionaceae, which like the Syntrophaceae are obligate anaerobes, however the Desulfovibrionaceae can only oxidize organics to acetate, as opposed to complete oxidation to CO2 [54]. Together, these sulfite reducers likely play an important role in the development of the pyrite rich dark layers of the granular biofilm. The reaction of hydrogen sulfide with iron sulfur (FeS + H2S ➔ FeS2 + H2 [55]) releases hydrogen as a substrate for hydrogenotrophic methanogens [56] or potentially other anaerobic hydrogen oxidation reactions, thus providing redox links between sulfate reduction, methanogenesis, and pyrite formation.

Diverse Pseudomonadota comprised the cluster 1 denitrifiers

Cluster 1 (Fig 2A) included one Gammaproteobacteria MAG (Bin.106) and four Betaproteobacteria MAGs (Bin.015, Bin.026, Bin.012, and Bin.086). All five MAGs contained nitrate and nitrite reductases genes (nar and nir), and one contained the full denitrification pathway (Bin.015). In total 58 KOs were significantly enriched in this cluster (S4 Table in S1 File), including cbb3-type cytochrome c oxidase, type IV pilus genes, and regulatory genes fis and sspAB. Bin.106 was assigned to the genus Thermomonas, which includes denitrifiers identified in engineered ecosystems [57] and has been isolated from wastewater treatment systems [58,59] and identified in marine sediments [60]. Bin.015 and Bin.026 were both assigned to order Burkholderiales. Bin.026 was further assigned to the genus Diaphorobacter, which includes several isolates capable of denitrification and utilization of acetate, lactic acid, and other organic acids [61,62]. Bin.086 was assigned to the family Methylophilaceae which includes diverse taxa primarily implicated in the oxidation of C1 compounds – methanol and methylated amines [63,64]. Bin.012 was assigned to the family Thiobacillaceae and contained dissimilatory sulfite reductase genes (dsr), unlike other members of Cluster 1, which may allow nitrate dependent sulfur oxidation. Species within the Thiobacillaceae have also been implicated in nitrate-dependent pyrite oxidation [65], and may play an important role in nitrate-dependent iron sulfide dissolution in freshwater ecosystems [66]. Pyrite observed in the dark layers of the granular biofilms [25] may support nitrate-dependent pyrite oxidation (FeS2 + 7.5NO3- + 3.5H2O ➔ Fe(OH)3 + 2SO4−2 + 7.5NO2- + 4H+) [65] that would regenerate oxidized iron and sulfur compounds that would in turn serve as electron acceptors and lead to regeneration of pyrite in a cryptic redox cycle.

Comparing granule community to other anaerobic systems

To place the granule biofilm community into a broader ecological context, we used read recruitment to compare its taxonomic and functional composition to those of diverse anaerobic systems, providing insight into shared and unique microbial features across these environments. Specifically, we assessed how the methanogenic biofilm community that developed under carbon-limited, nitrate-rich conditions compared to communities from other anaerobic digesters, as well as natural and polluted sites likely to harbor microorganisms performing similar anaerobic processes (S5 Table in S1 File). RPKM values for two samples from municipal landfills and six anaerobic digesters were the most correlated with the values observed for the granules in this study (Fig 3 col. 1−12). The samples that produced the highest observed mapped read percentages (S6 Table in S1 File) included the anaerobic digester samples (Fig 3 col. 3−6) that correlated well with the three granules in this study, but also included two less correlated samples – the two Y-12 field site groundwater samples (Fig 3 col. 25−26). The two Y-12 samples had comparatively higher RPKM values for Cluster 1 denitrifiers and reduced RPKM values for Cluster 2 methanogens and Cluster 8 fermenters, suggesting that these samples represent a respiration dependent environment.

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Fig 3. Metagenomic comparisons.

Heatmap presenting log normalized and scaled (−2 to 2) RPKM values obtained by mapping reads from 31 metagenomes and the three granule metagenome libraries (A, B, and C from this study) represented by each column against the 40 high MAGs, each row. Clustering of columns was based on pairwise correlation scores between each sample’s set of bin RPKM values. The order and taxonomy of MAGs in each row is consistent with Fig 1. Heatmap columns for compared metagenomes are numbered and the corresponding descriptions are listed in S5 Table in S1 File.

https://doi.org/10.1371/journal.pone.0330380.g003

The availability of nitrate or nitrite may also explain the higher observed read recruitment by Beta- and Gammaproteobacteria MAGs (Cluster 1) for the anaerobic granules in this study (Fig 3, col. A, B, and C) compared to other anerobic digester samples (col. 3–12). Samples from other sites that were also likely to support denitrification (activated sludge-col. 16, anammox reactor sludge-col. 17–18, and wetland soils-col. 19–22) had higher read recruitment to the Cluster 1 MAGs than other anaerobic digester samples. The opposite trend was observed for the Bacteroidia MAGs (Cluster 6) which had higher read recruitment from anaerobic digesters (Fig 3, col. 3–12) and Bovine rumen (Fig 3, col. 29–31) samples. This indicates that digester and rumen environments offer a consistent niche space for Bacteroidia populations involved in hydrolysis of polymers and fermentation. Read recruitment patterns were less cohesive for other clusters, suggesting that the unique set of selective pressures imposed by distinct environments shape the within guild diversity. These pressures may relate to genomic factors that govern utilization of specific electron donors (e.g., specific types of carbon substrates) and electron acceptors, as well as specific kinetic factors that may influence competitive outcomes under distinct substrate concentrations.

Conserved functions across different environments

Next, we assessed the coverage of individual genes in each MAG across all the compared metagenomes (Fig 3) to identify specific functions that were consistently present in the genomes of closely related organisms. Among the 40 high-quality MAGs, 6,342 genes were identified as conserved (S7 Table in S1 File), i.e., gene sequences that had an average mapped read depth of more than twice the expected value across all metagenome comparisons. Clustering of the 40 MAGs based on this set of conserved genes (Fig 4) resulted in significantly similar pairwise distances (Mantel Test, rho = 0.922, p ≤ 0.001) to the previous analysis that incorporated all KO annotated genes (Fig 2A). PERMANOVA analysis of this reduced gene set distance matrix using the same cluster definitions as in Fig 2 resulted in a higher pseudo-F statistic (999 permutations, 9 groups, pseudo-F = 4.18, p ≤ 0.001) than the previous cluster analysis, indicating a stronger effect of groupings on differences between pairwise distances. There were, however, some minor changes in how the different hydrolytic and fermentative MAGs were clustered. These shifts may indicate more accurate functional guild classifications. The Clostridia MAG (Bin.074) clustered more closely with three candidate phyla MAGs (Bin.008, Bin.024, and Bin.004). Of the three Clostridia MAGs, Bin.074 was the only one not assigned to the family Syntrophomonadaceae and the only one without identified hydrogenase genes (hydAB). These characteristics suggest that Bin.074 may have a different fermentation role than the other two Clostridia.

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Fig 4. Identification and functional clustering of conserved genes.

(A) Clustering of 40 MAGs based on the reduced set of KOs identified as conserved among any of the MAGs. Taxonomy is indicated by the legend. (B) Percent of genes within each genome identified as having significant read mapping (blue bars) and the percent of genes in each genome identified as significant but not having any annotation assignment from KEGG, eggNOG, or CAZyme database searches (cyan bars). (C) The left panel histogram depicts the distribution of MAGs within each range of genome proportion identified as significant (1% width bins, blue bars). The right panel histogram presents the distribution of MAGs based on percent of genes identified as significant but not annotated (0.25% width bins, cyan bars).

https://doi.org/10.1371/journal.pone.0330380.g004

On average, 4.3% (±1.5% SD n = 40) of genes in each MAG were identified as conserved, a fraction that was normally distributed across all MAGs (Shapiro-Wilk Test, stat = 0.985, p = 0.858) (Fig 4B). The proportion of these genes that had no KO annotation or COG category assignment averaged 0.59% (±0.38% SD n = 40) and was not normally distributed (Shapiro-Wilk Test, stat = 0.891, p = 0.0011). The annotated conserved genes, often corresponded to genes previously identified as enriched within specific functional guilds including: cbb3 type cytochrome c-oxidase in cluster 1, genes required for methanogenesis in cluster 2, amino acid transporters in cluster 3, ribose and nucleoside transporters in cluster 5, glycosyl hydrolases in cluster 6, and a fermentation pathway related gene methylmalonyl-CoA mutase [67] in cluster 7. While this analysis does not indicate that the specific genomes recovered from the granules sequenced in this study are representative of the same species found in the compared environmental samples, it does suggest that the identified genes are conserved among closely related organisms that may perform similar functions in those environments.

Discussion

Catalytic biomass within anaerobic digesters converts organic material through a set of sequential processes (i.e., hydrolysis, acidogenesis, acetogenesis and methanogenesis) carried out by different microbial functional guilds. In these systems, overall performance is governed by a number of reactor-specific environmental and operational parameters [68]. The addition of iron to anaerobic digesters is a common operation performed to enhance organic matter removal and reduce odors associated with hydrogen sulfide (H2S) production [69] and also provides an important trace mineral required for enzymes used in methanogenesis [70]. The granules analyzed in this study were based on our previous research that revealed a unique biofilm morphology of alternating light biomass-rich and dark FeS/FeS2-rich layers. This morphology developed in an anaerobic digester with repeated iron additions, followed by exposure to nitrate-rich conditions in dedicated lab reactor studies aimed at nitrate removal without addition of any organic carbon [25]. Nitrate reduction was linked to the cryptic oxidation of reduced iron and sulfur compounds as well as organic carbon from within the granule [25]. In addition to the research goal of assessing the feasibility of utilizing anaerobic digester granules for treatment of nitrate polluted waters [25], we sought to examine the impacts of nitrate addition in terms of microbial populations enriched following the change in redox conditions and further compare the resulting community to other natural and engineered ecosystems.

Defining microbial community structure in terms of functional guilds

We compared the functional content of 40 high-quality genome bins recovered from the assembly and identified significantly distinct clusters that corresponded to functional guilds with the genomic potential to perform metabolic roles expected to occur within the system (Fig 2). This approach revealed taxonomic cohesiveness among the organisms within each of these broad functional groups. Within each of these functional groups we observed finer scale niche adaptations, such as the different sugar transporter repertoires observed for the Anaerolinea MAGs (Table 1). This implies that functional units within a microbial community are operationally defined and reflect both the specific ecosystem and the research focus. For this study we were primarily concerned with identifying the populations responsible for the general metabolic roles (i.e., hydrolysis, fermentation, methanogenesis, nitrate reduction, and sulfate reduction) to describe the observed system level functions, i.e., nitrate reduction without addition of exogenous reductant. Activity-based batch tests in our earlier research [25] were supported by the functional classification of recovered MAGs presented here, which also demonstrated that the applied selective pressure promoted the growth of a community enriched in functional genes supporting N, S, Fe and C cycling in the bioreactor system. Future metagenomics analyses should leverage genomic clustering approaches to develop quantitative metrics for functional characterization of microbial communities that build upon macro ecological concepts such as functional diversity or functional composition [71,72]. Microbial functional diversity metrics would facilitate comparisons of within community (i.e., alpha diversity) or between community (i.e., beta diversity) that could elucidate community assembly rules and identify relationships between phylogenetic and functional diversity.

Environmental relevance of a redox-enriched anaerobic granule community

Metagenomic analysis revealed some similarities between the granular biofilms in this study and prior investigations of anaerobic digester communities [14,21,29], with shared diverse taxa responsible for organic matter hydrolysis, acidogenesis, and syntrophic acetogenesis as well as abundant methanogenic populations. These similarities were also observed through direct comparisons with anaerobic digester metagenomes (Fig 3). However, the supply of nitrate and sulfate enriched the community in populations capable of anaerobic respiration and potentially capable of reducing iron or involved in the oxidation of reduced sulfate or iron (including iron sulfur minerals such as pyrite). Pyrite oxidation plays an important role in natural environments [73], serving as a link between iron, sulfur, and nitrogen cycles in marine sediments [26,74] and wetlands [66]. Furthermore, the utilization of pyrite to enhance denitrification in engineered ecosystems has also been explored with some success [25,75–77]. Although not included in the analysis of high-quality MAGs, one of the lower quality genome bins was associated with taxa that have been implicated in pyrite oxidation. Thiobacillus (Bin.108) has been reported to couple denitrification with the oxidation of iron sulfides [78,79]. While the role of iron and iron sulfur redox metabolisms was likely important to the biofilm community examined in this study, characterizing the functions of iron oxidizing and reducing taxa within metagenomes remains challenging as annotation of iron redox genes requires contiguous assemblies that enable characterization of operon structures [80]. The development of less phylogenetically complex and more experimentally tractable model systems that mimic natural microbial communities will enable more mechanistic insight into the impacts of environmental changes [81,82] such as the impact of nitrate pollution on groundwater ecosystems or the impact of sulfate intrusion on wetland soils following climate change induced sea level rise [83,84].

The anaerobic granular biofilms in this study represent such a model system, containing functional guilds involved in hydrolysis, fermentation, methanogenesis, and anaerobic respiration that link carbon, sulfur, nitrogen, and iron cycles (Fig 5). Furthermore, specific genes related to these diverse functional roles were identified in microbial populations found in natural and engineered ecosystems (Fig 4). In addition to containing representative populations possessing diverse metabolic functionality found in natural anoxic ecosystems, the structure of granular biofilms provides similar chemical gradients. The granular biofilm microbial community functions within a counter-diffusive environment: hydrolysis and fermentation products diffuse outward, while nitrate and sulfate supplied in the media diffuse inward. This shapes chemical gradients and transitory niche spaces along which competition for substrates would likely result in a gradual shift from methanogens to sulfate- and nitrate-reducers. The community conserves energy by linking carbon and hydrogen oxidation with sulfur, iron, and nitrogen redox cycles. This suggests that the observed differences in community structure compared to anaerobic digesters, e.g., the abundance of facultative anaerobic denitrifiers, and the observed nitrate removal is dependent upon the availability of organic compounds in the outer layers of the biofilm where inward diffusing nitrate is not yet depleted. This counter-diffusive gradient of organics and nitrate would provide a range of nitrate to organic carbon ratios, potentially favoring denitrification at the granule exterior and DNRA toward the carbon rich and nitrate depleted granule interior [85].

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Fig 5. Granular biofilms as model systems for complex soil ecosystems.

The granular biofilms examined in this study possess microbial functional guilds, clusters 1-8, that perform similar functions as in the more complex microbial communities of natural soil aggregates.

https://doi.org/10.1371/journal.pone.0330380.g005

Study implications and limitations

Using a genome-centric approach, this study demonstrated how clustering MAGs by their functional gene composition can reveal functional guilds within anaerobic granules. This strategy has broader applications for identifying guilds that drive nutrient transformations in other ecosystems, including those with uncultured microorganisms lacking physiological data. Our comparative analysis also showed that these functional guilds are relevant across diverse anaerobic environments.

Although we analyzed only three individual granules, their consistent taxonomic profiles suggest they were representative of the broader bioreactor community, and the metagenome comparisons supported the relevance of our findings beyond this specific system. While this approach is based on functional potential rather than direct in situ activity, the correspondence between identified guild members and known cultured representatives indicates that the results remain biologically significant.

Conclusion

By investigating a relatively low complexity microbial community, we were able to characterize the abundant taxa according to their functional roles, highlighting the utility of engineered ecosystems as model systems for microbial ecology. Taxa were differentiated into functional guilds based on their annotated genomic features and incorporated publicly available metagenomic data to better characterize the microbial community and further delineate the functional roles of specific taxa based on biogeographic distribution patterns and gene specific selective pressures. While natural environments are often too complex to manipulate experimentally, engineered systems offer controlled conditions and tractable diversity, enabling targeted investigation of microbial community assembly and responses to perturbations, such as nitrate addition in this study. The granules in this study demonstrated how enrichment of nitrate and sulfate reducers from an anaerobic digester community can lead to a functionally diverse microbial community, however, similar systems could be used to investigate the structural and functional changes from anthropogenic impacts on naturally occurring low redox potential environments.

Materials and methods

Origin of granular biofilms

The origin of the granular biofilms was described previously [25]. Briefly, anaerobic granules from a full-scale upflow anaerobic sludge blanket reactor fed with organic carbon, ferric iron, and sulfate were used to seed a 40 L pilot-scale rotating drum reactor and 3.5 L lab-scale sequencing batch reactor. Both reactor systems were fed anoxically with nitrate and no organic carbon at either 20oC or 30oC depending on the phase. These reactors demonstrated the capacity for nitrate removal connected to iron, sulfur, and organic carbon compounds contained within the granules. Nitrate removal rates ranged from 0.25–4.83 mgNO3-•gVSS-1•d-1 depending on phase.

Metagenome sequencing, assembly, and binning

Three individual granules from the pilot-scale reactor exhibiting layered biofilm structure (Fig 1) were selected for separate DNA extractions using the Qiagen DNEasy Power Biofilm Kit (Qiagen, Germany). Individual granules were used instead of pooling biomass to capture potential inter-granule variability. DNA was quantified using a NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, Germany). DNA aliquots from each granule were sent to BGI America for library preparation and sequencing on the Illumina NovaSeq platform producing 2x150 bp paired end reads. The three libraries (A, B, and C) contained 49,050,464, 49,117,576, and 48,706,712 paired end reads respectively. Reads were uploaded to the DOE KBase platform [86], merged into one library with 146,964,752 reads, then quality filtered and trimmed using Trimmomatic [87] resulting in a single library with 145,235,876 paired reads. An aliquot of DNA from one granule (granule C) was selected for long-read sequencing using the Oxford Nanopore MinION [88] platform. The Rapid Sequencing Kit (SQK-RAD004) was used for library preparation and run on a single flow-cell. Base calling was performed locally using Albacore (Oxford Nanopore Technologies) and reads shorter than 1,000 bases were removed, resulting in 1,053,672 reads totaling 3,866,526,020 bases and a mean length of 3,669.57 bases. MinION reads were uploaded to DOE KBase [86] and assembled along with the combined Illumina short read library using hybridSPAdes [89]. The combined Illumina libraries were also assembled in parallel with metaSPADEs [90] using the default parameters and was compared with the hybridSPAdes [89] assembly using QUAST [91] (S1 Table in S1 File). Both assemblies (hybrid and short-read) were binned using MaxBin2 [92] and assessed with CheckM [93] (S2 Table in S1 File). Illumina libraries for the three individual granules were mapped against the assemblies with Bowtie2 [94] to determine how much of each sequence library was represented by each assembly (S1 Table in S1 File) and assess the relative abundance of binned contigs as Reads Per Kilobase of transcript per Million mapped reads (RPKM) values (S6 Table in S1 File). The hybrid assembly was longer, more contiguous, captured more of the sequence libraries, and had less ambiguities (S1 Table in S1 File) so it was selected for further analysis. Taxonomy for bins recovered from the hybrid assembly was assigned using GTDB-Tk v1.6.0 [95], manually checked with phylogenetic trees using the KBase [86] SpeciesTreeBuilder app [96], and converted to National Center for Biotechnology Information (NCBI) nomenclature using the GTDB website (gtdb.ecogenomic.org) (S3 Table in S1 File).

Functional annotation and analysis

Gene calling for the hybrid assembly was performed using PRODIGAL [97]. Functional annotation of predicted coding sequences (CDS) for the entire assembly was performed with several tools. EggNOGmapper.py [98] was used to search against the EggNOG [99] database in diamond [100] mode. Carbohydrate active enzymes (CAZyme) were annotated using diamond [100] searches against the dbCAN database [101]. Kegg Orthology (KO) assignments were performed with GhostKOALA [102] (https://www.kegg.jp/ghostkoala/). FeGenie [80] was used to search for iron redox genes. High quality bins, those with ≥ 80% completeness and ≤ 20% contamination as assessed by CheckM [93] (S2 Table in S1 File) were also annotated using the DRAM [103] pipeline as implemented in KBase [86].

Forty high-quality bins (i.e., MAGs) were clustered based on KO content using tools from the SciPy spatial.distance and cluster.hierarchy libraries. Prior to clustering, MAG KO counts were normalized by subtracting the average relative abundance of KOs in all MAGs from the observed relative abundance of KOs in each individual MAG and dividing by the average relative abundance of KOs in all MAGs. In other words, the normalized KO array for MAG[i] would be calculated as shown in Eq. 1.

(1)

Functionally similar clusters of MAGs were manually identified from the dendrogram that was created using python scripts and the SciPy pdist (using Pearson correlation scores), SciPy linkage, and SciPy dendrogram libraries. PERMANOVA and Mantel tests were performed using scikit-bio (scikit-bio.org). Non-parametric tests for identifying significantly enriched KO assignments within functional clusters were performed by comparing observed counts for each KO identified among all members of each cluster to KO count distributions generated from 10,000 random samples of annotations of equivalent genome sizes (S4 Table in S1 File). Clustering based on a reduced set of conserved KOs utilized the same methods as clustering with the entire KO set.

Metagenome comparisons

The 40 high-quality MAGs were compared to 32 publicly available metagenomes downloaded from NCBI SRA (S5 Table in S1 File). The metagenomes were selected to represent diverse anaerobic environments and were required to have been sequenced using Illumina short-read technology with a sufficient depth (> 2 million reads). Sequences were mapped to the hybrid assembly using Bowtie2, and RPKM values for MAGs were calculated (S6 Table in S1 File). MAGs were clustered based on normalized RPKM values across all mapped sequence libraries and distinct clusters were compared based on taxonomic and functional content. The biogeographic distribution of individual gene sequences within MAGs was examined to identify the functional distribution of highly conserved gene sequences. Sequence alignments were converted to mpileup format [104]. Then position specific coverage information was used to determine the coverage for each gene within each of the 40 high-quality MAGs across all 32 compared metagenomes. Individual genes were identified as conserved if coverage from mapped reads was substantially higher than the null expectation that reads would align evenly across the MAG. Specifically they were identified as conserved if the log base 2 of the average percent difference (D) between the observed (o) and the expected (e) under the null condition was greater than 0 for n different metagenome libraries (i.e., the average observed coverage was at least two times the average expected coverage)(Eq. 2):

(2)

Identified conserved genes for the 40 MAGs are listed in S7 Table in S1 File. Clustering of MAGs based on KO assignments limited to the set of genes identified as conserved was previously described in the previous section.

Supporting information

S1 File.

S1 Table. Sequencing, assembly, and binning statistics. S2 Table. Bin quality and coverage statistics. S3 Table. Taxonomic assignment of bins. S4 Table. Significant genes for functional clusters. S5 Table. Publicly available metagenomic libraries used for comparisons. SRA accension numbers, sample names, study names, number of reads, and alignment rate is detailed. S6 Table. Bin coverage based on read-mapping. Reads per kilobase per million mapped reads (RPKM) values from mapping reads from metagenome libraries, including publicly available ones, to the set of bins. S7 Table. Conserved genes in MAGs. Genes identified as conserved in MAGs based on metagenome comparison.

https://doi.org/10.1371/journal.pone.0330380.s001

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