Biology subjects

Fierer, N.

Publications and source records attributed to Fierer, N..

At least 19 recordsLinked to original sources

bioRxiv2026

Airborne DNA reveals synchronized responses of tropical forest assemblages to precipitation

Tropical forests contain much of Earth's biodiversity, yet community-wide responses to seasonal climate transitions remain poorly resolved. We used weekly airborne environmental DNA sampling, supplemented by spatially intensive dry- and wet-season campaigns, to characterize fungi, plants, arthropods, and vertebrates across the dry-to-wet-season transition in a lowland tropical forest. All four assemblages shifted abruptly and nearly synchronously following rainfall late in the dry season, before the meteorological wet season began. These compositional transitions were largely independent of taxonomic richness and airborne DNA concentrations, indicating coordinated changes in detection patterns rather than simple seasonal gains in richness. Across all samples, we recovered more than 5,400 operational taxonomic units, including 2,148 fungi, 857 plants, 2,157 arthropods, and 239 vertebrates. We also recovered 949 full-length insect DNA barcodes, demonstrating compatibility with standard barcoding approaches and expanding opportunities for species discovery. Because the onset of the meteorological wet season showed no long-term trend at Barro Colorado Island, predicting future phenological and compositional shifts will require greater attention to dry-season rainfall variability and the cues that organisms track during this transition. Airborne environmental DNA offers a scalable, noninvasive framework for monitoring biodiversity and phenology across taxonomic groups.

ecology↗

bioRxiv2026

Targeted hybridization capture enables comprehensive detection of freshwater bioassessment invertebrates from environmental DNA

Freshwater bioassessment relies on assessing aquatic assemblages to infer ecological conditions, yet conventional surveys require extensive field sampling, specimen processing, and specialized taxonomic expertise. Existing environmental DNA (eDNA) methods have not yet provided a practical alternative to conventional macroinvertebrate assays in part because current approaches cannot feasibly recover broad taxonomic diversity at sufficient taxonomic resolution. Here, we evaluated targeted hybridization capture of mitochondrial cytochrome oxidase I (COI) target sequences as a unified molecular approach for cross-phylum freshwater bioassessment. Environmental DNA was collected at 18 sites along 63 km of Boulder Creek spanning nearly 1,500 m of elevation from forested headwaters to agricultural plains. COI targets were enriched using custom RNA bait panels designed to target regional freshwater arthropods, annelids, and molluscs. Hybridization capture increased recovery of COI sequences [~]1,760-fold relative to unenriched shotgun libraries, generating Folmer-region COI contigs that averaged [~]400 bp. Across the watershed, we recovered sequences for approximately 450 macroinvertebrate genera across 8 phyla. Detected macroinvertebrate richness averaged 56 genera per site and increased down Boulder Canyon before declining downstream of the city. Macroinvertebrate assemblage composition from hybridization capture paralleled patterns observed with past conventional bioassessment. These results demonstrate that targeted hybridization capture enables robust, cross-phylum detection of species used for freshwater bioassessment from environmental DNA.

ecology↗

bioRxiv2026

Identification of soil microbes associated with real-time plastic degradation using in situ conductivity sensors

Microbial-mediated plastic degradation has the potential to address the persistent global problems of plastic waste and pollution. Previous work has shown that soils can harbour microbes capable of plastic degradation, but we expect there is a broader diversity of soil microbes capable of metabolizing plastics than identified to date using more traditional cultivation-based screening methods. Here we demonstrate a novel approach to identify putative plastic degrading microbes in soil. We paired in situ, real-time measurements of microbial plastic degradation on conductive sensors with subsequent microbial community profiling of the sensor-associated biofilms exhibiting appreciable degradation. To illustrate the utility of our approach, we focus on microbial degradation of the bioplastic polymer PHBV, poly(3-hydroxybutuyrate-co-3-hydroxyvalerate). We screened a range of soils with the in situ sensors to identify a subset of five soils with high PHBV degradation rates, and confirmed that PHBV degradation was due to microbial activity. We then extracted DNA directly from sensors placed in soils with high measured rates of PHBV degradation and used marker gene sequencing to identify the bacterial and fungal taxa associated with the observed PHBV degradation. We confirmed via in vitro culturing that microbes isolated from the sensors have a demonstrated capacity for PHBV metabolism. Together, these results highlight the benefit and feasibility of using low-cost, in-soil sensors to simultaneously collect real-time data on plastic degradation rates in soil and identify previously unrecognized microbial taxa capable of degrading and metabolizing plastic polymers in situ.

microbiology↗

bioRxiv2026

Predicting optimal growth temperatures of bacteria using learned structural information from a single protein

Temperature is a fundamental determinant of bacterial physiology and ecology. Optimal growth temperature (OGT) is highly variable across species, contributing to differences in where and when species are most likely to thrive. Although the OGTs for most bacteria remain unknown, the increasing availability of genomes from uncultivated and cultivated taxa has made it advantageous to build genomic, cultivation-independent models to infer OGT. However, pre-existing genomic models often lack the generalizability and mechanistic grounding required for robust inferences of OGT. We propose a novel framework for predicting bacterial OGT which uses learned protein structural signatures of thermal adaptation. We hypothesize that biophysical tradeoffs which dictate enzymatic functions across variable temperatures provide a more robust empirical basis for OGT prediction than broad genomic features. Our OGT-predicting model, ROSEATE, is based on a single gene, adenylate kinase (ADK), that encodes for a ubiquitous enzyme essential for energy homeostasis. ROSEATE uses high-dimensional latent space encoding via MSA Transformer, a protein language model which embeds ADKs in a manner which preserves biophysical information about embedded proteins. We show that the accuracy of the ROSEATE model is on par with other genome-based models, has a high degree of phylogenetic generalizability, and the ESM embeddings effectively capture key temperature-adaptive enzyme characteristics derived from AlphaFold structures. Because ROSEATE is based on analyses of a single ubiquitous protein, it can be used with metagenomic data to infer the community-level variation in bacterial OGTs. We demonstrate this feature of ROSEATE by reconstructing ADK sequences from over 500 environmental and host-associated metagenomes, successfully distinguishing community-wide thermal preferences across diverse habitats, from polar oceans to mammalian guts. By transitioning from genomic proxies to informationally dense protein structural features, this work provides an efficient, interpretable tool for predicting bacterial OGTs across taxa and whole communities. Author SummaryThe temperature preferences of bacteria are key to determining where species are most likely to grow and how bacterial communities may respond to changes in temperature regimes. Unfortunately, the optimal growth temperatures of most bacteria, including a broad diversity of bacteria found in many host-associated and environmental systems, currently remain unknown as many bacterial species cannot be grown or studied in a laboratory. While we now have genomic data for many bacteria, using these data to infer optimal temperatures for bacterial growth has remained a persistent challenge. We developed and validated a novel approach to predict bacterial temperature preferences. When heated, proteins often unfold, becoming nonfunctional. To adapt to warmer environments, organisms evolve more stable proteins which resist denaturing at high temperatures. Instead of analyzing a bacterias entire genome, our approach uses a protein language model to quantify stability-enhancing changes in a single protein found across all bacteria. We found that this single-protein approach can be used to effectively predict the optimal growth temperatures of individual bacterial species and even whole bacterial communities. By changing how we use genomic information to predict temperature preferences, our framework provides a scalable blueprint for predicting other important bacterial traits from protein structure information.

bioinformatics↗

bioRxiv2026

Evidence for endemism and local adaptation in Antarctic soil bacteria

Antarctic soils represent one of the more extreme environments for microbial life on Earth, yet they harbor heterogeneous and diverse microbial communities. Biologists have long hypothesized that Antarctic microorganisms are unique from those found on other continents due to the extreme geographic isolation and the cold, dry, and challenging conditions typical of Antarctica. To test this hypothesis, we focused on a cosmopolitan bacterial genus, Arthrobacter, that is widely distributed across global soils. We first profiled a global metagenomic dataset from both Antarctic and non-Antarctic surface soils to quantify the distributions of Arthrobacter strains. Despite high strain-level diversity, 90% of the strains found in the Antarctic soils were only found on the continent. We then used cultivation-based phenotypic analyses and strain-level genomic comparisons to assess how Antarctic strains and non-Antarctic strains differ in their traits and environmental preferences. Not only did we find evidence of endemism, but Antarctic Arthrobacter also have genomic characteristics and environmental tolerances that suggest they are uniquely adapted to Antarctic conditions. Significance StatementAntarctic soils are among the most extreme environments on Earth, yet they host diverse microbial communities whose adaptations are poorly understood. To test whether Antarctic microbes are distinct from those elsewhere, we examined Arthrobacter, a bacterial genus common in soils worldwide. Analysis of global metagenomic data revealed Arthrobacter strains in Antarctic soils are found exclusively on the continent. Cultivation experiments and comparative genomics further showed that Antarctic strains differ from nonAntarctic relatives in genomic features and environmental tolerances. Together, these results demonstrate that geographically isolated and extreme conditions can drive microbial endemism and local adaptation, even within globally distributed bacterial lineages.

ecology↗

bioRxiv2026

Moss Transplants in the Tundra Reveal Host-Specific Microbiomes and Nitrogen Fixation Responses

In tundra ecosystems, moss-associated microbes are a major source of new nitrogen, yet the relative contributions of environment, host identity, and microbiome composition to variation in nitrogen-fixation rates are difficult to disentangle. To test how environmental change alters moss microbiomes and nitrogen-fixation rates, we used a one-year reciprocal transplant experiment between two Alaskan tundra sites that differ by 5{degrees}C in mean annual temperature. Intact moss cores containing one of three moss species, Hylocomium splendens, Aulacomnium turgidum, and Pleurozium schreberi, were transplanted between sites or returned to their home site. After one year, we quantified nitrogen-fixation rates using 15N incubation and characterized bacterial communities using 16S rRNA gene amplicon sequencing. H. splendens showed consistently low nitrogen-fixation rates with little transplant response, whereas P. schreberi and A. turgidum home and transplant tundra cores generally exhibited higher rates at the cooler, more northern site regardless of origin. In contrast, bacterial community structure changed little following transplantation, with composition driven primarily by moss species. Only in cyanobacteria and some heterotrophic bacterial lineages did we find subtle ASV-level changes. The absence of an association between microbial composition and nitrogen fixation, together with the heterogeneity among moss species, suggests that over short timescales, host physiology and microenvironment play a larger role in the variation of nitrogen-fixation rates than community turnover. The fact that short-term shifts in moss-associated nitrogen-fixation rate are driven primarily by host species identity, rather than microbiome restructuring, has important implications for near-term predictions of nitrogen inputs under Arctic climate change.

microbiology↗

bioRxiv2026

Quantifying the oxygen preferences of bacterial communities using a metagenome-based approach

Oxygen is a primary driver of the distribution and activity of microbial life. Since oxygen levels are often difficult to measure in situ, one potential solution is to use bacteria as bioindicators of oxygen levels. As bacteria range from obligate aerobes to obligate anaerobes, quantification of bacterial community oxygen preferences could be used to infer variation in environmental oxygen levels and bacterial metabolic strategies. After using ensemble machine learning to select the 20 most important genes that predict oxygen tolerances in individual bacteria, we established a relationship between the abundance ratio of aerobic: anaerobic indicator genes and the proportional abundance of aerobic bacteria using simulated metagenomes with varying ratios of known aerobic and anaerobic bacteria. We developed a tool, OxyMetaG, that takes metagenomic reads as input, extracts bacterial reads, maps reads to the 20 genes, and predicts the proportion of aerobic versus anaerobic bacteria in any given sample. We tested OxyMetaG on a suite of metagenomes with measured or inferred oxygen levels across a variety of environmental and host-associated samples. To demonstrate the utility of our approach, we applied OxyMetaG to 540 surface soils, showing that surface soils are typically dominated by aerobes, but wetter sites with finer textures have relatively more anaerobes. Lastly, we applied OxyMetaG to 73 human gut samples, showing that in the first three years of life, human guts progress from having up to 61% aerobes to being completely dominated by anaerobes. We expect OxyMetaG to have broad utility for characterizing both modern and ancient environments. ImportanceOxygen is one of the most important environmental variables affecting microbial activity and composition but is often difficult to measure in situ. We developed a tool, OxyMetaG, that leverages differences in bacterial gene content across known aerobic and anaerobic taxa to predict the proportion of aerobes and anaerobes in a given sample directly from shotgun metagenomic reads. OxyMetaG works on samples with low sequencing depth and avoids computationally expensive genome assembly, which often captures only a fraction of the microbial community in a given environment. With OxyMetaG, bacteria can be used as bioindicators of oxygen availability over broader time scales than just a single measurement and provide crucial environmental context in cases where oxygen has not or cannot be measured. OxyMetaG is publicly available and can be used to answer a wide variety of ecological questions in both environmental and host-associated systems.

microbiology↗

bioRxiv2025

Spatiotemporal dynamics in airborne fungi and fungal allergens across the United States

A broad diversity of fungi can be found in the near-surface atmosphere, with both the amounts and types of airborne fungi varying across space and time. However, the specific spatiotemporal patterns in airborne fungal assemblages often remain unquantified. This knowledge gap is particularly notable for allergenic fungi, despite the relevance of airborne fungal allergen exposures to public health. To better understand how airborne fungi, including known allergens, vary across broad spatial and temporal scales, we leveraged a pre-existing air sampling network to obtain bioaerosol samples from 7 national parks representing diverse biome types across the United States, with samples collected from each site every three days over an entire calendar year. We used marker gene DNA sequencing and quantitative PCR to characterize fungal assemblage composition and concentrations, including the concentrations of ten known allergenic genera. As expected, the composition of the airborne fungal assemblages, including the amounts and types of known allergens, varied across biomes. We also observed substantial temporal variation in the total amounts and types of fungi detected, particularly at higher latitude sites. While some of the temporal variation in allergen abundances followed seasonal patterns, we detected pronounced daily and weekly fluctuations in taxon-specific allergen abundances, with higher wind speeds generally associated with higher fungal allergen concentrations. Together, these results expand our understanding of fungal aerobiology across natural ecosystems and demonstrate how combining extensive air-sampling efforts with DNA-based analyses can improve assessments of public health risks associated with exposure to allergenic fungi in outdoor air. IMPORTANCEDespite major advances in sampling methodologies, sequencing technologies, and access to air quality monitoring networks, comprehensive assessments of the spatial and temporal variation in airborne fungi remain limited, even though fungi constitute a substantial proportion of the aerobiome. This is true even for allergenic fungal taxa, despite their importance to human health. Using DNA-based approaches, we characterized fungal assemblages in the near-surface atmosphere over a single calendar year at 7 national parks across the US. We found that each site had distinct airborne fungal assemblages with unique temporal patterns in fungal abundances and composition. Substantial spatiotemporal variation was also observed for known fungal allergens, driven by both seasonal trends and environmental factors. This study advances our understanding of the ecological patterns that structure airborne fungal communities and the factors influencing outdoor exposures to allergenic fungi, improving our ability to assess and predict health risks associated with fungal allergens.

microbiology↗

bioRxiv2025

A cross-environment comparison of nontuberculous mycobacterial diversity

Nontuberculous mycobacteria (NTM) are a group of environmental bacteria that encompass nearly 200 described species, some of which can cause chronic pulmonary infection in humans. What makes these infections unique is that they are environmentally acquired, yet there remains a limited understanding of how different environments contribute to potential pathogen exposure. Here, we use new and existing marker gene datasets to compare the amounts and types of NTM across three environments known to harbor mycobacteria, surface waters, soil, and household plumbing biofilms, to better understand potential pathogen occurrence in each environment. We used 16S rRNA gene sequencing, in tandem with mycobacterial-specific marker gene sequencing to characterize variation in the relative abundances of the genus Mycobacterium and specific mycobacterial taxa across the three environments, with a focus on a clinically significant NTM. We found that household plumbing biofilms contained both the highest relative abundance of the genus Mycobacterium (on average, 13.7% of bacteria were members of the genus), as well as the highest occurrence of clinically relevant species detected (Mycobacterium avium, Mycobacterium abscessus), compared to surface waters and soil. Although mycobacteria are ubiquitous across many different environments, mycobacterial diversity is highly variable between environments with clinically relevant species largely restricted to household plumbing biofilms, information that is critical for understanding the ecology and epidemiology of NTM disease. ImportanceNontuberculous mycobacteria, or NTM, are a diverse group of bacteria within the genus Mycobacterium that are common in many environments. While most members of the genus pose little threat to human health, a handful of species, namely the Mycobacterium avium complex, M. abscessus, and M. mucogenicum, can cause severe and prolonged lung infections. These environmentally acquired infections are on the rise in the United States and around the world, yet we still dont have a good understanding of which environment types pose the greatest risk of infection to susceptible populations. Our study used cultivation independent approaches to identify the specific NTM taxa found in over 1,000 samples from three potentially important environmental reservoirs - surface waters, soils, and household plumbing systems, to determine which of these environments are most likely to harbor NTM of clinical significance. Our results highlight the high degree of variability in the types of NTM taxa detected in different environments (including extensive novel diversity within the genus) and show that household plumbing biofilms are likely the most important reservoir and subsequent route of transmission for clinically significant NTM.

microbiology↗

bioRxiv2025

Surveying Tropical Faunal Diversity via Airborne DNA Analyses

Here, we assess the potential of airborne eDNA (airDNA) metabarcoding to characterize arthropod and vertebrate assemblages in a tropical forest. We deployed 28 high-flow air samplers across a 1.5 km2 area on Barro Colorado Island, Panama, over two consecutive 24- hour periods and sequenced captured DNA using general eukaryotic and vertebrate-specific metabarcoding primers. AirDNA sampling detected 1293 arthropod operational taxonomic units (OTUs) alongside 157 vertebrate OTUs representing birds, mammals, reptiles, amphibians, and fish. Arthropod richness was comparable to that quantified locally with light and Malaise trap surveys, while vertebrate richness exceeded that typically observed with conventional techniques. The level of field and lab effort employed in this study captured approximately 84% of the asymptotic richness for arthropods and 76% for vertebrates, implying that relatively little additional richness would have been quantified with additional effort within the same domain of sampling. Observed and asymptotic richness increased with the number of sites, the number of days a site was sampled, and the number of PCR replicates run per sample, highlighting the need to standardize effort among future applications of airDNA to compare richness across systems. These results demonstrate that airDNA metabarcoding can efficiently and non- invasively profile tropical terrestrial faunal biodiversity.

ecology↗

bioRxiv2025

A periodic table of bacteria?: Mapping bacterial diversity in trait space

Bacterial diversity can be overwhelming. There is an ever-expanding number of bacterial taxa being discovered, but many of these taxa remain uncharacterized with unknown traits and environmental preferences. This diversity makes it challenging to interpret ecological patterns in microbiomes and understand why individual taxa, or assemblages, may vary across space and time. While we can use information from the rapidly growing databases of bacterial genomes to infer traits, we still need an approach to organize what we know, or think we know, about bacterial taxa to match taxonomic and phylogenetic information to trait inferences. Inspired by the periodic table of the elements, we have constructed a periodic table of bacterial taxa to organize and visualize monophyletic groups of bacteria based on the distributions of key traits predicted from genomic data. By analyzing 50,745 genomes across 31 bacterial phyla, we used the Haar-like wavelet transformation, a model-free transformation of trait data, to identify clades of bacteria which are nearly uniform with respect to six selected traits - oxygen tolerance, autotrophy, chlorophototrophy, maximum potential growth rate, GC content and genome size. The identified functionally uniform clades of bacteria are presented in a concise periodic table-like format to facilitate identification and exploration of bacterial lineages in trait space. While our approach could be improved and expanded in the future, we demonstrate its utility for integrating phylogenetic information with genome-derived trait values to improve our understanding of the bacterial diversity found in environmental and host-associated microbiomes.

bioinformatics↗

bioRxiv2025

Continent-wide assessment of the strain-level diversity of Bradyrhizobium, a dominant soil bacterial genus

Global surveys of soil bacteria have identified several taxa that are nearly ubiquitous and often the most abundant members of soil bacterial communities. However, it remains unclear why these taxa are so dominant across a wide range of soil types and environmental conditions. Here we use genome-resolved metagenomics to test the hypothesis that strain-level differences exist in these taxa that are not adequately captured with standard marker gene sequencing, and that distinct strains harbor unique traits that reflect adaptations to different soil environments. We analyzed data from 331 natural soils spanning Australia to assess strain differentiation in Bradyrhizobium, a dominant soil bacterial genus of ecological importance. We developed a workflow for strain-level bacterial analyses of complex soil metagenomes, combining genomes from pre-existing databases with new genomes generated via targeted assembly from metagenomes to detect 181 Bradyrhizobium strains across the soil collection. In addition to a high degree of phylogenetic variation, we observed substantial variation in pangenome content and inferred traits, highlighting the breadth of diversity within this widespread genus. While members of the genus Bradyrhizobium were detected in > 80% of samples, most individual strains were restricted in their distributions. The overall strain-level community composition of Bradyrhizobium varied significantly across geographic space and environmental gradients, and was particularly associated with differences in temperature, soil pH, and soil nitrate and metal concentrations. Our work provides a general framework and methodology for studying the strain-level ecology of soil bacteria and highlights the ecological and pangenomic diversity within this dominant soil bacterial genus.

microbiology↗

bioRxiv2024

The ecological relevance of flagellar motility in soil bacterial communities

Flagellar motility is a key bacterial trait as it allows bacteria to navigate their immediate surroundings. Not all bacteria are capable of flagellar motility, and the distribution of this trait, its ecological associations, and the life history strategies of flagellated taxa remain poorly characterized. We developed and validated a genome-based approach to infer the potential for flagellar motility across 12 bacterial phyla (26,192 genomes in total). The capacity for flagellar motility was associated with a higher prevalence of genes for carbohydrate metabolism and higher maximum potential growth rates, suggesting that flagellar motility is more prevalent in resource-rich environments due to the energetic costs associated with this trait. To test this hypothesis, we focused on soil bacterial communities, where flagellar motility is expected to be particularly important given the heterogeneous nature of the soil environment. We applied a method to infer the prevalence of flagellar motility in whole bacterial communities from metagenomic data, and quantified the prevalence of flagellar motility across 4 independent field studies that each captured putative gradients in soil carbon availability (148 metagenomes). As expected, we observed a positive relationship between the prevalence of bacterial flagellar motility and soil carbon availability in each of these datasets. Given that soil carbon availability is often correlated with other factors that could influence the prevalence of flagellar motility, we validated these observations using metagenomic data acquired from a soil incubation experiment where carbon availability was directly manipulated with glucose amendments, confirming that the prevalence of bacterial flagellar motility is consistently associated with soil carbon availability over other potential confounding factors. Flagellar motility is a fundamental phenotypic trait for bacterial adaptation to soil, defining life history strategies primarily associated with resource availability. More generally, this work highlights the value of combining genomic and metagenomic approaches to expand our understanding of microbial phenotypic traits and reveal their general environmental associations.

ecology↗

bioRxiv2023

Building a genome-based understanding of bacterial pH preferences

The environmental preferences of many microbes remain undetermined. This is the case for bacterial pH preferences, which can be difficult to predict a priori despite the importance of pH as a factor structuring bacterial communities in many systems. We compiled data on bacterial distributions from five datasets spanning pH gradients in soil and freshwater systems (1470 samples in total), quantified the pH preferences of bacterial taxa across these datasets, and compiled genomic data from representative bacterial taxa. While taxonomic and phylogenetic information were generally poor predictors of bacterial pH preferences, we identified genes consistently associated with pH preference across environments. We then developed and validated a machine learning model to estimate bacterial pH preferences from genomic information alone, a model which could aid in the selection of microbial inoculants, improve species distribution models, or help design effective cultivation strategies. More generally, we demonstrate the value of combining biogeographic and genomic data to infer and predict the environmental preferences of diverse bacterial taxa.

ecology↗

bioRxiv2022

Leaf side determines the relative importance of dispersal versus host filtering in the phyllosphere microbiome

Leaf surface-associated bacterial communities play a significant role in plant health and have therefore been the focus of increasing interest. Despite this, we currently lack a predictive understanding of how leaf-associated bacterial communities are structured within and across hosts, including how leaf traits shape this variation and how community assembly processes may differ across distinct microbial habitats on a leaf. In this study, we characterize the composition of bacterial phyllosphere communities from the upper and lower leaf surfaces of 66 plants across 24 species grown at a common site using 16S rRNA amplicon sequencing. By comparing leaves that vary in pH and stomatal densities and analyzing the leaf surfaces separately, we were able to test the key factors shaping the phyllosphere across host plant species from diverse geographical origins. We found a surprisingly large shared/core microbiome across species, as well as a strong effect of plant species and native origin in shaping composition. Importantly, we found the lower leaf side, where pH values are generally lower and stomatal densities higher, to have lower taxonomic richness relative to the upper leaf side. While the upper leaf side community appears to be more strongly influenced by dispersal effects, the lower leaf appears to be more strongly influenced by plant host filtering effects, as supported by higher relative abundance of shared core taxa and higher signatures of endemism. This work highlights important differences in community assembly processes across the upper and lower leaf microbiomes and underscores the importance of considering differences among habitats within a host when explaining microbial community assembly and composition.

microbiology↗

bioRxiv2022

A metagenomic investigation of spatial and temporal changes in sewage microbiomes across a university campus

Wastewater microbial communities are not static and can vary significantly across time and space, but this variation and the factors driving the observed spatiotemporal variation often remain undetermined. We used a shotgun metagenomic approach to investigate changes in wastewater microbial communities across 17 locations in a sewer network, with samples collected from each location over a 3-week period. Fecal-derived bacteria constituted a relatively small fraction of the taxa found in the collected samples, highlighting the importance of environmental sources to the sewage microbiome. The prokaryotic communities were highly variable in composition depending on the location within the sampling network and this spatial variation was most strongly associated with location-specific differences in sewage pH. However, we also observed substantial temporal variation in the composition of the prokaryotic communities at individual locations. This temporal variation was asynchronous across sampling locations, emphasizing the importance of independently considering both spatial and temporal variation when assessing the wastewater microbiome. The spatiotemporal patterns in viral community composition closely tracked those of the prokaryotic communities, allowing us to putatively identify the bacterial hosts of some of the dominant viruses in these systems. Finally, we found that antibiotic resistance gene profiles also exhibit a high degree of spatiotemporal variability with most of these genes unlikely to be derived from fecal bacteria. Together these results emphasize the dynamic nature of the wastewater microbiome, the challenges associated with studying these systems, and the utility of metagenomic approaches for building a multi-faceted understanding of these microbial communities and their functional attributes. ImportanceSewage systems harbor extensive microbial diversity, including microbes derived from both human and environmental sources. Studies of the sewage microbiome are useful for monitoring public health and the health of our infrastructure, but the sewage microbiome can be highly variable in ways that are often unresolved. We sequenced DNA recovered from wastewater samples collected over a 3-week period at 17 locations in a single sewer system to determine how these communities vary across time and space. Most of the wastewater bacteria, and the antibiotic resistance genes they harbor, were not derived from human feces, but human usage patterns did impact how the amounts and types of bacteria and bacterial genes we found in these systems varied over time. Likewise, the wastewater communities, including both bacteria and their viruses, varied depending on location within the sewage network, highlighting the challenges, and opportunities, in efforts to monitor and understand the sewage microbiome.

microbiology↗

bioRxiv2022

Hydrogen stable isotope probing of lipids demonstrates slow rates of microbial growth in soil

The rate at which microorganisms grow and reproduce is fundamental to our understanding of microbial physiology and ecology. While soil microbiologists routinely quantify soil microbial biomass levels and the growth rates of individual taxa in culture, there is a limited understanding of how quickly microbes actually grow in soil. For this work, we posed the simple question: what are the growth rates of soil microorganisms? In this study, we measure these rates in three distinct soil environments using hydrogen stable isotope probing of lipids with 2H-enriched water. This technique provides a taxa-agnostic quantification of in situ microbial growth from the degree of 2H enrichment of intact polar lipid compounds ascribed to bacteria and fungi. We find that average apparent generation times in soil are quite slow (20 to 64 days) but also highly variable at the compound-specific level (6 to 1137 days), suggesting differential growth rates between community subsets. We observe that low-biomass communities can exhibit more rapid growth rates than high-biomass communities, highlighting that biomass quantity alone does not predict microbial productivity in soil. Furthermore, within a given soil, the rates at which specific lipids are being synthesized do not relate to their quantity, suggesting a general decoupling of microbial abundance and growth in soil microbiomes. More generally, we demonstrate the utility of lipid stable isotope probing for measuring microbial growth rates in soil and highlight the importance of measuring growth rates to complement more standard analyses of soil microbial communities. SignificanceGeneration times, how quickly organisms grow and reproduce, are a key feature of biology. However, there are few measurements of microbial generation times in soil, despite the crucial importance of soil microbes to terrestrial ecosystems. By measuring the rate at which isotopically labeled water is incorporated into microbial membranes, we find that the generation times of soil microorganisms are far longer than those typically observed in culture. Surprisingly, we observe that lower-biomass soils exhibited faster growth rates than high-biomass soils. More abundant microorganisms are not necessarily the fastest growing and most soil microorganisms are slow growers. Our results underscore the importance of considering slow and variable growth rates when studying microbial communities and their contributions to ecosystem processes.

microbiology↗

bioRxiv2021

An ecological perspective on microbial genes of unknown function in soil

Genes that remain hypothetical, uncharacterized, and unannotated comprise a substantial portion of metagenomic datasets and are likely to be particularly prevalent in soils where poorly characterized taxa predominate. Documenting the prevalence, distribution, and potential roles of these genes of unknown function is an important first step to understanding their functional contributions in soil communities. We identified genes of unknown function from 50 soil metagenomes and analyzed their environmental distributions and ecological associations. We found that genes of unknown function are prevalent in soils, particularly fine-textured, higher pH soils that harbor greater abundances of Crenarchaeota, Gemmatimonadota, Nitrospirota, and Methylomirabilota. We identified 43 dominant (abundant and ubiquitous) gene clusters of unknown function and determined their associations with soil microbial phyla and other "known" genes. We found that these dominant unknown genes were commonly associated with microbial phyla that are relatively uncharacterized, with the majority of these dominant unknown genes associated with mobile genetic elements. This work demonstrates a strategy for investigating genes of unknown function in soils, emphasizes the biological insights that can be learned by adopting this strategy, and highlights specific hypotheses that warrant further investigation regarding the functional roles of abundant and ubiquitous genes of unknown function in soil metagenomes.

microbiology↗