Seven years of microbial community metagenomes from temperate soils affected by an ongoing coal seam fire.

We examined the dynamics of soil microbiomes under heat press disturbance from an underground coal mine fire in Centralia, PA. Here, we present metagenomic sequencing and assembly data from soil microbiomes across seven consecutive years at repeatedly sampled fire-affected sites along with unaffected reference sites.

Arrive and wait: Inactive bacterial taxa contribute to perceived soil microbiome resilience after a multidecadal press disturbance.

Long-term (press) disturbances like the climate crisis and other anthropogenic pressures are fundamentally altering ecosystems and their functions. Many critical ecosystem functions, such as biogeochemical cycling, are facilitated by microbial communities. Understanding the functional consequences of microbiome responses to press disturbances requires ongoing observations of the active populations that contribute to functions. This study leverages a 7-year time series of a 60-year-old coal seam fire (Centralia, Pennsylvania, USA) to examine the resilience of soil bacterial microbiomes to a press disturbance. Using 16S rRNA and 16S rRNA gene amplicon sequencing, we assessed the interannual dynamics of the active subset and the 'whole' bacterial community. Contrary to our hypothesis, the whole communities demonstrated greater resilience than active subsets, suggesting that inactive members contributed to overall structural resilience. Thus, in addition to selection mechanisms of active populations, perceived microbiome resilience is also supported by mechanisms of dispersal, persistence, and revival from the local dormant pool.

Metagenomic stable isotope probing reveals bacteriophage participation in soil carbon cycling.

Soil viruses are important components of the carbon (C) cycle, yet we still know little about viral ecology in soils. We added diverse 13 C-labelled carbon sources to soil and we used metagenomic-SIP to detect 13 C assimilation by viruses and their putative bacterial hosts. These data allowed us to link a 13 C-labelled bacteriophage to its 13 C-labelled Streptomyces putative host, and we used qPCR to track the dynamics of the putative host and phage in response to C inputs. Following C addition, putative host numbers increased rapidly for 3 days, and then more gradually, reaching maximal abundance on Day 6. Viral abundance and virus:host ratio increased dramatically over 6 days, and remained high thereafter (8.42 ± 2.94). From Days 6 to 30, virus:host ratio remained high, while putative host numbers declined more than 50%. Putative host populations were 13 C-labelled on Days 3-30, while 13 C-labelling of phage was detected on Days 14 and 30. This dynamic suggests rapid growth and 13 C-labelling of the host fueled by new C inputs, followed by extensive host mortality driven by phage lysis. These findings indicate that the viral shunt promotes microbial turnover in soil following new C inputs, thereby altering microbial community dynamics, and facilitating soil organic matter production.

Genomic Features Predict Bacterial Life History Strategies in Soil, as Identified by Metagenomic Stable Isotope Probing.

Bacteria catalyze the formation and destruction of soil organic matter, but the bacterial dynamics in soil that govern carbon (C) cycling are not well understood. Life history strategies explain the complex dynamics of bacterial populations and activities based on trade-offs in energy allocation to growth, resource acquisition, and survival. Such trade-offs influence the fate of soil C, but their genomic basis remains poorly characterized. We used multisubstrate metagenomic DNA stable isotope probing to link genomic features of bacteria to their C acquisition and growth dynamics. We identify several genomic features associated with patterns of bacterial C acquisition and growth, notably genomic investment in resource acquisition and regulatory flexibility. Moreover, we identify genomic trade-offs defined by numbers of transcription factors, membrane transporters, and secreted products, which match predictions from life history theory. We further show that genomic investment in resource acquisition and regulatory flexibility can predict bacterial ecological strategies in soil. IMPORTANCE Soil microbes are major players in the global carbon cycle, yet we still have little understanding of how the carbon cycle operates in soil communities. A major limitation is that carbon metabolism lacks discrete functional genes that define carbon transformations. Instead, carbon transformations are governed by anabolic processes associated with growth, resource acquisition, and survival. We use metagenomic stable isotope probing to link genome information to microbial growth and carbon assimilation dynamics as they occur in soil. From these data, we identify genomic traits that can predict bacterial ecological strategies which define bacterial interactions with soil carbon.

Tracing Carbon Metabolism with Stable Isotope Metabolomics Reveals the Legacy of Diverse Carbon Sources in Soil.

Tracking the metabolic activity of whole soil communities can improve our understanding of the transformation and fate of carbon in soils. We used stable isotope metabolomics to trace 13C from nine labeled carbon sources into the water-soluble metabolite pool of an agricultural soil over time. Soil was amended with a mixture of all nine sources, with one source isotopically labeled in each treatment. We compared changes in the 13C enrichment of metabolites with respect to carbon source and time over a 48-day incubation and contrasted differences between soluble sources (glucose, xylose, amino acids, etc.) and insoluble sources (cellulose and palmitic acid). Whole soil metabolite profiles varied singularly by time, while the composition of 13C-labeled metabolites differed primarily by carbon source (R2 = 0.68) rather than time (R2 = 0.07), with source-specific differences persisting throughout incubations. The 13C labeling of metabolites from insoluble carbon sources occurred slower than that from soluble sources but yielded a higher average atom percent (atom%) 13C in metabolite markers of biomass (amino acids and nucleic acids). The 13C enrichment of metabolite markers of biomass stabilized between 5 and 15 atom% 13C by the end of incubations. Temporal patterns in the 13C enrichment of tricarboxylic acid cycle intermediates, nucleobases (uracil and thymine), and by-products of DNA salvage (allantoin) closely tracked microbial activity. Our results demonstrate that metabolite production in soils is driven by the carbon source supplied to the community and that the fate of carbon in metabolites do not generally converge over time as a result of ongoing microbial processing and recycling. IMPORTANCE Carbon metabolism in soil remains poorly described due to the inherent difficulty of obtaining information on the microbial metabolites produced by complex soil communities. Our study demonstrates the use of stable isotope probing (SIP) to study carbon metabolism in soil by tracking 13C from supplied carbon sources into metabolite pools and biomass. We show that differences in the metabolism of sources influence the fate of carbon in soils. Heterogeneity in 13C-labeled metabolite profiles corresponded with compositional differences in the metabolically active populations, providing a basis for how microbial community composition correlates with the quality of soil carbon. Our study demonstrates the application of SIP-metabolomics in studying soils and identifies several metabolite markers of growth, activity, and other aspects of microbial function.

Bacterial community dynamics explain carbon mineralization and assimilation in soils of different land-use history.

Soil dwelling microorganisms are key players in the terrestrial carbon cycle, driving both the degradation and stabilization of soil organic matter. Bacterial community structure and function vary with respect to land use; yet the ecological drivers of this variation remain poorly described and difficult to predict. We conducted a multi-substrate DNA-stable isotope probing experiment across cropland, old-field, and forest habitats to link carbon mineralization dynamics with the dynamics of bacterial growth and carbon assimilation. We tracked the movement of 13 C derived from five distinct carbon sources as it was assimilated into bacterial DNA over time. We show that carbon mineralization, community composition, and carbon assimilation dynamics all differed with respect to land use. We also show that microbial community dynamics affect carbon assimilation dynamics and are associated with soil DNA content. Soil DNA yield is easy to measure and may be useful in predicting microbial community dynamics linked to soil carbon cycling. Soil dwelling microorganisms are key players in the terrestrial carbon cycle, driving both the degradation and stabilization of soil organic matter. Microbial communities vary with respect to land use, but we still have an incomplete understanding of how variation in community structure links to variation in community function. DNA stable isotope probing (DNA-SIP) is a high-resolution method that can identify specific microbial taxa that assimilate carbon in situ. We conducted a large-scale multi-substrate DNA-SIP experiment to explore differences in bacterial activity across land-use regimes. We show that microbial community dynamics vary with land use, that these dynamics are linked to soil carbon cycling, and that they are associated with easily measured soil properties.

Multisubstrate DNA stable isotope probing reveals guild structure of bacteria that mediate soil carbon cycling.

Soil microorganisms determine the fate of soil organic matter (SOM), and their activities compose a major component of the global carbon (C) cycle. We employed a multisubstrate, DNA-stable isotope probing experiment to track bacterial assimilation of C derived from distinct sources that varied in bioavailability. This approach allowed us to measure microbial contributions to SOM processing by measuring the C assimilation dynamics of diverse microorganisms as they interacted within soil. We identified and tracked 1,286 bacterial taxa that assimilated 13C in an agricultural soil over a period of 48 d. Overall 13C-assimilation dynamics of bacterial taxa, defined by the source and timing of the 13C they assimilated, exhibited low phylogenetic conservation. We identified bacterial guilds composed of taxa that had similar 13C assimilation dynamics. We show that C-source bioavailability explained significant variation in both C mineralization dynamics and guild structure, and that the growth dynamics of bacterial guilds differed significantly in response to C addition. We also demonstrate that the guild structure explains significant variation in the biogeographical distribution of bacteria at continental and global scales. These results suggest that an understanding of in situ growth dynamics is essential for understanding microbial contributions to soil C cycling. We interpret these findings in the context of bacterial life history strategies and their relationship to terrestrial C cycling.

Community Organization and Metagenomics of Bacterial Assemblages Across Local Scale pH Gradients in Northern Forest Soils.

Soil pH has shown to predict bacterial diversity, but mechanisms are still poorly understood. To investigate how bacteria distribute themselves as a function of soil pH, we assessed community composition, diversity, assembly, and gene abundance across local (ca. 1 km) scale gradients in soil pH from ~ 3.8 to 6.5 created by differences in soil parent material in three northern forests. Plant species were the same on all sites, with no evidence of agriculture in the past. Concentrations of extractable calcium, iron, and phosphorus also varied significantly across the pH gradients. Among taxa, Alphaproteobacteria and Acidobacteria were more common in soils with acidic pH values. Overall richness and diversity of OTUs peaked at intermediate pH values. Variations in OTU richness and diversity also had a quadratic fit with concentrations of extractable calcium and phosphorus. Community assembly was via homogeneous deterministic processes in soils with acidic pH values, whereas stochastic processes dominated in soils with near-neutral pH values. Although we expected selection via genes for acid tolerance response in acidic soils, genes for genetic information processing were more selective. Taxa in higher pH soils had differential abundance of transporter genes, suggesting adaptation to acquire metabolic substrates from soils. Soil bacterial communities in northern forest soils are incredibly diverse, and we still have much to learn about how soil pH and co-varying soil parameters directly drive gene selection in this critical component of ecosystem structure.

Simulating metagenomic stable isotope probing datasets with MetaSIPSim.

BACKGROUND: DNA-stable isotope probing (DNA-SIP) links microorganisms to their in-situ function in diverse environmental samples. Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes from complex communities to their specific functions and improves the assembly and binning of these targeted genomes. However, empirical development of metagenomic-SIP methods is hindered by the complexity and cost of these studies. We developed a toolkit, 'MetaSIPSim,' to simulate sequencing read libraries for metagenomic-SIP experiments. MetaSIPSim is intended to generate datasets for method development and testing. To this end, we used MetaSIPSim generated data to demonstrate the advantages of metagenomic-SIP over a conventional shotgun metagenomic sequencing experiment. RESULTS: Through simulation we show that metagenomic-SIP improves the assembly and binning of isotopically labeled genomes relative to a conventional metagenomic approach. Improvements were dependent on experimental parameters and on sequencing depth. Community level G + C content impacted the assembly of labeled genomes and subsequent binning, where high community G + C generally reduced the benefits of metagenomic-SIP. Furthermore, when a high proportion of the community is isotopically labeled, the benefits of metagenomic-SIP decline. Finally, the choice of gradient fractions to sequence greatly influences method performance. CONCLUSIONS: Metagenomic-SIP is a valuable method for recovering isotopically labeled genomes from complex communities. We show that metagenomic-SIP performance depends on optimization of experimental parameters. MetaSIPSim allows for simulation of metagenomic-SIP datasets which facilitates the optimization and development of metagenomic-SIP experiments and analytical approaches for dealing with these data.

Evidence for phylogenetically and catabolically diverse active diazotrophs in deep-sea sediment.

Diazotrophic microorganisms regulate marine productivity by alleviating nitrogen limitation. However, we know little about the identity and activity of diazotrophs in deep-sea sediments, a habitat covering nearly two-thirds of the planet. Here, we identify candidate diazotrophs from Pacific Ocean sediments collected at 2893 m water depth using 15N-DNA stable isotope probing and a novel pipeline for nifH sequence analysis. Together, these approaches detect an unexpectedly diverse assemblage of active diazotrophs, including members of the Acidobacteria, Firmicutes, Nitrospirae, Gammaproteobacteria, and Deltaproteobacteria. Deltaproteobacteria, predominately members of the Desulfobacterales and Desulfuromonadales, are the most abundant diazotrophs detected, and display the most microdiversity of associated nifH sequences. Some of the detected lineages, including those within the Acidobacteria, have not previously been shown to fix nitrogen. The diazotrophs appear catabolically diverse, with the potential for using oxygen, nitrogen, iron, sulfur, and carbon as terminal electron acceptors. Therefore, benthic diazotrophy may persist throughout a range of geochemical conditions and provide a stable source of fixed nitrogen over geologic timescales. Our results suggest that nitrogen-fixing communities in deep-sea sediments are phylogenetically and catabolically diverse, and open a new line of inquiry into the ecology and biogeochemical impacts of deep-sea microorganisms.

Soil characteristics and land-use drive bacterial community assembly patterns.

Land-use and soil characteristics drive variation in soil community composition, but the influences of these factors on dispersal and community assembly at regional scale remain poorly characterized. Land-use remains a consistent driver of soil community composition even when exhibiting patchy spatial distribution at regional scale. In addition, disturbed and early successional soils often exhibit stochastic community assembly patterns. These observations suggest local community composition is influenced by dispersal and assembly from regional species pools. We examined bacterial community assembly within agricultural cropland, old-field, and forested sites across 10 landscapes in the region around Ithaca, New York (USA). We found that the Sloan neutral model explained assembly well at regional scale (R2 = 0.763), but that both soil pH and land-use imposed selection that shaped community composition. We show that homogeneous selection was a dominant assembly process with respect to both soil pH and land-use regime, but that these two factors interacted in their effects on bacterial community assembly. We conclude that bacterial community assembly at a regional scale is driven by dispersal from regional species pools and local selection on the basis of soil pH and other soil characteristics that vary with land-use.

Data Analysis for DNA Stable Isotope Probing Experiments Using Multiple Window High-Resolution SIP.

DNA stable isotope probing (DNA-SIP) allows for the identification of microbes that assimilate isotopically labeled substrates into DNA. Here we describe the analysis of sequencing data using the multiple window high-resolution DNA-SIP method (MW-HR-SIP). MW-HR-SIP has improved accuracy over other methods and is easily implemented on the statistical platform R. We also discuss key experimental parameters to consider when designing DNA-SIP experiments and how these parameters affect accuracy of analysis.

Diverse genotypes of the amphibian-killing fungus produce distinct phenotypes through plastic responses to temperature.

Phenotypes are the target of selection and affect the ability of organisms to persist in variable environments. Phenotypes can be influenced directly by genes and/or by phenotypic plasticity. The amphibian-killing fungus Batrachochytrium dendrobatidis (Bd) has a global distribution, unusually broad host range, and high genetic diversity. Phenotypic plasticity may be an important process that allows this pathogen to infect hundreds of species in diverse environments. We quantified phenotypic variation of nine Bd genotypes from two Bd lineages (Global Pandemic Lineage [GPL] and Brazil) and a hybrid (GPL-Brazil) grown at three temperatures (12, 18 and 24°C). We measured five functional traits including two morphological traits (zoospore and zoosporangium sizes) and three life history traits (carrying capacity, time to fastest growth and exponential growth rate) in a phylogenetic framework. Temperature caused highly plastic responses within each genotype, with all Bd genotypes showing phenotypic plasticity in at least three traits. Among genotypes, Bd generally showed the same direction of plastic response to temperature: larger zoosporangia, higher carrying capacity, longer time to fastest growth and slower exponential growth at lower temperatures. The exception was zoospore size, which was highly variable. Our findings indicate that Bd genotypes have evolved novel phenotypes through plastic responses to temperature over very short timescales. High phenotypic variability likely extends to other traits and may facilitate the large host range and rapid spread of Bd.

SIPSim: A Modeling Toolkit to Predict Accuracy and Aid Design of DNA-SIP Experiments.

DNA Stable isotope probing (DNA-SIP) is a powerful method that links identity to function within microbial communities. The combination of DNA-SIP with multiplexed high throughput DNA sequencing enables simultaneous mapping of in situ assimilation dynamics for thousands of microbial taxonomic units. Hence, high throughput sequencing enabled SIP has enormous potential to reveal patterns of carbon and nitrogen exchange within microbial food webs. There are several different methods for analyzing DNA-SIP data and despite the power of SIP experiments, it remains difficult to comprehensively evaluate method accuracy across a wide range of experimental parameters. We have developed a toolset (SIPSim) that simulates DNA-SIP data, and we use this toolset to systematically evaluate different methods for analyzing DNA-SIP data. Specifically, we employ SIPSim to evaluate the effects that key experimental parameters (e.g., level of isotopic enrichment, number of labeled taxa, relative abundance of labeled taxa, community richness, community evenness, and beta-diversity) have on the specificity, sensitivity, and balanced accuracy (defined as the product of specificity and sensitivity) of DNA-SIP analyses. Furthermore, SIPSim can predict analytical accuracy and power as a function of experimental design and community characteristics, and thus should be of great use in the design and interpretation of DNA-SIP experiments.

HTSSIP: An R package for analysis of high throughput sequencing data from nucleic acid stable isotope probing (SIP) experiments.

Combining high throughput sequencing with stable isotope probing (HTS-SIP) is a powerful method for mapping in situ metabolic processes to thousands of microbial taxa. However, accurately mapping metabolic processes to taxa is complex and challenging. Multiple HTS-SIP data analysis methods have been developed, including high-resolution stable isotope probing (HR-SIP), multi-window high-resolution stable isotope probing (MW-HR-SIP), quantitative stable isotope probing (qSIP), and ΔBD. Currently, there is no publicly available software designed specifically for analyzing HTS-SIP data. To address this shortfall, we have developed the HTSSIP R package, an open-source, cross-platform toolset for conducting HTS-SIP analyses in a straightforward and easily reproducible manner. The HTSSIP package, along with full documentation and examples, is available from CRAN at https://cran.r-project.org/web/packages/HTSSIP/index.html and Github at https://github.com/buckleylab/HTSSIP.

Inhibition of Fungal Pathogens across Genotypes and Temperatures by Amphibian Skin Bacteria.

Symbiotic bacteria may dampen the impacts of infectious diseases on hosts by inhibiting pathogen growth. However, our understanding of the generality of pathogen inhibition by different bacterial taxa across pathogen genotypes and environmental conditions is limited. Bacterial inhibitory properties are of particular interest for the amphibian-killing fungal pathogens (Batrachochytrium dendrobatidis and Batrachochytrium salamandrivorans), for which probiotic applications as conservation strategies have been proposed. We quantified the inhibition strength of five putatively B. dendrobatidis-inhibitory bacteria isolated from woodland salamander skin against six Batrachochytrium genotypes at two temperatures (12 and 18°C). We selected six genotypes from across the Batrachochytrium phylogeny: B. salamandrivorans, B. dendrobatidis-Brazil and four genotypes of the B. dendrobatidis Global Panzootic Lineage (GPL1: JEL647, JEL404; GPL2: SRS810, JEL423). We performed 96-well plate challenge assays in a full factorial design. We detected a Batrachochytrium genotype by temperature interaction on bacterial inhibition score for all bacteria, indicating that bacteria vary in ability to inhibit Batrachochytrium depending on pathogen genotype and temperature. Acinetobacter rhizosphaerae moderately inhibited B. salamandrivorans at both temperatures (µ = 46-53%), but not any B. dendrobatidis genotypes. Chryseobacterium sp. inhibited three Batrachochytrium genotypes at both temperatures (µ = 5-71%). Pseudomonas sp. strain 1 inhibited all Batrachochytrium genotypes at 12°C and four Batrachochytrium genotypes at 18°C (µ = 5-100%). Pseudomonas sp. strain 2 and Stenotrophomonas sp. moderately to strongly inhibited all six Batrachochytrium genotypes at both temperatures (µ = 57-100%). All bacteria consistently inhibited B. salamandrivorans. Using cluster analysis of inhibition scores, we found that more closely related Batrachochytrium genotypes grouped together, suggesting that bacterial inhibition strength may be predictable based on Batrachochytrium relatedness. We conclude that bacterial inhibition capabilities change among bacterial strains, Batrachochytrium genotypes and temperatures. A comprehensive understanding of bacterial inhibitory function, across pathogen genotypes and temperatures, is needed to better predict the role of bacterial symbionts in amphibian disease ecology. For targeted conservation applications, we recommend using bacterial strains identified as strongly inhibitory as they are most likely to produce broad-spectrum antimicrobial agents at a range of temperatures.