Persistence of location-specific microbial signatures on boats during voyages.

Objects collect microorganisms from their surroundings and develop a microbial "fingerprint" that may be useful for determining an object's past location (provenance). It may be possible to use ubiquitous microorganisms for forensics or as environmental sensors. Here, we use microbial communities in the Chesapeake Bay region to demonstrate the use of natural microorganisms as biological sensors to determine the past location of boats. The microbiomes of two boats and of the open water were sampled as these vessels traveled from the Port of Baltimore to the Port of Norfolk, and back to Baltimore. 16S rRNA sequencing was performed to identify microorganisms. Differential abundance and machine learning analyses were utilized to identify microbial signatures and predicted probabilities which were used to determine the vessel's previous location. The work presented here provides a better understanding of how microbes in aquatic systems can be leveraged as utility for object biosensors.

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Coexistence of specialist and generalist species within mixed plastic derivative-utilizing microbial communities.

BACKGROUND: Plastic-degrading microbial isolates offer great potential to degrade, transform, and upcycle plastic waste. Tandem chemical and biological processing of plastic wastes has been shown to substantially increase the rates of plastic degradation; however, the focus of this work has been almost entirely on microbial isolates (either bioengineered or naturally occurring). We propose that a microbial community has even greater potential for plastic upcycling. A microbial community has greater metabolic diversity to process mixed plastic waste streams and has built-in functional redundancy for optimal resilience. RESULTS: Here, we used two plastic-derivative degrading communities as a model system to investigate the roles of specialist and generalist species within the microbial communities. These communities were grown on five plastic-derived substrates: pyrolysis treated high-density polyethylene, chemically deconstructed polyethylene terephthalate, disodium terephthalate, terephthalamide, and ethylene glycol. Short-read metagenomic and metatranscriptomic sequencing were performed to evaluate activity of microorganisms in each treatment. Long-read metagenomic sequencing was performed to obtain high-quality metagenome assembled genomes and evaluate division of labor. CONCLUSIONS: Data presented here show that the communities are primarily dominated by Rhodococcus generalists and lower abundance specialists for each of the plastic-derived substrates investigated here, supporting previous research that generalist species dominate batch culture. Additionally, division of labor may be present between Hydrogenophaga terephthalate degrading specialists and lower abundance protocatechuate degrading specialists. Video Abstract.

Comparative assessment of bacterial diversity and composition in arsenic hyperaccumulator, Pteris vittata L. and non-accumulator, Pteris ensiformis Burm.

The use of arsenic (As) for various industrial and agricultural applications has led to worldwide environmental contamination. Phytoremediation using hyperaccumulators is a sustainable soil As mitigation strategy. Microbial processes play an important role in the tolerance and uptake of trace elements such as in plants. The rhizospheric and endophytic microbial communities are responsible for accelerating the mobility of trace elements around the roots and the production of plant growth-promoting compounds and enzymes. Several studies have reported that the As hyperaccumulator, Pteris vittata L. (PV) influences the microbial community in its rhizosphere and roots. Deciphering the differences in the microbiomes of hyperaccumulators and non-accumulators is crucial in understanding the mechanism of hyperaccumulation. We hypothesized that there are significant differences in the microbiome of roots, rhizospheric soil, and bulk soil between the hyperaccumulator PV and a non-accumulator of the same genus, Pteris ensiformis Burm. (PE), and that the differential recruitment of bacterial communities provides PV with an advantage in As contaminated soil. We compared root endophytic, rhizospheric, and bulk soil microbial communities between PV and PE species grown in As-contaminated soil in a greenhouse setting. There was a significant difference (p < 0.001) in the microbiome of the three compartments between the ferns. Differential abundance analysis showed 328 Amplicon Sequence Variants (ASVs) enriched in PV compared to 172 in PE. The bulk and rhizospheric soil of both ferns were abundant in As-resistant genera. However, As-tolerant root endophytic genera were present in PV but absent in PE. Our findings show that there is a difference between the bacterial composition of an As hyperaccumulator and a non-accumulator species grown in As-contaminated soil. These differences need to be further explored to develop strategies for improving the efficiency of metal uptake in plants growing in As polluted soil.

Biogeographic patterns in populations of marine Pseudoalteromonas atlantica isolates.

Intra-specific genomic diversity is well documented in microbes. The question, however, remains whether natural selection or neutral evolution is the major contributor to this diversity. We undertook this study to estimate genomic diversity in Pseudoalteromonas atlantica populations and whether the diversity, if present, could be attributed to environmental factors or distance effects. We isolated and sequenced twenty-three strains of P. atlantica from three geographically distant deep marine basins and performed comparative genomic analyses to study the genomic diversity of populations among these basins. Average nucleotide identity followed a strictly geographical pattern. In two out of three locations, the strains within the location exhibited >99.5% identity, whereas, among locations, the strains showed <98.11% identity. Phylogenetic and pan-genome analysis also reflected the biogeographical separation of the strains. Strains from the same location shared many accessory genes and clustered closely on the phylogenetic tree. Phenotypic diversity between populations was studied in ten out of twenty-three strains testing carbon and nitrogen source utilization and osmotolerance. A genetic basis for phenotypic diversity could be established in most cases but was apparently not influenced by local environmental conditions. Our study suggests that neutral evolution may have a substantial role in the biodiversity of P. atlantica.

Metagenomic Sequencing of Two Cultures Grown on Chemically Deconstructed Plastic Products.

We report the metagenome sequences of two microbial cultures that were grown with chemically deconstructed plastic products as their sole carbon source. These metagenomes will provide insights into the metabolic capabilities of cultures grown on deconstructed plastics and can serve as a starting point for the identification of novel plastic degradation mechanisms.

Deconstructed Plastic Substrate Preferences of Microbial Populations from the Natural Environment.

Over half of the world's plastic waste is landfilled, where it is estimated to take hundreds of years to degrade. Given the continued use and disposal of plastic products, it is vital that we develop fast and effective ways to utilize plastic waste. Here, we explore the potential of tandem chemical and biological processing to process various plastics quickly and effectively. Four samples of compost or sediment were used to set up enrichment cultures grown on mixtures of compounds, including disodium terephthalate and terephthalic acid (monomers of polyethylene terephthalate), compounds derived from the chemical deconstruction of polycarbonate, and pyrolysis oil derived from high-density polyethylene plastics. Established enrichment communities were also grown on individual substrates to investigate the substrate preferences of different taxa. Biomass harvested from the cultures was characterized using 16S rRNA gene amplicon sequencing and shotgun metagenomic sequencing. These data reveal low-diversity microbial communities structured by differences in culture inoculum, culture substrate source plastic type, and time. Microbial populations from the classes Alphaproteobacteria, Gammaproteobacteria, Actinobacteria, and Acidobacteriae were significantly enriched when grown on substrates derived from high-density polyethylene and polycarbonate. The metagenomic data contain abundant aromatic and aliphatic hydrocarbon degradation genes relevant to the biodegradation of deconstructed plastic substrates used here. We show that microbial populations from diverse environments are capable of growth on substrates derived from the chemical deconstruction or pyrolysis of multiple plastic types and that paired chemical and biological processing of plastics should be further developed for industrial applications to manage plastic waste. IMPORTANCE The durability and impermeable nature of plastics have made them a popular material for numerous applications, but these same qualities make plastics difficult to dispose of, resulting in massive amounts of accumulated plastic waste in landfills and the natural environment. Since plastic use and disposal are projected to increase in the future, novel methods to effectively break down and dispose of current and future plastic waste are desperately needed. We show that the products of chemical deconstruction or pyrolysis of plastic can successfully sustain the growth of low-diversity microbial communities. These communities were enriched from multiple environmental sources and are capable of degrading complex xenobiotic carbon compounds. This study demonstrates that tandem chemical and biological processing can be used to degrade multiple types of plastics over a relatively short period of time and may be a future avenue for the mitigation of rapidly accumulating plastic waste.

Impacts of Nutrients on Alkene Biodegradation Rates and Microbial Community Composition in Enriched Consortia from Natural Inocula.

There is a growing need for biological and chemical methods for upcycling plastic waste streams. Pyrolysis processes can accelerate plastic depolymerization by breaking polyethylene into smaller alkene components which may be more biodegradable than the initial polymer. While the biodegradation of alkanes has been extensively studied, the role microorganisms play in alkene breakdown is not well understood. Alkene biodegradation holds the potential to contribute to the coupling of chemical and biological processing of polyethylene plastics. In addition, nutrient levels are known to impact rates of hydrocarbon degradation. Model alkenes were used (C6, C10, C16, and C20) to follow the breakdown capability of microbial communities from three environmental inocula in three nutrient levels over the course of 5 days. Higher-nutrient cultures were anticipated to exhibit enhanced biodegradation capabilities. Alkene mineralization was assessed by measuring CO2 production in the culture headspace using GC-FID (gas chromatography-flame ionization detection), and alkene breakdown was directly quantified by measuring extracted residual hydrocarbons using gas chromatography-mass spectrometry (GC/MS). Here, the efficacy of enriched consortia derived from the microbial communities of three inoculum sources (farm compost, Caspian Sea sediment, and an iron-rich sediment) at alkene breakdown was investigated over the course of 5 days across three nutrient treatments. No significant differences in CO2 production across nutrient levels or inoculum types were found. A high extent of biodegradation was observed in all sample types, with most samples achieving 60% to 95% biodegradation of all quantified compounds. Here, our findings indicate that alkene biodegradation is a common metabolic process in diverse environments and that nutrient levels common to culture media can support the growth of alkene-biodegrading consortia, primarily from the families Xanthamonadaceae, Nocardiaceae, and Beijerinkiaceae. IMPORTANCE Excess plastic waste poses a major environmental problem. Microorganisms can metabolize many of the breakdown products (alkenes) of plastics. While microbial degradation of plastics is typically slow, coupling chemical and biological processing of plastics has the potential to lead to novel methods for the upcycling of plastic wastes. Here, we explored how microbial consortia derived from diverse environments metabolize alkenes, which are produced by the pyrolysis of polyolefin plastics such as HDPE, and PP. We found that microbial consortia from diverse environments can rapidly metabolize alkenes of different chain lengths. We also explored how nutrients affect the rates of alkene breakdown and the microbial diversity of the consortia. Here, the findings indicate that alkene biodegradation is a common metabolism in diverse environments (farm compost, Caspian sediment, and iron-rich sediment) and that nutrient levels common to culture medium can support growth of alkene-biodegrading consortia, primarily from families Xanthamonadaceae, Nocardiaceae, and Beijerinkiaceae.

Versatile microbial communities rapidly assimilate ammonium hydroxide-treated plastic waste.

Waste plastic presently accumulates in landfills or the environment. While natural microbial metabolisms can degrade plastic polymers, biodegradation of plastic is very slow. This study demonstrates that chemical deconstruction of polyethylene terephthalate (PET) with ammonium hydroxide can replace the rate limiting step (depolymerization) and by producing plastic-derived terephthalic acid and terephthalic acid monoamide. The deconstructed PET (DCPET) is neutralized with phosphoric acid prior to bioprocessing, resulting in a product containing biologically accessible nitrogen and phosphorus from the process reactants. Three microbial consortia obtained from compost and sediment degraded DCPET in ultrapure water and scavenged river water without addition of nutrients. No statistically significant difference was observed in growth rate compared to communities grown on DCPET in minimal culture medium. The consortia were dominated by Rhodococcus spp., Hydrogenophaga spp., and many lower abundance genera. All taxa were related to species known to degrade aromatic compounds. Microbial consortia are known to confer flexibility in processing diverse substrates. To highlight this, we also demonstrate that two microbial consortia can grow on similarly deconstructed polyesters, polyamides, and polyurethanes in water instead of medium. Our findings suggest that microbial communities may enable flexible bioprocessing of mixed plastic wastes when coupled with chemical deconstruction.

Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research.

Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.

Impacts of dispersants on microbial communities and ecological systems.

Accidental oil spills can result in catastrophic ecological insults and therefore require rapid intervention to mitigate the potential impacts to aquatic ecosystems. One of the largest oil spills, known as the Deepwater Horizon oil spill, occurred in the Spring of 2010 near the coast of Louisiana (USA) due to an explosion during oil drilling activities. Millions of gallons of oil were released into the Gulf of Mexico, impacting thousands of ocean miles and coastal areas linked to the gulf. Among the actions taken during the remediation efforts was the unprecedented large use of Corexit dispersants, including at the subsurface to prevent oil from reaching the surface. While there is evidence that dispersants can accelerate the biodegradation of oil, reports on their potential toxicity to aquatic biota and to microbial functions have also been documented. In this review, we will examine the most recent literature on the impact of dispersants on microbial communities implicated in oil degradation and overall ecological networks. The primary focus will be on studies using Corexit but other dispersants will be discussed if data are available. We will share the literature gaps identified and discuss future work that is needed to reconcile some of the discrepancies found on the effectiveness of dispersants on oil degradation and their potential toxicity. KEY POINTS: • Chemical dispersants have been applied as a chemical response measure for oil spills. • The effects of chemical dispersants on microbial communities have been the subject of substantial research. • This work seeks to review recent work on the impact of chemical dispersants on oil biodegradation, microbial communities, and ecosystems.

Killing two birds with one stone: chemical and biological upcycling of polyethylene terephthalate plastics into food.

Most polyethylene terephthalate (PET) plastic waste is landfilled or pollutes the environment. Additionally, global food production must increase to support the growing population. This article explores the feasibility of using microorganisms in an industrial system that upcycles PET into edible microbial protein powder to solve both problems simultaneously. Many microorganisms can utilize plastics as feedstock, and the resultant microbial biomass contains fats, nutrients, and proteins similar to those found in human diets. While microbial degradation of PET is promising, biological PET depolymerization is too slow to resolve the global plastic crisis and projected food shortages. Evidence reviewed here suggests that by coupling chemical depolymerization and biological degradation of PET, and using cooperative microbial communities, microbes can efficiently convert PET waste into food.

Geochemistry and Multiomics Data Differentiate Streams in Pennsylvania Based on Unconventional Oil and Gas Activity.

Unconventional oil and gas (UOG) extraction is increasing exponentially around the world, as new technological advances have provided cost-effective methods to extract hard-to-reach hydrocarbons. While UOG has increased the energy output of some countries, past research indicates potential impacts in nearby stream ecosystems as measured by geochemical and microbial markers. Here, we utilized a robust data set that combines 16S rRNA gene amplicon sequencing (DNA), metatranscriptomics (RNA), geochemistry, and trace element analyses to establish the impact of UOG activity in 21 sites in northern Pennsylvania. These data were also used to design predictive machine learning models to determine the UOG impact on streams. We identified multiple biomarkers of UOG activity and contributors of antimicrobial resistance within the order Burkholderiales. Furthermore, we identified expressed antimicrobial resistance genes, land coverage, geochemistry, and specific microbes as strong predictors of UOG status. Of the predictive models constructed (n = 30), 15 had accuracies higher than expected by chance and area under the curve values above 0.70. The supervised random forest models with the highest accuracy were constructed with 16S rRNA gene profiles, metatranscriptomics active microbial composition, metatranscriptomics active antimicrobial resistance genes, land coverage, and geochemistry (n = 23). The models identified the most important features within those data sets for classifying UOG status. These findings identified specific shifts in gene presence and expression, as well as geochemical measures, that can be used to build robust models to identify impacts of UOG development. IMPORTANCE The environmental implications of unconventional oil and gas extraction are only recently starting to be systematically recorded. Our research shows the utility of microbial communities paired with geochemical markers to build strong predictive random forest models of unconventional oil and gas activity and the identification of key biomarkers. Microbial communities, their transcribed genes, and key biomarkers can be used as sentinels of environmental changes. Slight changes in microbial function and composition can be detected before chemical markers of contamination. Potential contamination, specifically from biocides, is especially concerning due to its potential to promote antibiotic resistance in the environment. Additionally, as microbial communities facilitate the bulk of nutrient cycling in the environment, small changes may have long-term repercussions. Supervised random forest models can be used to identify changes in those communities, greatly enhance our understanding of what such impacts entail, and inform environmental management decisions.

Comparative Analysis of the Mechanism of Resistance to Silver Nanoparticles and the Biocide 2,2-Dibromo-3-Nitrilopropionamide.

Antimicrobials such as nanoparticles and biocides are used to control microbial growth. We used Escherichia coli to study the process of acquired resistance to silver nanoparticles (Ag-NP) and the industrial biocide DBNPA when grown in sub-MICs. We determined the MICs of these two antimicrobials against E. coli. We then performed an experimental evolution study where E. coli was grown in subinhibitory concentrations of the antimicrobials and transferred 10 times. We then tracked the changes in growth characteristics, lactate dehydrogenase (LDH) activity, reactive oxidative species (ROS) production, and the role of efflux pumps in conferring resistance. We also performed genome sequencing to determine the genetic basis for acquired resistance. Our results showed that E. coli could rapidly develop resistance to Ag-NP and DBNPA after growth in low concentrations of the antimicrobials. The expression of efflux pumps plays a vital role in both Ag-NP and DBNPA resistance. Multiple mutations occurred in the adapted strains that may confer resistance to both Ag-NP and DBNPA. Our study provides insights into mechanisms of adaptation and resistance to antimicrobials. Our results suggest that there are some shared mechanisms to resist nanoparticles and biocides as well as some key differences. The mechanism of resistance to Ag-NP might be related to flagellin production, while efflux pumps seem to be associated with resistance to DBNPA. This work provides a comparative study of the mechanisms of acquired resistance to these two types of antimicrobials.

Draft Genome Sequencing of Three Glutaraldehyde-Tolerant Bacteria from Produced Water from Hydraulic Fracturing.

Here, we report the draft genome sequence of three glutaraldehyde-resistant isolates from produced water from hydraulic fracturing operations. The three strains were identified as Marinobacter sp. strain G11, Halomonas sp. strain G15, and Bacillus sp. strain G16. The genome sequences of these isolates will provide insights into biocide resistance in hydraulic fracturing operations.

Partitioning and sources of microbial pollution in the Venice Lagoon.

Microbial pollutants are a serious threat to human and environmental health in coastal areas. Based on the hypothesis that pollution from multiple sources may produce a distinct microbial signature and that microbial pollutants seem to distribute between a free-living and a particle-attached fraction, we investigated the occurrence, partitioning and sources of microbial pollutants in water samples collected in the Venice Lagoon (Italy). The area was taken as a case study of an environment characterized by a long history of industrial pollution and by growing human pressure. We found a variety of pollutants from several sources, with sewage-associated and faecal bacteria accounting for up to 5.98% of microbial communities. Sewage-associated pollutants were most abundant close to the city centre. Faecal pollution was highest in the area of the industrial port and was dominated by human inputs, whereas contamination from animal faeces was mainly detected at the interface with the mainland. Microbial pollutants were almost exclusively associated with the particle-attached fraction. The samples also contained other potential pathogens. Our findings stress the need for monitoring and managing microbial pollution in highly urbanized lagoon and semi-enclosed systems and suggest that management plans to reduce microbial inputs to the waterways should include measures to reduce particulate matter inputs to the lagoon. Finally, High-Throughput Sequencing combined with computational approaches proved critical to assess water quality and appears to be a valuable tool to support the monitoring of waterborne diseases.

Codon usage bias and dinucleotide preference in 29 Drosophila species.

Codon usage bias, where certain codons are used more frequently than their synonymous counterparts, is an interesting phenomenon influenced by three evolutionary forces: mutation, selection, and genetic drift. To better understand how these evolutionary forces affect codon usage bias, an extensive study to detect how codon usage patterns change across species is required. This study investigated 668 single-copy orthologous genes independently in 29 Drosophila species to determine how the codon usage patterns change with phylogenetic distance. We found a strong correlation between phylogenetic distance and codon usage bias and observed striking differences in codon preferences between the two subgenera Drosophila and Sophophora. As compared to the subgenus Sophophora, species of the subgenus Drosophila showed reduced codon usage bias and a reduced preference specifically for codons ending with C, except for codons with G in the second position. We found that codon usage patterns in all species were influenced by the nucleotides in the codon's 2nd and 3rd positions rather than the biochemical properties of the amino acids encoded. We detected a concordance between preferred codons and preferred dinucleotides (at positions 2 and 3 of codons). Furthermore, we observed an association between speciation, codon preferences, and dinucleotide preferences. Our study provides the foundation to understand how selection acts on dinucleotides to influence codon usage bias.

Comparative study of the effects of biocides and metal oxide nanoparticles on microbial community structure in a stream impacted by hydraulic fracturing.

Our study goal was to investigate the impact of biocides and nanoparticles (NPs) on the microbial diversity in a hydraulic fracturing impacted stream. Biocides and NPs are known for their antimicrobial properties and controlling microbial growth. Previous work has shown that biocides can alter the microbial community composition of stream water and may select for biocide-resistant bacteria. Additional studies have shown that nanoparticles can also alter microbial community composition. However, previous work has often focused on the response to a single compound. Here we provide a more thorough analysis of the microbial community response to three different biocides and three different nanoparticles. A microcosm-based study was undertaken that exposed stream microbial communities to either biocides or NPs. Our results showed a decrease in bacterial abundance with different types of nanoparticles, but an increase in microbial abundance in biocide-amended treatments. The microbial community composition (MCC) was distinct from the controls in all biocide and NP treatments, which resulted in differentially enriched taxa in the treatments compared to the controls. Our results indicate that NPs slightly altered the MCC compared to the biocide-treated microcosms. After 14 days, the MCC in the nanoparticle-treated conditions was similar to the MCC in the control. Conversely, the MCC in the biocide-treated microcosms was distinct from the controls at day 14 and distinct from all conditions at day 0. This finding may point to the use of NPs as an alternative to biocides in some settings.

Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures.

Hydraulic fracturing (HF), commonly called "fracking", uses a mixture of high-pressure water, sand, and chemicals to fracture rocks, releasing oil and gas. This process revolutionized the U.S. energy industry, as it gives access to resources that were previously unobtainable and now produces two-thirds of the total natural gas in the United States. Although fracking has had a positive impact on the U.S. economy, several studies have highlighted its detrimental environmental effects. Of particular concern is the effect of fracking on headwater streams, which are especially important due to their disproportionately large impact on the health of the entire watershed. The bacteria within those streams can be used as indicators of stream health, as the bacteria present and their abundance in a disturbed stream would be expected to differ from those in an otherwise comparable but undisturbed stream. Therefore, this protocol aims to use the bacterial community to determine if streams have been impacted by fracking. To this end, sediment, and water samples, from streams near fracking (potentially impacted) and upstream or in a different watershed of fracking activity (unimpacted) must be collected. Those samples are then subjected to nucleic acid extraction, library preparation, and sequencing to investigate microbial community composition. Correlational analysis and machine learning models can subsequently be employed to identify which features are explanative of variation in the community, as well as identification of predictive biomarkers for fracking's impact. These methods can reveal a variety of differences in the microbial communities among headwater streams, based on the proximity to fracking, and serve as a foundation for future investigations on the environmental impact of fracking activities.

The Rhizosphere Responds: Rich Fen Peat and Root Microbial Ecology after Long-Term Water Table Manipulation.

Hydrologic shifts due to climate change will affect the cycling of carbon (C) stored in boreal peatlands. Carbon cycling in these systems is carried out by microorganisms and plants in close association. This study investigated the effects of experimentally manipulated water tables (lowered and raised) and plant functional groups on the peat and root microbiomes in a boreal rich fen. All samples were sequenced and processed for bacterial, archaeal (16S DNA genes; V4), and fungal (internal transcribed spacer 2 [ITS2]) DNA. Depth had a strong effect on microbial and fungal communities across all water table treatments. Bacterial and archaeal communities were most sensitive to the water table treatments, particularly at the 10- to 20-cm depth; this area coincides with the rhizosphere or rooting zone. Iron cyclers, particularly members of the family Geobacteraceae, were enriched around the roots of sedges, horsetails, and grasses. The fungal community was affected largely by plant functional group, especially cinquefoils. Fungal endophytes (particularly Acephala spp.) were enriched in sedge and grass roots, which may have underappreciated implications for organic matter breakdown and cycling. Fungal lignocellulose degraders were enriched in the lowered water table treatment. Our results were indicative of two main methanogen communities, a rooting zone community dominated by the archaeal family Methanobacteriaceae and a deep peat community dominated by the family Methanomicrobiaceae. IMPORTANCE This study demonstrated that roots and the rooting zone in boreal fens support organisms likely capable of methanogenesis, iron cycling, and fungal endophytic association and are directly or indirectly affecting carbon cycling in these ecosystems. These taxa, which react to changes in the water table and associate with roots and, particularly, graminoids, may gain greater biogeochemical influence, as projected higher precipitation rates could lead to an increased abundance of sedges and grasses in boreal fens.