Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Environmental stress mediates groundwater microbial community assembly

Community assembly describes how different ecological processes shape microbial community composition and structure. How environmental factors impact community assembly remains elusive. Here we sampled microbial communities and >200 biogeochemical variables in groundwater at the Oak Ridge Field Research Center, a former nuclear waste disposal site, and developed a theoretical framework to conceptualize the relationships between community assembly processes and environmental stresses. We found that stochastic assembly processes were critical (>60% on average) in shaping community structure, but their relative importance decreased as stress increased. Dispersal limitation and 'drift' related to random birth and death had negative correlations with stresses, whereas the selection processes leading to dissimilar communities increased with stresses, primarily related to pH, cobalt and molybdenum. Assembly mechanisms also varied greatly among different phylogenetic groups. Our findings highlight the importance of microbial dispersal limitation and environmental heterogeneity in ecosystem restoration and management.

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and "transduce" signals to adjust internal processes. We hypothesized that an ecosystem's unique stimuli leave a sensor "fingerprint," able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection's nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient's disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model's feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

Microcystis blooms caused the decreasing richness of and interactions between free-living microbial functional genes in Lake Taihu, China

Microcystis blooms have a marked effect on microbial taxonomical diversity in eutrophic lakes, but their influence on the composition of microbial functional genes is still unclear. In this study, the free-living microbial functional genes (FMFG) composition was investigated in the period before Microcystis blooms (March) and during Microcystis blooms (July) using a comprehensive functional gene array (GeoChip 5.0). The composition and richness of FMFG in the water column was significantly different between these two periods. The FMFG in March was enriched in the functional categories of nitrogen, sulfur, and phosphorus cycling, whereas the FMFG in July was enriched in carbon cycling, organic remediation, and metal homeostasis. Molecular ecological network analysis further demonstrated fewer functional gene interactions and reduced complexity in July than in March. Module hubs of the March network were mediated by functional genes associated with carbon, nitrogen, sulfur, and phosphorus, whereas those in July by a metal homeostasis functional gene. We also observed stronger deterministic processes in the FMFG assembly in July than in March. Collectively, this study demonstrated that Microcystis blooms induced significant changes in FMFG composition and metabolic potential, and abundance-information, which can support the understanding and management of biogeochemical cycling in eutrophic lake ecosystems.

Unveiling the biogeochemical mechanism of nitrate in the vadose zone-groundwater system: Insights from integrated microbiology, isotope techniques, and hydrogeochemistry

Clarifying the biogeochemical mechanism of nitrate (NO3-) in the vadose zone-groundwater system, particularly in agricultural contexts, is crucial for mitigating groundwater NO3- pollution. However, comprehensive studies on the impacts of changes in chemical indicators and microbial communities on NO3- are still lacking. This paper aims to address this gap by employing hydrogeochemistry, stable isotopes, and microbial techniques to assess the NO3- biogeochemical processes in the vadose zone-groundwater system. The findings suggested that NO3- in upper soil layers was primarily influenced by plant root absorption, assimilation, and nitrification processes. The oxygen contents gradually decreased with the nitrification process, resulting in the occurrence of the denitrification. However, denitrification predominantly occurred in the 60-80 cm soil layer in the study area. The limited thickness of the denitrification layer results in less NO3- consumption, leading to increased NO3- leaching into groundwater. Hydrochemical and isotopic characteristics further indicated that groundwater NO3- concentrations were mainly controlled by nitrification, followed by denitrification and mixing processes. The 16S rRNA sequencing analysis revealed great influences of soil sampling depths and groundwater NO3- concentrations on the microbial community structure. Additionally, the PICRUSt2-based prediction results demonstrated a stronger potential for dissimilatory reduction of NO3- to ammonium (DNRA) in both soil and groundwater compared to the other processes, potentially due to the widespread presence of the nrfH functional genes. However, the chemical indicators and isotopes used in this study did not support the occurrence of DNRA process in the vadose zone-groundwater system. This finding highlights the importance of an integrated approach combining microbiological, isotopic, and hydrogeochemical data to comprehensive understanding biogeochemical processes. The study developed a conceptual model elucidating the NO3- biogeochemical processes in the vadose zone-groundwater system within an agricultural area, contributing to enhanced comprehension and advancement of sustainable management practices for groundwater nitrogen.

Effects of a long-term operation wetland for wastewater treatment on the spatial pattern and function of microbial communities in groundwater

Constructed wetlands have been used globally for wastewater treatment owing to low energy inputs and operating costs. However, the impact of their long-term operation on groundwater microbial communities is still unclear. This study aims to investigate the effects and further reveal the linkage between a large-scale surface flow constructed wetland (in operation for 14 years) and groundwater. Changes in the characteristics of groundwater microbial communities and their potential influencing factors were studied based on hydrochemical analysis, Illumina MiSeq sequencing, and multivariate statistical analysis methods. Results show that the long-term operation wetland significantly elevated groundwater nutrient levels and increased the risk of ammonia nitrogen pollution compared to background values. An apparent heterogeneity of microbial communities exhibited in the vertical direction and a similarity in the horizontal direction. Wetland operations substantially altered the structure of microbial communities at 3, 5, and 12 m depths, particularly a reduced abundance of denitrifying and chemoheterotrophic functional genera. The formation and evolution of groundwater microbial community structure mainly subjected to the contributions of dissolved oxygen (33.70%), total nitrogen (21.40%), dissolved organic carbon (11.09%), and pH (10.60%) variations resulted from the wetland operation and largely differed in depths. A combined effect of these factors on the groundwater should be concerned for such a long-term running wetland system. This study provides a new insight into the responses of groundwater microbial community structure driving by wetland operation and a better understanding of corresponding variation of microbial-based geochemical processes.

Response of microbial taxonomic and nitrogen functional attributes to elevated nitrate in suburban groundwater

Anthropogenic nitrogen (N) input has led to elevated levels of nitrate nitrogen (NO₃^--N) in the groundwater. However, insights into the responses of the microbial community and its N metabolic functionality to elevated NO₃^--N in suburban groundwater are still limited. Here, we explored the microbial taxonomy, N metabolic attributes, and their responses to NO₃^--N pollution in groundwaters from Chaobai River catchment (CR) and Huai River catchment (HR) in Beijing, China. Results showed that average NO₃^--N and NH₄⁺-N concentrations in CR groundwater were 1.7 and 3.0 folds of those in HR. NO₃^--N was the dominant nitrogen specie both in HR and CR groundwater (over 80 %). Significantly different structures and compositions of the microbial communities and N cycling gene profiles were found between CR groundwater and HR groundwater (p < 0.05), with CR groundwater harboring significantly lower microbial richness and abundance of N metabolic genes. However, denitrification was the dominant microbial N cycling process in both CR and HR groundwater. Strong associations among NO₃^--N, NH₄⁺-N, microbial taxonomic, and N functional attributes were found (p < 0.05), suggesting denitrifiers and Candidatus_Brocadia might serve as potential featured biomarkers for the elevated NO₃^--N and NH₄⁺-N concentration in groundwater. Path analysis further revealed the significant effect of NO₃^--N on the overall microbial N functionality and microbial denitrification (p < 0.05). Collectively, our results provide field evidence that elevated levels of NO₃^--N and NH₄⁺-N under different hydrogeologic conditions had a significant effect on the microbial taxonomic and N functional attributes in groundwater, with potential implications for improving sustainable N management and risk assessment of groundwater.

Characteristics of groundwater microbial communities' structure under the impact of elevated nitrate concentrations in north China plain

In groundwater environments, the interaction between microbial communities and the hydrogeochemical parameters have been investigated extensively in the past years. However, little is known whether the maximum contamination level (MCL) is a threshold value that dictates the microbial composition. In this study, we analyzed 10 groundwater samples for their nitrate, nitrite, COD and sulfate concentrations, and characterized their microbial compositions using 16 S rRNA based high-throughput sequencing methods. All the 10 samples had oxygen demands higher than the corresponding MCL of China (10 mg L^-1); moreover, 4 out of 10 samples also had nitrate concentrations higher than the corresponding MCL, which indicated that the groundwater quality was negatively impacted by anthropogenic activities. Comparing the microbial composition of groundwater that had higher-than-MCL nitrate concentrations to those that had lower-than-MCL nitrate concentrations, no significant differences were detected in communities' richness and diversity. However, the non-metric multi-dimensional analysis suggested that the 4 groundwater samples whose nitrate concentration exceed MCL are distinctly different from those of the rest 6 samples, indicating that MCL does have a significant impact on microbial structures. Pearson's correlation analysis suggested that none of the four analyzed hydrochemical parameters had significant impact on microbial communities' richness and diversity; however, at the genus level, the correlation results suggested that JG30-KM-CM45, Sphingomonas and Rhodococcus are closely correlated with nitrate concentration. The findings of this study deepened our understanding with respect to the relationships between the environmental quality indices and the microbial compositions of groundwater.

Microbial diversity and geochemistry of groundwater impacted by steel slag leachates

To understand long-term impacts of steel slag material on aquifer geochemistry and microbial communities, we conducted four sampling campaigns in the Gier alluvial groundwater (Loire, France). In its northern part, the aquifer flows under a 200,000 m³ steel slag exhibiting high levels of chromium and molybdenum. Geochemical analyses of the water table revealed the existence of water masses with different chemical signatures. They allowed us to identify an area particularly contaminated by leachates from the slag heap, whatever the sampling period. Water samples from this area were compared to non-contaminated samples, with geochemical characteristics similar to the river samples. To follow changes in microbial communities, the V3-V4 region of 16 s rRNA gene was sequenced. Overall, we observed lower diversity indices in contaminated areas, with higher relative abundances of Verrucomicrobiota and Myxococcota phyla, while several Proteobacteria orders exhibited lower relative abundances. In particular, one single genus among the Verrucomicrobiota, Candidatus Omnitrophus, represented up to 36 % of total taxon abundance in areas affected by steel slag leachates. A large proportion of taxa identified in groundwater were also detected in the upstream river, indicating strong river-groundwater interactions. Our findings pave the way for future research work on C. Omnitrophus remediation capacities.

Marine Bacteria and Omic Approaches: A Novel and Potential Repository for Bioremediation Assessment

Marine environments accommodating diverse assortments of life constitute a great pool of differentiated natural resources. The cumulative need to remedy unpropitious effects of anthropogenic activities on estuaries, and coastal marine ecosystems has propelled the development of effective bioremediation strategies. Marine bacteria producing biosurfactants are promising agents for bio-remediating oil pollution in marine environments, making them prospective candidates for enhancing oil recovery. Molecular omics technologies are considered an emerging field of research in ecological and diversity assessment owing to their utility in environmental surveillance and bioremediation of polluted sites. A thorough literature review was undertaken to understand the applicability of different omic techniques employed for bioremediation assessment using marine bacteria. This review further establishes that for bioremediation of environmental pollutants (i.e., heavy metals, hydrocarbons, xenobiotic and numerous recalcitrant compounds), organisms isolated from marine environments can be better utilized for their removal. The literature survey shows that omics approaches can provide exemplary knowledge about microbial communities and their role in the bioremediation of environmental pollutants. This review centres on applications of marine bacteria in enhanced bioremediation, utilizing the omics approaches that can be a vital biological contrivance in environmental monitoring to tackle environmental degradation. The paper aims to identify the gaps in investigations involving marine bacteria to help researchers, ecologists, and decision-makers to develop a holistic understanding regarding their utility in bioremediation assessment.

Selective pressure on microbial communities in a drinking water aquifer - Geochemical parameters vs. micropollutants

Groundwater quality is crucial for drinking water production, but groundwater resources are increasingly threatened by contamination with pesticides. As pesticides often occur at micropollutant concentrations, they are unattractive carbon sources for microorganisms and typically remain recalcitrant. Exploring microbial communities in aquifers used for drinking water production is an essential first step towards understanding the fate of micropollutants in groundwater. In this study, we investigated the interaction between groundwater geochemistry, pesticide presence, and microbial communities in an aquifer used for drinking water production. Two groundwater monitoring wells in The Netherlands were sampled in 2014, 2015, and 2016. In both wells, water was sampled from five discrete depths ranging from 13 to 54 m and was analyzed for geochemical parameters, pesticide concentrations and microbial community composition using 16S rRNA gene sequencing and qPCR. Groundwater geochemistry was stable throughout the study period and pesticides were heterogeneously distributed at low concentrations (μg L^-1 range). Microbial community composition was also stable throughout the sampling period. Integration of a unique dataset of chemical and microbial data showed that geochemical parameters and to a lesser extent pesticides exerted selective pressure on microbial communities. Microbial communities in both wells showed similar composition in the deeper aquifer, where pumping results in horizontal flow. This study provides insight into groundwater parameters that shape microbial community composition. This information can contribute to the future implementation of remediation technologies to guarantee safe drinking water production.

Enzymatic biodegradation of highly p-xylene contaminated soil using cold-active enzymes: A soil column study

Enzymatic bioremediation is a sustainable and environment-friendly method for the clean-up of contaminated soil and water. In the present study, enzymatic bioremediation was designed using cold-active enzymes (psychrozymes) which catalyze oxidation steps of p-xylene biodegradation in highly contaminated soil (initial concentration of 13,000 mg/kg). The enzymes were obtained via co-culture of two psychrophilic Pseudomonas strains and characterized by kinetic studies and tandem LC-MS/MS. To mimic in situ application of enzyme mixture, bioremediation of p-xylene contaminated soil was carried out in soil column (140 mL) tests with the injection (3 pore volume) of different concentrations of enzyme cocktails (X, X/5, and X/10). Enzyme cocktail in X concentration contained about 10 U/mL of xylene monooxygenase (XMO) and 20 U/mL of catechol 2, 3 dioxygenases (C2,3D). X/5 and X/10 correspond to 5x and 10x dilution of enzyme cocktail respectively. The results showed that around 92-94% p-xylene removal was achieved in the treated soil column with enzyme concentration X, X/5 after second enzyme injection. While the p-xylene removal rate obtained by X/10 concentration of enzyme was less than 30% and near to untreated soil column (22.2%). The analysis of microbial diversity and biotoxicity assay (root elongation and seed germination) confirmed the advantage of using enzymes as a green and environmentally friendly approach for decontamination of pollutants with minimal or even positive effects on microbial community and also enrichment of soil after treatment.

Saline mine-water alters the structure and function of prokaryote communities in shallow groundwater below a tropical stream

Bacteria and archaea (prokaryotes) are vital components for maintaining healthy function of groundwater ecosystems. The prokaryotic community composition and associated putative functional processes were examined in a shallow sandy aquifer in a wet-dry tropical environment. The aquifer had a contaminated gradient of saline mine-water, which primarily consisted of elevated magnesium (Mg²⁺) and sulfate (SO₄^2-), although other major ions and trace metals were also present. Groundwaters were sampled from piezometers, approximately 2 m in depth, located in the creek channel upstream and downstream of the mine-water influence. Sampling occurred during the dry-season when only subsurface water flow was present. Next generation sequencing was used to analyse the prokaryote assemblages using 16S rDNA and metabolic functions were predicted with FAPROTAX. Significant changes in community composition and functional processes were observed with exposure to mine-waters. Communities in the exposed sites had significantly lower relative abundance of methanotrophs such as Methylococcaceae and methanogens (Methanobacteriaceae), but higher abundance in Nitrososphaeraceae, associated with nitrification, indicating potentially important changes in the biogeochemistry of the exposed sites. The changes were most strongly correlated with concentrations of SO₄^2-, Mg²⁺ and Na⁺. This knowledge allows an assessment of the risk of mine-water contamination to groundwater ecosystem function and aids mine-water management.

Differential structure and functional gene response to geochemistry associated with the suspended and attached shallow aquifer microbiomes from the Illinois Basin, IL

Despite the clear ecological significance of the microbiomes inhabiting groundwater and connected ecosystems, our current understanding of their habitats, functionality, and the ecological processes controlling their assembly have been limited. In this study, an efficient pipeline combining geochemistry, high-throughput Fluidigm^TM functional gene amplification and sequencing was developed to analyze the suspended and attached microbial communities inhabiting five groundwater monitoring wells in the Illinois Basin, USA. The dominant taxa in the suspended and the attached microbial communities exhibited significantly different spatial and temporal changes in both alpha- and beta-diversity. Further analyses of representative functional genes affiliated with N₂ fixation (nifH), methane oxidation (pmoA), and sulfate reduction (dsrB, and aprA), suggested functional redundancy within the shallow aquifer microbiomes. While more diversified functional gene taxa were observed for the suspended microbial communities than the attached ones except for pmoA, different levels of changes over time and space were observed between these functional genes. Notably, deterministic and stochastic ecological processes shaped the assembly of microbial communities and functional gene reservoirs differently. While homogenous selection was the prevailing process controlling assembly of microbial communities, the neutral processes (e.g., dispersal limitation, drift and others) were more important for the functional genes. The results suggest complex and changing shallow aquifer microbiomes, whose functionality and assembly vary even between the spatially proximate habitats and fractions. This research underscored the importance to include all the interface components for a more holistic understanding of the biogeochemical processes in aquifer ecosystems, which is also instructive for practical applications.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

Disentangling Responses of the Subsurface Microbiome to Wetland Status and Implications for Indicating Ecosystem Functions

In this study, we analyzed microbial community composition and the functional capacities of degraded sites and restored/natural sites in two typical wetlands of Northeast China-the Phragmites marsh and the Carex marsh, respectively. The degradation of these wetlands, caused by grazing or land drainage for irrigation, alters microbial community components and functional structures, in addition to changing the aboveground vegetation and soil geochemical properties. Bacterial and fungal diversity at the degraded sites were significantly lower than those at restored/natural sites, indicating that soil microbial groups were sensitive to disturbances in wetland ecosystems. Further, a combined analysis using high-throughput sequencing and GeoChip arrays showed that the abundance of carbon fixation and degradation, and ~95% genes involved in nitrogen cycling were increased in abundance at grazed Phragmites sites, likely due to the stimulating impact of urine and dung deposition. In contrast, the abundance of genes involved in methane cycling was significantly increased in restored wetlands. Particularly, we found that microbial composition and activity gradually shifts according to the hierarchical marsh sites. Altogether, this study demonstrated that microbial communities as a whole could respond to wetland changes and revealed the functional potential of microbes in regulating biogeochemical cycles.

Testing Different Membrane Filters for 16S rRNA Gene-Based Metabarcoding in Karstic Springs

Introduction: Karstic springs are used worldwide by rural communities as sources of fresh water for humans and livestock. In Romania, one-third of the population has no direct access to a public water supply. The present study is part of a country-wide project to develop simple, quick and cheap methods for seasonal environmental and microbiological monitoring of karstic springs used as drinking water by rural populations. Critical steps for monitoring workflow consist of evaluating water quality and selecting suitable membrane filters to efficiently capture environmental DNA for further microbial diversity estimation using 16S rRNA gene-based metabarcoding. Methods: Several commercial membrane filters of different compositions and pore sizes were tested on the water sampled from three karstic springs in Romania, followed by water chemistry and whole community 16S rRNA gene-based metabarcoding analysis. Results: We found that different types of applied membrane filters provide varying recovery in diversity and abundance of both overall and pathogenic bacteria. Conclusions: The result of the experiment with different filters shows that mixed cellulose ester, cellulose acetate, and nitrate membranes of 0.20 and 0.22 µm are the best for amplicon-based metabarcoding monitoring of karst springs.

Microbial functional genes commonly respond to elevated carbon dioxide

Atmospheric CO₂ concentration is increasing, largely due to anthropogenic activities. Previous studies of individual free-air CO₂ enrichment (FACE) experimental sites have shown significant impacts of elevated CO₂ (eCO₂) on soil microbial communities; however, no common microbial response patterns have yet emerged, challenging our ability to predict ecosystem functioning and sustainability in the future eCO₂ environment. Here we analyzed 66 soil microbial communities from five FACE sites, and showed common microbial response patterns to eCO₂, especially for key functional genes involved in carbon and nitrogen fixation (e.g., pcc/acc for carbon fixation, nifH for nitrogen fixation), carbon decomposition (e.g., amyA and pulA for labile carbon decomposition, mnp and lcc for recalcitrant carbon decomposition), and greenhouse gas emissions (e.g., mcrA for methane production, norB for nitrous oxide production) across five FACE sites. Also, the relative abundance of those key genes was generally increased and directionally associated with increased biomass, soil carbon decomposition, and soil moisture. In addition, a further literature survey of more disparate FACE experimental sites indicated increased biomass, soil carbon decay, nitrogen fixation, methane and nitrous oxide emissions, plant and soil carbon and nitrogen under eCO₂. A conceptual framework was developed to link commonly responsive functional genes with ecosystem processes, such as pcc/acc vs. soil carbon storage, amyA/pulA/mnp/lcc vs. soil carbon decomposition, and nifH vs. nitrogen availability, suggesting that such common responses of microbial functional genes may have the potential to predict ecosystem functioning and sustainability in the future eCO₂ environment.

In-field bioreactors demonstrate dynamic shifts in microbial communities in response to geochemical perturbations

Subsurface microbial communities mediate the transformation and fate of redox sensitive materials including organic matter, metals and radionuclides. Few studies have explored how changing geochemical conditions influence the composition of groundwater microbial communities over time. We temporally monitored alterations in abiotic forces on microbial community structure using 1L in-field bioreactors receiving background and contaminated groundwater at the Oak Ridge Reservation, TN. Planktonic and biofilm microbial communities were initialized with background water for 4 days to establish communities in triplicate control reactors and triplicate test reactors and then fed filtered water for 14 days. On day 18, three reactors were switched to receive filtered groundwater from a contaminated well, enriched in total dissolved solids relative to the background site, particularly chloride, nitrate, uranium, and sulfate. Biological and geochemical data were collected throughout the experiment, including planktonic and biofilm DNA for 16S rRNA amplicon sequencing, cell counts, total protein, anions, cations, trace metals, organic acids, bicarbonate, pH, Eh, DO, and conductivity. We observed significant shifts in both planktonic and biofilm microbial communities receiving contaminated water. This included a loss of rare taxa, especially amongst members of the Bacteroidetes, Acidobacteria, Chloroflexi, and Betaproteobacteria, but enrichment in the Fe- and nitrate- reducing Ferribacterium and parasitic Bdellovibrio. These shifted communities were more similar to the contaminated well community, suggesting that geochemical forces substantially influence microbial community diversity and structure. These influences can only be captured through such comprehensive temporal studies, which also enable more robust and accurate predictive models to be developed.

Keystone taxa of water microbiome respond to environmental quality and predict water contamination

The human activity introduces strong environmental stresses, and results in great spatiotemporal heterogeneity for the environment. Although the effects of environmental factors on the microbial diversity and succession have been widely studied, knowledge about how keystone taxa respond to environmental stresses remains poorly understood. We examined bacterial and archaeal communities from 45 wetland ponds covering a wide range of waters in Hangzhou. We found that shifts in bacterial and archaeal communities were strongly correlated with water pollution as indicated by the comprehensive water quality identification (CWQI). The SEGMENTED analysis suggested that there were non-linear responses of microbial communities and keystone taxa to the water pollution gradient. Moreover, these significant tipping points (e.g., CWQI > 4.0) would afford a warning line for urban wetland management. Notably, keystone taxa of bacterial communities could be used to successfully (~88.9% accuracy) predict water contamination levels. This study provides new insights into the potential for keystone bacterial taxa to predict water contamination.

Functional potential and assembly of microbes from sediments in a lake bay and adjoining river ecosystem for polycyclic aromatic hydrocarbon biodegradation

Lake and adjoining river ecosystems are ecologically and economically valuable and are heavily threatened by anthropogenic activities. Determining the inherent capacity of ecosystems for polycyclic aromatic hydrocarbon (PAH) biodegradation can help quantify environmental impacts on the functioning of ecosystems, especially on that of the microbial community. Here, PAH biodegradation potential was compared between sediments collected from a lake bay (LS) and an adjoining river (RS) ecosystem. Microbial community composition, function, and their co-occurrence patterns were also explored. In the RS, the biodegradation rates (K_D ) of pyrene or PAH were almost two orders of magnitude higher than those in the LS. Sediment functional community structure and network interactions were dramatically different between the LS and RS. Although PAH degradation genes (p450aro, quinoline, and qorl) were detected in the LS, the community activity of these genes needed to be biostimulated for accelerated bioremediation. In contrast, functional communities in the RS were capable of spontaneous natural attenuation of PAH. The degradation of PAH in the RS also required coordinated response of the complex functional community. Taken together, elucidating functions and network interactions in sediment microbial communities and their responses to environmental changes are very important for the bioremediation of anthropogenic toxic contaminants.

Microbial characteristic and bacterial community assessment of sediment sludge upon uranium exposure

The microbial characteristics and bacterial communities of sediment sludge upon different concentrations of exposure to uranium were investigated by high solution transmission electron microscopy (HRTEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and high-throughput sequencing. After exposure to initial uranium concentrations of 10-50 μM for 24 h in synthetic wastewater, the removal efficiencies of uranium reached 80.7%-96.5%. The spherical and short rod bacteria were dominant in the sludge exposed to uranium. HRTEM-EDS and XPS analyses indicated that reduction and adsorption were the main mechanisms for uranium removal. Short-term exposure to low concentrations of uranium resulted in a decrease in bacterial richness but an increase in diversity. A dramatic change in the composition and abundances of the bacterial community were present in the sediment sludge exposed to uranium. The highest removal efficiency was identified in the sediment sludge exposed to 30 μM uranium, and the dominant bacteria included Acinetobacter (44.9%), Klebsiella (20.0%), Proteiniclasticum (6.7%), Enterobacteriaceae (6.6%), Desulfovibrio (4.4%), Porphyromonadaceae (4.1%), Comamonas (2.4%) and Sedimentibacter (2.3%). By comparison to the inoculum sediment sludge, exposure to uranium caused a substantial difference in the majority of bacterial abundance.

Evaluation of gaseous substrates for microbial immobilization of contaminant mixtures in unsaturated subsurface sediments

Extensive vadose zone metals and organic contamination remains at many former industrial and defense manufacturing sites, and effective remedial solutions are needed to slow or prevent its migration to groundwater. In this study, the application of gaseous substrates to stimulate microbial respiratory reduction of comingled radioisotopes and nitrate under unsaturated conditions was examined for possible application at the Hanford Site, a former nuclear production facility in southeastern WA, USA. First, screening studies were performed to qualitatively measure the sediment respiratory response to 14 gaseous or volatile organic substrates at two moisture contents, 4% and 8%. Volatile substrates produced the strongest respiratory response, among them were butyrate, pentane, butyl acetate. Ethane and butane were the most effective gaseous substrates but only at 8% water content. Hanford sediment from two waste sites with distinctive chemistries were wetted to 7% moisture content, packed into columns, and treated with ethane or butane. After 4 weeks, columns were then leached to quantify retardation in the mobility of aqueous contaminant concentrations compared to no gas control columns. Treatment with both gases resulted in >80% removal of Cr from the aqueous phase. However, NO₃ concentration and a waste sites exposure history to NO₃ had a major effect on U and Tc reduction. Incomplete nitrate reduction outcompeted U and Tc in waste site sediments having limited prior exposure to NO₃. Conversely, waste site sediments co-contaminated with NO₃ were able to achieve highly reduced conditions resulting in complete denitrification of NO₃, and delayed leaching of U and Tc. This implied effective reduction of both contaminants to less mobile species. This study demonstrates that unsaturated vadose sediments at Hanford waste sites have the capacity for a sustained respiratory response to gaseous substrate injection, which could potentially be deployed as part of an overall strategy to reduce the flux of long-lived radionuclides to groundwater at Hanford and other legacy waste sites.

Environmental antibiotics drives the genetic functions of resistome dynamics

The increasing prevalence of antibiotic-resistant microorganisms imposes a global threat to public health. The over reliant use of antibiotics in the food industry has contributed considerably to the dissemination of antibiotics into various environments, yet the mechanisms by which antibiotic dissemination influences the assembly of the microbial community continues to remain obscure. Here, we examine bacterial and fungal community assemblies in swine manure, compost, compost amended, and unamended agricultural soil in five suburban areas of Beijing, China. Total antibiotic concentration decreased by factors of 10-1000 from manure and compost to soils. The bacterial α-diversity was found to be low in manure and compost samples, while the fungal α-diversity was similar across all samples. We detected significantly (p < 0.05) higher relative abundances of well recognized pathogenic microbial taxa, virulence associated genes, and antibiotic resistance genes (ARGs) in manure and compost than those in agricultural soils, revealing the higher microbial capacity of pathogenicity, virulence and antibiotic resistance. Unexpectedly, the relative abundances of both bacterial and fungal taxa did not predict the antibiotic concentration. A possible explanation was that bacterial and fungal communities were mainly shaped by random assemblies. Rather, antibiotic concentration could be well predicted by relative abundances of antibiotic resistance, stress and virulence associated genes. Despite the weak interconnection between ARGs and the microbiome, we demonstrate that microbial genes should be the focal point in tracking the ecological effects of antibiotic dissemination by revealing microbial community patterns along the dissemination chain of antibiotics.

An artificial neural network and Random Forest identify glyphosate-impacted brackish communities based on 16S rRNA amplicon MiSeq read counts

Machine learning algorithms can be trained on complex data sets to detect, predict, or model specific aspects. Aim of this study was to train an artificial neural network in comparison to a Random Forest model to detect induced changes in microbial communities, in order to support environmental monitoring efforts of contamination events. Models were trained on taxon count tables obtained via next-generation amplicon sequencing of water column samples originating from a lab microcosm incubation experiment conducted over 140 days to determine the effects of glyphosate on succession within brackish-water microbial communities. Glyphosate-treated assemblages were classified correctly; a subsetting approach identified the taxa primarily responsible for this, permitting the reduction of input features. This study demonstrates the potential of artificial neural networks to predict indicator species for glyphosate contamination. The results could empower the development of environmental monitoring strategies with applications limited to neither glyphosate nor amplicon sequence data.

The Spatial Distribution of the Microbial Community in a Contaminated Aquitard below an Industrial Zone

The industrial complex Neot Hovav, in Israel, is situated above an anaerobic fractured chalk aquitard, which is polluted by a wide variety of hazardous organic compounds. These include volatile and non-volatile, halogenated, organic compounds. In this study, we characterized the indigenous bacterial population in 17 boreholes of the groundwater environment, while observing the spatial variations in the population and structure as a function of distance from the polluting source. In addition, the de-halogenating potential of the microbial groundwater population was tested through a series of lab microcosm experiments, thus exemplifying the potential and limitations for bioremediation of the site. In all samples, the dominant phylum was Proteobacteria. In the production plant area, the non-obligatory organo-halide respiring bacteria (OHRB) Firmicutes Phylum was also detected in the polluted water, in abundancies of up to 16 %. Non-metric multidimensional scaling (NMDS) analysis of the microbial community structure in the groundwater exhibited clusters of distinct populations following the location in the industrial complex and distance from the polluting source. Dehalogenation of halogenated ethylene was demonstrated in contrast to the persistence of brominated alcohols. Persistence is likely due to the chemical characteristics of brominated alcohols, and not because of the absence of active de-halogenating bacteria.

A general framework for quantitatively assessing ecological stochasticity

Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. Here we propose a general mathematical framework to quantify ecological stochasticity under different situations in which deterministic factors drive the communities more similar or dissimilar than null expectation. An index, normalized stochasticity ratio (NST), was developed with 50% as the boundary point between more deterministic (<50%) and more stochastic (>50%) assembly. NST was tested with simulated communities by considering abiotic filtering, competition, environmental noise, and spatial scales. All tested approaches showed limited performance at large spatial scales or under very high environmental noise. However, in all of the other simulated scenarios, NST showed high accuracy (0.90 to 1.00) and precision (0.91 to 0.99), with averages of 0.37 higher accuracy (0.1 to 0.7) and 0.33 higher precision (0.0 to 1.8) than previous approaches. NST was also applied to estimate stochasticity in the succession of a groundwater microbial community in response to organic carbon (vegetable oil) injection. Our results showed that community assembly was shifted from more deterministic (NST = 21%) to more stochastic (NST = 70%) right after organic carbon input. As the vegetable oil was consumed, the community gradually returned to be more deterministic (NST = 27%). In addition, our results demonstrated that null model algorithms and community similarity metrics had strong effects on quantifying ecological stochasticity.

Functional Gene Array-Based Ultrasensitive and Quantitative Detection of Microbial Populations in Complex Communities

The rapid development of metagenomic technologies, including microarrays, over the past decade has greatly expanded our understanding of complex microbial systems. However, because of the ever-expanding number of novel microbial sequences discovered each year, developing a microarray that is representative of real microbial communities, is specific and sensitive, and provides quantitative information remains a challenge. The newly developed GeoChip 5.0 is the most comprehensive microarray available to date for examining the functional capabilities of microbial communities important to biogeochemistry, ecology, environmental sciences, and human health. The GeoChip 5 is highly specific, sensitive, and quantitative based on both computational and experimental assays. Use of the array on a contaminated groundwater sample provided novel insights on the impacts of environmental contaminants on groundwater microbial communities.

While functional gene arrays (FGAs) have greatly expanded our understanding of complex microbial systems, specificity, sensitivity, and quantitation challenges remain. We developed a new generation of FGA, GeoChip 5.0, using the Agilent platform. Two formats were created, a smaller format (GeoChip 5.0S), primarily covering carbon-, nitrogen-, sulfur-, and phosphorus-cycling genes and others providing ecological services, and a larger format (GeoChip 5.0M) containing the functional categories involved in biogeochemical cycling of C, N, S, and P and various metals, stress response, microbial defense, electron transport, plant growth promotion, virulence, gyrB, and fungus-, protozoan-, and virus-specific genes. GeoChip 5.0M contains 161,961 oligonucleotide probes covering >365,000 genes of 1,447 gene families from broad, functionally divergent taxonomic groups, including bacteria (2,721 genera), archaea (101 genera), fungi (297 genera), protists (219 genera), and viruses (167 genera), mainly phages. Computational and experimental evaluation indicated that designed probes were highly specific and could detect as little as 0.05 ng of pure culture DNAs within a background of 1 μg community DNA (equivalent to 0.005% of the population). Additionally, strong quantitative linear relationships were observed between signal intensity and amount of pure genomic (∼99% of probes detected; r > 0.9) or soil (∼97%; r > 0.9) DNAs. Application of the GeoChip to a contaminated groundwater microbial community indicated that environmental contaminants (primarily heavy metals) had significant impacts on the biodiversity of the communities. This is the most comprehensive FGA to date, capable of directly linking microbial genes/populations to ecosystem functions.

IMPORTANCE The rapid development of metagenomic technologies, including microarrays, over the past decade has greatly expanded our understanding of complex microbial systems. However, because of the ever-expanding number of novel microbial sequences discovered each year, developing a microarray that is representative of real microbial communities, is specific and sensitive, and provides quantitative information remains a challenge. The newly developed GeoChip 5.0 is the most comprehensive microarray available to date for examining the functional capabilities of microbial communities important to biogeochemistry, ecology, environmental sciences, and human health. The GeoChip 5 is highly specific, sensitive, and quantitative based on both computational and experimental assays. Use of the array on a contaminated groundwater sample provided novel insights on the impacts of environmental contaminants on groundwater microbial communities.

Bioremediation of benzene-contaminated groundwater by calcium peroxide (CaO2) nanoparticles: Continuous-flow and biodiversity studies

Calcium peroxide (CaO₂) nanoparticles have been extensively applied in treatment of contaminated groundwater through bioremediation or modified Fenton (MF) processes. In the present study utilization of CaO₂ in bioremediation and MF (CaO₂+FeSO₄) reaction is investigated for benzene (50 mg/L) removal in continuous flow sand-packed columns. The results indicated that MF produced OH radicals markedly increased benzene remediation at first 30 days (up to 93%). But, OH generation rate was gradually declined when the pH was increased and finally 75% of initial benzene removed after 100d. In bioremediation column, because of supplying adequate oxygen by CaO₂, the number of planktonic bacteria logarithmically increased to more than 5 × 10⁶ CFU/mL (two orders of magnitude) and consequently 100% benzene removal was achieved by the end of experiment. Scanning electron microscopy analysis visualized the attached biofilm growth on sand surfaces in CaO₂ injected columns indicating their key role in the remediation process. The impact of each process on the microbial biodiversity of groundwater was investigated by next generation sequencing (NGS) of the 16S rRNA gene. The alpha and beta analysis indicated that microbial diversity is decreased by CaO₂ injection while benzene-degrading species such as Silanimonas, Arthrobacter and Pseudomonas spp. were dominated in remediation column.

The Characterization of Microbial Communities Response to Shallow Groundwater Contamination in Typical Piedmont Region of Taihang Mountains in the North China Plain

Regional-scale nitrate and organic contaminants in the shallow groundwater were investigated in the Piedmont region of Taihang Mountains (PRTM), but the information of the microbial communities is limited. However, microorganisms provide a dominated contribution to indicate and degrade the contaminants in the aquifer. Therefore, this study investigates the microbial diversity and contamination microbial indicators of groundwater samples with different contaminated types to better understand the contamination in the PRTM. Seventy-six samples were collected between two rivers in the Tang-Dasha River Basin covering 4000 km2 in the PRTM. High-throughput sequencing was employed to determine the samples’ DNA sequences. The samples were divided into four groups: background (B), nitrate contamination (N), organic contamination (O) and organic-nitrate contamination (O_N) based on the cumulative probability distribution and the Chinese groundwater standard levels of NO3−, COD and DO concentrations. Then, the microbial diversity and contamination microbial indicators were studied in the four groups. The results showed that the O group exhibited lower diversity than other groups. Bacteria detected in these four groups covered 531 families, 987 genera, and 1881 species. Taxonomic assignment analysis indicated that Rhodobacter, Vogesella, Sphingobium dominated in the O_N group, N group, and O group, and accounted for 18.05%, 17.74%, 16.45% in each group at genus level, respectively. Furthermore, these three genera were identified as contamination microbial indicators to the three types of contamination, respectively. The results provide a potential molecular microbiological method to identity contamination in shallow groundwater, and established a strong foundation for further investigation and remediation in the PRTM.

Seasonal microbial variation accounts for arsenic dynamics in shallow alluvial aquifer systems

Determining the temporal variation of microbial communities in groundwater systems is essential to improve our understanding of hydrochemical dynamics in aquifers, particularly as it relates to the fate of redox-sensitive contaminants like arsenic (As). Therefore, a high-resolution hydrobiogeochemical investigation was conducted in the As-affected alluvial aquifer systems of the Jianghan Plain. In two 25 m-deep monitoring wells, the seasonal variation in the composition of groundwater microbial communities was positively correlated with the change in groundwater level (R = 0.47 and 0.39 in NH03B and NH05B, respectively, P <  0.01), implying that the latter could be a primary driver of the seasonal microbial dynamics. In response to the fluctuating groundwater level, iron (Fe) reducers within the Desulfuromonadales were dominant (9.9 ± 4.7% among different sampling sites) in groundwater microbial communities during the monsoon season and associated with high concentrations of Fe(II) and As, while the predominance (16.7 ± 15.2% among different sampling sites) of iron-oxidizers the Gallionellaceae was accompanied by low Fe(II) and As in the non-monsoon season. These results suggest that microbially-mediated iron reduction/oxidation may have governed the seasonal mobilization/scavenging of As in groundwater. Our results provide new insights into mechanisms responsible for seasonal variations in groundwater As concentrations in similar aquifer systems.

Large Circular Plasmids from Groundwater Plasmidomes Span Multiple Incompatibility Groups and Are Enriched in Multimetal Resistance Genes

Naturally occurring plasmids constitute a major category of mobile genetic elements responsible for harboring and transferring genes important in survival and fitness. A targeted evaluation of plasmidomes can reveal unique adaptations required by microbial communities. We developed a model system to optimize plasmid DNA isolation procedures targeted to groundwater samples which are typically characterized by low cell density (and likely variations in the plasmid size and copy numbers). The optimized method resulted in successful identification of several hundred circular plasmids, including some large plasmids (11 plasmids more than 50 kb in size, with the largest being 1.7 Mb in size). Several interesting observations were made from the analysis of plasmid DNA isolated in this study. The plasmid pool (plasmidome) was more conserved than the corresponding microbiome distribution (16S rRNA based). The circular plasmids were diverse as represented by the presence of seven plasmid incompatibility groups. The genes carried on these groundwater plasmids were highly enriched in metal resistance. Results from this study confirmed that traits such as metal, antibiotic, and phage resistance along with toxin-antitoxin systems are encoded on abundant circular plasmids, all of which could confer novel and advantageous traits to their hosts. This study confirms the ecological role of the plasmidome in maintaining the latent capacity of a microbiome, enabling rapid adaptation to environmental stresses.IMPORTANCE Plasmidomes have been typically studied in environments abundant in bacteria, and this is the first study to explore plasmids from an environment characterized by low cell density. We specifically target groundwater, a significant source of water for human/agriculture use. We used samples from a well-studied site and identified hundreds of circular plasmids, including one of the largest sizes reported in plasmidome studies. The striking similarity of the plasmid-borne ORFs in terms of taxonomical and functional classifications across several samples suggests a conserved plasmid pool, in contrast to the observed variability in the 16S rRNA-based microbiome distribution. Additionally, the stress response to environmental factors has stronger conservation via plasmid-borne genes as marked by abundance of metal resistance genes. Last, identification of novel and diverse plasmids enriches the existing plasmid database(s) and serves as a paradigm to increase the repertoire of biological parts that are available for modifying novel environmental strains.

Analysis of uranium removal capacity of anaerobic granular sludge bacterial communities under different initial pH conditions

The bacterial community of an anaerobic granular sludge associated with uranium depletion was investigated following its exposure to uranium under different initial pH conditions (pH 4.5, 5.5, and 6.5). The highest uranium removal efficiency (98.1%) was obtained for the sample with an initial pH of 6.5, which also supported the highest bacterial community richness and diversity. Venn diagrams visualized the decrease in the number of genera present in both the inoculum and the uranium-exposed biomass as the initial pH decreased from 6.5 to 4.5. Compared with the inoculum, a significant increase in the abundances of the phyla Chloroflexi and Proteobacteria was observed following uranium exposure. At initial pH conditions of 6.5 to 4.5, the proportions of the taxa Anaerolineaceae, Chryseobacterium, Acinetobacter, Pseudomonas, and Sulfurovum increased significantly, likely contributing to the observed uranium removal. Uranium exposure induced a greater level of dynamic diversification of bacterial abundances than did the initial pH difference.

Presence of organohalide-respiring bacteria in and around a permeable reactive barrier at a trichloroethylene-contaminated Superfund site

Trichloroethylene (TCE) is one of the most common groundwater contaminants in the United States; however clean-up efforts are a challenge due to its physical and chemical properties. TCE and several of its degradation products were detected in the groundwater of the Beaver Dam Road Landfill site (Beltsville, MD) at concentrations above accepted maximum contaminant levels. A permeable reactive barrier (i.e., biowall) was installed to remediate the groundwater. Microbial infiltration and colonization of the biowall with native site bacteria was expected to occur. An array of molecular biological tools was applied to survey the microbial community for presence of organohalide-respiring microorganisms at the site. Microorganisms belonging to methanogens, acetogens, sulfate-reducing bacteria, and chlorinated aliphatic hydrocarbon-metabolizing bacteria were identified, thus making way for the application of the microbial populations in the biowall bioaugmentation efforts. In concomitant laboratory studies, molecular approaches were used to monitor continuously-fed column reactors containing saturated biowall material spiked with a commercially-available, Dehalococcoides-containing culture (SDC-9), with or without zero-valent iron (ZVI) shavings. The column without ZVI had the highest abundance of Dehalococcoides spp. (2.7 × 10⁶ cells g^-1 material, S.D. = 3.8 × 10⁵ cells g^-1 material), while the addition of ZVI did not affect the overall population. Although the addition of ZVI and biostimulation did change ratios of the Dehalococcoides strains, the results suggests that if ZVI would be applied as a biowall material amendment, biostimulation would not be required to maintain a Dehalococcoides population. These experimental results will be utilized in future remediation and/or biowall expansion plans to utilize the natural resources most effectively at the biowall site.

Impact of hydrologic boundaries on microbial planktonic and biofilm communities in shallow terrestrial subsurface environments

Subsurface environments contain a large proportion of planetary microbial biomass and harbor diverse communities responsible for mediating biogeochemical cycles important to groundwater used by human society for consumption, irrigation, agriculture and industry. Within the saturated zone, capillary fringe and vadose zones, microorganisms can reside in two distinct phases (planktonic or biofilm), and significant differences in community composition, structure and activity between free-living and attached communities are commonly accepted. However, largely due to sampling constraints and the challenges of working with solid substrata, the contribution of each phase to subsurface processes is largely unresolved. Here, we synthesize current information on the diversity and activity of shallow freshwater subsurface habitats, discuss the challenges associated with sampling planktonic and biofilm communities across spatial, temporal and geological gradients, and discuss how biofilms may be constrained within shallow terrestrial subsurface aquifers. We suggest that merging traditional activity measurements and sequencing/-omics technologies with hydrological parameters important to sediment biofilm assembly and stability will help delineate key system parameters. Ultimately, integration will enhance our understanding of shallow subsurface ecophysiology in terms of bulk-flow through porous media and distinguish the respective activities of sessile microbial communities from more transient planktonic communities to ecosystem service and maintenance.

Predicting bacterial growth conditions from mRNA and protein abundances

Cells respond to changing nutrient availability and external stresses by altering the expression of individual genes. Condition-specific gene expression patterns may thus provide a promising and low-cost route to quantifying the presence of various small molecules, toxins, or species-interactions in natural environments. However, whether gene expression signatures alone can predict individual environmental growth conditions remains an open question. Here, we used machine learning to predict 16 closely-related growth conditions using 155 datasets of E. coli transcript and protein abundances. We show that models are able to discriminate between different environmental features with a relatively high degree of accuracy. We observed a small but significant increase in model accuracy by combining transcriptome and proteome-level data, and we show that measurements from stationary phase cells typically provide less useful information for discriminating between conditions as compared to exponentially growing populations. Nevertheless, with sufficient training data, gene expression measurements from a single species are capable of distinguishing between environmental conditions that are separated by a single environmental variable.

Responses exhibited by various microbial groups relevant to uranium exposure

There is a strong interest in knowing how various microbial systems respond to the presence of uranium (U), largely in the context of bioremediation. There is no known biological role for uranium so far. Uranium is naturally present in rocks and minerals. The insoluble nature of the U(IV) minerals keeps uranium firmly bound in the earth's crust minimizing its bioavailability. However, anthropogenic nuclear reaction processes over the last few decades have resulted in introduction of uranium into the environment in soluble and toxic forms. Microbes adsorb, accumulate, reduce, oxidize, possibly respire, mineralize and precipitate uranium. This review focuses on the microbial responses to uranium exposure which allows the alteration of the forms and concentrations of uranium within the cell and in the local environment. Detailed information on the three major bioprocesses namely, biosorption, bioprecipitation and bioreduction exhibited by the microbes belonging to various groups and subgroups of bacteria, fungi and algae is provided in this review elucidating their intrinsic and engineered abilities for uranium removal. The survey also highlights the instances of the field trials undertaken for in situ uranium bioremediation. Advances in genomics and proteomics approaches providing the information on the regulatory and physiologically important determinants in the microbes in response to uranium challenge have been catalogued here. Recent developments in metagenomics and metaproteomics indicating the ecologically relevant traits required for the adaptation and survival of environmental microbes residing in uranium contaminated sites are also included. A comprehensive understanding of the microbial responses to uranium can facilitate the development of in situ U bioremediation strategies.