EcoGenoRisk: Developing a computational ecological risk assessment tool for synthetic biology.

The expanding field of synthetic biology (synbio) supports new opportunities in the design of targeted bioproducts or modified microorganisms. However, this rapid development of synbio products raises concerns surrounding the potential risks of modified microorganisms contaminating unintended environments. These potential invasion risks require new bioinformatic tools to inform the design phase. EcoGenoRisk is a newly constructed computational risk assessment tool for invasiveness that aims to predict where synbio microorganisms may establish a population by screening for habitats of genetically similar microorganisms. The first module of the tool identifies genetically similar microorganisms and potential ecological relationships such as competition, mutualism, and inhibition. In total, 520 archaeal and 32,828 bacterial complete assembly genomes were analyzed to test the specificity and accuracy of the tool as well as to characterize the enzymatic profiles of different taxonomic lineages. Additionally, ecological relationships were analyzed to determine which would result in the greatest potential overlap between shared functional profiles. Notably, competition displayed the significantly highest overlap of shared functions between compared genomes. Overall, EcoGenoRisk is a flexible software pipeline that assists environmental risk assessors to query large databases of known microorganisms and prioritize follow-up bench scale studies.

Wastewater surveillance for bacterial targets: current challenges and future goals.

Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods.IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs.

To sample or not to sample: A governance-focused decision tree for wastewater service providers considering participation in wastewater-based epidemiology (WBE) in support of public health programs.

Wastewater-based epidemiology (WBE) provides value to public health monitoring and protection. Participation of public and private wastewater system operators in WBE efforts is critical to public health surveillance program success and sustainability. However, given the number of WBE solicitations wastewater service providers receive, the limitation of service provider resources, the concerns around privacy, ethics, and equity, and the fatigue associated with responding to COVID-19, operators are becoming more hesitant to participate in WBE efforts. While various ethical concerns and sustainability challenges associated with WBE have been documented, no efforts to date have investigated what factors should systematically influence the decision to provide samples to a WBE effort. Therefore, this study develops a decision-making tool for WBE teams to proactively monitor, manage, and avoid wastewater system operators' operational risks and potential liabilities. Ultimately, using this tool allows WBE program partners in academia, government, and industry to better understand wastewater system operators' needs and challenges surrounding data quality and use, public health ethics, and daily wastewater infrastructure operation.

Structured Ethical Review for Wastewater-Based Testing in Support of Public Health.

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.

Structured Ethical Review for Wastewater-Based Testing.

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns. Synopsis: Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.

A Metagenomic Investigation of Spatial and Temporal Changes in Sewage Microbiomes across a University Campus.

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

Passive sampling to scale wastewater surveillance of infectious disease: Lessons learned from COVID-19.

Much of what is known and theorized concerning passive sampling techniques has been developed considering chemical analytes. Yet, historically, biological analytes, such as Salmonella typhi, have been collected from wastewater via passive sampling with Moore swabs. In response to the COVID-19 pandemic, passive sampling is re-emerging as a promising technique to monitor SARS-CoV-2 RNA in wastewater. Method comparisons and disease surveillance using composite, grab, and passive sampling for SARS-CoV-2 RNA detection have found passive sampling with a variety of materials routinely produced qualitative results superior to grab samples and useful for sub-sewershed surveillance of COVID-19. Among individual studies, SARS-CoV-2 RNA concentrations derived from passive samplers demonstrated heterogeneous correlation with concentrations from paired composite samples ranging from weak (R2 = 0.27, 0.31) to moderate (R2 = 0.59) to strong (R2 = 0.76). Among passive sampler materials, electronegative membranes have shown great promise with linear uptake of SARS-CoV-2 RNA observed for exposure durations of 24 to 48 h and in several cases RNA positivity on par with composite samples. Continuing development of passive sampling methods for the surveillance of infectious diseases via diverse forms of fecal waste should focus on optimizing sampler materials for the efficient uptake and recovery of biological analytes, kit-free extraction, and resource-efficient testing methods capable of rapidly producing qualitative or quantitative data. With such refinements passive sampling could prove to be a fundamental tool for scaling wastewater surveillance of infectious disease, especially among the 1.8 billion persons living in low-resource settings served by non-traditional wastewater collection infrastructure.

Effectiveness of building-level sewage surveillance during both community-spread and sporadic-infection phases of SARS-CoV-2 in a university campus population.

Pathogen surveillance within wastewater rapidly progressed during the SARS-CoV-2 pandemic and informed public health management. In addition to the successful monitoring of entire sewer catchment basins at the treatment facility scale, subcatchment or building-level monitoring enabled targeted support of resource deployment. However, optimizing the temporal and spatial resolution of these monitoring programs remains complex due to population dynamics and within-sewer physical, chemical, and biological processes. To address these limitations, this study explores the advancement of the building-scale network that monitored the on-campus residential population at the University of Colorado Boulder between August 2020 and May 2021 through a daily SARS-CoV-2 surveillance campaign. During the study period, SARS-CoV-2 infection prevalence transitioned from robust community spread in Fall 2020 to sporadic infections in Spring 2021. Temporally, these distinct phases enabled investigating the effectiveness of resource commitment by exploring subsets of the original daily sampling data. Spatially, select sampling sites were installed along the flow path of the pipe network, enabling the exploration of the conservation of viral concentrations within the wastewater. Infection prevalence and resource commitment for informed action displayed an inverted relationship: higher temporal and spatial resolution surveillance is more imperative during sporadic infection phases than during high prevalence periods. This relationship was reinforced when norovirus (two minor clusters) and influenza (primarily absent) were additionally surveilled at a weekly frequency. Overall, resource commitment should scale to meet the objectives of the monitoring campaign-providing a general prevalence estimate requires fewer resources than an early-warning and targeted-action monitoring framework.

Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance.

SARS-CoV-2 RNA detection in wastewater is being rapidly developed and adopted as a public health monitoring tool worldwide. With wastewater surveillance programs being implemented across many different scales and by many different stakeholders, it is critical that data collected and shared are accompanied by an appropriate minimal amount of metainformation to enable meaningful interpretation and use of this new information source and intercomparison across datasets. While some databases are being developed for specific surveillance programs locally, regionally, nationally, and internationally, common globally-adopted data standards have not yet been established within the research community. Establishing such standards will require national and international consensus on what metainformation should accompany SARS-CoV-2 wastewater measurements. To establish a recommendation on minimum information to accompany reporting of SARS-CoV-2 occurrence in wastewater for the research community, the United States National Science Foundation (NSF) Research Coordination Network on Wastewater Surveillance for SARS-CoV-2 hosted a workshop in February 2021 with participants from academia, government agencies, private companies, wastewater utilities, public health laboratories, and research institutes. This report presents the primary two outcomes of the workshop: (i) a recommendation on the set of minimum meta-information that is needed to confidently interpret wastewater SARS-CoV-2 data, and (ii) insights from workshop discussions on how to improve standardization of data reporting.

High-resolution within-sewer SARS-CoV-2 surveillance facilitates informed intervention.

To assist in the COVID-19 public health guidance on a college campus, daily composite wastewater samples were withdrawn at 20 manhole locations across the University of Colorado Boulder campus. Low-cost autosamplers were fabricated in-house to enable an economical approach to this distributed study. These sample stations operated from August 25th until November 23rd during the fall 2020 semester, with 1512 samples collected. The concentration of SARS-CoV-2 in each sample was quantified through two comparative reverse transcription quantitative polymerase chain reactions (RT-qPCRs). These methods were distinct in the utilization of technical replicates and normalization to an endogenous control. (1) Higher temporal resolution compensates for supply chain or other constraints that prevent technical or biological replicates. (2) The data normalized by an endogenous control agreed with the raw concentration data, minimizing the utility of normalization. The raw wastewater concentration values reflected SARS-CoV-2 prevalence on campus as detected by clinical services. Overall, combining the low-cost composite sampler with a method that quantifies the SARS-CoV-2 signal within six hours enabled actionable and time-responsive data delivered to key stakeholders. With daily reporting of the findings, wastewater surveillance assisted in decision making during critical phases of the pandemic on campus, from detecting individual cases within populations ranging from 109 to 2048 individuals to monitoring the success of on-campus interventions.

Microbial community shifts in streams receiving treated wastewater effluent.

Wastewater treatment plant (WWTP) effluents release not only chemical constituents in watersheds, but also contain microorganisms. Thus, an understanding of what microorganisms are released and how they change microbial communities within natural streams is needed. To characterize the community shifts in streams receiving WWTP effluent, we sampled water-column microorganisms from upstream, downstream, and the effluent of WWTPs located on 23 headwater streams in which no other effluent was released upstream. We characterized the bacterial community by sequencing the V3-V4 region of the 16S rRNA gene. We hypothesized that the downstream community profile would be a hydraulic mixture between the two sources (i.e., upstream and effluent). In ordination analyses, the downstream bacterial community profile was a mixture between the upstream and effluent. For 14 of the sites, the main contribution (>50%) to the downstream community originated from bacteria in the WWTP effluent and significant shifts in relative abundance of specific sequence variants were detected. These shifts in sequence variants may serve as general bioindicators of wastewater-effluent influenced streams, with a human-gut related Ruminococcus genus displaying the highest shift (30-fold higher abundances downstream). However, not all taxa composition changes were predicted based on hydraulic mixing alone. Specifically, the decrease of Cyanobacteria/Chloroplast reads was not adequately described by hydraulic mixing. The potential alteration of stream microbial communities via a high inflow of human-gut related bacteria and a decrease in autotrophic functional groups resulting from WWTP effluent creates the potential for general shifts in stream ecosystem function.

Relating Metatranscriptomic Profiles to the Micropollutant Biotransformation Potential of Complex Microbial Communities.

Biotransformation of chemical contaminants is of importance in various natural and engineered systems. However, in complex microbial communities and with chemical contaminants at low concentrations, our current understanding of biotransformation at the level of enzyme-chemical interactions is limited. Here, we explored an approach to identify associations between micropollutant biotransformation and specific gene products in complex microbial communities, using association mining between chemical and metatranscriptomic data obtained from experiments with activated sludge grown at different solid retention times. We successfully demonstrate proportional relationships between the measured rate constants and associated gene transcripts for nitrification as a major community function, but also for the biotransformation of two nitrile-containing micropollutants (bromoxynil and acetamiprid) and transcripts of nitrile hydratases, a class of enzymes that we experimentally confirmed to produce the detected amide transformation products. As these results suggest that metatranscriptomic information can indeed be quantitatively correlated with low abundant community functions such as micropollutant biotransformation in complex microbial communities, we proceeded to explore the potential of association mining to highlight enzymes likely involved in catalyzing less well-understood micropollutant biotransformation reactions. Specifically, we use the cases of nitrile hydration and oxidative biotransformation reactions to show that the consideration of additional experimental evidence (such as information on biotransformation pathways) increases the likelihood of detecting plausible novel enzyme-chemical relationships. Finally, we identify a cluster of mono- and dioxygenase fourth-level enzyme classes that most strongly correlate with oxidative micropollutant biotransformation reactions in activated sludge.

Detection of Organohalide-Respiring Enzyme Biomarkers at a Bioaugmented TCE-Contaminated Field Site.

RNA-based biomarkers have been successfully detected at field sites undergoing in situ bioremediation, but the detection of expressed enzymes is a more direct way to prove activity for a particular biocatalytic process of interest since they provide evidence of potential in situ activity rather than simply confirming presence and abundance of genes in a given population by measurement of DNA copies using qPCR. Here we successfully applied shotgun proteomics to field samples from a trichloroethene (TCE)-contaminated industrial site in southern Ontario, Canada that had been bio-augmented with the commercially available KB-1TM microbial culture. The KB-1TM culture contains multiple strains of Dehalococcoides mccartyi (D. mccartyi) as well as an organohalide respiring Geobacter species. The relative abundances of specific enzymatic proteins were subsequently compared to corresponding qPCR-derived levels of DNA and RNA biomarkers in the same samples. Samples were obtained from two wells with high hydraulic connectivity to the KB-1TM-bioaugemented enhanced in situ bioremediation system, and two control wells that showed evidence of low levels of native organohalide respiring bacteria (OHRB), Dehalococcoides and Geobacter. Enzymes involved in organohalide respiration were detected in the metaproteomes of all four field samples, as were chaperonins of D. mccartyi, chemotaxis proteins, and ATPases. The most highly expressed RDase in the bioaugmentation culture (VcrA) was the most highly detected enzyme overall in the bioaugmented groundwater samples. In one background groundwater well, we found high expression of the Geobacter pceA RDase. The DNA and RNA biomarkers detected using qPCR-based assays were a set of orthologs of Dehalococcoides reductive dehalogenases (VcrA, TceA, BvcA, dehalogenase "DET1545"), and the Ni-Fe uptake hydrogenase, HupL. Within a sample, RNA levels for key enzymes correlated with relative protein abundance. These results indicate that laboratory observations of TCE-bioremediation biomarker protein expression are recapitulated in field environmental systems and that both RNA and protein biomarker monitoring hold promise for activity monitoring of in situ populations of OHRB.

Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities.

A remaining challenge within microbial ecology is to understand the determinants of richness and diversity observed in environmental microbial communities. In a range of systems, including activated sludge bioreactors, the microbial residence time (MRT) has been previously shown to shape the microbial community composition. However, the physiological and ecological mechanisms driving this influence have remained unclear. Here, this relationship is explored by analyzing an activated sludge system fed with municipal wastewater. Using a model designed in this study based on Monod-growth kinetics, longer MRTs were shown to increase the range of growth parameters that enable persistence, resulting in increased richness and diversity in the modeled community. In laboratory experiments, six sequencing batch reactors treating domestic wastewater were operated in parallel at MRTs between 1 and 15 days. The communities were characterized using both 16S ribosomal RNA and non-target messenger RNA sequencing (metatranscriptomic analysis), and model-predicted monotonic increases in richness were confirmed in both profiles. Accordingly, taxonomic Shannon diversity also increased with MRT. In contrast, the diversity in enzyme class annotations resulting from the metatranscriptomic analysis displayed a non-monotonic trend over the MRT gradient. Disproportionately high abundances of transcripts encoding for rarer enzymes occur at longer MRTs and lead to the disconnect between taxonomic and functional diversity profiles.

Trends in Micropollutant Biotransformation along a Solids Retention Time Gradient.

For many polar organic micropollutants, biotransformation by activated sludge microorganisms is a major removal process during wastewater treatment. However, our current understanding of how wastewater treatment operations influence microbial communities and their micropollutant biotransformation potential is limited, leaving major parts of observed variability in biotransformation rates across treatment facilities unexplained. Here, we present biotransformation rate constants for 42 micropollutants belonging to different chemical classes along a gradient of solids retention time (SRT). The geometric mean of biomass-normalized first-order rate constants shows a clear increase between 3 and 15 d SRT by 160% and 87%, respectively, in two experiments. However, individual micropollutants show a variety of trends. Rate constants of oxidative biotransformation reactions mostly increased with SRT. Yet, nitrifying activity could be excluded as primary driver. For substances undergoing other than oxidative reactions, i.e., mostly substitution-type reactions, more diverse dependencies on SRT were observed. Most remarkably, characteristic trends were observed for groups of substances undergoing similar types of initial transformation reaction, suggesting that shared enzymes or enzyme systems that are conjointly regulated catalyze biotransformation reactions within such groups. These findings open up opportunities for correlating rate constants with measures of enzyme abundance such as genes or gene products, which in turn should help to identify enzymes associated with the respective biotransformation reactions.

Biotransformation of Sulfonamide Antibiotics in Activated Sludge: The Formation of Pterin-Conjugates Leads to Sustained Risk.

The presence of antibiotics in treated wastewater and consequently in surface and groundwater resources raises concerns about the formation and spread of antibiotic resistance. Improving the removal of antibiotics during wastewater treatment therefore is a prime objective of environmental engineering. Here we obtained a detailed picture of the fate of sulfonamide antibiotics during activated sludge treatment using a combination of analytical methods. We show that pterin-sulfonamide conjugates, which are formed when sulfonamides interact with their target enzyme to inhibit folic acid synthesis, represent a major biotransformation route for sulfonamides in laboratory batch experiments with activated sludge. The same major conjugates were also present in the effluents of nine Swiss wastewater treatment plants. The demonstration of this biotransformation route, which is related to bacterial growth, helps explain seemingly contradictory views on optimal conditions for sulfonamide removal. More importantly, since pterin-sulfonamide conjugates show retained antibiotic activity, our findings suggest that risk from exposure to sulfonamide antibiotics may be less reduced during wastewater treatment than previously assumed. Our results thus further emphasize the inadequacy of focusing on parent compound removal and the importance of investigating biotransformation pathways and removal of bioactivity to properly assess contaminant removal in both engineered and natural systems.

Altered Microbiome Leads to Significant Phenotypic and Transcriptomic Differences in a Lipid Accumulating Chlorophyte.

Given the challenges facing the economically favorable production of products from microalgae, understanding factors that might impact productivity rates including growth rates and accumulation of desired products, for example, triacylglycerols (TAG) for biodiesel feedstock, remains critical. Although operational parameters such as media composition and reactor design can clearly effect growth rates, the role of microbe-microbe interactions is just beginning to be elucidated. In this study an oleaginous marine algae Chlorella spp. C596 culture is shown to be better described as a microbial community. Perturbations to this microbial community showed a significant impact on phenotypes including sustained differences in growth rate and TAG accumulation of 2.4 and 2.5 fold, respectively. Characterization of the associated community using Illumina 16S rRNA amplicon and random shotgun transcriptomic analyses showed that the fast growth rate correlated with two specific bacterial species ( Ruegeria and Rhodobacter spp). The transcriptomic response of the Chlorella species revealed that the slower growing algal consortium C596-S1 upregulated genes associated with photosynthesis and resource scavenging and decreased the expression of genes associated with transcription and translation relative to the initial C596-R1. Our studies advance the appreciation of the effects microbiomes can have on algal growth in bioreactors and suggest that symbiotic interactions are involved in a range of critical processes including nitrogen, carbon cycling, and oxidative stress.

Biomarkers' Responses to Reductive Dechlorination Rates and Oxygen Stress in Bioaugmentation Culture KB-1TM.

Using mRNA transcript levels for key functional enzymes as proxies for the organohalide respiration (OHR) rate, is a promising approach for monitoring bioremediation populations in situ at chlorinated solvent-contaminated field sites. However, to date, no correlations have been empirically derived for chlorinated solvent respiring, Dehalococcoides mccartyi (DMC) containing, bioaugmentation cultures. In the current study, genome-wide transcriptome and proteome data were first used to confirm the most highly expressed OHR-related enzymes in the bioaugmentation culture, KB-1TM, including several reductive dehalogenases (RDases) and a Ni-Fe hydrogenase, Hup. Different KB-1™ DMC strains could be resolved at the RNA and protein level through differences in the sequence of a common RDase (DET1545-like homologs) and differences in expression of their vinyl chloride-respiring RDases. The dominant strain expresses VcrA, whereas the minor strain utilizes BvcA. We then used quantitative reverse-transcriptase PCR (qRT-PCR) as a targeted approach for quantifying transcript copies in the KB-1TM consortium operated under a range of TCE respiration rates in continuously-fed, pseudo-steady-state reactors. These candidate biomarkers from KB-1TM demonstrated a variety of trends in terms of transcript abundance as a function of respiration rate over the range: 7.7 × 10-12 to 5.9 × 10-10 microelectron equivalents per cell per hour (µeeq/cell∙h). Power law trends were observed between the respiration rate and transcript abundance for the main DMC RDase (VcrA) and the hydrogenase HupL (R² = 0.83 and 0.88, respectively), but not transcripts for 16S rRNA or three other RDases examined: TceA, BvcA or the RDase DET1545 homologs in KB1TM. Overall, HupL transcripts appear to be the most robust activity biomarker across multiple DMC strains and in mixed communities including DMC co-cultures such as KB1TM. The addition of oxygen induced cell stress that caused respiration rates to decline immediately (>95% decline within one hour). Although transcript levels did decline, they did so more slowly than the respiration rate observed (transcript decay rates between 0.02 and 0.03 per hour). Data from strain-specific probes on the pangenome array strains suggest that a minor DMC strain in KB-1™ that harbors a bvcA homolog preferentially recovered following oxygen stress relative to the dominant, vcrA-containing strain.

Inferring Gene Networks for Strains of Dehalococcoides Highlights Conserved Relationships between Genes Encoding Core Catabolic and Cell-Wall Structural Proteins.

The interpretation of high-throughput gene expression data for non-model microorganisms remains obscured because of the high fraction of hypothetical genes and the limited number of methods for the robust inference of gene networks. Therefore, to elucidate gene-gene and gene-condition linkages in the bioremediation-important genus Dehalococcoides, we applied a Bayesian inference strategy called Reverse Engineering/Forward Simulation (REFS™) on transcriptomic data collected from two organohalide-respiring communities containing different Dehalococcoides mccartyi strains: the Cornell University mixed community D2 and the commercially available KB-1® bioaugmentation culture. In total, 49 and 24 microarray datasets were included in the REFS™ analysis to generate an ensemble of 1,000 networks for the Dehalococcoides population in the Cornell D2 and KB-1® culture, respectively. Considering only linkages that appeared in the consensus network for each culture (exceeding the determined frequency cutoff of ≥ 60%), the resulting Cornell D2 and KB-1® consensus networks maintained 1,105 nodes (genes or conditions) with 974 edges and 1,714 nodes with 1,455 edges, respectively. These consensus networks captured multiple strong and biologically informative relationships. One of the main highlighted relationships shared between these two cultures was a direct edge between the transcript encoding for the major reductive dehalogenase (tceA (D2) or vcrA (KB-1®)) and the transcript for the putative S-layer cell wall protein (DET1407 (D2) or KB1_1396 (KB-1®)). Additionally, transcripts for two key oxidoreductases (a [Ni Fe] hydrogenase, Hup, and a protein with similarity to a formate dehydrogenase, "Fdh") were strongly linked, generalizing a strong relationship noted previously for Dehalococcoides mccartyi strain 195 to multiple strains of Dehalococcoides. Notably, the pangenome array utilized when monitoring the KB-1® culture was capable of resolving signals from multiple strains, and the network inference engine was able to reconstruct gene networks in the distinct strain populations.

Use of De Novo Transcriptome Libraries to Characterize a Novel Oleaginous Marine Chlorella Species during the Accumulation of Triacylglycerols.

Marine chlorophytes of the genus Chlorella are unicellular algae capable of accumulating a high proportion of cellular lipids that can be used for biodiesel production. In this study, we examined the broad physiological capabilities of a subtropical strain (C596) of Chlorella sp. "SAG-211-18" including its heterotrophic growth and tolerance to low salt. We found that the alga replicates more slowly at diluted salt concentrations and can grow on a wide range of carbon substrates in the dark. We then sequenced the RNA of Chlorella strain C596 to elucidate key metabolic genes and investigate the transcriptomic response of the organism when transitioning from a nutrient-replete to a nutrient-deficient condition when neutral lipids accumulate. Specific transcripts encoding for enzymes involved in both starch and lipid biosynthesis, among others, were up-regulated as the cultures transitioned into a lipid-accumulating state whereas photosynthesis-related genes were down-regulated. Transcripts encoding for two of the up-regulated enzymes-a galactoglycerolipid lipase and a diacylglyceride acyltransferase-were also monitored by reverse transcription quantitative polymerase chain reaction assays. The results of these assays confirmed the transcriptome-sequencing data. The present transcriptomic study will assist in the greater understanding, more effective application, and efficient design of Chlorella-based biofuel production systems.