Wildfire Ashes from the Wildland-Urban Interface Alter Vibrio vulnificus Growth and Gene Expression.

Climate change-induced stressors are contributing to the emergence of infectious diseases, including those caused by marine bacterial pathogens such as Vibrio spp. These stressors alter Vibrio temporal and geographical distribution, resulting in increased spread, exposure, and infection rates, thus facilitating greater Vibrio-human interactions. Concurrently, wildfires are increasing in size, severity, frequency, and spread in the built environment due to climate change, resulting in the emission of contaminants of emerging concern. This study aimed to understand the potential effects of urban interface wildfire ashes on Vibrio vulnificus (V. vulnificus) growth and gene expression using transcriptomic approaches. V. vulnificus was exposed to structural and vegetation ashes and analyzed to identify differentially expressed genes using the HTSeq-DESeq2 strategy. Exposure to wildfire ash altered V. vulnificus growth and gene expression, depending on the trace metal composition of the ash. The high Fe content of the vegetation ash enhanced bacterial growth, while the high Cu, As, and Cr content of the structural ash suppressed growth. Additionally, the overall pattern of upregulated genes and pathways suggests increased virulence potential due to the selection of metal- and antibiotic-resistant strains. Therefore, mixed fire ashes transported and deposited into coastal zones may lead to the selection of environmental reservoirs of Vibrio strains with enhanced antibiotic resistance profiles, increasing public health risk.

Building-level wastewater surveillance of SARS-CoV-2 is associated with transmission and variant trends in a university setting.

The University of South Carolina (UofSC) was among the first universities to include building-level wastewater surveillance of SARS-CoV-2 to complement clinical testing during its reopening in the Fall 2020 semester. In the Spring 2021 semester, 24h composite wastewater samples were collected twice per week from 10 residence halls and the on-campus student isolation and quarantine building. The isolation and quarantine building served as a positive control site. The wastewater was analyzed using RT-ddPCR for the quantification of nucleocapsid genes (N1 and N2) to identify viral transmission trends within residence halls. Log10 SARS-CoV-2 RNA concentrations were compared to both new clinical cases identified in the days following wastewater collection and recovered cases returning to sites during the days preceding sample collection to test temporal and spatial associations. There was a statistically significant positive relationship between the number of cases reported from the sites during the seven-day period following wastewater sampling and the log10 viral RNA copies/L (overall IRR 1.08 (1.02, 1.16) p-value 0.0126). Additionally, a statistically significant positive relationship was identified between the number of cases returning to the residence halls after completing isolation during the seven-day period preceding wastewater sampling and the log10 viral RNA copies/L (overall 1.09 (1.01, 1.17) p-value 0.0222). The statistical significance of both identified cases and recovered return cases on log10 viral RNA copies/L in wastewater indicates the importance of including both types of clinical data in wastewater-based epidemiology (WBE) research. Genetic mutations associated with variants of concern (VOCs) were also monitored. The emergence of the Alpha variant on campus was identified, which contributed to the second wave of COVID-19 cases at UofSC. The study was able to identify sub-community transmission hotspots for targeted intervention in real-time, making WBE cost-effective and creating less of a burden on the general public compared to repeated individual testing methods.

Influences of 23 different equations used to calculate gene copies of SARS-CoV-2 during wastewater-based epidemiology.

Following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the use of wastewater-based surveillance (WBS) has increased dramatically along with associated infrastructure globally. However, due to the global nature of its application, and various workflow adaptations (e.g., sample collection, water concentration, RNA extraction kits), numerous methods for back-calculation of gene copies per volume (gc/L) of sewage have also emerged. Many studies have considered the comparability of processing methods (e.g., water concentration, RNA extraction); however, for equations used to calculate gene copies in a wastewater sample and subsequent influences on monitoring viral trends in a community and its association with epidemiological data, less is known. Due to limited information on how many formulas exist for the calculation of SARS-CoV-2 gene copies in wastewater, we initially attempted to quantify how many equations existed in the referred literature. We identified 23 unique equations, which were subsequently applied to an existing wastewater dataset. We observed a range of gene copies based on use of different equations, along with variability of AUC curve values, and results from correlation and regression analyses. Though a number of individual laboratories appear to have independently converged on a similar formula for back-calculation of viral load in wastewater, and share similar relationships with epidemiological data, differential influences of various equations were observed for variation in PCR volumes, RNA extraction volumes, or PCR assay parameters. Such observations highlight challenges when performing comparisons among WBS studies when numerous methodologies and back-calculation methods exist. To facilitate reproducibility among studies, the different gc/L equations were packaged as an R Shiny app, which provides end users the ability to investigate variability within their datasets and support comparisons among studies.

Long-term operation of microbial electrosynthesis systems improves acetate production by autotrophic microbiomes.

Microbial electrosynthesis is the biocathode-driven production of chemicals from CO2 and has the promise to be a sustainable, carbon-consuming technology. To date, microbial electrosynthesis of acetate, the first step in order to generate liquid fuels from CO2, has been characterized by low rates and yields. To improve performance, a previously established acetogenic biocathode was operated in semi-batch mode at a poised potential of -590 mV vs SHE for over 150 days beyond its initial development. Rates of acetate production reached a maximum of 17.25 mM day(-1) (1.04 g L(-1) d(-1)) with accumulation to 175 mM (10.5 g L(-1)) over 20 days. Hydrogen was also produced at high rates by the biocathode, reaching 100 mM d(-1) (0.2 g L(-1) d(-1)) and a total accumulation of 1164 mM (2.4 g L(-1)) over 20 days. Phylogenetic analysis of the active electrosynthetic microbiome revealed a similar community structure to what was observed during an earlier stage of development of the electroacetogenic microbiome. Acetobacterium spp. dominated the active microbial population on the cathodes. Also prevalent were Sulfurospirillum spp. and an unclassified Rhodobacteraceae. Taken together, these results demonstrate the stability, resilience, and improved performance of electrosynthetic biocathodes following long-term operation. Furthermore, sustained product formation at faster rates by a carbon-capturing microbiome is a key milestone addressed in this study that advances microbial electrosynthesis systems toward commercialization.

SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales.

Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.

Influence of storage conditions and multiple freeze-thaw cycles on N1 SARS-CoV-2, PMMoV, and BCoV signal.

Wastewater-based epidemiology/wastewater-based surveillance (WBE/WBS) continues to serve as an effective means of monitoring various diseases, including COVID-19 and the emergence of SARS-CoV-2 variants, at the population level. As the use of WBE expands, storage conditions of wastewater samples will play a critical role in ensuring the accuracy and reproducibility of results. In this study, the impacts of water concentration buffer (WCB), storage temperature, and freeze-thaw cycles on the detection of SARS-CoV-2 and other WBE-related gene targets were examined. Freeze-thawing of concentrated samples did not significantly affect (p > 0.05) crossing/cycle threshold (Ct) value for any of the gene targets studied (SARS-CoV-2 N1, PMMoV, and BCoV). However, use of WCB during concentration resulted in a significant (p < 0.05) decrease in Ct for all targets, and storage at -80 °C (in contrast to -20 °C) appeared preferable for wastewater storage signal stability based on decreased Ct values, although this was only significantly different (p < 0.05) for the BCoV target. Interestingly, when Ct values were converted to gene copies per influent sample, no significant differences (p > 0.05) were observed in any of the targets examined. Stability of RNA targets in concentrated wastewater against freeze-thaw degradation supports archiving of concentrated samples for use in retrospective examination of COVID-19 trends and tracing SARS-CoV-2 variants and potentially other viruses, and provides a starting point for establishing a consistent procedure for specimen collection and storage for the WBE/WBS community.

Electrosynthesis of commodity chemicals by an autotrophic microbial community.

A microbial community originating from brewery waste produced methane, acetate, and hydrogen when selected on a granular graphite cathode poised at -590 mV versus the standard hydrogen electrode (SHE) with CO(2) as the only carbon source. This is the first report on the simultaneous electrosynthesis of these commodity chemicals and the first description of electroacetogenesis by a microbial community. Deep sequencing of the active community 16S rRNA revealed a dynamic microbial community composed of an invariant Archaea population of Methanobacterium spp. and a shifting Bacteria population. Acetobacterium spp. were the most abundant Bacteria on the cathode when acetogenesis dominated. Methane was generally the dominant product with rates increasing from <1 to 7 mM day(-1) (per cathode liquid volume) and was concomitantly produced with acetate and hydrogen. Acetogenesis increased to >4 mM day(-1) (accumulated to 28.5 mM over 12 days), and methanogenesis ceased following the addition of 2-bromoethanesulfonic acid. Traces of hydrogen accumulated during initial selection and subsequently accelerated to >11 mM day(-1) (versus 0.045 mM day(-1) abiotic production). The hypothesis of electrosynthetic biocatalysis occurring at the microbe-electrode interface was supported by a catalytic wave (midpoint potential of -460 mV versus SHE) in cyclic voltammetry scans of the biocathode, the lack of redox active components in the medium, and the generation of comparatively high amounts of products (even after medium exchange). In addition, the volumetric production rates of these three commodity chemicals are marked improvements for electrosynthesis, advancing the process toward economic feasibility.

Dispersion of SARS-CoV-2 RNA across a wastewater treatment plant and its workers.

Within urban and suburban sewersheds, SARS-CoV-2 released through faeces is transported through sewage systems into municipal wastewater treatment plants (WWTPs). Studies have shown that viral RNA is detectable in untreated wastewater but not in WWTP effluent. In this study, we investigated treatment steps between the influent and final treated effluent to identify the point at which viral RNA is below detection. Additionally, we examined air surrounding high turbulence treatment steps to test for the presence of SARS-CoV-2 RNA in WWTP-generated bioaerosols. To examine potential worker exposure to SARS-CoV-2, WWTP workers were tested for the presence of viral RNA. The data show that despite high viral RNA concentration in the influent, SARS-CoV-2 RNA concentration decreased significantly (p < 0.02) in the main treatment steps and was below detection in the effluent. Additionally, SARS-CoV-2 RNA was below detection in air samples (n = 42), and the worker rate of infection was not significantly different (p = 0.99) from the rate of infection in the surrounding community. These results suggest that WWTP workers may have minimal exposure to SARS-CoV-2 during routine outdoor work procedures and that the WWTP successfully reduces the amount of viral RNA entering effluent receiving waters, providing a vital public health service to communities.

Wastewater surveillance of SARS-CoV-2 mutational profiles at a university and its surrounding community reveals a 20G outbreak on campus.

Wastewater surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been leveraged during the Coronavirus Disease 2019 (COVID-19) pandemic as a public health tool at the community and building level. In this study, we compare the sequence diversity of SARS-CoV-2 amplified from wastewater influent to the Columbia, South Carolina, metropolitan wastewater treatment plant (WWTP) and the University of South Carolina campus during September 2020, which represents the peak of COVID-19 cases at the university during 2020. A total of 92 unique mutations were detected across all WWTP influent and campus samples, with the highest frequency mutations corresponding to the SARS-CoV-2 20C and 20G clades. Signature mutations for the 20G clade dominated SARS-CoV-2 sequences amplified from localized wastewater samples collected at the University of South Carolina, suggesting that the peak in COVID-19 cases during early September 2020 was caused by an outbreak of the 20G lineage. Thirteen mutations were shared between the university building-level wastewater samples and the WWTP influent collected in September 2020, 62% of which were nonsynonymous substitutions. Co-occurrence of mutations was used as a similarity metric to compare wastewater samples. Three pairs of mutations co-occurred in university wastewater and WWTP influent during September 2020. Thirty percent of the detected mutations, including 12 pairs of concurrent mutations, were only detected in university samples. This report affirms the close relationship between the prevalent SARS-CoV-2 genotypes of the student population at a university campus and those of the surrounding community. However, this study also suggests that wastewater surveillance at the building-level at a university offers important insight by capturing sequence diversity that was not apparent in the WWTP influent, thus offering a balance between the community-level wastewater and clinical sequencing.

Comparative Analysis of RNA-Extraction Approaches and Associated Influences on RT-qPCR of the SARS-CoV-2 RNA in a University Residence Hall and Quarantine Location.

Wastewater-based epidemiology (WBE) provides an early warning and trend analysis approach for determining the presence of COVID-19 in a community and complements clinical testing in assessing the population level, even as viral loads fluctuate. Here, we evaluate combinations of two wastewater concentration methods (i.e., ultrafiltration and composite supernatant-solid), four pre-RNA extraction modifications, and three nucleic acid extraction kits using two different wastewater sampling locations. These consisted of a quarantine facility containing clinically confirmed COVID-19-positive inhabitants and a university residence hall. Of the combinations examined, composite supernatant-solid with pre-RNA extraction consisting of water concentration and RNA/DNA shield performed the best in terms of speed and sensitivity. Further, of the three nucleic acid extraction kits examined, the most variability was associated with the Qiagen kit. Focusing on the quarantine facility, viral concentrations measured in wastewater were generally significantly related to positive clinical cases, with the relationship dependent on method, modification, kit, target, and normalization, although results were variable-dependent on individual time points (Kendall's Tau-b (τ) = 0.17 to 0.6) or cumulatively (Kendall's Tau-b (τ) = -0.048 to 1). These observations can support laboratories establishing protocols to perform wastewater surveillance and monitoring efforts for COVID-19.

Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States.

After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.

Vibrio parahaemolyticus and Vibrio vulnificus in vitro colonization on plastics influenced by temperature and strain variability.

Marine bacteria often exist in biofilms as communities attached to surfaces, like plastic. Growing concerns exist regarding marine plastics acting as potential vectors of pathogenic Vibrio, especially in a changing climate. It has been generalized that Vibrio vulnificus and Vibrio parahaemolyticus often attach to plastic surfaces. Different strains of these Vibrios exist having different growth and biofilm-forming properties. This study evaluated how temperature and strain variability affect V. parahaemolyticus and V. vulnificus biofilm formation and characteristics on glass (GL), low-density polyethylene (LDPE), polypropylene (PP), and polystyrene (PS). All strains of both species attached to GL and all plastics at 25, 30, and 35°C. As a species, V. vulnificus produced more biofilm on PS (p ≤ 0.05) compared to GL, and biofilm biomass was enhanced at 25°C compared to 30° (p ≤ 0.01) and 35°C (p ≤ 0.01). However, all individual strains' biofilm biomass and cell densities varied greatly at all temperatures tested. Comparisons of biofilm-forming strains for each species revealed a positive correlation (r = 0.58) between their dry biomass weight and OD570 values from crystal violet staining, and total dry biofilm biomass for both species was greater (p ≤ 0.01) on plastics compared to GL. It was also found that extracellular polymeric substance (EPS) chemical characteristics were similar on all plastics of both species, with extracellular proteins mainly contributing to the composition of EPS. All strains were hydrophobic at 25, 30, and 35°C, further illustrating both species' affinity for potential attachment to plastics. Taken together, this study suggests that different strains of V. parahaemolyticus and V. vulnificus can rapidly form biofilms with high cell densities on different plastic types in vitro. However, the biofilm process is highly variable and is species-, strain-specific, and dependent on plastic type, especially under different temperatures.

Characterization and quantitation of a novel ß-lactamase gene found in a wastewater treatment facility and the surrounding coastal ecosystem.

Wastewater treatment plants (WWTPs) are engineered structures that collect, concentrate, and treat human waste, ultimately releasing treated wastewater into local environments. While WWTPs efficiently remove most biosolids, it has been shown that many antibiotics and antibiotic-resistant bacteria can survive the treatment process. To determine how WWTPs influence the concentration and dissemination of antibiotic-resistant genes into the environment, a functional metagenomic approach was used to identify a novel antibiotic resistance gene within a WWTP, and quantitative PCR (qPCR) was used to determine gene copy numbers within the facility and the local coastal ecosystem. From the WWTP metagenomic library, the fosmid insert contained in one highly resistant clone (MIC, ≈ 416 µg ml(-1) ampicillin) was sequenced and annotated, revealing 33 putative genes, including a 927-bp gene that is 42% identical to a functionally characterized ß-lactamase from Staphylococcus aureus PC1. Isolation and subcloning of this gene, referred to as bla(M-1), conferred ampicillin resistance to its Escherichia coli host. When normalized to volume, qPCR showed increased concentrations of bla(M-1) during initial treatment stages but 2-fold-decreased concentrations during the final treatment stage. The concentration ng(-1) DNA increased throughout the WWTP process from influent to effluent, suggesting that bla(M-1) makes up a significant proportion of the overall genetic material being released into the coastal ecosystem. Average discharge was estimated to be 3.9 × 10(14) copies of the bla(M-1) gene released daily into this coastal ecosystem. Furthermore, the gene was observed in all sampled coastal water and sediment samples surrounding the facility. Our results suggest that WWTPs may be a pathway for the dissemination of novel antibiotic resistance genes into the environment.

Community-level SARS-CoV-2 sequence diversity revealed by wastewater sampling.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for causing the COVID-19 pandemic, can be detected in untreated wastewater. Wastewater surveillance of SARS-CoV-2 complements clinical data by offering earlier community-level detection, removing underlying factors such as access to healthcare, sampling asymptomatic patients, and reaching a greater population. Here, we compare 24-hour composite samples from the influents of two different wastewater treatment plants (WWTPs) in South Carolina, USA: Columbia and Rock Hill. The sampling intervals span the months of July 2020 and January 2021, which cover the first and second waves of elevated SARS-CoV-2 transmission and COVID-19 clinical cases in these regions. We identify four signature mutations in the surface glycoprotein (spike) gene that are associated with the following variants of interest or concern, VOI or VOC (listed in parenthesis): S477N (B.1.526, Iota), T478K (B.1.617.2, Delta), D614G (present in all VOC as of May 2021), and H655Y (P.1, Gamma). The N501Y mutation, which is associated with three variants of concern, was identified in samples from July 2020, but not detected in January 2021 samples. Comparison of mutations identified in viral sequence databases such as NCBI Virus and GISAID indicated that wastewater sampling detected mutations that were present in South Carolina, but not reflected in the clinical data deposited into databases.

BLAST-QC: automated analysis of BLAST results.

BACKGROUND: The Basic Local Alignment Search Tool (BLAST) from NCBI is the preferred utility for sequence alignment and identification for bioinformatics and genomics research. Among researchers using NCBI's BLAST software, it is well known that analyzing the results of a large BLAST search can be tedious and time-consuming. Furthermore, with the recent discussions over the effects of parameters such as '-max_target_seqs' on the BLAST heuristic search process, the use of these search options are questionable. This leaves using a stand-alone parser as one of the only options of condensing these large datasets, and with few available for download online, the task is left to the researcher to create a specialized piece of software anytime they need to analyze BLAST results. The need for a streamlined and fast script that solves these issues and can be easily implemented into a variety of bioinformatics and genomics workflows was the initial motivation for developing this software. RESULTS: In this study, we demonstrate the effectiveness of BLAST-QC for analysis of BLAST results and its desirability over the other available options. Applying genetic sequence data from our bioinformatic workflows, we establish BLAST_QC's superior runtime when compared to existing parsers developed with commonly used BioPerl and BioPython modules, as well as C and Java implementations of the BLAST_QC program. We discuss the 'max_target_seqs' parameter, the usage of and controversy around the use of the parameter, and offer a solution by demonstrating the ability of our software to provide the functionality this parameter was assumed to produce, as well as a variety of other parsing options. Executions of the script on example datasets are given, demonstrating the implemented functionality and providing test-cases of the program. BLAST-QC is designed to be integrated into existing software, and we establish its effectiveness as a module of workflows or other processes. CONCLUSIONS: BLAST-QC provides the community with a simple, lightweight and portable Python script that allows for easy quality control of BLAST results while avoiding the drawbacks of other options. This includes the uncertain results of applying the -max_target_seqs parameter or relying on the cumbersome dependencies of other options like BioPerl, Java, etc. which add complexity and run time when running large data sets of sequences. BLAST-QC is ideal for use in high-throughput workflows and pipelines common in bioinformatic and genomic research, and the script has been designed for portability and easy integration into whatever type of processes the user may be running.

Defining Genomic and Predicted Metabolic Features of the Acetobacterium Genus.

Acetogens are anaerobic bacteria capable of fixing CO2 or CO to produce acetyl coenzyme A (acetyl-CoA) and ultimately acetate using the Wood-Ljungdahl pathway (WLP). Acetobacterium woodii is the type strain of the Acetobacterium genus and has been critical for understanding the biochemistry and energy conservation in acetogens. Members of the Acetobacterium genus have been isolated from a variety of environments or have had genomes recovered from metagenome data, but no systematic investigation has been done on the unique and various metabolisms of the genus. To gain a better appreciation for the metabolic breadth of the genus, we sequenced the genomes of 4 isolates (A. fimetarium, A. malicum, A. paludosum, and A. tundrae) and conducted a comparative genome analysis (pan-genome) of 11 different Acetobacterium genomes. A unifying feature of the Acetobacterium genus is the carbon-fixing WLP. The methyl (cluster II) and carbonyl (cluster III) branches of the Wood-Ljungdahl pathway are highly conserved across all sequenced Acetobacterium genomes, but cluster I encoding the formate dehydrogenase is not. In contrast to A. woodii, all but four strains encode two distinct Rnf clusters, Rnf being the primary respiratory enzyme complex. Metabolism of fructose, lactate, and H2:CO2 was conserved across the genus, but metabolism of ethanol, methanol, caffeate, and 2,3-butanediol varied. Additionally, clade-specific metabolic potential was observed, such as amino acid transport and metabolism in the psychrophilic species, and biofilm formation in the A. wieringae clade, which may afford these groups an advantage in low-temperature growth or attachment to solid surfaces, respectively.IMPORTANCE Acetogens are anaerobic bacteria capable of fixing CO2 or CO to produce acetyl-CoA and ultimately acetate using the Wood-Ljungdahl pathway (WLP). This autotrophic metabolism plays a major role in the global carbon cycle and, if harnessed, can help reduce greenhouse gas emissions. Overall, the data presented here provide a framework for examining the ecology and evolution of the Acetobacterium genus and highlight the potential of these species as a source for production of fuels and chemicals from CO2 feedstocks.

Autoinducers extracted from microbial mats reveal a surprising diversity of N-acylhomoserine lactones (AHLs) and abundance changes that may relate to diel pH.

Microbial mats are highly structured and diverse communities, and one of the earliest-known life assemblages. Mat bacteria interact within an environment marked by strong geochemical gradients and fluctuations. We examined natural mat systems for the presence of autoinducers involved in quorum sensing, a form of cell-cell communication. Our results revealed that a diverse array of N-acylhomoserine lactones (AHLs) including C(4)- to C(14)-AHLs, were identified from mat extracts using mass spectrometry (MS), with further confirmation by MS/MS-collision-induced dissociation (CID), and additions of external standards. Microelectrode measurements showed that mats exhibited diel pH fluctuations, ranging from alkaline (pH 9.4) during daytime (net photosynthesis) to acidic (pH 6.8) during darkness (net respiration/fermentation). Under laboratory conditions, AHLs having shorter acyl-chains were degraded within the time frame that daily alkaline pH (> 8.2) conditions exist in mats. Intensive sampling of mats after full day- or night-time incubations revealed that accumulations of extractable shorter-chain AHLs (e.g. C(8)- and C(10)-AHLs) were significantly (P < 0.001) diminished during daytime. Our study offers evidence that stabilities of AHLs under natural conditions may be influenced by the proximal extracellular environment. We further propose that the ancient periodicity of photosynthesis/respiration in mats may potentially drive a mechanism for diel differences in activities of certain autoinducers, and hence bacterial activities mediated through quorum sensing.

Emission and dispersal of antibiotic resistance genes through bioaerosols generated during the treatment of municipal sewage.

Wastewater treatment plants act as socio-ecological couplers through the concentration, treatment, and subsequent environmental release of sewage collected from surrounding communities and are often considered hotspots for antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). While studies have identified the release of ARB/ARGs in treated liquid sewage, little is known about potential dispersal through wastewater bioaerosol emissions. The aim of this study was to better define the contribution of WWTP bioaerosols to potential environmental distribution of ARB/ARGs. Bioaerosols were collected immediately upwind and downwind from the aeration tanks of a municipal wastewater treatment plant and liquid sludge samples were obtained from the aeration tanks. From the bioaerosol and liquid samples, qPCR assays identified 44 ARGs that confer resistance to a wide range of antibiotics. Comparison of the ARG profiles across samples showed that the downwind bioaerosol profile was 68% similar to the profile found in liquid sludge samples. Community 16S rRNA gene sequencing also showed that downwind bioaerosols had similar taxonomic profiles as those generated from liquid sludge while the upwind profiles showed a distinct difference. Preliminary ARG dispersion modeling estimated an ARG emission rate of ~10,620 genes per hour from the liquid sludge and indicated that the bioaerosols have the potential to be carried kilometers away from the WWTP source based on wind speed. The overall results from this study suggest that bioaerosols generated during WWTP processes can aid in the emission and dispersal of bacteria and ARGs, resulting in a possible route of human exposure and deposition into surrounding environments.

Rapid screening of quorum-sensing signal N-acyl homoserine lactones by an in vitro cell-free assay.

A simple, sensitive, and rapid cell-free assay system was developed for detection of N-acyl homoserine lactone (AHL) autoinducers involved in bacterial quorum sensing (QS). The present approach improves upon previous whole-cell biosensor-based approaches in its utilization of a cell-free assay approach to conduct bioassays. The cell-free assay was derived from the AHL biosensor bacterium Agrobacterium tumefaciens NTL4(pCF218)(pCF372), allowing the expression of beta-galactosidase upon addition of exogenous AHLs. We have shown that beta-galactosidase expression is possible in cell-free solution [lysate from Agrobacterium tumefaciens NTL4(pCF218)(pCF372) culture]. Assay detection limits with the use of chromogenic substrate X-Gal (5-bromo-4-chloro-3-indolyl-beta-D-galactopyranoside) ranged from approximately 100 nM to 300 nM depending on the specific AHL. Replacement (of X-Gal) with the luminescent substrate Beta-Glo increased sensitivity to AHLs by 10-fold. A major advantage of the cell-free assay system is elimination of time-consuming steps for biosensor cell culture conditioning, which are required prior to whole-cell bioassays. This significantly reduced assay times from greater than 24 h to less than 3 h, while maintaining high sensitivity. Assay lysate may be prepared in bulk and stored (-80 degrees C) over 6 months for future use. Finally, the present protocol may be adapted for use with other biosensor strains and be used in high-throughput AHL screening of bacteria or metagenomic libraries.

Metagenome-Assembled Genome Sequences of Acetobacterium sp. Strain MES1 and Desulfovibrio sp. Strain MES5 from a Cathode-Associated Acetogenic Microbial Community.

Draft genome sequences of Acetobacterium sp. strain MES1 and Desulfovibrio sp. strain MES5 were obtained from the metagenome of a cathode-associated community enriched within a microbial electrosynthesis system (MES). The draft genome sequences provide insight into the functional potential of these microorganisms within an MES and a foundation for future comparative analyses.