A modeling pipeline to relate municipal wastewater surveillance and regional public health data.

As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.

Correlation of wastewater surveillance data with traditional influenza surveillance measures in Cook County, Illinois, October 2022-April 2023.

Influenza is a respiratory illness that can result in serious outcomes, particularly among persons who are immunocompromised, aged <5 years or aged >65 years. Traditional influenza surveillance approaches rely upon syndromic surveillance of emergency departments and public health reporting from clinicians and laboratories. Wastewater surveillance infrastructure developed to monitor SARS-CoV-2 is being used for influenza surveillance in the Chicago area. The goal was to evaluate timeliness and correlations between influenza virus detected through wastewater surveillance and traditional influenza surveillance measures to assess utility of wastewater surveillance for influenza at the county level. Specifically, we measured correlations between influenza virus gene copies in wastewater samples and 1) the number of intensive care unit admissions associated with a diagnosis of influenza, 2) the percentage emergency department (ED) visits for influenza-like-illness, and 3) the percentage of ED visits with influenza diagnosis at discharge2 in Cook County. Influenza concentrations in wastewater were strongly correlated with traditional influenza surveillance measures, particularly for catchment areas serving >100,000 residents. Wastewater indicators lagged traditional influenza surveillance measures by approximately one week when analyzed in cross-correlations. Although wastewater data lagged traditional influenza surveillance measures in this analysis, it can serve as a useful surveillance tool as a complement to syndromic surveillance; it is a form of influenza surveillance that does not rely on healthcare-seeking behavior or reporting by healthcare providers.

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes.

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. A synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation patterns, which could also explain the observed inconsistency between qPCR quantification and sequencing outcomes. Overall, extra attention should be paid to wastewater sample processing (i.e., concentration and homogenization) for sufficient and good quality SARS-CoV-2 RNA for downstream sequencing.

Reduction and discharge of SARS-CoV-2 RNA in Chicago-area water reclamation plants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is commonly excreted in the feces and urine of infected individuals and is, therefore, detected in wastewaters where infection is present in the surrounding population. Water reclamation plants (WRPs) that treat these wastewaters commonly discharge treated effluents into the surrounding environment, yet little is known about the removal or persistence of SARS-CoV-2 RNA through wastewater treatment systems and potential for eventual release into the environment. We collected 361 24-hour composite influent and effluent samples from seven WRPs in the Greater Chicago Area in Illinois. Samples were collected over a period of 21 weeks for three large WRPs (with design max flows of 1.89-2.32 billion gallons per day and serving a combined population of 4.62 million people) and 11 weeks for four smaller WRPs (with design max flows of 96.3-186 million gallons per day and serving a combined population of >0.5 million people). A total of two of the larger WRPs implemented seasonal disinfection (using UV light or chlorination/dechlorination) for 8 weeks of this sampling period. SARS-CoV-2 RNA was quantified in the influent and effluent samples by reverse-transcription quantitative PCR (RT-qPCR) of the N1 and N2 targets of the nucleocapsid (N) gene. Although SARS-CoV-2 RNA was regularly detected in influent and effluent from all WRPs, viral RNA concentrations in the effluent samples were considerably lower, with mean effluent: influent gene copy concentration ratios ranging from 1:160 to 1:2.95 between WRPs. Samples collected while disinfection was active vs. inactive did not show any significant difference in the portion of RNA persisting through the treatment process (P > .05).

Microbial and Viral Communities and Their Antibiotic Resistance Genes Throughout a Hospital Wastewater Treatment System.

Antibiotic resistance poses a serious threat to global public health, and antibiotic resistance determinants can enter natural aquatic systems through discharge of wastewater effluents. Hospital wastewater in particular is expected to contain high abundances of antibiotic resistance genes (ARGs) compared to municipal wastewater because it contains human enteric bacteria that may include antibiotic-resistant organisms originating from hospital patients, and can also have high concentrations of antibiotics and antimicrobials relative to municipal wastewater. Viruses also play an important role in wastewater treatment systems since they can influence the bacterial community composition through killing bacteria, facilitating transduction of genetic material between organisms, and modifying the chromosomal content of bacteria as prophages. However, little is known about the fate and connections between ARGs, viruses, and their associated bacteria in hospital wastewater systems. To address this knowledge gap, we characterized the composition and persistence of ARGs, dsDNA viruses, and bacteria from influent to effluent in a pilot-scale hospital wastewater treatment system in Israel using shotgun metagenomics. Results showed that ARGs, including genes conferring resistance to antibiotics of high clinical relevance, were detected in all sampling locations throughout the pilot-scale system, with only 16% overall depletion of ARGs per genome equivalent between influent and effluent. The most common classes of ARGs detected throughout the system conferred resistance to aminoglycoside, cephalosporin, macrolide, penam, and tetracycline antibiotics. A greater proportion of total ARGs were associated with plasmid-associated genes in effluent compared to in influent. No strong associations between viral sequences and ARGs were identified in viral metagenomes from the system, suggesting that phage may not be a significant vector for ARG transfer in this system. The majority of viruses in the pilot-scale system belonged to the families Myoviridae, Podoviridae, and Siphoviridae. Gammaproteobacteria was the dominant class of bacteria harboring ARGs and the most common putative viral host in all samples, followed by Bacilli and Betaproteobacteria. In the total bacterial community, the dominant class was Betaproteobacteria for each sample. Overall, we found that a variety of different types of ARGs and viruses were persistent throughout this hospital wastewater treatment system, which can be released to the environment through effluent discharge.

Comparative Analysis of Gut Microbiota Following Changes in Training Volume Among Swimmers.

Exercise can influence gut microbial community structure and diversity; however, the temporal dynamics of this association have rarely been explored. Here we characterized fecal microbiota in response to short term changes in training volume. Fecal samples, body composition, and training logs were collected from Division I NCAA collegiate swimmers during peak training through their in-season taper in 2016 (n=9) and 2017 (n=7), capturing a systematic reduction in training volume near the conclusion of their athletic season. Fecal microbiota were characterized using 16S rRNA V4 amplicon sequencing and multivariate statistical analysis, Spearman rank correlations, and random forest models. Peak training volume, measured as swimming distance, decreased significantly during the study period from 32.6±4.8 km/wk to 11.3±8.1 km/wk (ANOVA, p<0.05); however, body composition showed no significant changes. Coinciding with the decrease in training volume, the microbial community structure showed a significant decrease in overall microbial diversity, a decrease in microbial community structural similarity, and a decrease in the proportion of the bacterial genera Faecalibacterium and Coprococcus. Together these data demonstrate a significant association between short-term changes in training volume and microbial composition and structure in the gut; future research will establish whether these changes are associated with energy balance or nutrient intake.

Influences of claywater and greenwater on the skin microbiome of cultured larval sablefish (Anoplopoma fimbria).

BACKGROUND: The skin microbiome of marine fish is thought to come from bacteria in the surrounding water during the larval stages, although it is not clear how different water conditions affect the microbial communities in the water and, in turn, the composition and development of the larval skin microbiome. In aquaculture, water conditions are especially important; claywater and greenwater are often used in larval rearing tanks to increase water turbidity. Here, we explored the effects of these water additives on microbial communities in rearing water and on the skin of first-feeding sablefish larvae using 16S rRNA gene sequencing. We evaluated three treatments: greenwater, claywater, and greenwater with a switch to claywater after 1 week. RESULTS: We observed additive-specific effects on rearing water microbial communities that coincided with the addition of larvae and rotifer feed to the tanks, such as an increase in Vibrionaceae in greenwater tanks. Additionally, microbial communities from experimental tank water, especially those in claywater, began to resemble larval skin microbiomes by the end of the experiment. The differential effects of the additives on larval sablefish skin microbiomes were largest during the first week, post-first feed. Bacteria associated with greenwater, including Vibrionaceae and Pseudoalteromonas spp., were found on larval skin a week after the switch to claywater. In addition to additive-specific effects, larval skin microbiomes also retained bacterial families likely acquired from their hatchery silos. CONCLUSIONS: Our results suggest that larval sablefish skin microbiomes are most sensitive to the surrounding seawater up to 1 week following the yolk-sac stage and that claywater substituted for greenwater after 1 week post-first feed does not significantly impact skin-associated microbial communities. However, the larval skin microbiome changes over time under all experimental conditions. Furthermore, our findings suggest a potential two-way interaction between microbial communities on the host and the surrounding environment. To our knowledge, this is one of the few studies to suggest that fish might influence the microbial community of the seawater.

Ultraviolet disinfection impacts the microbial community composition and function of treated wastewater effluent and the receiving urban river.

BACKGROUND: In the United States, an estimated 14,748 wastewater treatment plants (WWTPs) provide wastewater collection, treatment, and disposal service to more than 230 million people. The quality of treated wastewater is often assessed by the presence or absence of fecal indicator bacteria. UV disinfection of wastewater is a common final treatment step used by many wastewater treatment plants in order to reduce fecal coliform bacteria and other pathogens; however, its potential impacts on the total effluent bacterial community are seemingly varied. This is especially important given that urban WWTPs typically return treated effluent to coastal and riverine environments and thus are a major source of microorganisms, genes, and chemical compounds to these systems. Following rainfall, stormflow conditions can result in substantial increases to effluent flow into combined systems. METHODS: Here, we conducted a lab-scale UV disinfection on WWTP effluent using UV dosage of 100 mJ/cm2 and monitored the active microbiome in UV-treated effluent and untreated effluent over the course of 48 h post-exposure using 16S rRNA sequencing. In addition, we simulated stormflow conditions with effluent UV-treated and untreated effluent additions to river water and compared the microbial communities to those in baseflow river water. We also tracked the functional profiles of genes involved in tetracycline resistance (tetW) and nitrification (amoA) in these microcosms using RT-qPCR. RESULTS: We showed that while some organisms, such as members of the Bacteroidetes, are inhibited by UV disinfection and overall diversity of the microbial community decreases following treatment, many organisms not only survive, but remain active. These include common WWTP-derived organisms such as Comamonadaceae and Pseudomonas. When combined with river water to mimic stormflow conditions, these organisms can persist in the environment and potentially enhance microbial functions such as nitrification and antibiotic resistance.

Viral composition and context in metagenomes from biofilm and suspended growth municipal wastewater treatment plants.

Wastewater treatment plants (WWTPs) contain high density and diversity of viruses which can significantly impact microbial communities in aquatic systems. While previous studies have investigated viruses in WWTP samples that have been specifically concentrated for viruses and filtered to exclude bacteria, little is known about viral communities associated with bacterial communities throughout wastewater treatment systems. Additionally, differences in viral composition between attached and suspended growth wastewater treatment bioprocesses are not well characterized. Here, shotgun metagenomics was used to analyse wastewater and biomass from transects through two full-scale WWTPs for viral composition and associations with bacterial hosts. One WWTP used a suspended growth activated sludge bioreactor and the other used a biofilm reactor (trickling filter). Myoviridae, Podoviridae and Siphoviridae were the dominant viral families throughout both WWTPs, which are all from the order Caudovirales. Beta diversity analysis of viral sequences showed that samples clustered significantly both by plant and by specific sampling location. For each WWTP, the overall bacterial community structure was significantly different than community structure of bacterial taxa associated with viral sequences. These findings highlight viral community composition in transects through different WWTPs and provide context for dsDNA viral sequences in bacterial communities from these systems.

Taxon-Driven Functional Shifts Associated with Storm Flow in an Urban Stream Microbial Community.

Urban streams are susceptible to stormwater and sewage inputs that can impact their ecological health and water quality. Microbial communities in streams play important functional roles, and their composition and metabolic potential can help assess ecological state and water quality. Although these environments are highly heterogenous, little is known about the influence of isolated perturbations, such as those resulting from rain events on urban stream microbiota. Here, we examined the microbial community composition and diversity in an urban stream during dry and wet weather conditions with both 16S rRNA gene sequencing across multiple years and shotgun metagenomics to more deeply analyze a single storm flow event. Metagenomics was used to assess population-level dynamics as well as shifts in the microbial community taxonomic profile and functional potential before and after a substantial rainfall. The results demonstrated general trends present in the stream under storm flow versus base flow conditions and also highlighted the influence of increased effluent flow following rain in shifting the stream microbial community from abundant freshwater taxa to those more associated with urban/anthropogenic settings. Shifts in the taxonomic composition were also linked to changes in functional gene content, particularly for transmembrane transport and organic substance biosynthesis. We also observed an increase in relative abundance of genes encoding degradation of organic pollutants and antibiotic resistance after rain. Overall, this study highlighted some differences in the microbial community of an urban stream under storm flow conditions and showed the impact of a storm flow event on the microbiome from an environmental and public health perspective.IMPORTANCE Urban streams in various parts of the world are facing increased anthropogenic pressure on their water quality, and storm flow events represent one such source of complex physical, chemical, and biological perturbations. Microorganisms are important components of these streams from both ecological and public health perspectives. Analysis of the effect of perturbations on the stream microbial community can help improve current knowledge on the impact such chronic disturbances can have on these water resources. This study examines microbial community dynamics during rain-induced storm flow conditions in an urban stream of the Chicago Area Waterway System. Additionally, using shotgun metagenomics we identified significant shifts in the microbial community composition and functional gene content following a high-rainfall event, with potential environment and public health implications. Previous work in this area has focused on specific genes/organisms or has not assessed immediate storm flow impact.

Antibiotic resistance genes show enhanced mobilization through suspended growth and biofilm-based wastewater treatment processes.

Wastewater treatment plants (WWTPs) are known to harbor antibiotic resistance genes (ARGs) that are disseminated into the environment via effluent. However, few studies have compared abundance, mobilization and selective pressures for ARGs in WWTPs as a function of variations in secondary treatment bioprocesses. We used shotgun metagenomics to provide a comprehensive analysis of ARG composition, relationship to mobile genetic elements and co-occurrences with antibiotic production genes (APGs) throughout two full-scale municipal WWTPs, one of which employs biofilm-based secondary treatment and another that uses a suspended growth system. Results showed that abundances of ARGs declined by over 90% per genome equivalent in both types of wastewater treatment processes. However, the fractions of ARGs associated with mobile genetic elements increased substantially between influent and effluent in each plant, indicating significant mobilization of ARGs throughout both treatment processes. Strong positive correlations between ARGs and APGs were found for the aminoglycoside antibiotic class in the suspended growth system and for the streptogramin antibiotic class in the biofilm system. The biofilm and suspended growth WWTPs exhibited similarities in ARG abundances, composition and mobilization trends. However, clear differences were observed for within-plant ARG persistence. These findings suggest that both biofilm and suspended growth-based WWTPs may promote genetic mobilization of persistent ARGs that are then disseminated in effluent to receiving water bodies.

Metagenomics Reveals the Impact of Wastewater Treatment Plants on the Dispersal of Microorganisms and Genes in Aquatic Sediments.

Wastewater treatment plants (WWTPs) release treated effluent containing mobile genetic elements (MGEs), antibiotic resistance genes (ARGs), and microorganisms into the environment, yet little is known about their influence on nearby microbial communities and the retention of these factors in receiving water bodies. Our research aimed to characterize the genes and organisms from two different WWTPs that discharge into Lake Michigan, as well as from surrounding lake sediments to determine the dispersal and fate of these factors with respect to distance from the effluent outfall. Shotgun metagenomics coupled to distance-decay analyses showed a higher abundance of genes identical to those in WWTP effluent genes in sediments closer to outfall sites than in sediments farther away, indicating their possible WWTP origin. We also found genes attributed to organisms, such as those belonging to Helicobacteraceae, Legionellaceae, Moraxellaceae, and Neisseriaceae, in effluent from both WWTPs and decreasing in abundance in lake sediments with increased distance from WWTPs. Moreover, our results showed that the WWTPs likely influence the ARG composition in lake sediments close to the effluent discharge. Many of these ARGs were located on MGEs in both the effluent and sediment samples, indicating a relatively broad propensity for horizontal gene transfer (HGT). Our approach allowed us to specifically link genes to organisms and their genetic context, providing insight into WWTP impacts on natural microbial communities. Overall, our results suggest a substantial influence of wastewater effluent on gene content and microbial community structure in the sediments of receiving water bodies.IMPORTANCE Wastewater treatment plants (WWTPs) release their effluent into aquatic environments. Although treated, effluent retains many genes and microorganisms that have the potential to influence the receiving water in ways that are poorly understood. Here, we tracked the genetic footprint, including genes specific to antibiotic resistance and mobile genetic elements and their associated organisms, from WWTPs to lake sediments. Our work is novel in that we used metagenomic data sets to comprehensively evaluate total gene content and the genetic and taxonomic context of specific genes in environmental samples putatively impacted by WWTP inputs. Based on two different WWTPs with different treatment processes, our findings point to an influence of WWTPs on the presence, abundance, and composition of these factors in the environment.

Quantifying the Importance of the Rare Biosphere for Microbial Community Response to Organic Pollutants in a Freshwater Ecosystem.

A single liter of water contains hundreds, if not thousands, of bacterial and archaeal species, each of which typically makes up a very small fraction of the total microbial community (<0.1%), the so-called "rare biosphere." How often, and via what mechanisms, e.g., clonal amplification versus horizontal gene transfer, the rare taxa and genes contribute to microbial community response to environmental perturbations represent important unanswered questions toward better understanding the value and modeling of microbial diversity. We tested whether rare species frequently responded to changing environmental conditions by establishing 20-liter planktonic mesocosms with water from Lake Lanier (Georgia, USA) and perturbing them with organic compounds that are rarely detected in the lake, including 2,4-dichlorophenoxyacetic acid (2,4-D), 4-nitrophenol (4-NP), and caffeine. The populations of the degraders of these compounds were initially below the detection limit of quantitative PCR (qPCR) or metagenomic sequencing methods, but they increased substantially in abundance after perturbation. Sequencing of several degraders (isolates) and time-series metagenomic data sets revealed distinct cooccurring alleles of degradation genes, frequently carried on transmissible plasmids, especially for the 2,4-D mesocosms, and distinct species dominating the post-enrichment microbial communities from each replicated mesocosm. This diversity of species and genes also underlies distinct degradation profiles among replicated mesocosms. Collectively, these results supported the hypothesis that the rare biosphere can serve as a genetic reservoir, which can be frequently missed by metagenomics but enables community response to changing environmental conditions caused by organic pollutants, and they provided insights into the size of the pool of rare genes and species.IMPORTANCE A single liter of water or gram of soil contains hundreds of low-abundance bacterial and archaeal species, the so called rare biosphere. The value of this astonishing biodiversity for ecosystem functioning remains poorly understood, primarily due to the fact that microbial community analysis frequently focuses on abundant organisms. Using a combination of culture-dependent and culture-independent (metagenomics) techniques, we showed that rare taxa and genes commonly contribute to the microbial community response to organic pollutants. Our findings should have implications for future studies that aim to study the role of rare species in environmental processes, including environmental bioremediation efforts of oil spills or other contaminants.

Dimethylsulfoniopropionate (DMSP) Increases Survival of Larval Sablefish, Anoplopoma fimbria.

High concentrations of dimethylsulfoniopropionate (DMSP), a chemical compound released by lysed phytoplankton, may indicate high rates of grazing by zooplankton and may thus be a foraging cue for planktivorous fishes. Previous studies have shown that some planktivorous fishes and birds aggregate or alter locomotory behavior in response to this chemical cue, which is likely adaptive because it helps them locate prey. These behavioral responses have been demonstrated in juveniles and adults, but no studies have tested for effects on larval fish. Larvae suffer from high mortality rates and are vulnerable to starvation. While larvae are generally thought to be visual predators, they actually have poor vision and cryptic prey. Thus, larval fish should benefit from a chemical cue that provides information on prey abundance. We reared larval sablefish, Anoplopoma fimbria, for one week and supplemented feedings with varying concentrations of DMSP to test the hypothesis that DMSP affects larval survival. Ecologically relevant DMSP concentrations increased larval survival by up to 70 %, which has implications for production in aquaculture and recruitment in nature. These results provide a new tool for increasing larval production in aquaculture and also suggest that larvae may use DMSP as an olfactory cue. The release of DMSP may be a previously unappreciated mechanism through which phytoplankton affect larval survival and recruitment.

Strengths and limitations of 16S rRNA gene amplicon sequencing in revealing temporal microbial community dynamics.

This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GS-FLX-Ti yielding ∼40,000 rRNA gene sequences from each sample and representing ∼300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ∼10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics in situ.

Evaluation of metatranscriptomic protocols and application to the study of freshwater microbial communities.

Metatranscriptomics of environmental samples enables the identification of community activities without a priori knowledge of taxonomic or functional composition. However, several technical challenges associated with the RNA preparation protocols can affect the relative representation of transcripts and data interpretation. Here, seven replicate metatranscriptomes from planktonic freshwater samples (Lake Lanier, USA) were sequenced to evaluate technical and biological reproducibility of different RNA extraction protocols. Organic versus bead-beating extraction showed significant enrichment for low versus high G + C% mRNA populations respectively. The sequencing data were best modelled by a negative binomial distribution to account for the large technical and biological variation observed. Despite the variation, the transcriptional activities of populations that persisted in year-round metagenomes from the same site consistently showed distinct expression patterns, reflecting different ecologic strategies and allowing us to test prevailing models on the contribution of both rare biosphere and abundant members to community activity. For instance, abundant members of the Verrucomicrobia phylum systematically showed low transcriptional activity compared with other abundant taxa. Our results provide a practical guide to the analysis of metatranscriptomes and advance understanding of the activity and ecology of abundant and rare members of temperate freshwater microbial communities.

Metagenomic insights into the evolution, function, and complexity of the planktonic microbial community of Lake Lanier, a temperate freshwater ecosystem.

Lake Lanier is an important freshwater lake for the southeast United States, as it represents the main source of drinking water for the Atlanta metropolitan area and is popular for recreational activities. Temperate freshwater lakes such as Lake Lanier are underrepresented among the growing number of environmental metagenomic data sets, and little is known about how functional gene content in freshwater communities relates to that of other ecosystems. To better characterize the gene content and variability of this freshwater planktonic microbial community, we sequenced several samples obtained around a strong summer storm event and during the fall water mixing using a random whole-genome shotgun (WGS) approach. Comparative metagenomics revealed that the gene content was relatively stable over time and more related to that of another freshwater lake and the surface ocean than to soil. However, the phylogenetic diversity of Lake Lanier communities was distinct from that of soil and marine communities. We identified several important genomic adaptations that account for these findings, such as the use of potassium (as opposed to sodium) osmoregulators by freshwater organisms and differences in the community average genome size. We show that the lake community is predominantly composed of sequence-discrete populations and describe a simple method to assess community complexity based on population richness and evenness and to determine the sequencing effort required to cover diversity in a sample. This study provides the first comprehensive analysis of the genetic diversity and metabolic potential of a temperate planktonic freshwater community and advances approaches for comparative metagenomics.

Transcriptomic analysis of a marine bacterial community enriched with dimethylsulfoniopropionate.

Dimethylsulfoniopropionate (DMSP) is an important source of reduced sulfur and carbon for marine microbial communities, as well as the precursor of the climate-active gas dimethylsulfide (DMS). In this study, we used metatranscriptomic sequencing to analyze gene expression profiles of a bacterial assemblage from surface waters at the Bermuda Atlantic Time-series Study (BATS) station with and without a short-term enrichment of DMSP (25 nM for 30 min). An average of 303 143 reads were obtained per treatment using 454 pyrosequencing technology, of which 51% were potential protein-encoding sequences. Transcripts from Gammaproteobacteria and Bacteroidetes increased in relative abundance on DMSP addition, yet there was little change in the contribution of two bacterioplankton groups whose cultured members harbor known DMSP degradation genes, Roseobacter and SAR11. The DMSP addition led to an enrichment of transcripts supporting heterotrophic activity, and a depletion of those encoding light-related energy generation. Genes for the degradation of C3 compounds were significantly overrepresented after DMSP addition, likely reflecting the metabolism of the C3 component of DMSP. Mapping these transcripts to known biochemical pathways indicated that both acetyl-CoA and succinyl-CoA may be common entry points of this moiety into the tricarboxylic acid cycle. In a short time frame (30 min) in the extremely oligotrophic Sargasso Sea, different gene expression patterns suggest the use of DMSP by a diversity of marine bacterioplankton as both carbon and sulfur sources.

Spatial patterns and light-driven variation of microbial population gene expression in surface waters of the oligotrophic open ocean.

Because bacterioplankton production rates do not vary strongly across vast expanses of the ocean, it is unclear how variability in community structure corresponds with functional variability in the open ocean. We surveyed community transcript functional profiles at eight locations in the open ocean, in both the light and in the dark, using the genomic subsystems approach, to understand variability in gene expression patterns in surface waters. Metatranscriptomes from geographically distinct areas and collected during the day and night shared a large proportion of metabolic functional similarity (74%) at the finest metabolic resolution possible. The variability between metatranscriptomes could be explained by phylogenetic differences between libraries (Mantel test, P < 0.0001). Several key gene expression pathways, including Photosystem I, Photosystem II and ammonium uptake, demonstrated the most variability both geographically and between light and dark. Libraries were dominated by transcripts of the cyanobacterium Prochlorocococcus marinus, where most geographical and diel variability between metatranscriptomes reflected between-station differences in cyanobacterial phototrophic metabolism. Our results demonstrate that active genetic machinery in surface waters of the ocean is dominated by photosynthetic microorganisms and their site-to-site variability, while variability in the remainder of assemblages is dependent on local taxonomic composition.