1
|
Cheng H, Monjed MK, Myshkevych Y, Wang T, Hong PY. Accounting for the microbial assembly of each process in wastewater treatment plants (WWTPs): study of four WWTPs receiving similar influent streams. Appl Environ Microbiol 2024; 90:e0225323. [PMID: 38440988 PMCID: PMC11022531 DOI: 10.1128/aem.02253-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 02/08/2024] [Indexed: 03/06/2024] Open
Abstract
We evaluated a unique model in which four full-scale wastewater treatment plants (WWTPs) with the same treatment schematic and fed with similar influent wastewater were tracked over an 8-month period to determine whether the community assembly would differ in the activated sludge (AS) and sand filtration (SF) stages. For each WWTP, AS and SF achieved an average of 1-log10 (90%) and <0.02-log10 (5%) reduction of total cells, respectively. Despite the removal of cells, both AS and SF had a higher alpha and beta diversity compared to the influent microbial community. Using the Sloan neutral model, it was observed that AS and SF were individually dominated by different assembly processes. Specifically, microorganisms from influent to AS were predominantly determined by the selective niche process for all WWTPs, while the microbial community in the SF was relatively favored by a stochastic, random migration process, except two WWTPs. AS also contributed more to the final effluent microbial community compared with the SF. Given that each WWTP operates the AS independently and that there is a niche selection process driven mainly by the chemical oxygen demand concentration, operational taxonomic units unique to each of the WWTPs were also identified. The findings from this study indicate that each WWTP has its distinct microbial signature and could be used for source-tracking purposes.IMPORTANCEThis study provided a novel concept that microorganisms follow a niche assembly in the activated sludge (AS) tank and that the AS contributed more than the sand filtration process toward the final microbial signature that is unique to each treatment plant. This observation highlights the importance of understanding the microbial community selected by the AS stage, which could contribute toward source-tracking the effluent from different wastewater treatment plants.
Collapse
Affiliation(s)
- Hong Cheng
- Key Laboratory of Eco-environments in Three Gorges Reservoir Region, Ministry of Education, College of Environment and Ecology, Chongqing University, Chongqing, China
- Environmental Science and Engineering, Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Mohammad K. Monjed
- Department of Biology, Faculty of Applied Science, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Yevhen Myshkevych
- Environmental Science and Engineering, Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Tiannyu Wang
- Water Desalination and Reuse Center, Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Pei-Ying Hong
- Environmental Science and Engineering, Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Water Desalination and Reuse Center, Biological and Environmental Sciences & Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| |
Collapse
|
2
|
Durán-Viseras A, Lindner BG, Hatt JK, Lai A, Wallace R, Ginn O, Brown J, Konstantinidis KT. Metagenomic insights into the impact of litter from poultry Concentrated Animal Feeding Operations (CAFOs) to adjacent soil and water microbial communities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 920:170772. [PMID: 38346660 DOI: 10.1016/j.scitotenv.2024.170772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/02/2024] [Accepted: 02/04/2024] [Indexed: 02/20/2024]
Abstract
In recent decades, human food consumption has led to an increased demand for animal-based foods, particularly chicken meat production. The state of Georgia, USA is one of the top broiler chicken producers in the United States, where animals are raised in Concentrated Animal Feeding Operations (CAFOs). Without proper management, CAFOs could negatively impact the environment and become a public health risk as a source of water and air pollution and/or by spreading antimicrobial resistance genes. In this study, we used metagenome sequencing to investigate the impact of the application of the CAFO's litter on adjacent soils and downstream creek waters in terms of microbial diversity and antimicrobial resistance profile changes. Our data indicate that while a few microbial groups increased in abundance within a short period of time after litter application, these populations subsequently decreased to levels similar to those found prior to the litter application or to below the detection limit of our metagenome sequencing effort. Microbial taxonomic composition analyses, relative abundance of Metagenome-Assembled Genomes (MAGs) and detection of Antimicrobial Resistance Genes (ARGs) allow us to conclude that this practice of litter application had a negligible effect on the microbiome or resistome profile of these soils and nearby waterways, likely due to its dilution in the field and/or outcompetition by indigenous microbes, revealing a minimal impact of these poultry facilities on the natural microbial communities.
Collapse
Affiliation(s)
- Ana Durán-Viseras
- Department of Microbiology and Parasitology, Faculty of Pharmacy, University of Sevilla, Sevilla 41012, Spain; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Blake G Lindner
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Janet K Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Amanda Lai
- Southern California Coastal Water Research Project, Costa Mesa, CA 92626, USA
| | - Robert Wallace
- Georgia Tech Research Institute, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Olivia Ginn
- Chemical, Materials and Biomedical Engineering Department and Institute for Bioinformatics, University of Georgia, Athens, GA 30601, USA
| | - Joe Brown
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | | |
Collapse
|
3
|
Royer C, Patin NV, Jesser KJ, Peña-Gonzalez A, Hatt JK, Trueba G, Levy K, Konstantinidis KT. Comparison of metagenomic and traditional methods for diagnosis of E. coli enteric infections. mBio 2024; 15:e0342223. [PMID: 38488359 PMCID: PMC11005377 DOI: 10.1128/mbio.03422-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 02/23/2024] [Indexed: 04/11/2024] Open
Abstract
Diarrheagenic Escherichia coli, collectively known as DEC, is a leading cause of diarrhea, particularly in children in low- and middle-income countries. Diagnosing infections caused by different DEC pathotypes traditionally relies on the cultivation and identification of virulence genes, a resource-intensive and error-prone process. Here, we compared culture-based DEC identification with shotgun metagenomic sequencing of whole stool using 35 randomly drawn samples from a cohort of diarrhea-afflicted patients. Metagenomic sequencing detected the cultured isolates in 97% of samples, revealing, overall, reliable detection by this approach. Genome binning yielded high-quality E. coli metagenome-assembled genomes (MAGs) for 13 samples, and we observed that the MAG did not carry the diagnostic DEC virulence genes of the corresponding isolate in 60% of these samples. Specifically, two distinct scenarios were observed: diffusely adherent E. coli (DAEC) isolates without corresponding DAEC MAGs appeared to be relatively rare members of the microbiome, which was further corroborated by quantitative PCR (qPCR), and thus unlikely to represent the etiological agent in 3 of the 13 samples (~23%). In contrast, ETEC virulence genes were located on plasmids and largely escaped binning in associated MAGs despite being prevalent in the sample (5/13 samples or ~38%), revealing limitations of the metagenomic approach. These results provide important insights for diagnosing DEC infections and demonstrate how metagenomic methods can complement isolation efforts and PCR for pathogen identification and population abundance. IMPORTANCE Diagnosing enteric infections based on traditional methods involving isolation and PCR can be erroneous due to isolation and other biases, e.g., the most abundant pathogen may not be recovered on isolation media. By employing shotgun metagenomics together with traditional methods on the same stool samples, we show that mixed infections caused by multiple pathogens are much more frequent than traditional methods indicate in the case of acute diarrhea. Further, in at least 8.5% of the total samples examined, the metagenomic approach reliably identified a different pathogen than the traditional approach. Therefore, our results provide a methodology to complement existing methods for enteric infection diagnostics with cutting-edge, culture-independent metagenomic techniques, and highlight the strengths and limitations of each approach.
Collapse
Affiliation(s)
- C. Royer
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - N. V. Patin
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - K. J. Jesser
- Department of Environmental and Occupational Health, University of Washington, Seattle, Washington, USA
| | - A. Peña-Gonzalez
- Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogotà, Colombia
| | - J. K. Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - G. Trueba
- Institute of Microbiology, Universidad San Francisco de Quito, Quito, Ecuador
| | - K. Levy
- Department of Environmental and Occupational Health, University of Washington, Seattle, Washington, USA
| | - K. T. Konstantinidis
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| |
Collapse
|
4
|
Cha G, Zhu KJ, Fischer JM, Flores CI, Brown J, Pinto A, Hatt JK, Konstantinidis KT, Graham KE. Metagenomic evaluation of the performance of passive Moore swabs for sewage monitoring relative to composite sampling over time resolved deployments. WATER RESEARCH 2024; 253:121269. [PMID: 38359595 DOI: 10.1016/j.watres.2024.121269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 01/07/2024] [Accepted: 02/05/2024] [Indexed: 02/17/2024]
Abstract
Moore swabs have re-emerged as a versatile tool in the field of wastewater-based epidemiology during the COVID-19 pandemic and offer unique advantages for monitoring pathogens in sewer systems, especially at the neighborhood-level. However, whether Moore swabs provide comparable results to more commonly used composite samples remains to be rigorously tested including the optimal duration of Moore swab deployment. This study provides new insights into these issues by comparing the results from Moore swab samples to those of paired composite samples collected from the same sewer lines continuously over six to seventy-two hours post-deployment, during low COVID-19 prevalence periods. Our results show that Moore swabs accumulated approximately 10-fold higher PMMoV concentrations (on a basis of mL of Moore swab squeezed filtrate to mL of composite sewage) and showed comparable trends in terms of bacterial species abundance when compared to composite samples. Moore swabs also generally captured higher SARS-CoV-2 N1/N2 RNA concentrations than composite samples. Moore swabs showed comparable trends in terms of abundance dynamics of the sewage microbiome to composite samples and variable signs of saturation over time that were site and/or microbial population-specific. Based on our dual ddRT-PCR and shotgun metagenomic approach, we find that Moore swabs at our sites were optimally deployed for 6 h at a time at two sites.
Collapse
Affiliation(s)
- Gyuhyon Cha
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Kevin J Zhu
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
| | - Jamie M Fischer
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Camryn I Flores
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Joe Brown
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
| | - Ameet Pinto
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Janet K Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - Katherine E Graham
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
| |
Collapse
|
5
|
Lindner BG, Gerhardt K, Feistel DJ, Rodriguez-R LM, Hatt JK, Konstantinidis KT. A user's guide to the bioinformatic analysis of shotgun metagenomic sequence data for bacterial pathogen detection. Int J Food Microbiol 2024; 410:110488. [PMID: 38035404 DOI: 10.1016/j.ijfoodmicro.2023.110488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 09/15/2023] [Accepted: 11/11/2023] [Indexed: 12/02/2023]
Abstract
Metagenomics, i.e., shotgun sequencing of the total microbial community DNA from a sample, has become a mature technique but its application to pathogen detection in clinical, environmental, and food samples is far from common or standardized. In this review, we summarize ongoing developments in metagenomic sequence analysis that facilitate its wider application to pathogen detection. We examine theoretical frameworks for estimating the limit of detection for a particular level of sequencing effort, current approaches for achieving species and strain analytical resolution, and discuss some relevant modern tools for these tasks. While these recent advances are significant and establish metagenomics as a powerful tool to provide insights not easily attained by culture-based approaches, metagenomics is unlikely to emerge as a widespread, routine monitoring tool in the near future due to its inherently high detection limits, cost, and inability to easily distinguish between viable and non-viable cells. Instead, metagenomics seems best poised for applications involving special circumstances otherwise challenging for culture-based and molecular (e.g., PCR-based) approaches such as the de novo detection of novel pathogens, cases of co-infection by more than one pathogen, and situations where it is important to assess the genomic composition of the pathogenic population(s) and/or its impact on the indigenous microbiome.
Collapse
Affiliation(s)
- Blake G Lindner
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Kenji Gerhardt
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Dorian J Feistel
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis M Rodriguez-R
- Department of Microbiology, Digital Science Center (DiSC), University of Innsbruck, Innsbruck, Austria
| | - Janet K Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Konstantinos T Konstantinidis
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
| |
Collapse
|
6
|
Woodworth MH, Conrad RE, Haldopoulos M, Pouch SM, Babiker A, Mehta AK, Sitchenko KL, Wang CH, Strudwick A, Ingersoll JM, Philippe C, Lohsen S, Kocaman K, Lindner BG, Hatt JK, Jones RM, Miller C, Neish AS, Friedman-Moraco R, Karadkhele G, Liu KH, Jones DP, Mehta CC, Ziegler TR, Weiss DS, Larsen CP, Konstantinidis KT, Kraft CS. Fecal microbiota transplantation promotes reduction of antimicrobial resistance by strain replacement. Sci Transl Med 2023; 15:eabo2750. [PMID: 37910603 PMCID: PMC10821315 DOI: 10.1126/scitranslmed.abo2750] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/05/2023] [Indexed: 11/03/2023]
Abstract
Multidrug-resistant organism (MDRO) colonization is a fundamental challenge in antimicrobial resistance. Limited studies have shown that fecal microbiota transplantation (FMT) can reduce MDRO colonization, but its mechanisms are poorly understood. We conducted a randomized, controlled trial of FMT for MDRO decolonization in renal transplant recipients called PREMIX (NCT02922816). Eleven participants were enrolled and randomized 1:1 to FMT or an observation period followed by delayed FMT if stool cultures were MDRO positive at day 36. Participants who were MDRO positive after one FMT were treated with a second FMT. At last visit, eight of nine patients who completed all treatments were MDRO culture negative. FMT-treated participants had longer time to recurrent MDRO infection versus PREMIX-eligible controls who were not treated with FMT. Key taxa (Akkermansia muciniphila, Alistipes putredinis, Phocaeicola dorei, Phascolarctobacterium faecium, Alistipes species, Mesosutterella massiliensis, Barnesiella intestinihominis, and Faecalibacterium prausnitzii) from the single feces donor used in the study that engrafted in recipients and metabolites such as short-chain fatty acids and bile acids in FMT-responding participants uncovered leads for rational microbiome therapeutic and diagnostic development. Metagenomic analyses revealed a previously unobserved mechanism of MDRO eradication by conspecific strain competition in an FMT-treated subset. Susceptible Enterobacterales strains that replaced baseline extended-spectrum β-lactamase-producing strains were not detectable in donor microbiota manufactured as FMT doses but in one case were detectable in the recipient before FMT. These data suggest that FMT may provide a path to exploit strain competition to reduce MDRO colonization.
Collapse
Affiliation(s)
- Michael H. Woodworth
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Emory Antibiotic Resistance Center; Atlanta, Georgia, 30322, USA
| | - Roth E Conrad
- Ocean Science & Engineering, School of Biological Sciences, Georgia Institute of Technology; Atlanta, Georgia, 30332, USA
| | | | - Stephanie M. Pouch
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Emory Antibiotic Resistance Center; Atlanta, Georgia, 30322, USA
| | - Ahmed Babiker
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Emory Antibiotic Resistance Center; Atlanta, Georgia, 30322, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Aneesh K. Mehta
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Emory Transplant Center; Atlanta, Georgia, 30322, USA
| | - Kaitlin L. Sitchenko
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Charlotte H. Wang
- Emory College of Arts and Sciences, Emory University; Atlanta, Georgia, 30322, USA
| | - Amanda Strudwick
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Jessica M. Ingersoll
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Cécile Philippe
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Sarah Lohsen
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Kumru Kocaman
- School of Civil and Environmental Engineering, Georgia Institute of Technology; Atlanta, Georgia, 30332, USA
| | - Blake G. Lindner
- School of Civil and Environmental Engineering, Georgia Institute of Technology; Atlanta, Georgia, 30332, USA
| | - Janet K. Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology; Atlanta, Georgia, 30332, USA
| | - Rheinallt M. Jones
- Division of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Candace Miller
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Andrew S. Neish
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - Rachel Friedman-Moraco
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | | | - Ken H. Liu
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University; Atlanta, Georgia, 30322, USA
| | - Dean P. Jones
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University; Atlanta, Georgia, 30322, USA
| | - C. Christina Mehta
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University; Atlanta, GA, 30322, USA
| | - Thomas R. Ziegler
- Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| | - David S. Weiss
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Emory Antibiotic Resistance Center; Atlanta, Georgia, 30322, USA
| | | | | | - Colleen S. Kraft
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
- Emory Antibiotic Resistance Center; Atlanta, Georgia, 30322, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine; Atlanta, Georgia, 30322, USA
| |
Collapse
|
7
|
Albright S, Louca S. Trait biases in microbial reference genomes. Sci Data 2023; 10:84. [PMID: 36759614 PMCID: PMC9911409 DOI: 10.1038/s41597-023-01994-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 01/31/2023] [Indexed: 02/11/2023] Open
Abstract
Common culturing techniques and priorities bias our discovery towards specific traits that may not be representative of microbial diversity in nature. So far, these biases have not been systematically examined. To address this gap, here we use 116,884 publicly available metagenome-assembled genomes (MAGs, completeness ≥80%) from 203 surveys worldwide as a culture-independent sample of bacterial and archaeal diversity, and compare these MAGs to the popular RefSeq genome database, which heavily relies on cultures. We compare the distribution of 12,454 KEGG gene orthologs (used as trait proxies) in the MAGs and RefSeq genomes, while controlling for environment type (ocean, soil, lake, bioreactor, human, and other animals). Using statistical modeling, we then determine the conditional probabilities that a species is represented in RefSeq depending on its genetic repertoire. We find that the majority of examined genes are significantly biased for or against in RefSeq. Our systematic estimates of gene prevalences across bacteria and archaea in nature and gene-specific biases in reference genomes constitutes a resource for addressing these issues in the future.
Collapse
Affiliation(s)
- Sage Albright
- Department of Biology, University of Oregon, Eugene, USA
| | - Stilianos Louca
- Department of Biology, University of Oregon, Eugene, USA. .,Institute of Ecology and Evolution, University of Oregon, Eugene, USA.
| |
Collapse
|
8
|
Roguet A, Newton RJ, Eren AM, McLellan SL. Guts of the Urban Ecosystem: Microbial Ecology of Sewer Infrastructure. mSystems 2022; 7:e0011822. [PMID: 35762794 PMCID: PMC9426572 DOI: 10.1128/msystems.00118-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/25/2022] [Indexed: 11/20/2022] Open
Abstract
Microbes have inhabited the oceans and soils for millions of years and are uniquely adapted to their habitat. In contrast, sewer infrastructure in modern cities dates back only ~150 years. Sewer pipes transport human waste and provide a view into public health, but the resident organisms that likely modulate these features are relatively unexplored. Here, we show that the bacterial assemblages sequenced from untreated wastewater in 71 U.S. cities were highly coherent at a fine sequence level, suggesting that urban infrastructure separated by great spatial distances can give rise to strikingly similar communities. Within the overall microbial community structure, temperature had a discernible impact on the distribution patterns of closely related amplicon sequence variants, resulting in warm and cold ecotypes. Two bacterial genera were dominant in most cities regardless of their size or geographic location; on average, Arcobacter accounted for 11% and Acinetobacter 10% of the entire community. Metagenomic analysis of six cities revealed these highly abundant resident organisms carry clinically important antibiotic resistant genes blaCTX-M, blaOXA, and blaTEM. In contrast, human fecal bacteria account for only ~13% of the community; therefore, antibiotic resistance gene inputs from human sources to the sewer system could be comparatively small, which will impact measurement capabilities when monitoring human populations using wastewater. With growing awareness of the metabolic potential of microbes within these vast networks of pipes and the ability to examine the health of human populations, it is timely to increase our understanding of the ecology of these systems. IMPORTANCE Sewer infrastructure is a relatively new habitat comprised of thousands of kilometers of pipes beneath cities. These wastewater conveyance systems contain large reservoirs of microbial biomass with a wide range of metabolic potential and are significant reservoirs of antibiotic resistant organisms; however, we lack an adequate understanding of the ecology or activity of these communities beyond wastewater treatment plants. The striking coherence of the sewer microbiome across the United States demonstrates that the sewer environment is highly selective for a particular microbial community composition. Therefore, results from more in-depth studies or proven engineering controls in one system could be extrapolated more broadly. Understanding the complex ecology of sewer infrastructure is critical for not only improving our ability to treat human waste and increasing the sustainability of our cities but also to create scalable and effective sewage microbial observatories, which are inevitable investments of the future to monitor health in human populations.
Collapse
Affiliation(s)
- Adélaïde Roguet
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - Ryan J. Newton
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - A. Murat Eren
- Helmholtz Institute for Functional Marine Biodiversity, Oldenburg, Germany
- Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA
| | - Sandra L. McLellan
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| |
Collapse
|
9
|
Abstract
Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases.
Collapse
|