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Griggs JL, Chi L, Hanley NM, Kohan M, Herbin-Davis K, Thomas DJ, Lu K, Fry RC, Bradham KD. Bioaccessibility of arsenic from contaminated soils and alteration of the gut microbiome in an in vitro gastrointestinal model. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 309:119753. [PMID: 35835276 PMCID: PMC9667710 DOI: 10.1016/j.envpol.2022.119753] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 06/15/2022] [Accepted: 07/08/2022] [Indexed: 05/11/2023]
Abstract
Arsenic exposure has been reported to alter the gut microbiome in mice. Activity of the gut microbiome derived from fecal microbiota has been found to affect arsenic bioaccessibility in an in vitro gastrointestinal (GI) model. Only a few studies have explored the relation between arsenic exposure and changes in the composition of the gut microbiome and in arsenic bioaccessibility. Here, we used simulated GI model system (GIMS) containing a stomach, small intestine, colon phases and microorganisms obtained from mouse feces (GIMS-F) and cecal contents (GIMS-C) to assess whether exposure to arsenic-contaminated soils affect the gut microbiome and whether composition of the gut microbiome affects arsenic bioaccessibility. Soils contaminated with arsenic did not alter gut microbiome composition in GIMS-F colon phase. In contrast, arsenic exposure resulted in the decline of bacteria in GIMS-C, including members of Clostridiaceae, Rikenellaceae, and Parabacteroides due to greater diversity and variability in microbial sensitivity to arsenic exposure. Arsenic bioaccessibility was greatest in the acidic stomach phase of GIMS (pH 1.5-1.7); except for GIMS-C colon phase exposed to mining-impacted soil in which greater levels of arsenic solubilized likely due to microbiome effects. Physicochemical properties of different test soils likely influenced variability in arsenic bioaccessibility (GIMS-F bioaccessibility range: 8-37%, GIMS-C bioaccessibility range: 2-18%) observed in this study.
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Affiliation(s)
- Jennifer L Griggs
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Liang Chi
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Nancy M Hanley
- Chemical Characterization and Exposure Division, Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709, USA
| | - Michael Kohan
- Chemical Characterization and Exposure Division, Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709, USA
| | - Karen Herbin-Davis
- Chemical Characterization and Exposure Division, Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709, USA
| | - David J Thomas
- Chemical Characterization and Exposure Division, Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709, USA
| | - Kun Lu
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Karen D Bradham
- Watershed and Ecosystem Characterization Division, Center for Environmental Measurement and Modelling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709, USA
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Modulation of microbial community dynamics by spatial partitioning. Nat Chem Biol 2022; 18:394-402. [PMID: 35145274 PMCID: PMC8967799 DOI: 10.1038/s41589-021-00961-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 12/14/2021] [Indexed: 12/21/2022]
Abstract
Microbial communities inhabit spatial architectures that divide a global environment into isolated or semi-isolated local environments, which leads to the partitioning of a microbial community into a collection of local communities. Despite its ubiquity and great interest in related processes, how and to what extent spatial partitioning affects the structures and dynamics of microbial communities is poorly understood. Using modeling and quantitative experiments with simple and complex microbial communities, we demonstrate that spatial partitioning modulates the community dynamics by altering the local interaction types and global interaction strength. Partitioning promotes the persistence of populations with negative interactions but suppresses those with positive interactions. For a community consisting of populations with both positive and negative interactions, an intermediate level of partitioning maximizes the overall diversity of the community. Our results reveal a general mechanism underlying the maintenance of microbial diversity and have implications for natural and engineered communities.
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Junkins EN, McWhirter JB, McCall LI, Stevenson BS. Environmental structure impacts microbial composition and secondary metabolism. ISME COMMUNICATIONS 2022; 2:15. [PMID: 37938679 PMCID: PMC9723690 DOI: 10.1038/s43705-022-00097-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 01/03/2022] [Accepted: 01/18/2022] [Indexed: 05/11/2023]
Abstract
Determining the drivers of microbial community assembly is a central theme of microbial ecology, and chemical ecologists seek to characterize how secondary metabolites mediate these assembly patterns. Environmental structure affects how communities assemble and what metabolic pathways aid in that assembly. Here, we bridged these two perspectives by addressing the chemical drivers of community assembly within a spatially structured landscape with varying oxygen availability. We hypothesized that structured environments would favor higher microbial diversity and metabolite diversity. We anticipated that the production of a compound would be more advantageous in a structured environment (less mixing) compared to an unstructured environment (more mixing), where the molecule would have a diminished local effect. We observed this to be partially true in our experiments: structured environments had similar microbial diversity compared to unstructured environments but differed significantly in the metabolites produced. We also found that structured environments selected for communities with higher evenness, rather than communities with higher richness. This supports the idea that when characterizing the drivers of community assembly, it matters less about who is there and more about what they are doing. Overall, these data contribute to a growing effort to approach microbial community assembly with interdisciplinary tools and perspectives.
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Affiliation(s)
- Emily N Junkins
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA.
| | - Joseph B McWhirter
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
| | - Laura-Isobel McCall
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
| | - Bradley S Stevenson
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
- Department of Earth and Planetary Science, Northwestern University, Chicago, IL, USA
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Abstract
Bacterial communities in water, soil, and humans play an essential role in environmental ecology and human health. PCR-based amplicon analysis, such as 16S rRNA sequencing, is a fundamental tool for quantifying and studying microbial composition, dynamics, and interactions. However, given the complexity of microbial communities, a substantial number of samples becomes necessary for analyses that parse the factors that determine microbial composition. A common bottleneck in performing these kinds of experiments is genomic DNA (gDNA) extraction, which is time-consuming, expensive, and often biased based on the types of species present. Direct PCR method is a potentially simpler and more accurate alternative to gDNA extraction methods that do not require the intervening purification step. In this study, we evaluated three variations of direct PCR methods using diverse heterogeneous bacterial cultures, including both Gram-positive and Gram-negative species, ZymoBIOMICS microbial community standards, and groundwater. By comparing direct PCR methods with DNeasy Blood and Tissue Kits for microbial isolates and DNeasy PowerSoil Kits for microbial communities, we found that a specific variant of the direct PCR method exhibits an overall efficiency comparable to that of the conventional DNeasy PowerSoil protocol in the circumstances we tested. We also found that the method showed higher efficiency for extracting gDNA from the Gram-negative strains compared to DNeasy Blood and Tissue protocol. This direct PCR method is 1,600 times less expensive ($0.34 for 96 samples) and 10 times simpler (15 min hands-on time for 96 samples) than the DNeasy PowerSoil protocol. The direct PCR method can also be fully automated and is compatible with small-volume samples, thereby permitting scaling of samples and replicates needed to support high-throughput large-scale bacterial community analysis. IMPORTANCE Understanding bacterial interactions and assembly in complex microbial communities using 16S rRNA sequencing normally requires a large experimental load. However, the current DNA extraction methods, including cell disruption and genomic DNA purification, are normally biased, costly, time-consuming, labor-intensive, and not amenable to miniaturization by droplets or 1,536-well plates due to the significant DNA loss during the purification step for tiny-volume and low-cell-density samples. A direct PCR method could potentially solve these problems. In this study, we developed a direct PCR method which exhibits similar efficiency as the widely used method, the DNeasy PowerSoil protocol, while being 1,600 times less expensive and 10 times faster to execute. This simple, cost-effective, and automation-friendly direct-PCR-based 16S rRNA sequencing method allows us to study the dynamics, microbial interaction, and assembly of various microbial communities in a high-throughput fashion.
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Griggs JL, Thomas DJ, Fry R, Bradham KD. Improving the predictive value of bioaccessibility assays and their use to provide mechanistic insights into bioavailability for toxic metals/metalloids - A research prospectus. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2021; 24:307-324. [PMID: 34092204 PMCID: PMC8390437 DOI: 10.1080/10937404.2021.1934764] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Widespread contamination of soil, dust, and food with toxic metal(loid)s pose a significant public health concern. Only a portion of orally ingested metal(loid) contaminants are bioavailable, which is defined as the fraction of ingested metal(loid)s absorbed across the gastrointestinal barrier and into systemic circulation. Bioaccessibility tools are a class of in vitro assays used as a surrogate to estimate risk of oral exposure and bioavailability. Although development and use of bioaccessibility tools have contributed to our understanding of the factors influencing oral bioavailability of metal(loid)s, some of these assays may lack data that support their use in decisions concerning adverse health risks and soil remediation. This review discusses the factors known to influence bioaccessibility of metal(loid) contaminants and evaluates experimental approaches and key findings of SW-846 Test Method 1340, Unified BARGE Method, Simulated Human Intestinal Microbial Ecosystem, Solubility Bioaccessibility Research Consortium assay, In Vitro Gastrointestinal model, TNO-Gastrointestinal Model, and Dutch National Institute for Public Health and the Environment bioaccessibility models which are used to assess oral absolute bioavailability and relative bioavailability in solid matrices. The aim of this review was to identify emerging knowledge gaps and research needs with an emphasis on research required to evaluate these models on (1) standardization of assay techniques and methodology, and (2) use of common criteria for assessing the performance of bioaccessibility models.
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Affiliation(s)
- Jennifer L. Griggs
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599 USA
| | - David J. Thomas
- Chemical Characterization and Exposure Division, Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709 USA
| | - Rebecca Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599 USA
| | - Karen D. Bradham
- Watershed and Ecosystem Characterization Division, Center for Environmental Measurement and Modelling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27709 USA
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Junkins EN, Stevenson BS. Using Plate-Wash PCR and High-Throughput Sequencing to Measure Cultivated Diversity for Natural Product Discovery Efforts. Front Microbiol 2021; 12:675798. [PMID: 34354680 PMCID: PMC8329497 DOI: 10.3389/fmicb.2021.675798] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/28/2021] [Indexed: 12/16/2022] Open
Abstract
Molecular techniques continue to reveal a growing disparity between the immense diversity of microbial life and the small proportion that is in pure culture. The disparity, originally dubbed “the great plate count anomaly” by Staley and Konopka, has become even more vexing given our increased understanding of the importance of microbiomes to a host and the role of microorganisms in the vital biogeochemical functions of our biosphere. Searching for novel antimicrobial drug targets often focuses on screening a broad diversity of microorganisms. If diverse microorganisms are to be screened, they need to be cultivated. Recent innovative research has used molecular techniques to assess the efficacy of cultivation efforts, providing invaluable feedback to cultivation strategies for isolating targeted and/or novel microorganisms. Here, we aimed to determine the efficiency of cultivating representative microorganisms from a non-human, mammalian microbiome, identify those microorganisms, and determine the bioactivity of isolates. Sequence-based data indicated that around 57% of the ASVs detected in the original inoculum were cultivated in our experiments, but nearly 53% of the total ASVs that were present in our cultivation experiments were not detected in the original inoculum. In light of our controls, our data suggests that when molecular tools were used to characterize our cultivation efforts, they provided a more complete and more complex, understanding of which organisms were present compared to what was eventually detected during cultivation. Lastly, about 3% of the isolates collected from our cultivation experiments showed inhibitory bioactivity against an already multidrug-resistant pathogen panel, further highlighting the importance of informing and directing future cultivation efforts with molecular tools.
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Affiliation(s)
- Emily N Junkins
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, United States
| | - Bradley S Stevenson
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, United States
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Lui LM, Majumder ELW, Smith HJ, Carlson HK, von Netzer F, Fields MW, Stahl DA, Zhou J, Hazen TC, Baliga NS, Adams PD, Arkin AP. Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology. Front Microbiol 2021; 12:642422. [PMID: 33841364 PMCID: PMC8024649 DOI: 10.3389/fmicb.2021.642422] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 02/22/2021] [Indexed: 11/13/2022] Open
Abstract
Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.
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Affiliation(s)
- Lauren M. Lui
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Erica L.-W. Majumder
- Department of Bacteriology, University of Wisconsin–Madison, Madison, WI, United States
| | - Heidi J. Smith
- Center for Biofilm Engineering, Department of Microbiology and Immunology, Montana State University, Bozeman, MT, United States
| | - Hans K. Carlson
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Frederick von Netzer
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Matthew W. Fields
- Center for Biofilm Engineering, Department of Microbiology and Immunology, Montana State University, Bozeman, MT, United States
| | - David A. Stahl
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Jizhong Zhou
- Institute for Environmental Genomics, Department of Microbiology & Plant Biology, School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, United States
| | - Terry C. Hazen
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | | | - Paul D. Adams
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
| | - Adam P. Arkin
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
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Aguirre de Cárcer D. Experimental and computational approaches to unravel microbial community assembly. Comput Struct Biotechnol J 2020; 18:4071-4081. [PMID: 33363703 PMCID: PMC7736701 DOI: 10.1016/j.csbj.2020.11.031] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 12/12/2022] Open
Abstract
Microbial communities have a preponderant role in the life support processes of our common home planet Earth. These extremely diverse communities drive global biogeochemical cycles, and develop intimate relationships with most multicellular organisms, with a significant impact on their fitness. Our understanding of their composition and function has enjoyed a significant thrust during the last decade thanks to the rise of high-throughput sequencing technologies. Intriguingly, the diversity patterns observed in nature point to the possible existence of fundamental community assembly rules. Unfortunately, these rules are still poorly understood, despite the fact that their knowledge could spur a scientific, technological, and economic revolution, impacting, for instance, agricultural, environmental, and health-related practices. In this minireview, I recapitulate the most important wet lab techniques and computational approaches currently employed in the study of microbial community assembly, and briefly discuss various experimental designs. Most of these approaches and considerations are also relevant to the study of microbial microevolution, as it has been shown that it can occur in ecological relevant timescales. Moreover, I provide a succinct review of various recent studies, chosen based on the diversity of ecological concepts addressed, experimental designs, and choice of wet lab and computational techniques. This piece aims to serve as a primer to those new to the field, as well as a source of new ideas to the more experienced researchers.
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Free A, McDonald MA, Pagaling E. Diversity-Function Relationships in Natural, Applied, and Engineered Microbial Ecosystems. ADVANCES IN APPLIED MICROBIOLOGY 2018; 105:131-189. [PMID: 30342721 DOI: 10.1016/bs.aambs.2018.07.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The connection between ecosystem function and taxonomic diversity has been of interest and relevance to macroecologists for decades. After many years of lagging behind due to the difficulty of assigning both taxonomy and function to poorly distinguishable microscopic cells, microbial ecology now has access to a suite of powerful molecular tools which allow its practitioners to generate data relating to diversity and function of a microbial community on an unprecedented scale. Instead, the problem facing today's microbial ecologists is coupling the ease of generation of these datasets with the formulation and testing of workable hypotheses relating the diversity and function of environmental, host-associated, and engineered microbial communities. Here, we review the current state of knowledge regarding the links between taxonomic alpha- and beta-diversity and ecosystem function, comparing our knowledge in this area to that obtained by macroecologists who use more traditional techniques. We consider the methodologies that can be applied to study these properties and how successful they are at linking function to diversity, using examples from the study of model microbial ecosystems, methanogenic bioreactors (anaerobic digesters), and host-associated microbiota. Finally, we assess ways in which our newly acquired understanding might be used to manipulate diversity in ecosystems of interest in order to improve function for the benefit of us or the environment in general through the provision of ecosystem services.
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Affiliation(s)
- Andrew Free
- School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Michael A McDonald
- School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Eulyn Pagaling
- The James Hutton Institute, Craigiebuckler, Aberdeen, United Kingdom
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