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DeVilbiss SE, Taylor JM, Hicks M. Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment-bound bacterial communities in agricultural streams. GLOBAL CHANGE BIOLOGY 2023; 29:5615-5633. [PMID: 37548955 DOI: 10.1111/gcb.16905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023]
Abstract
Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy-stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, whereas nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.
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Affiliation(s)
- Stephen E DeVilbiss
- U.S. Geological Survey, Lower Mississippi-Gulf Water Science Center, Oxford, Mississippi, USA
| | - Jason M Taylor
- United States Department of Agriculture-Agricultural Research Service, National Sedimentation Laboratory, Oxford, Mississippi, USA
| | - Matthew Hicks
- United States Geological Survey, Lower Mississippi-Gulf Water Science Center, Jackson, Mississippi, USA
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Garner E, Davis BC, Milligan E, Blair MF, Keenum I, Maile-Moskowitz A, Pan J, Gnegy M, Liguori K, Gupta S, Prussin AJ, Marr LC, Heath LS, Vikesland PJ, Zhang L, Pruden A. Next generation sequencing approaches to evaluate water and wastewater quality. WATER RESEARCH 2021; 194:116907. [PMID: 33610927 DOI: 10.1016/j.watres.2021.116907] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 01/15/2021] [Accepted: 02/03/2021] [Indexed: 05/24/2023]
Abstract
The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.
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Affiliation(s)
- Emily Garner
- Wadsworth Department of Civil and Environmental Engineering, West Virginia University, 1306 Evansdale Drive, Morgantown, WV 26505, United States.
| | - Benjamin C Davis
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Erin Milligan
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Matthew Forrest Blair
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Ishi Keenum
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Ayella Maile-Moskowitz
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Jin Pan
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Mariah Gnegy
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Krista Liguori
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Suraj Gupta
- The Interdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA 24061, United States
| | - Aaron J Prussin
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Linsey C Marr
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Lenwood S Heath
- Department of Computer Science, Virginia Tech, 225 Stranger Street, Blacksburg, VA 24061, United States
| | - Peter J Vikesland
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States
| | - Liqing Zhang
- Department of Computer Science, Virginia Tech, 225 Stranger Street, Blacksburg, VA 24061, United States
| | - Amy Pruden
- Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, 1145 Perry Street, Blacksburg, VA 24061, United States.
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LeBrun ES, Kang S. A comparison of computationally predicted functional metagenomes and microarray analysis for microbial P cycle genes in a unique basalt-soil forest. F1000Res 2018; 7:179. [PMID: 30057749 PMCID: PMC6051228 DOI: 10.12688/f1000research.13841.1] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2018] [Indexed: 02/01/2023] Open
Abstract
Here we compared microbial results for the same Phosphorus (P) biogeochemical cycle genes from a GeoChip microarray and PICRUSt functional predictions from 16S rRNA data for 20 samples in the four spatially separated Gotjawal forests on Jeju Island in South Korea. The high homogeneity of microbial communities detected at each site allows sites to act as environmental replicates for comparing the two different functional analysis methods. We found that while both methods capture the homogeneity of the system, both differed greatly in the total abundance of genes detected, as well as the diversity of taxa detected. Additionally, we introduce a more comprehensive functional assay that again captures the homogeneity of the system but also captures more extensive community gene and taxonomic information and depth. While both methods have their advantages and limitations, PICRUSt appears better suited to asking questions specifically related to microbial community P as we did here. This comparison of methods makes important distinctions between both the results and the capabilities of each method and can help select the best tool for answering different scientific questions.
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Affiliation(s)
- Erick S. LeBrun
- Center for Reservoir and Aquatic Systems Research, Department of Biology, Baylor University, Waco, TX, 76798-7388, USA
| | - Sanghoon Kang
- Center for Reservoir and Aquatic Systems Research, Department of Biology, Baylor University, Waco, TX, 76798-7388, USA
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