Metagenomics survey unravels diversity of biogas microbiomes with potential to enhance productivity in Kenya
The obstacle to optimal utilization of biogas technology is poor understanding of biogas microbiomes diversities over a wide geographical coverage. We performed random shotgun sequencing on twelve environmental samples. Randomized complete block design was utilized to assign the twelve treatments to...
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description | The obstacle to optimal utilization of biogas technology is poor understanding of biogas microbiomes diversities over a wide geographical coverage. We performed random shotgun sequencing on twelve environmental samples. Randomized complete block design was utilized to assign the twelve treatments to four blocks, within eastern and central regions of Kenya. We obtained 42 million paired-end reads that were annotated against sixteen reference databases using two ENVO ontologies, prior to β-diversity studies. We identified 37 phyla, 65 classes and 132 orders. Bacteria dominated and comprised 28 phyla, 42 classes and 92 orders, conveying substrate's versatility in the treatments. Though, Fungi and Archaea comprised 5 phyla, the Fungi were richer; suggesting the importance of hydrolysis and fermentation in biogas production. High β-diversity within the taxa was largely linked to communities' metabolic capabilities. Clostridiales and Bacteroidales, the most prevalent guilds, metabolize organic macromolecules. The identified Cytophagales, Alteromonadales, Flavobacteriales, Fusobacteriales, Deferribacterales, Elusimicrobiales, Chlamydiales, Synergistales to mention but few, also catabolize macromolecules into smaller substrates to conserve energy. Furthermore, δ-Proteobacteria, Gloeobacteria and Clostridia affiliates syntrophically regulate PH2 and reduce metal to provide reducing equivalents. Methanomicrobiales and other Methanomicrobia species were the most prevalence Archaea, converting formate, CO2(g), acetate and methylated substrates into CH4(g). Thermococci, Thermoplasmata and Thermoprotei were among the sulfur and other metal reducing Archaea that contributed to redox balancing and other metabolism within treatments. Eukaryotes, mainly fungi were the least abundant guild, comprising largely Ascomycota and Basidiomycota species. Chytridiomycetes, Blastocladiomycetes and Mortierellomycetes were among the rare species, suggesting their metabolic and substrates limitations. Generally, we observed that environmental and treatment perturbations influenced communities' abundance, β-diversity and reactor performance largely through stochastic effect. Understanding diversity of biogas microbiomes over wide environmental variables and its' productivity provided insights into better management strategies that ameliorate biochemical limitations to effective biogas production. |
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We performed random shotgun sequencing on twelve environmental samples. Randomized complete block design was utilized to assign the twelve treatments to four blocks, within eastern and central regions of Kenya. We obtained 42 million paired-end reads that were annotated against sixteen reference databases using two ENVO ontologies, prior to β-diversity studies. We identified 37 phyla, 65 classes and 132 orders. Bacteria dominated and comprised 28 phyla, 42 classes and 92 orders, conveying substrate's versatility in the treatments. Though, Fungi and Archaea comprised 5 phyla, the Fungi were richer; suggesting the importance of hydrolysis and fermentation in biogas production. High β-diversity within the taxa was largely linked to communities' metabolic capabilities. Clostridiales and Bacteroidales, the most prevalent guilds, metabolize organic macromolecules. The identified Cytophagales, Alteromonadales, Flavobacteriales, Fusobacteriales, Deferribacterales, Elusimicrobiales, Chlamydiales, Synergistales to mention but few, also catabolize macromolecules into smaller substrates to conserve energy. Furthermore, δ-Proteobacteria, Gloeobacteria and Clostridia affiliates syntrophically regulate PH2 and reduce metal to provide reducing equivalents. Methanomicrobiales and other Methanomicrobia species were the most prevalence Archaea, converting formate, CO2(g), acetate and methylated substrates into CH4(g). Thermococci, Thermoplasmata and Thermoprotei were among the sulfur and other metal reducing Archaea that contributed to redox balancing and other metabolism within treatments. Eukaryotes, mainly fungi were the least abundant guild, comprising largely Ascomycota and Basidiomycota species. Chytridiomycetes, Blastocladiomycetes and Mortierellomycetes were among the rare species, suggesting their metabolic and substrates limitations. Generally, we observed that environmental and treatment perturbations influenced communities' abundance, β-diversity and reactor performance largely through stochastic effect. Understanding diversity of biogas microbiomes over wide environmental variables and its' productivity provided insights into better management strategies that ameliorate biochemical limitations to effective biogas production.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0244755</identifier><identifier>PMID: 33395690</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acetic acid ; Analysis ; Archaea ; Archaea - genetics ; Bacteria - genetics ; Bacteria, Anaerobic - genetics ; Bacteria, Anaerobic - metabolism ; Biodiversity ; Biofuels - microbiology ; Biogas ; Biology and Life Sciences ; Bioreactors - microbiology ; Carbon dioxide ; Ecology and Environmental Sciences ; Energy conservation ; Engineering and Technology ; Environmental conditions ; Environmental management ; Eukaryotes ; Euryarchaeota - metabolism ; Fermentation ; Fungi ; Fungi - genetics ; Guilds ; Kenya ; Kenyatta, Jomo (1894-1978) ; Macromolecules ; Medicine and Health Sciences ; Metabolism ; Metagenomics ; Metagenomics - methods ; Methane - metabolism ; Methanomicrobiales - metabolism ; Microbiomes ; Microbiota (Symbiotic organisms) ; Microbiota - genetics ; Microbiota - physiology ; Ontology ; Phylogeny ; Physical Sciences ; Productivity ; Rare species ; RNA, Ribosomal, 16S ; Stochasticity ; Substrates ; Sulfur ; Systems stability ; Taxonomy</subject><ispartof>PloS one, 2021-01, Vol.16 (1), p.e0244755-e0244755</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-767dc6eb2bbfc379f09470a5912ce6563306cc35e343da2c81a64d16c3af59c03</citedby><cites>FETCH-LOGICAL-c692t-767dc6eb2bbfc379f09470a5912ce6563306cc35e343da2c81a64d16c3af59c03</cites><orcidid>0000-0002-6581-2195 ; 0000-0002-5763-0383 ; 0000-0003-1053-085X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781671/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781671/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23865,27923,27924,53790,53792,79371,79372</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33395690$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Abdullah, Bawadi</contributor><creatorcontrib>Muturi, Samuel Mwangangi</creatorcontrib><creatorcontrib>Muthui, Lucy Wangui</creatorcontrib><creatorcontrib>Njogu, Paul Mwangi</creatorcontrib><creatorcontrib>Onguso, Justus Mong'are</creatorcontrib><creatorcontrib>Wachira, Francis Nyamu</creatorcontrib><creatorcontrib>Opiyo, Stephen Obol</creatorcontrib><creatorcontrib>Pelle, Roger</creatorcontrib><title>Metagenomics survey unravels diversity of biogas microbiomes with potential to enhance productivity in Kenya</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The obstacle to optimal utilization of biogas technology is poor understanding of biogas microbiomes diversities over a wide geographical coverage. 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Understanding diversity of biogas microbiomes over wide environmental variables and its' productivity provided insights into better management strategies that ameliorate biochemical limitations to effective biogas production.</description><subject>Acetic acid</subject><subject>Analysis</subject><subject>Archaea</subject><subject>Archaea - genetics</subject><subject>Bacteria - genetics</subject><subject>Bacteria, Anaerobic - genetics</subject><subject>Bacteria, Anaerobic - metabolism</subject><subject>Biodiversity</subject><subject>Biofuels - microbiology</subject><subject>Biogas</subject><subject>Biology and Life Sciences</subject><subject>Bioreactors - microbiology</subject><subject>Carbon dioxide</subject><subject>Ecology and Environmental Sciences</subject><subject>Energy conservation</subject><subject>Engineering and Technology</subject><subject>Environmental conditions</subject><subject>Environmental management</subject><subject>Eukaryotes</subject><subject>Euryarchaeota - metabolism</subject><subject>Fermentation</subject><subject>Fungi</subject><subject>Fungi - genetics</subject><subject>Guilds</subject><subject>Kenya</subject><subject>Kenyatta, Jomo (1894-1978)</subject><subject>Macromolecules</subject><subject>Medicine and Health Sciences</subject><subject>Metabolism</subject><subject>Metagenomics</subject><subject>Metagenomics - methods</subject><subject>Methane - metabolism</subject><subject>Methanomicrobiales - metabolism</subject><subject>Microbiomes</subject><subject>Microbiota (Symbiotic organisms)</subject><subject>Microbiota - genetics</subject><subject>Microbiota - physiology</subject><subject>Ontology</subject><subject>Phylogeny</subject><subject>Physical Sciences</subject><subject>Productivity</subject><subject>Rare species</subject><subject>RNA, Ribosomal, 16S</subject><subject>Stochasticity</subject><subject>Substrates</subject><subject>Sulfur</subject><subject>Systems stability</subject><subject>Taxonomy</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk12PEyEUhidG467Vf2CUxMToRSszMFBuTDYbPxrXbOLXLWGYMy0NhQpMtf9eamc3HbMXhgsI87wvw8s5RfG0xLOS8PLN2vfBKTvbegczXFHK6_pecV4KUk1Zhcn9k_VZ8SjGNcY1mTP2sDgjhIiaCXxe2M-Q1BKc3xgdUezDDvaod0HtwEbUmh2EaNIe-Q41xi9VRBkMPq83ENEvk1Zo6xO4ZJRFySNwK-U0oG3wba-T2R3ExqFP4PbqcfGgUzbCk2GeFN_fv_t2-XF6df1hcXlxNdVMVGnKGW81g6Zqmk4TLjosKMeqFmWlgdWMEMy0JjUQSlpV6XmpGG1LponqaqExmRTPj75b66McgoqyyhFhLjA5EIsj0Xq1lttgNirspVdG_t3wYSlVSEZbkI3SFOpmroB1lPBW0JpwUHOOmWi1aLLX2-G0vtlAq3MYQdmR6fiLMyu59DvJ-bxkvMwGrwaD4H_2EJPcmKjBWuXA98f_JoKVvMroi3_Qu283UEuVL2Bc5_O5-mAqLxjllNZVLoVJMbuDyqOF_Ma5qjqT90eC1yNBZhL8TkvVxygXX7_8P3v9Y8y-PGFXoGxaRW_7ZLyLY5AewVyBMQbobkMusTw0xU0a8tAUcmiKLHt2-kC3opsuIH8A0yAJMA</recordid><startdate>20210104</startdate><enddate>20210104</enddate><creator>Muturi, Samuel Mwangangi</creator><creator>Muthui, Lucy Wangui</creator><creator>Njogu, Paul Mwangi</creator><creator>Onguso, Justus Mong'are</creator><creator>Wachira, Francis Nyamu</creator><creator>Opiyo, Stephen Obol</creator><creator>Pelle, Roger</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-6581-2195</orcidid><orcidid>https://orcid.org/0000-0002-5763-0383</orcidid><orcidid>https://orcid.org/0000-0003-1053-085X</orcidid></search><sort><creationdate>20210104</creationdate><title>Metagenomics survey unravels diversity of biogas microbiomes with potential to enhance productivity in Kenya</title><author>Muturi, Samuel Mwangangi ; Muthui, Lucy Wangui ; Njogu, Paul Mwangi ; Onguso, Justus Mong'are ; Wachira, Francis Nyamu ; Opiyo, Stephen Obol ; Pelle, Roger</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-767dc6eb2bbfc379f09470a5912ce6563306cc35e343da2c81a64d16c3af59c03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acetic acid</topic><topic>Analysis</topic><topic>Archaea</topic><topic>Archaea - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Muturi, Samuel Mwangangi</au><au>Muthui, Lucy Wangui</au><au>Njogu, Paul Mwangi</au><au>Onguso, Justus Mong'are</au><au>Wachira, Francis Nyamu</au><au>Opiyo, Stephen Obol</au><au>Pelle, Roger</au><au>Abdullah, Bawadi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metagenomics survey unravels diversity of biogas microbiomes with potential to enhance productivity in Kenya</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-01-04</date><risdate>2021</risdate><volume>16</volume><issue>1</issue><spage>e0244755</spage><epage>e0244755</epage><pages>e0244755-e0244755</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The obstacle to optimal utilization of biogas technology is poor understanding of biogas microbiomes diversities over a wide geographical coverage. We performed random shotgun sequencing on twelve environmental samples. Randomized complete block design was utilized to assign the twelve treatments to four blocks, within eastern and central regions of Kenya. We obtained 42 million paired-end reads that were annotated against sixteen reference databases using two ENVO ontologies, prior to β-diversity studies. We identified 37 phyla, 65 classes and 132 orders. Bacteria dominated and comprised 28 phyla, 42 classes and 92 orders, conveying substrate's versatility in the treatments. Though, Fungi and Archaea comprised 5 phyla, the Fungi were richer; suggesting the importance of hydrolysis and fermentation in biogas production. High β-diversity within the taxa was largely linked to communities' metabolic capabilities. Clostridiales and Bacteroidales, the most prevalent guilds, metabolize organic macromolecules. The identified Cytophagales, Alteromonadales, Flavobacteriales, Fusobacteriales, Deferribacterales, Elusimicrobiales, Chlamydiales, Synergistales to mention but few, also catabolize macromolecules into smaller substrates to conserve energy. Furthermore, δ-Proteobacteria, Gloeobacteria and Clostridia affiliates syntrophically regulate PH2 and reduce metal to provide reducing equivalents. Methanomicrobiales and other Methanomicrobia species were the most prevalence Archaea, converting formate, CO2(g), acetate and methylated substrates into CH4(g). Thermococci, Thermoplasmata and Thermoprotei were among the sulfur and other metal reducing Archaea that contributed to redox balancing and other metabolism within treatments. Eukaryotes, mainly fungi were the least abundant guild, comprising largely Ascomycota and Basidiomycota species. Chytridiomycetes, Blastocladiomycetes and Mortierellomycetes were among the rare species, suggesting their metabolic and substrates limitations. Generally, we observed that environmental and treatment perturbations influenced communities' abundance, β-diversity and reactor performance largely through stochastic effect. Understanding diversity of biogas microbiomes over wide environmental variables and its' productivity provided insights into better management strategies that ameliorate biochemical limitations to effective biogas production.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33395690</pmid><doi>10.1371/journal.pone.0244755</doi><tpages>e0244755</tpages><orcidid>https://orcid.org/0000-0002-6581-2195</orcidid><orcidid>https://orcid.org/0000-0002-5763-0383</orcidid><orcidid>https://orcid.org/0000-0003-1053-085X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2021-01, Vol.16 (1), p.e0244755-e0244755 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2475079030 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS); EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Acetic acid Analysis Archaea Archaea - genetics Bacteria - genetics Bacteria, Anaerobic - genetics Bacteria, Anaerobic - metabolism Biodiversity Biofuels - microbiology Biogas Biology and Life Sciences Bioreactors - microbiology Carbon dioxide Ecology and Environmental Sciences Energy conservation Engineering and Technology Environmental conditions Environmental management Eukaryotes Euryarchaeota - metabolism Fermentation Fungi Fungi - genetics Guilds Kenya Kenyatta, Jomo (1894-1978) Macromolecules Medicine and Health Sciences Metabolism Metagenomics Metagenomics - methods Methane - metabolism Methanomicrobiales - metabolism Microbiomes Microbiota (Symbiotic organisms) Microbiota - genetics Microbiota - physiology Ontology Phylogeny Physical Sciences Productivity Rare species RNA, Ribosomal, 16S Stochasticity Substrates Sulfur Systems stability Taxonomy |
title | Metagenomics survey unravels diversity of biogas microbiomes with potential to enhance productivity in Kenya |
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