Revealing metabolic mechanisms of interaction in the anaerobic digestion microbiome by flux balance analysis

被引:55
作者
Basile, Arianna [1 ]
Campanaro, Stefano [1 ,2 ]
Kovalovszki, Adam [3 ]
Zampieri, Guido [1 ,4 ]
Rossi, Alessandro [1 ]
Angelidaki, Irini [3 ]
Valle, Giorgio [1 ]
Treu, Laura [1 ]
机构
[1] Univ Padua, Dept Biol, Via U Bassi 58-B, I-35121 Padua, Italy
[2] Univ Padua, CRIBI Biotechnol Ctr, I-35131 Padua, Italy
[3] Tech Univ Denmark, Dept Environm Engn, DK-2800 Lyngby, Denmark
[4] Teesside Univ, Dept Comp Sci & Informat Syst, Middlesbrough, Cleveland, England
关键词
Anaerobic digestion/flux balance analysis/genone-scale metabolic mode microbial interactions/renewable energy; VOLATILE FATTY-ACIDS; WASTE-WATER; BACTERIA; IDENTIFICATION; COMMUNITIES; GENE;
D O I
10.1016/j.ymben.2020.08.013
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Anaerobic digestion is a key biological process for renewable energy, yet the mechanistic knowledge on its hidden microbial dynamics is still limited. The present work charted the interaction network in the anaerobic digestion microbiome via the full characterization of pairwise interactions and the associated metabolite exchanges. To this goal, a novel collection of 836 genome-scale metabolic models was built to represent the functional capabilities of bacteria and archaea species derived from genome-centric metagenomics. Dominant microbes were shown to prefer mutualistic, parasitic and commensalistic interactions over neutralism, amensalism and competition, and are more likely to behave as metabolite importers and profiteers of the coexistence. Additionally, external hydrogen injection positively influences microbiome dynamics by promoting commensalism over amensalism. Finally, exchanges of glucogenic amino acids were shown to overcome auxotrophies caused by an incomplete tricarboxylic acid cycle. Our novel strategy predicted the most favourable growth conditions for the microbes, overall suggesting strategies to increasing the biogas production efficiency. In principle, this approach could also be applied to microbial populations of biomedical importance, such as the gut microbiome, to allow a broad inspection of the microbial interplays.
引用
收藏
页码:138 / 149
页数:12
相关论文
共 78 条
[1]  
AHRING BK, 1995, APPL MICROBIOL BIOT, V43, P559, DOI 10.1007/BF00218466
[2]   HTSeq-a Python']Python framework to work with high-throughput sequencing data [J].
Anders, Simon ;
Pyl, Paul Theodor ;
Huber, Wolfgang .
BIOINFORMATICS, 2015, 31 (02) :166-169
[3]   Biogas upgrading and utilization: Current status and perspectives [J].
Angelidaki, Irini ;
Treu, Laura ;
Tsapekos, Panagiotis ;
Luo, Gang ;
Campanaro, Stefano ;
Wenzel, Henrik ;
Kougias, Panagiotis G. .
BIOTECHNOLOGY ADVANCES, 2018, 36 (02) :452-466
[4]   Predictive analytics of environmental adaptability in multi-omic network models [J].
Angione, Claudio ;
Lio, Pietro .
SCIENTIFIC REPORTS, 2015, 5
[5]   Eco-evolutionary Red Queen dynamics regulate biodiversity in a metabolite-driven microbial system [J].
Bonachela, Juan A. ;
Wortel, Meike T. ;
Stenseth, Nils Chr. .
SCIENTIFIC REPORTS, 2017, 7
[6]   Interactions in the microbiome: communities of organisms and communities of genes [J].
Boon, Eva ;
Meehan, Conor J. ;
Whidden, Chris ;
Wong, Dennis H. -J. ;
Langille, Morgan G. I. ;
Beiko, Robert G. .
FEMS MICROBIOLOGY REVIEWS, 2014, 38 (01) :90-118
[7]   Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea [J].
Bowers, Robert M. ;
Kyrpides, Nikos C. ;
Stepanauskas, Ramunas ;
Harmon-Smith, Miranda ;
Doud, Devin ;
Reddy, T. B. K. ;
Schulz, Frederik ;
Jarett, Jessica ;
Rivers, Adam R. ;
Eloe-Fadrosh, Emiley A. ;
Tringe, Susannah G. ;
Ivanova, Natalia N. ;
Copeland, Alex ;
Clum, Alicia ;
Becraft, Eric D. ;
Malmstrom, Rex R. ;
Birren, Bruce ;
Podar, Mircea ;
Bork, Peer ;
Weinstock, George M. ;
Garrity, George M. ;
Dodsworth, Jeremy A. ;
Yooseph, Shibu ;
Sutton, Granger ;
Gloeckner, Frank O. ;
Gilbert, Jack A. ;
Nelson, William C. ;
Hallam, Steven J. ;
Jungbluth, Sean P. ;
Ettema, Thijs J. G. ;
Tighe, Scott ;
Konstantinidis, Konstantinos T. ;
Liu, Wen-Tso ;
Baker, Brett J. ;
Rattei, Thomas ;
Eisen, Jonathan A. ;
Hedlund, Brian ;
McMahon, Katherine D. ;
Fierer, Noah ;
Knight, Rob ;
Finn, Rob ;
Cochrane, Guy ;
Karsch-Mizrachi, Ilene ;
Tyson, Gene W. ;
Rinke, Christian ;
Lapidus, Alla ;
Meyer, Folker ;
Yilmaz, Pelin ;
Parks, Donovan H. ;
Eren, A. M. .
NATURE BIOTECHNOLOGY, 2017, 35 (08) :725-731
[8]   Recon3D enables a three-dimensional view of gene variation in human metabolism [J].
Brunk, Elizabeth ;
Sahoo, Swagatika ;
Zielinski, Daniel C. ;
Altunkaya, Ali ;
Drager, Andreas ;
Mih, Nathan ;
Gatto, Francesco ;
Nilsson, Avlant ;
Gonzalez, German Andres Preciat ;
Aurich, Maike Kathrin ;
Prlic, Andreas ;
Sastry, Anand ;
Danielsdottir, Anna D. ;
Heinken, Almut ;
Noronha, Alberto ;
Rose, Peter W. ;
Burley, Stephen K. ;
Fleming, Ronan M. T. ;
Nielsen, Jens ;
Thiele, Ines ;
Palsson, Bernhard O. .
NATURE BIOTECHNOLOGY, 2018, 36 (03) :272-+
[9]   A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems [J].
Budinich, Marko ;
Bourdon, Jeremie ;
Larhlimi, Abdelhalim ;
Eveillard, Damien .
PLOS ONE, 2017, 12 (02)
[10]   New insights from the biogas microbiome by comprehensive genome-resolved metagenomics of nearly 1600 species originating from multiple anaerobic digesters [J].
Campanaro, Stefano ;
Treu, Laura ;
Rodriguez-R, Luis M. ;
Kovalovszki, Adam ;
Ziels, Ryan M. ;
Maus, Irena ;
Zhu, Xinyu ;
Kougias, Panagiotis G. ;
Basile, Arianna ;
Luo, Gang ;
Schluter, Andreas ;
Konstantinidis, Konstantinos T. ;
Angelidaki, Irini .
BIOTECHNOLOGY FOR BIOFUELS, 2020, 13 (01)