Cellulose-induced shifts in microbial communities and microbial interactions in an anoxic/aerobic membrane bioreactor

2021 ◽  
Vol 42 ◽  
pp. 102106
Author(s):  
Chunli Chen ◽  
Zhihao Gan ◽  
Ronghua Xu ◽  
Fangang Meng
2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.


2018 ◽  
Vol 35 (13) ◽  
pp. 2332-2334 ◽  
Author(s):  
Federico Baldini ◽  
Almut Heinken ◽  
Laurent Heirendt ◽  
Stefania Magnusdottir ◽  
Ronan M T Fleming ◽  
...  

Abstract Motivation The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. Results To address this gap, we created a comprehensive toolbox to model (i) microbe–microbe and host–microbe metabolic interactions, and (ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the constraint-based reconstruction and analysis toolbox. Availability and implementation The Microbiome Modeling Toolbox and the tutorials at https://git.io/microbiomeModelingToolbox.


2022 ◽  
Author(s):  
Gayathri Sambamoorthy ◽  
Karthik Raman

Microbes thrive in communities, embedded in a complex web of interactions. These interactions, particularly metabolic interactions, play a crucial role in maintaining the community structure and function. As the organisms thrive and evolve, a variety of evolutionary processes alter the interactions among the organisms in the community, although the community function remains intact. In this work, we simulate the evolution of two-member microbial communities in silico to study how evolutionary forces can shape the interactions between organisms. We employ genomescale metabolic models of organisms from the human gut, which exhibit a range of interaction patterns, from mutualism to parasitism. We observe that the evolution of microbial interactions varies depending upon the starting interaction and also on the metabolic capabilities of the organisms in the community. We find that evolutionary constraints play a significant role in shaping the dependencies of organisms in the community. Evolution of microbial communities yields fitness benefits in only a small fraction of the communities, and is also dependent on the interaction type of the wild-type communities. The metabolites cross-fed in the wild-type communities appear in only less than 50% of the evolved communities. A wide range of new metabolites are cross-fed as the communities evolve. Further, the dynamics of microbial interactions are not specific to the interaction of the wild-type community but vary depending on the organisms present in the community. Our approach of evolving microbial communities in silico provides an exciting glimpse of the dynamics of microbial interactions and offers several avenues for future investigations.


2018 ◽  
Vol 54 (3) ◽  
pp. 363-372 ◽  
Author(s):  
Xingang Zhou ◽  
Jianhui Zhang ◽  
Dandan Pan ◽  
Xin Ge ◽  
Xue Jin ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Anthony Horner ◽  
Samuel S. Browett ◽  
Rachael E. Antwis

AbstractModern agricultural practices have vastly increased crop production but negatively affected soil health. As such, there is a call to develop sustainable, ecologically-viable approaches to food production. Mixed-cropping of plant varieties can increase yields, although impacts on plant-associated microbial communities are unclear, despite their critical role in plant health and broader ecosystem function. We investigated how mixed-cropping between two field pea (Pisum sativum L.) varieties (Winfreda and Ambassador) influenced root-associated microbial communities and yield. The two varieties supported significantly different fungal and bacterial communities when grown as mono-crops. Mixed-cropping caused changes in microbial communities but with differences between varieties. Root bacterial communities of Winfreda remained stable in response to mixed-cropping, whereas those of Ambassador became more similar to Winfreda. Conversely, root fungal communities of Ambassador remained stable under mixed-cropping, and those of Winfreda shifted towards the composition of Ambassador. Microbial co-occurrence networks of both varieties were stronger and larger under mixed-cropping, which may improve stability and resilience in agricultural soils. Both varieties produced slightly higher yields under mixed-cropping, although overall Ambassador plants produced higher yields than Winfreda plants. Our results suggest that variety diversification may increase yield and promote microbial interactions.


2019 ◽  
Vol 366 (11) ◽  
Author(s):  
Alan R Pacheco ◽  
Daniel Segrè

ABSTRACTBeyond being simply positive or negative, beneficial or inhibitory, microbial interactions can involve a diverse set of mechanisms, dependencies and dynamical properties. These more nuanced features have been described in great detail for some specific types of interactions, (e.g. pairwise metabolic cross-feeding, quorum sensing or antibiotic killing), often with the use of quantitative measurements and insight derived from modeling. With a growing understanding of the composition and dynamics of complex microbial communities for human health and other applications, we face the challenge of integrating information about these different interactions into comprehensive quantitative frameworks. Here, we review the literature on a wide set of microbial interactions, and explore the potential value of a formal categorization based on multidimensional vectors of attributes. We propose that such an encoding can facilitate systematic, direct comparisons of interaction mechanisms and dependencies, and we discuss the relevance of an atlas of interactions for future modeling and rational design efforts.


mSystems ◽  
2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Elizabeth A. Shank

ABSTRACT Over the last decades, sequencing technologies have transformed our ability to investigate the composition and functional capacity of microbial communities. Even so, critical questions remain about these complex systems that cannot be addressed by the bulk, community-averaged data typically provided by sequencing methods. In this Perspective, I propose that future advances in microbiome research will emerge from considering “the lives of microbes”: we need to create methods to explicitly interrogate how microbes exist and interact in native-setting-like microenvironments. This approach includes developing approaches that expose the phenotypic heterogeneity of microbes; exploring the effects of coculture cues on cellular differentiation and metabolite production; and designing visualization systems that capture features of native microbial environments while permitting the nondestructive observation of microbial interactions over space and time with single-cell resolution.


2012 ◽  
Vol 113 ◽  
pp. 181-190 ◽  
Author(s):  
Dimuth Navaratna ◽  
Jennifer Elliman ◽  
Alanna Cooper ◽  
Li Shu ◽  
Kanagaratnam Baskaran ◽  
...  

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Cameron Wagg ◽  
Klaus Schlaeppi ◽  
Samiran Banerjee ◽  
Eiko E. Kuramae ◽  
Marcel G. A. van der Heijden

Abstract The soil microbiome is highly diverse and comprises up to one quarter of Earth’s diversity. Yet, how such a diverse and functionally complex microbiome influences ecosystem functioning remains unclear. Here we manipulated the soil microbiome in experimental grassland ecosystems and observed that microbiome diversity and microbial network complexity positively influenced multiple ecosystem functions related to nutrient cycling (e.g. multifunctionality). Grassland microcosms with poorly developed microbial networks and reduced microbial richness had the lowest multifunctionality due to fewer taxa present that support the same function (redundancy) and lower diversity of taxa that support different functions (reduced  functional uniqueness). Moreover, different microbial taxa explained different ecosystem functions pointing to the significance of functional diversity in microbial communities. These findings indicate the importance of microbial interactions within and among fungal and bacterial communities for enhancing ecosystem performance and demonstrate that the extinction of complex ecological associations belowground can impair ecosystem functioning.


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