Microbial Systems Biology

2022 ◽  
2020 ◽  
Vol 57 ◽  
pp. vi-vii
Author(s):  
Athanasios (Nassos) Typas ◽  
Gene-Wei Li

2008 ◽  
Vol 128 (1) ◽  
pp. 16-21 ◽  
Author(s):  
Stanley Brul ◽  
Femke I.C. Mensonides ◽  
Klaas J. Hellingwerf ◽  
M. Joost Teixeira de Mattos

2021 ◽  
Vol 12 ◽  
Author(s):  
Victor Mataigne ◽  
Nathan Vannier ◽  
Philippe Vandenkoornhuyse ◽  
Stéphane Hacquard

Understanding how microorganism-microorganism interactions shape microbial assemblages is a key to deciphering the evolution of dependencies and co-existence in complex microbiomes. Metabolic dependencies in cross-feeding exist in microbial communities and can at least partially determine microbial community composition. To parry the complexity and experimental limitations caused by the large number of possible interactions, new concepts from systems biology aim to decipher how the components of a system interact with each other. The idea that cross-feeding does impact microbiome assemblages has developed both theoretically and empirically, following a systems biology framework applied to microbial communities, formalized as microbial systems ecology (MSE) and relying on integrated-omics data. This framework merges cellular and community scales and offers new avenues to untangle microbial coexistence primarily by metabolic modeling, one of the main approaches used for mechanistic studies. In this mini-review, we first give a concise explanation of microbial cross-feeding. We then discuss how MSE can enable progress in microbial research. Finally, we provide an overview of a MSE framework mostly based on genome-scale metabolic-network reconstruction that combines top-down and bottom-up approaches to assess the molecular mechanisms of deterministic processes of microbial community assembly that is particularly suitable for use in synthetic biology and microbiome engineering.


2009 ◽  
Vol 33 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Víctor De Lorenzo ◽  
Michael Galperin

2015 ◽  
Vol 27 ◽  
pp. viii-ix
Author(s):  
Eric D Brown ◽  
Athanasios Typas

Author(s):  
Prerak Desai

The use of systems biology to study complex biological questions is gaining ground due to the ever-increasing amount of genetic tools and genome sequences available. As such, systems biology concepts and approaches are increasingly underpinning our concept of microbial physiology. Three tools for use in functional genomics are gene expression, proteomics, and metabolomics. However, these tools produce such large data sets that we sometimes become paralyzed trying to merge the data and link it to form a consistent biological interpretation. Use of functional groupings has relieved some of the issues in merging data for biological meaning. Statistical analysis and visualization of these multi-dimension data sets are needed to aid the microbiologist, which brings additional methods that are often not familiar. Progress is being made to bring these diverse data types together to understand fundamental metabolic processes and pathways. These efforts are paying tremendous dividends in our understanding of how microbes live, grow, survive, and metabolize nutrients. These insights allow metabolic engineering to progress and allow scientists to further define the mechanisms of metabolism.


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