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Written by | Edited by Xue Yue | Xi microbes play an important role in sustaining life on earth, global nutrient cycling, wastewater treatment and human health
.
A challenge in microbial ecology research is to explore how community metabolism is determined by community taxonomy, metabolic characteristics, and their genes
.
Answering this question requires mapping the genotype of a community to its metabolic signature, and analyzing the complex interaction of metabolic signature and genotype on a community-wide basis
.
Linking genome structure to community metabolism can help to explore community gene load analysis and understand the impact of gene gain and loss on community metabolism
.
Recently, Seppe Kuehn's team from the University of Chicago published an article entitled Genomic structure predicts metabolite dynamics in microbial communities in Cell
.
This article enables prediction of metabolite changes and phenotype analysis from the genome by establishing metabolite kinetic parameters using 79 bacterial species, combined with genomic diversity analysis
.
The authors first established a denitrification metabolic model, the denitrification model
.
This process can be carried out in different bacterial groups, the mechanism at the molecular level has been elucidated, the relevant metabolites are relatively easy to quantify, and denitrifying bacteria can be easily isolated and cultured, and a large amount of genomic data can be obtained
.
Denitrification is a form of anaerobic respiration in which microorganisms use nitrogen compounds as electron acceptors to drive four reduction reactions
.
Denitrification in nature is a collective process, and strains can utilize electron acceptors produced by other strains
.
This paper mainly focuses on the first two steps of the denitrification process, the conversion of NO3- to NO2- and then to NO
.
Nitrates and nitrites are soluble and can be measured on a large scale
.
The authors isolated 78 strains of Proteobacteria from soil
.
The 78 strains were divided into three categories: Nar/Nir strains performed both nitrate and nitrite reduction; Nar strains performed nitrate reduction only; and Nir strains performed nitrite reduction only
.
At the same time, the author also used the denitrification model bacteria Paracoccus denitrificans
.
The authors next quantified the metabolites nitrate and nitrite for all strains
.
Samples were taken at logarithmic intervals over a 64-hour period and nitrate and nitrite concentrations were determined
.
The authors parameterized the metabolite kinetics using a consumer-resource model to correlate the growth and metabolic kinetics of each strain
.
Understanding how genomic variation affects community metabolism requires first understanding how genomic variation affects individual metabolic characteristics
.
Finally, the authors employ a simple linear regression approach to map gene content to consumer-resource model parameters
.
The authors found that in the Nar + Nir community, the inhibition of nitrate reduction was caused by NO production by the Nir strain, and the most inhibitory Nar strain lacked NO reductase and was unable to reduce virulence
.
While the weak inhibitory Nar strain has membrane-bound nitrate reductase
.
Although Nir strains possess nitric oxide reductase, Nir strains typically accumulate NO transiently
.
This also suggests that metabolic genes can predict community function, enabling prediction of metabolite dynamics from the genome
.
This study reveals the relationship between gene content and metabolite kinetics in different colonies, and hopes that this method can be used to understand and predict the metabolic activities of microbial communities in the natural environment in the future
.
Original link: https://doi.
org/10.
1016/j.
cell.
2021.
12.
036 Publisher: 11th reprint notice [Original article] BioArt original article, welcome to forward and share personally, reprint is prohibited without permission, all published articles The copyright of the work is owned by BioArt
.
BioArt reserves all legal rights and violators will be held accountable
.
.
A challenge in microbial ecology research is to explore how community metabolism is determined by community taxonomy, metabolic characteristics, and their genes
.
Answering this question requires mapping the genotype of a community to its metabolic signature, and analyzing the complex interaction of metabolic signature and genotype on a community-wide basis
.
Linking genome structure to community metabolism can help to explore community gene load analysis and understand the impact of gene gain and loss on community metabolism
.
Recently, Seppe Kuehn's team from the University of Chicago published an article entitled Genomic structure predicts metabolite dynamics in microbial communities in Cell
.
This article enables prediction of metabolite changes and phenotype analysis from the genome by establishing metabolite kinetic parameters using 79 bacterial species, combined with genomic diversity analysis
.
The authors first established a denitrification metabolic model, the denitrification model
.
This process can be carried out in different bacterial groups, the mechanism at the molecular level has been elucidated, the relevant metabolites are relatively easy to quantify, and denitrifying bacteria can be easily isolated and cultured, and a large amount of genomic data can be obtained
.
Denitrification is a form of anaerobic respiration in which microorganisms use nitrogen compounds as electron acceptors to drive four reduction reactions
.
Denitrification in nature is a collective process, and strains can utilize electron acceptors produced by other strains
.
This paper mainly focuses on the first two steps of the denitrification process, the conversion of NO3- to NO2- and then to NO
.
Nitrates and nitrites are soluble and can be measured on a large scale
.
The authors isolated 78 strains of Proteobacteria from soil
.
The 78 strains were divided into three categories: Nar/Nir strains performed both nitrate and nitrite reduction; Nar strains performed nitrate reduction only; and Nir strains performed nitrite reduction only
.
At the same time, the author also used the denitrification model bacteria Paracoccus denitrificans
.
The authors next quantified the metabolites nitrate and nitrite for all strains
.
Samples were taken at logarithmic intervals over a 64-hour period and nitrate and nitrite concentrations were determined
.
The authors parameterized the metabolite kinetics using a consumer-resource model to correlate the growth and metabolic kinetics of each strain
.
Understanding how genomic variation affects community metabolism requires first understanding how genomic variation affects individual metabolic characteristics
.
Finally, the authors employ a simple linear regression approach to map gene content to consumer-resource model parameters
.
The authors found that in the Nar + Nir community, the inhibition of nitrate reduction was caused by NO production by the Nir strain, and the most inhibitory Nar strain lacked NO reductase and was unable to reduce virulence
.
While the weak inhibitory Nar strain has membrane-bound nitrate reductase
.
Although Nir strains possess nitric oxide reductase, Nir strains typically accumulate NO transiently
.
This also suggests that metabolic genes can predict community function, enabling prediction of metabolite dynamics from the genome
.
This study reveals the relationship between gene content and metabolite kinetics in different colonies, and hopes that this method can be used to understand and predict the metabolic activities of microbial communities in the natural environment in the future
.
Original link: https://doi.
org/10.
1016/j.
cell.
2021.
12.
036 Publisher: 11th reprint notice [Original article] BioArt original article, welcome to forward and share personally, reprint is prohibited without permission, all published articles The copyright of the work is owned by BioArt
.
BioArt reserves all legal rights and violators will be held accountable
.
