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Bridging the knowledge gap: from microbiome composition to function.

Faith JJ - Mol. Syst. Biol. (2015)

View Article: PubMed Central - PubMed

Affiliation: Immunology Institute and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

ABSTRACT

Despite the wealth of metagenomic sequencing data, the functions of most bacterial genes from the mammalian microbiota have remained poorly understood. In their recent study (Yaung et al 2015), Wang, Gerber, and colleagues present a platform which allows functional mining of bacterial genomes for genes that contribute to fitness in vivo and holds great potential for forward engineering microbes with enhanced colonization abilities in the microbiota.

No MeSH data available.


Related in: MedlinePlus

Overview of temporal functional metagenomics sequencing (TFUMseq).A plasmid library of approximately one hundred thousand ∽2.5 kb DNA fragments covering the genome of B. thetaiotaomicron was generated (A) and transformed into E. coli (B). The abundance of B. thetaiotaomicron regions over time (up to 28 days post-inoculation) was tracked by sequencing DNA samples from fecal pellets (C). The regions that are overrepresented over time (i.e. #4) indicate genes that provide a fitness advantage. (D, E) Future applications of TFUMseq. (D) Libraries from the same donor strain can be tested in several different recipient strains. (E) Libraries representing a pool of the genetic content of numerous organisms can be used, allowing the parallel analysis of multiple genomes.
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fig01: Overview of temporal functional metagenomics sequencing (TFUMseq).A plasmid library of approximately one hundred thousand ∽2.5 kb DNA fragments covering the genome of B. thetaiotaomicron was generated (A) and transformed into E. coli (B). The abundance of B. thetaiotaomicron regions over time (up to 28 days post-inoculation) was tracked by sequencing DNA samples from fecal pellets (C). The regions that are overrepresented over time (i.e. #4) indicate genes that provide a fitness advantage. (D, E) Future applications of TFUMseq. (D) Libraries from the same donor strain can be tested in several different recipient strains. (E) Libraries representing a pool of the genetic content of numerous organisms can be used, allowing the parallel analysis of multiple genomes.


Bridging the knowledge gap: from microbiome composition to function.

Faith JJ - Mol. Syst. Biol. (2015)

Overview of temporal functional metagenomics sequencing (TFUMseq).A plasmid library of approximately one hundred thousand ∽2.5 kb DNA fragments covering the genome of B. thetaiotaomicron was generated (A) and transformed into E. coli (B). The abundance of B. thetaiotaomicron regions over time (up to 28 days post-inoculation) was tracked by sequencing DNA samples from fecal pellets (C). The regions that are overrepresented over time (i.e. #4) indicate genes that provide a fitness advantage. (D, E) Future applications of TFUMseq. (D) Libraries from the same donor strain can be tested in several different recipient strains. (E) Libraries representing a pool of the genetic content of numerous organisms can be used, allowing the parallel analysis of multiple genomes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4380927&req=5

fig01: Overview of temporal functional metagenomics sequencing (TFUMseq).A plasmid library of approximately one hundred thousand ∽2.5 kb DNA fragments covering the genome of B. thetaiotaomicron was generated (A) and transformed into E. coli (B). The abundance of B. thetaiotaomicron regions over time (up to 28 days post-inoculation) was tracked by sequencing DNA samples from fecal pellets (C). The regions that are overrepresented over time (i.e. #4) indicate genes that provide a fitness advantage. (D, E) Future applications of TFUMseq. (D) Libraries from the same donor strain can be tested in several different recipient strains. (E) Libraries representing a pool of the genetic content of numerous organisms can be used, allowing the parallel analysis of multiple genomes.

View Article: PubMed Central - PubMed

Affiliation: Immunology Institute and Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

ABSTRACT

Despite the wealth of metagenomic sequencing data, the functions of most bacterial genes from the mammalian microbiota have remained poorly understood. In their recent study (Yaung et al 2015), Wang, Gerber, and colleagues present a platform which allows functional mining of bacterial genomes for genes that contribute to fitness in vivo and holds great potential for forward engineering microbes with enhanced colonization abilities in the microbiota.

No MeSH data available.


Related in: MedlinePlus