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Biology subjects

Segota, I.

Publications and source records attributed to Segota, I..

2 recordsLinked to original sources

Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria

Bacteria allocate their proteome to cellular functions differently in different growth conditions. It is largely unknown how such allocation arises from known mechanisms of gene regulation while constrained by limited translation capacity and fixed protein density. Here, we performed absolute transcriptomic and proteomic analysis for E. coli across many conditions, obtaining a plethora of results on promoters and mRNAs characteristics that clash with conventional expectations: the majority of mRNAs exhibit similar translational efficiencies, while the promoter strengths are vastly different across genes. These characteristics prescribe two principles of gene regulation guiding bacteria to attain the desired protein allocation under global constraints: Total transcriptional output is tightly coordinated with ribosomal activity, and the concentrations of individual proteins are largely set by transcription. These two principles lead to a quantitative formulation of Central Dogma which unravels the complex relationship between gene regulatory activities and mRNA/protein concentrations across conditions. The knowledge obtained will be invaluable for accurately inferring gene regulatory interactions from omics data, as well as for guiding the design of genetic circuits for synthetic biology applications in E. coli and other organisms.

systems biology↗

A high-resolution pipeline for 16S-sequencing identifies bacterial strains in human microbiome

We developed a High-resolution Microbial Analysis Pipeline (HiMAP) for 16S amplicon sequencing data analysis, aiming at bacterial species or strain-level identification from human microbiome to enable experimental validation for causal effects of the associated bacterial strains on health and diseases. HiMAP achieved higher accuracy in identifying species in human microbiome mock community than other pipelines. HiMAP identified majority of the species, with strain-level resolution wherever possible, as detected by whole genome shotgun sequencing using MetaPhlAn2 and reported comparable relative abundances. HiMAP is an open-source R package available at https://github.com/taolonglab/himap.

bioinformatics↗