AIMC Topic: Gene Expression Regulation, Bacterial

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Unveiling the landscape of prokaryotic global regulators through deep protein language models.

mSystems
Global regulators (GRs) are key transcription factors that orchestrate the expression of multiple genes, playing essential roles in stress responses, virulence, secondary metabolism, and antibiotic resistance-traits that make them powerful tools for ...

Stability of quorum sensing decision states in heterogeneous bacterial communities.

Physical biology
Bacteria utilize cell-cell signaling to coordinate gene expression in populations of cells. Bacterial signal exchange was originally interpreted as a mechanism bacteria use to regulate gene expression in response to changes in cell density, denoted a...

Structural and functional analysis of the accessory gene regulators of Staphylococcus aureus and Staphylococcus epidermidis: an in Silico approach.

BMC microbiology
BACKGROUND: Staphylococcus aureus and Staphylococcus epidermidis are tenacious pathogens that cause toxic shock syndrome. Accessory gene regulator (Agr) of Staphylococcus sp. controls the expression of multiple genes that encode virulence properties....

Integrative machine learning and RT-qPCR analysis identify key stress-responsive genes in Thermus thermophilus HB8.

Genetica
Bacteria are constantly exposed to diverse environmental stresses, necessitating complex adaptive mechanisms for survival. Thermus thermophilus, a thermophilic extremophile, serves as an excellent model for investigating these responses due to its re...

Machine learning uncovers the transcriptional regulatory network for the production host Streptomyces albidoflavus.

Cell reports
Streptomyces albidoflavus is a widely used strain for natural product discovery and production through heterologous biosynthetic gene clusters (BGCs). However, the transcriptional regulatory network (TRN) and its impact on secondary metabolism remain...

Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.

Communications biology
A complex interplay of genetic and environmental factors influences bacterial growth. Understanding these interactions is crucial for insights into complex living systems. This study employs a data-driven approach to uncover the principles governing ...

Machine learning reveals the transcriptional regulatory network and circadian dynamics of PCC 7942.

Proceedings of the National Academy of Sciences of the United States of America
is an important cyanobacterium that serves as a versatile and robust model for studying circadian biology and photosynthetic metabolism. Its transcriptional regulatory network (TRN) is of fundamental interest, as it orchestrates the cell's adaptatio...

Machine-Learning Analysis of Streptomyces coelicolor Transcriptomes Reveals a Transcription Regulatory Network Encompassing Biosynthetic Gene Clusters.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Streptomyces produces diverse secondary metabolites of biopharmaceutical importance, yet the rate of biosynthesis of these metabolites is often hampered by complex transcriptional regulation. Therefore, a fundamental understanding of transcriptional ...

Novel candidate genes for environmental stresses response in Synechocystis sp. PCC 6803 revealed by machine learning algorithms.

Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
Cyanobacteria have developed acclimation strategies to adapt to harsh environments, making them a model organism. Understanding the molecular mechanisms of tolerance to abiotic stresses can help elucidate how cells change their gene expression patter...

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.

mSphere
antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investiga...