AIMC Topic: Quorum Sensing

Clear Filters Showing 1 to 10 of 19 articles

Machine Learning in Microbiome Research and Engineering.

ACS synthetic biology
Microbiomes, complex communities of microorganisms and their genetic material, hold immense potential for addressing global challenges in diverse sectors, including healthcare, agriculture, and bioproduction. Engineering these intricate ecosystems, h...

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...

Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.

Nature communications
Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed...

Metabolic reprogramming and machine learning-guided cofactor engineering to boost nicotinamide mononucleotide production in Escherichia coli.

Bioresource technology
Nicotinamide mononucleotide (NMN) is a bioactive compound in NAD(P) metabolism, which exhibits diverse pharmaceutical interests. However, enhancing NMN biosynthesis faces the challange of competing with cell growth and disturbing intracellular redox ...

Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches.

Journal of molecular modeling
CONTEXT: Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expres...

Gene regulatory networks with binary weights.

Bio Systems
An evolutionary computation framework to learn binary threshold networks is presented. Inspired by the recent trend of binary neural networks, where weights and activation thresholds are represented using 1 and -1 such that they can be stored in 1-bi...

Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome.

Nature communications
The transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcrip...

iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou's 5-Steps Rule and Informative Physicochemical Properties.

International journal of molecular sciences
Understanding of quorum-sensing peptides (QSPs) in their functional mechanism plays an essential role in finding new opportunities to combat bacterial infections by designing drugs. With the avalanche of the newly available peptide sequences in the p...

A neural network model predicts community-level signaling states in a diverse microbial community.

PLoS computational biology
Signal crosstalk within biological communication networks is common, and such crosstalk can have unexpected consequences for decision making in heterogeneous communities of cells. Here we examined crosstalk within a bacterial community composed of fi...

Aeromonas hydrophila biofilm, exoprotease, and quorum sensing responses to co-cultivation with diverse foodborne pathogens and food spoilage bacteria on crab surfaces.

Biofouling
The effects of dual species interactions on biofilm formation by Aeromonas hydrophila in the presence of Pseudomonas aeruginosa, Pseudomonas fluorescens, Pectobacterium carotovorum, Salmonella Typhimurium, and Listeria monocytogenes were examined. Hi...