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Virulence Factors

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inhibition of biofilm and virulence factor production in azole-resistant strains of isolated from diabetic foot by stabilized tin (IV) oxide nanoparticles.

Frontiers in cellular and infection microbiology
The advent of nanotechnology has been instrumental in the development of new drugs with novel targets. Recently, metallic nanoparticles have emerged as potential candidates to combat the threat of drug-resistant infections. Diabetic foot ulcers (DFUs...

Phenotype-Based Threat Assessment.

Proceedings of the National Academy of Sciences of the United States of America
Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pa...

Mechanism of assembly of type 4 filaments: everything you always wanted to know (but were afraid to ask).

Microbiology (Reading, England)
Type 4 filaments (T4F) are a superfamily of filamentous nanomachines - virtually ubiquitous in prokaryotes and functionally versatile - of which type 4 pili (T4P) are the defining member. T4F are polymers of type 4 pilins, assembled by conserved mult...

Comprehensive Review on the Virulence Factors and Therapeutic Strategies with the Aid of Artificial Intelligence against Mucormycosis.

ACS infectious diseases
Mucormycosis, a rare but deadly fungal infection, was an epidemic during the COVID-19 pandemic. The rise in cases (COVID-19-associated mucormycosis, CAM) is attributed to excessive steroid and antibiotic use, poor hospital hygiene, and crowded settin...

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

Briefings in bioinformatics
High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an e...

Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models.

Microbial pathogenesis
Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in human. In recent years, an increasing number of strains of K. pneumoniae resistant to multiple antibiotics have emerged, posing a significant threat t...

DTVF: A User-Friendly Tool for Virulence Factor Prediction Based on ProtT5 and Deep Transfer Learning Models.

Genes
Virulencefactors (VFs) are key molecules that enable pathogens to evade the immune systems of the host. These factors are crucial for revealing the pathogenic processes of microbes and drug discovery. Identification of virulence factors in microbes b...

Protein interactions in human pathogens revealed through deep learning.

Nature microbiology
Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lit...

Using core genome and machine learning for serovar prediction in Salmonella enterica subspecies I strains.

FEMS microbiology letters
This study presents a dual investigation of Salmonella enterica subspecies I, focusing on serovar prediction and core genome characteristics. We utilized two large genomic datasets (panX and NCBI Pathogen Detection) to test machine learning methods f...

Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction.

Nature communications
Identifying and characterizing virulence proteins secreted by Gram-negative bacteria are fundamental for deciphering microbial pathogenicity as well as aiding the development of therapeutic strategies. Effector predictors utilizing pre-trained protei...