Bacterial Infection

Tripleknock: predicting lethal effect of three-gene knockout in bacteria by deep learning

Investigating the lethal effect of multi-gene knockout is essential for discovering novel antibiotics targets and metabolic engineering. Unlike single genes or gene pairs, three-gene combinations involve more intricate interactions, making experimental screening time-consuming. Computational methods, particularly Genome-scale metabolic Model (GEM)-based Flux Balance Analysis (FBA), requires constr...

HPInet: Interpretable prediction of Host-Pathogen protein-protein Interactions using a transformer-based neural network

Gram-negative bacteria utilize a series of secretion systems (T1SS-T10SS) to deliver secreted effector proteins (T1SE-T10SE) into host cells, leading to infections and diseases. Understanding the interactions between these effector proteins and host proteins is crucial for unraveling the pathogenic mechanisms of bacterial pathogens. Despite advancements in sequencing technologies that have signifi...

Genomic constraints shape the evolution of alternative routes to drug resistance in prokaryotes

Variation within the prokaryotic pangenome is not random, and natural selection that favours particular combinations of genes appears to dominate over...

PAM adenine methylation and flanking sequence regulate SaCas9 activity in bacteria

Cas9 nucleases are the effectors of the class 2 type II CRISPR system in bacteria and function to restrict invading DNA. They can also be used with si...

The role of active mRNA-ribosome dynamics and closing constriction in daughter chromosome separation in Escherichia coli

The mechanisms by which two sister chromosomes separate and partition into daughter cells in bacteria remain poorly understood. A recent theoretical m...

Moremi Bio Agent: Leveraging Agentic Large Language Model for the Discovery of Broad-Spectrum Antibiotics for Enterobacteriaceae

Antimicrobial resistance (AMR) is a pressing global health crisis, exacerbated by a stagnating antibiotic discovery pipeline and the emergence of mult...

Intra-genomic genes-to-genes correlation enables bacterial genome representation

The bacterial pan-genome consists of core genes shared by all members of a taxonomy and accessory genes found in only a subset. The correlation among ...

Accurate and robust classification of Mycobacterium bovis-infected cattle using peripheral blood RNA-seq data

The zoonotic bacterium, Mycobacterium bovis, causes bovine tuberculosis (bTB) and is closely related to Mycobacterium tuberculosis, the primary cause ...

Large-language-model-based antibiotic resistance gene prediction and resistomes mining in cyanobacterial blooms

The rapid spread of antibiotic resistance genes (ARGs) in aquatic ecosystems poses a serious public health threat. Conventional ARG detection methods,...

ppIRIS: deep learning for proteome-wide prediction of bacterial protein-protein interactions

Protein–protein interactions (PPIs) are central to cellular processes and host–pathogen dynamics, yet bacterial interactomes remain poorly mapped, esp...

Scalable and interpretable secretion system annotation with Sismis

Secretion systems play critical roles in bacterial growth, survival, and pathogenesis. Genes encoding secretion system components often co-occur toget...

Machine Learning-Guided Synthetic Microbial Communities Enable Functional and Sustainable Degradation of Persistent Environmental Pollutants

Persistent environmental pollutants demand the use of diverse microbial metabolic capabilities for effective degradation. While naturally occurring co...

PhageAI: a new approach to predicting the lifestyle of bacteriophages using proteinBERT and convolutional neural networks

Bacteriophages are viruses that infect bacteria, including temperate, virulent and chronic phages. In the current times of increasing resistance to an...

Species-agnostic and Salmonella-specific Models for Antimicrobial Resistance Prediction Using FCGR and ResNet-18

Antimicrobial resistance (AMR) prediction from bacterial genomes remains a major challenge for clinical microbiology and surveillance. We developed de...

Predicting Clinical Outcomes in Helicobacter pylori-positive Patients using Supervised Learning through the Integration of Demographic and Genomic Features

Helicobacter pylori (H. pylori) infection is widespread globally and is linked to outcomes ranging from chronic gastritis to gastric cancer. However, ...

Intracellular acidification by bacteria-derived valeric acid is a mechanism of trans-kingdom ecology against Candida parapsilosis colonization

In hematopoietic cell transplant patients, intestinal Candida parapsilosis expansion and translocation cause life-threatening candidemia, yet how comm...

Breaking the culture habit: metagenomic diagnosis of companion animal skin infections

Skin infections have been described as the primary cause for presentation in veterinary small animal practices and they frequently result in prescript...

A deep reinforcement learning platform for antibiotic discovery

Antimicrobial resistance (AMR) is projected to cause up to 10 million deaths annually by 2050, underscoring the urgent need for new antibiotics. Here ...

Efficacy and safety evaluation of artificial intelligence-identified antimicrobial peptides for use against avian pathogenic Escherichia coli in the poultry industry

The overuse of antibiotics in both veterinary and human medicine has resulted in the emergence of antibiotic-resistant bacteria, prompting a search fo...

Early detection of ampicillin susceptibility in Enterococcus faecium with MALDI-TOF MS and machine learning

Enterococcus faecium can cause severe infections and is often resistant to the first-line antibiotic ampicillin. Consequently, clinicians usually pres...