Bacterial Infection

Predicting antimicrobial resistance using conserved genes.

A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features derived from comprehensive sets of AMR genes or whole genome sequences and may not be suitable for use when genomes are incomplete. In this study, we ex...

Anaerobic condition induces a viable but nonculturable state of the PCB-degrading Bacteria Rhodococcus biphenylivorans TG9.

Significant microbial removal of highly chlorinated polychlorinated biphenyls (PCBs) requires the cooperation of anaerobic and aerobic bacteria. During the sequencing process of anaerobic dechlorination and aerobic degradation of PCBs, aerobic degrading bacteria have to undergo anaerobic stress. However, the survival strategy of aerobic degrading bacteria under anaerobic condition is not well-unde...

DeeplyEssential: a deep neural network for predicting essential genes in microbes.

BACKGROUND: Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provi...

Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our rec...

A Study of the Chemistries, Growth Mechanisms, and Antibacterial Properties of Cerium- and Yttrium-Containing Nanoparticles.

Under the current climate, physicians prescribe antibiotics for treating bacterial infections, and such a limitation to a single class of drugs is dis...

Machine learning-driven electronic identifications of single pathogenic bacteria.

A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report o...

Antimicrobial activity of DC and its synergistic interaction with nisin against food-related bacteria.

The antimicrobial activities of DC essential oil (EO) and hydroalcoholic extract (HE) were evaluated. The EO showed broad antimicrobial activity and ...

Determination of the antioxidant, antimicrobial and anticancer properties of the honey phenolic extract of five different regions of Bingöl province.

Bingol is a famous region for honey in Turkey. The amount of phenolic substance is also considered important for the anticancer, antioxidant and antim...

SAPPHIRE: a neural network based classifier for σ70 promoter prediction in Pseudomonas.

BACKGROUND: In silico promoter prediction represents an important challenge in bioinformatics as it provides a first-line approach to identifying regu...

Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis.

Of all bacterial infectious diseases, infection by Mycobacterium tuberculosis poses one of the highest morbidity and mortality burdens on humans throu...

Rational design, synthesis and testing of novel tricyclic topoisomerase inhibitors for the treatment of bacterial infections part 1.

The alarming reduction in drug effectiveness against bacterial infections has created an urgent need for the development of new antibacterial agents t...

Rational design, synthesis and testing of novel tricyclic topoisomerase inhibitors for the treatment of bacterial infections part 2.

Building on our previously-reported novel tricyclic topoisomerase inhibitors (NTTIs), we disclose the discovery of REDX07965, which has an MIC of 0.5 ...

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.

It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing a...

Machine Learning Strategy for Gut Microbiome-Based Diagnostic Screening of Cardiovascular Disease.

Cardiovascular disease (CVD) is the number one leading cause for human mortality. Besides genetics and environmental factors, in recent years, gut mic...

Hydroxyl Radical Generation Through the Fenton-Like Reaction of Hematin- and Catechol-Functionalized Microgels.

Hydroxyl radical (OH) is a potent reactive oxygen species with the ability to degrade hazardous organic compounds, kill bacteria, and inactivate virus...

Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review.

The development of Microbial Source Tracking (MST) technologies was borne out of necessity. This was largely due to the: 1) inadequacies of the fecal ...

Discovery of Novel Type II Bacteriocins Using a New High-Dimensional Bioinformatic Algorithm.

Antimicrobial compounds first arose in prokaryotes by necessity for competitive self-defense. In this light, prokaryotes invented the first host defen...

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether ...

Triazole-based osmium(ii) complexes displaying red/near-IR luminescence: antimicrobial activity and super-resolution imaging.

Cellular uptake, luminescence imaging and antimicrobial activity against clinically relevant methicillin-resistant (MRSA) bacteria are reported. The ...

Predicting Gram-Positive Bacterial Protein Subcellular Location by Using Combined Features.

There are a lot of bacteria in the environment, and Gram-positive bacteria are the most common ones. Some Gram-positive bacteria are very harmful to t...