New research identifies metabolic targets to combat antibiotic-resistant bacterial infections

New research identifies metabolic targets to combat antibiotic-resistant bacterial infections

The study shows how targeting unique metabolic pathways in specific pathogens can lead to precision antibiotics and provide a solution to antimicrobial resistance.

In a recently published study inPLOS biologyPresentA group of researchers identified niche-specific metabolic phenotypes and essential genes in pathogens using scale-up metabolic reconstructions of the genome (genres), demonstrating their potential as targets for the development of targeted antimicrobial therapies.

background

Bacterial pathogens are responsible for significant global mortality, accounting for 16% of deaths worldwide and 44% in low-resource settings. With over 500 known human-associated pathogens, growing antimicrobial resistance has become increasingly difficult.

Targeting metabolic pathways unique to specific physiological niches offers a promising alternative to broad-spectrum antibiotics and potentially reduces the development of resistance. Evolutionary phenomena such as natural selection and convergent evolution likely influence the metabolic phenotypes of pathogens in different niches, but these connections remain underexploited.

High-throughput genres can reveal niche-specific metabolic signatures and pave the way for novel, targeted antimicrobial therapies. Further research is required for validation.

About the study

Bacterial genome sequences from the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) version 3.6.12 database were filtered based on quality, completeness, and human host origin. The criteria for inclusion required genomes to be at least 80% complete, have contaminant levels below 10%, and have high consistency with known protein sequences.

Metadata-driven selection sequences with comprehensive annotations that ensure accurate downstream analyses. This process yielded 914 unique genome sequences, which were annotated using rapid annotation using subsystem technology (RAST) version 2.0 and reconstructed into genres via the reconstructor algorithm. Benchmarking with the MEMOTE (Metabolic Model Testing) tool confirmed the quality of the reconstructed models.

A reaction presence matrix was created to analyze metabolic variability and classify reactions into core, accessory, and unique categories. A histogram revealed 232 responses unique to a single strain, underscoring the diversity of metabolic functions across pathogens.

Flux balance analysis (FBA) was performed for all genres, followed by dimensionality reduction using T-Distributed Stochastic Neighbor Embedding (T-SNE) for visualization. This approach highlighted taxonomic and niche-specific clustering and validated the use of 10 river samples per genre for effective analysis.

Essential genes were identified by FBA-based single-gene knockouts, isolating niche-specific genes. The thymidylate synthase X gene(thyx)Clearly important for gastric isolates was attacked with the compound Lawone.

Experimental validation using microbial growth assays confirmed their effectiveness, supporting the computational predictions and demonstrating the potential of niche-specific antimicrobial strategies.

Study results

To capture the diversity of functional metabolic phenotypes across bacterial pathogens, 914 in silico genres were generated, encompassing 345 species across nine bacterial phyla. These reconstructions, generated by an automated pipeline, include over a million combined reactions, genes and metabolites.

On average, each model contains approximately 1,500 genes, reactions and metabolites. The gene collection, referred to as pathogen genome network reconstruction (Pathgenn), is the first high-quality compilation of metabolic reconstructions for all known human-associated bacterial pathogens.

The models were constructed using publicly available genome sequences from the Bacterial and Viral Bioinformatics Resource Center (BV-BRC), and their quality was validated using Memote benchmarking, confirming an average score of 84%, indicating high biological relevance.

Pathgenn provides valuable insights into pathogen metabolism by categorizing metabolic reactions as core (in >75% of genres), accessory (25%-75%), or unique (<25%). Reaction annotation revealed that unique reactions often involve terpenoid, polyketide and xenobiotic metabolism, which are associated with drug metabolism and antimicrobial resistance.

The analysis also showed that clustering of metabolic phenotypes is consistent with both taxonomic class and physiological niche, highlighting the effects of evolutionary history and environmental pressures on metabolic function.

Focused in the studyThyxwhich encodes thymidylate synthase. This enzyme, crucial forDeoxyribonucleic acid(DNA) synthesis is lacking in humans, making it a promising target for antimicrobial development.

LawSone, a known inhibitor ofThyxwas tested for its ability to selectively inhibit the growth of gastric pathogens. Experimental validation demonstrated that LawSone effectively inhibited the growth of stomach-associated pathogens without affecting non-stomach-associated isolates, supporting computational predictions and the potential for targeted antimicrobial therapies.

The results highlight the potential of exploiting physiological niches to develop site-specific antimicrobial strategies. Targeting uniquely essential genes shared by pathogens in a specific environment could reduce reliance on broad-spectrum antibiotics and combat antimicrobial resistance.

Conclusions

In summary, the antimicrobial resistance crisis requires innovative strategies to identify new or repurposed therapies. Using genomic data and modabolic network modeling, this study identifiedThyxa niche-specific essential gene as a promising antimicrobial target in gastric pathogens.

A collection of 914 genres provided valuable insights into pathogen metabolism. Validation experiments confirmed that Lawsone, aThyxInhibitor selectively inhibited the stomach-specific pathogens without affecting nonstomach isolates.

This approach highlights the potential for targeted, site-specific antimicrobial therapies to address resistance challenges.

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