Cytochrome P450 Monooxygenase CYP139 Family Involved in the Synthesis of Secondary Metabolites in 824 Mycobacterial Species

Tuberculosis (TB) is one of the top infectious diseases causing numerous human deaths in the world. Despite enormous efforts, the physiology of the causative agent, Mycobacterium tuberculosis, is poorly understood. To contribute to better understanding the physiological capacity of these microbes, we have carried out extensive in silico analyses of the 1111 mycobacterial species genomes focusing on revealing the role of the orphan cytochrome P450 monooxygenase (CYP) CYP139 family. We have found that CYP139 members are present in 894 species belonging to three mycobacterial groups: M. tuberculosis complex (850-species), Mycobacterium avium complex (34-species), and non-tuberculosis mycobacteria (10-species), with all CYP139 members belonging to the subfamily “A”. CYP139 members have unique amino acid patterns at the CXG motif. Amino acid conservation analysis placed this family in the 8th among CYP families belonging to different biological domains and kingdoms. Biosynthetic gene cluster analyses have revealed that 92% of CYP139As might be associated with producing different secondary metabolites. Such enhanced secondary metabolic potentials with the involvement of CYP139A members might have provided mycobacterial species with advantageous traits in diverse niches competing with other microbial or viral agents, and might help these microbes infect hosts by interfering with the hosts’ metabolism and immune system.

In Silico Analysis of P450s and Their Role in Secondary Metabolism in the Bacterial Class Gammaproteobacteria

The impact of lifestyle on shaping the genome content of an organism is a well-known phenomenon and cytochrome P450 enzymes (CYPs/P450s), heme-thiolate proteins that are ubiquitously present in organisms, are no exception. Recent studies focusing on a few bacterial species such as Streptomyces, Mycobacterium, Cyanobacteria and Firmicutes revealed that the impact of lifestyle affected the P450 repertoire in these species. However, this phenomenon needs to be understood in other bacterial species. We therefore performed genome data mining, annotation, phylogenetic analysis of P450s and their role in secondary metabolism in the bacterial class Gammaproteobacteria. Genome-wide data mining for P450s in 1261 Gammaproteobacterial species belonging to 161 genera revealed that only 169 species belonging to 41 genera have P450s. A total of 277 P450s found in 169 species grouped into 84 P450 families and 105 P450 subfamilies, where 38 new P450 families were found. Only 18% of P450s were found to be involved in secondary metabolism in Gammaproteobacterial species, as observed in Firmicutes as well. The pathogenic or commensal lifestyle of Gammaproteobacterial species influences them to such an extent that they have the lowest number of P450s compared to other bacterial species, indicating the impact of lifestyle on shaping the P450 repertoire. This study is the first report on comprehensive analysis of P450s in Gammaproteobacteria.

Ancient Bacterial Class Alphaproteobacteria Cytochrome P450 Monooxygenases Can Be Found in Other Bacterial Species

Cytochrome P450 monooxygenases (CYPs/P450s), heme-thiolate proteins, are well-known players in the generation of chemicals valuable to humans and as a drug target against pathogens. Understanding the evolution of P450s in a bacterial population is gaining momentum. In this study, we report comprehensive analysis of P450s in the ancient group of the bacterial class Alphaproteobacteria. Genome data mining and annotation of P450s in 599 alphaproteobacterial species belonging to 164 genera revealed the presence of P450s in only 241 species belonging to 82 genera that are grouped into 143 P450 families and 214 P450 subfamilies, including 77 new P450 families. Alphaproteobacterial species have the highest average number of P450s compared to Firmicutes species and cyanobacterial species. The lowest percentage of alphaproteobacterial species P450s (2.4%) was found to be part of secondary metabolite biosynthetic gene clusters (BGCs), compared other bacterial species, indicating that during evolution large numbers of P450s became part of BGCs in other bacterial species. Our study identified that some of the P450 families found in alphaproteobacterial species were passed to other bacterial species. This is the first study to report on the identification of CYP125 P450, cholesterol and cholest-4-en-3-one hydroxylase in alphaproteobacterial species (Phenylobacterium zucineum) and to predict cholesterol side-chain oxidation capability (based on homolog proteins) by P. zucineum.

Pezizomycetes Genomes Reveal Diverse P450 Complements Characteristic of Saprotrophic and Ectomycorrhizal Lifestyles

Cytochrome P450 monooxygenases (CYPs/P450s) are heme proteins that play a role in organisms' primary and secondary metabolism. P450s play an important role in organism adaptation since lifestyle influences P450 composition in their genome. This phenomenon is well-documented in bacteria but less so in fungi. This study observed this phenomenon where diverse P450 complements were identified in saprophytic and ectomycorrhizal Pezizomycetes. Genome-wide data mining, annotation, and phylogenetic analysis of P450s in 19 Pezizomycetes revealed 668 P450s that can be grouped into 153 P450 families and 245 P450 subfamilies. Only four P450 families, namely, CYP51, CYP61, CYP5093, and CYP6001, are conserved across 19 Pezizomycetes, indicating their important role in these species. A total of 5 saprophyte Pezizomycetes have 103 P450 families, whereas 14 ectomycorrhizal Pezizomycetes have 89 P450 families. Only 39 P450 families were common, and 50 and 64 P450 families, respectively, were unique to ectomycorrhizal and saprophytic Pezizomycetes. These findings suggest that the switch from a saprophytic to an ectomycorrhizal lifestyle led to both the development of diverse P450 families as well as the loss of P450s, which led to the lowest P450 family diversity, despite the emergence of novel P450 families in ectomycorrhizal Pezizomycetes.

From patterns to prediction: machine learning and antifungal resistance biomarker discovery

Fungal pathogens significantly impact human health, agriculture, and ecosystems, with infections leading to high morbidity and mortality, especially among immunocompromised individuals. The increasing prevalence of antifungal resistance (AFR) exacerbates these challenges, limiting the effectiveness of current treatments. Identifying robust biomarkers associated AFR could accelerate targeted diagnosis, shorten decision time for treatment strategies, and improve patient health. This paper examines traditional avenues of AFR biomarker detection, contrasting them with the increasingly effective role of machine learning (ML) in advancing diagnostic and therapeutic strategies. The integration of ML with technologies such as mass spectrometry, molecular dynamics, and various omics-based approaches often results in the discovery of diverse and novel resistance biomarkers. ML's capability to analyse complex data patterns enhances the identification of resistance biomarkers and potential drug targets, offering innovative solutions to AFR management. This paper highlights the importance of interdisciplinary approaches and continued innovation in leveraging ML to combat AFR, aiming for more effective and targeted treatments for fungal infections.