Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis

BACKGROUND

Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or require skilled expertise, warranting alternate tests. Application of machine-learning tools to heterogeneous and high-dimensional multi-omics datasets finds promising potential in data integration and may aid biomarker discovery.

OBJECTIVES

The present study aimed to evaluate the potential of the microbiome and metabolome-derived biomarkers in BV diagnosis. Interpretable machine-learning algorithms were used to evaluate the utility of an integrated-omics-derived classification model.

METHODS

Vaginal samples obtained from reproductive-age group women with (n = 40) and without BV (n = 40) were subjected to 16S rRNA amplicon sequencing and LC-MS-based metabolomics. The vaginal microbiome and metabolome were characterized, and machine-learning analysis was performed to build a classification model using biomarkers with the highest diagnostic accuracy.

RESULTS

Microbiome-based diagnostic model exhibited a ROC-AUC (10-fold CV) of 0.84 ± 0.21 and accuracy of 0.79 ± 0.18, and important features were Aerococcus spp., Mycoplasma hominis, Sneathia spp., Lactobacillus spp., Prevotella spp., Gardnerella spp. and Fannyhessea vaginae. The metabolome-derived model displayed superior performance with a ROC-AUC of 0.97 ± 0.07 and an accuracy of 0.92 ± 0.08. Beta-leucine, methylimidazole acetaldehyde, dimethylethanolamine, L-arginine and beta cortol were among key predictive metabolites for BV. A predictive model combining both microbial and metabolite features exhibited a high ROC-AUC of 0.97 ± 0.07 and accuracy of 0.94 ± 0.08 with diagnostic performance only slightly superior to the metabolite-based model.

CONCLUSION

Application of machine-learning tools to multi-omics datasets aid biomarker discovery with high predictive performance. Metabolome-derived classification models were observed to have superior diagnostic performance in predicting BV than microbiome-based biomarkers.

Terbinafine resistance in dermatophytes: Time to revisit alternate antifungal therapy

Resistant superficial dermatophytic infections of the skin and its appendages have emerged as a major health problem in India. Mutations in Squalene epoxidase gene have led to increasing incidence of resistance to terbinafine in dermatophytic isolates. We examined six patients with recalcitrant dermatophytosis attending Dermatology OPD at a tertiary care hospital and demonstrated terbinafine resistance by molecular method. Immediate hyperitivity (IH) reaction to Trichophytin antigen was highlighted in these patients. The patients were treated with alternate antifungals after demonstration of resistance to terbinafine based on the antifungal susceptibility testing (AFST). On follow up the patients responded well to the substitute but the duration of therapy had to be prolonged beyond six weeks.

The TB structural genomics consortium: a resource for Mycobacterium tuberculosis biology

The TB Structural Genomics Consortium is an organization devoted to encouraging, coordinating, and facilitating the determination and analysis of structures of proteins from Mycobacterium tuberculosis. The Consortium members hope to work together with other M. tuberculosis researchers to identify M. tuberculosis proteins for which structural information could provide important biological information, to analyze and interpret structures of M. tuberculosis proteins, and to work collaboratively to test ideas about M. tuberculosis protein function that are suggested by structure or related to structural information. This review describes the TB Structural Genomics Consortium and some of the proteins for which the Consortium is in the progress of determining three-dimensional structures.

Metal ions modulate the plastic nature of Mycobacterium tuberculosis chaperonin-10

Chaperonin-10s possess a highly flexible segment of approximately 10 residues that covers their dome-like structure and closes the central cavity of the chaperonin assembly. The dome loop is believed to contribute to the plasticity of their oligomeric structure. We have exploited the presence of a single tryptophan residue occurring in the dome loop of Mycobacterium tuberculosis chaperonin-10 (cpn-10), and through intrinsic fluorescence measurements show that in the absence of metal ions, the tryptophan is almost fully solvent exposed at neutral pH. The dome loop, however, assumes a closed conformation in the presence of metal ions, or at low pH. These changes are fully reversed in the presence of chelating agents such as EDTA, confirming the role of cations in modulating the metastable states of cpn-10.

Conserved structural features and sequence patterns in the GroES fold family

An irregular, all beta-class of proteins, comprising members of the chaperonin-10, quinone oxidoreductase, glucose dehydrogenase and alcohol dehydrogenase families has earlier been classified as the GroES fold. In this communication, we present an extensive analysis of sequences and three dimensional structures of proteins belonging to this family. The individual protein structures can be superposed within 1.6 A for more than 60 structurally equivalent residues. The comparisons show a highly conserved hydrophobic core and conservation of a few key residues. A glycyl-aspartate dipeptide is suggested as being critical for the maintenance of the GroES fold. One of the surprising findings of the study is the non-conservative nature of Ile to Leu mutations in the protein core, although Ile to Val mutations are found to occur frequently.