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Precise Mycobacterial Species and Subspecies Identification Using the PEP-TORCH Peptidome Algorithm

ABSTRACT: Mycobacterial infections pose a significant global health concern, requiring precise identification for effective treatment. However, diagnosing them is challenging due to inaccurate identifications and prolonged times. In this study, we aimed to develop a novel peptidome-based method using mycobacterial growth indicator tube (MGIT) cultures for faster and more accurate identification. We created the Peptide Taxonomy/Organism CHecking (PEP-TORCH), an algorithm that analyzes tryptic-peptide identified by mass spectrometry to diagnose species and subspecies with predominance scores. PEP-TORCH demonstrated 100% accuracy in identifying mycobacterial species, subspecies, and co-infections in 62 individuals suspected of mycobacterial infections, eliminating the need for a sub-solid culture procedure, the gold standard in clinical practice. A notable strength of PEP-TORCH is its ability to provide information on species and subspecies simultaneously, a process conventionally achieved sequentially. This capability significantly expedites pathogen identification. Furthermore, a targeted proteomics method was validated in 43 clinical samples using the taxa-specific peptides selected by PEP-TORCH, making them suitable as biomarkers in more clinically friendly settings. This comprehensive identification approach holds promise for streamlining treatment strategies in clinical practice.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Mycobacteriaceae

TISSUE(S): Saliva

SUBMITTER: Duran Bao

LAB HEAD: Duran Bao

PROVIDER: PXD059923 | Pride | 2025-02-09

REPOSITORIES: pride

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Project description:Francisella tularensis is one of just three bacterial species designated as a Category A select agent by the Centre for Disease Control (CDC), a category indicating agents most likely to be employed as a biological weapon. F. tularensis can be divided into four different subspecies, and it is well known that the type, severity and duration of the disease can differ substantially depending on what subspecies is responsible for the infection. Of the four subspecies, subsp. tularensis (Type A) and subsp. holartica (Type B) are of primary clinical significance, and account for nearly all recorded incidences of the disease in humans. Though Type A is considered to be much more virulent than Type B, recent reports have shown that Type A can be further subdivided into two genetically distinct populations, termed A.I and A.II, which differ with respect to geographical location, disease outcome and source of recovered isolates. Of these two subpopulations, clinical data suggests that Type A.I strains are much more virulent than Type A.II, and Type A.II strains appear to have a disease outcome similar to infections with Type B. During natural infections, host mononuclear phagocytes appear to be the primary target of all F. tularensis subsp. Despite the differences in disease outcome between different subspecies, the mechanisms involved in phagosomal escape, the modulation of phagosomal biogenesis, phagosomal disruption and bacterial egress appears to be indistinguishable between subspecies, at least at a physiological level. However, recent reports suggest that at the molecular level there appears to be significant differences between subspecies during infection, and this may account for the dramatically different disease outcome associated with different subspecies. Our long-term goal is to identify unique molecular markers associated with the more virulent Type A.I strains with the potential for use as vaccine or therapeutic targets, and to provide a greater insight into the molecular differences associated with F. tularensis infection. Our overall objective of this application, which is the next step in the pursuit of that goal, is to obtain a full transcriptional profile of Type A.I, Type A.II and Type B strains following infection of human monocyte derived macrophage (hMDM) using a novel full genome quantitative real time PCR array (qRT-PCR). The central hypothesis of the application is that Type A.I, Type A.II and Type B strains activate different transcriptional networks during the course of infection of macrophage, and that these differences are at least partially responsible for the observed differences in disease outcome between the subspecies. This hypothesis has been formulated on the basis of preliminary data obtained at our laboratory that shows significant differences in the global transcriptional profiles of Type A and Type B strains exposed to environmental stimuli that mimic the intracellular environment (see Preliminary studies).The rationale for the proposed research is that by investigating differences in the transcriptional profiles of the three subspecies, we can identify unique pathogen-associated molecules or networks that can be targeted for future therapeutic research. Complementary to our supportive preliminary data, we are particularly well prepared to undertake the proposed research, with the recent development of a full genome qRT-PCR array that will allow accurate and comprehensive detection of transcriptional changes from pictogram quantities of starting RNA. This is a pilot study

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Precise Mycobacterial Species and Subspecies Identification Using the PEP-TORCH Peptidome Algorithm

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