Investigating guinea pigs as a model for serum-based pulmonary TB metabolomics research

Abstract

Animal models are important for tuberculosis (TB) research, offering controlled settings to study disease mechanisms. However, their ability to replicate TB-induced metabolic responses in humans remains uncertain. In this study, a systematic review was conducted (Chapter 3, Section A) to summarise and evaluate the use of animal models in TB metabolomics to date, with a particular focus on how well TB-induced metabolite profiles in animal models reflect host metabolic changes observed during active pulmonary TB in humans. Three databases - PubMed, Scopus, and Web of Science - were systematically searched for metabolomics studies of pulmonary TB in humans and animal models, following PRISMA guidelines. Eligible studies were screened, and quality was assessed using QUDOMICS and STAIR tools. Data were synthesised by species, sample matrix, experimental design, and reported differential metabolites. Corresponding differential metabolites identified across species were compared and subjected to pathway analysis in MetaboAnalyst 6.0. Of the 80 eligible studies, nine involved animal models, predominantly mice. These models captured only 4.7% of human TB-associated differential metabolites, with the highest overlap (3.8%) observed in mouse lung tissue. Despite low concordance at the metabolite level, conserved disruptions were observed in amino acid, glutathione, and one-carbon metabolism pathways. Guinea pigs demonstrated a substantially smaller overlap (0.5%), observed in both serum and lung tissue datasets. However, the literature review also highlighted that guinea pigs remain underutilised in TB metabolomics research, with only two previous studies - conducted by the same research group - using this model. This limited utilisation is noteworthy given the well-documented high susceptibility of guinea pigs to Mycobacterium tuberculosis (Mtb) infection and their histopathology resemblance to human necrotising granulomas. In the experimental component of this study, a previously established serum preparation method was optimised for untargeted metabolomics analysis of the guinea pig samples pertaining to this investigation, using two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGCTOFMS). The optimised analytical method was successfully applied to the full research cohort, demonstrating sufficient performance and coverage to detect biologically relevant metabolic features across all experimental groups. Serum samples collected from healthy controls, Mtb-infected animals, Mtb-infected animals treated with placebo, and Mtb-infected animals treated with rifampicin (RIF) were analysed to explore potential metabolic changes resulting from Mtb infection and anti-TB treatment (specifically RIF) in guinea pigs. Statistical analysis identified 28 metabolites that differed between Mtb-infected guinea pigs and healthy controls; 27 of these metabolites overlapped with those previously identified in human studies, with prominent changes in lipid and amino acid metabolic pathways. Furthermore, statistical analysis identified 55 annotated differential metabolites across both short-term and medium-term treatment, including 15 metabolites previously reported in human studies and 11 metabolites potentially representing novel findings. The observed overlap suggests several metabolic responses to RIF exposure may be conserved across species. Collectively, findings from the systematic review and experimental component of this project suggest that guinea pigs may possess translational potential for human TB metabolomics research. The detection of treatment-associated metabolic changes that are consistent with previous human and rat metabolomics studies further supports the potential value of this model, despite the limited availability of directly comparable literature. Future studies may benefit from multi-omics strategies that integrate metabolomics with complementary approaches, such as transcriptomics and proteomics, to provide a more holistic understanding of host-pathogen interactions during Mtb infection and RIF treatment.