🎓 Bandana Pandia
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As part of my Ph.D., I have worked on the pathogenic strains of Cutibacterium acnes (formerly known as Propionibacterium acnes), which are extremely slow-growing skin anaerobes. Studying anaerobes is challenging because they require an oxygen-free environment to be maintained in laboratory conditions. The opportunistic skin anaerobe C. acnes contributes to skin homeostasis with its antioxidant and immunomodulatory activities. In acnes, the orifices of these units get clogged by secretions from the sebaceous glands to form a perfect lipid-rich, hypoxic niche for the proliferation of lipophilic, anaerobic C.acnes. Elucidating the moklecular mechanisms by which C. acnes switches between growth and dormancy will help in understanding its adaptation to different oxygen envirnoments and ultimately finding strategies to kill the bacteria in the pathogenic niche.
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During my PhD, I constructed a Genome-Scale Metabolic Model (GSM) for Cutibacterium acnes KPA171202 - iCacnesBP475, which I had the opportunity to present at the Cell Symposia 2023 (Infection Biology). Validation of the model was performed using Memote, followed by an analysis of porphyrin biosynthesis in C. acnes under low- and standard- potassium conditions (using transcriptome data obtained from Yu-fei Lin et al. 2013). Further, potential drug targets were identified in C. acnes through a combined analaysis of transcriptome-integrated flux balance models comparing low and standard potassium conditions, along with in silico single- and double- gene knockout simulations. Additionally, a section of my PhD work involves the consolidation of iCAcnesBP475 and iCA843 (Kim et al., 2023) to construct the GSM iCA845. Furthermore, we integrated in-house generated transcriptome data of C. acnes to develop context-specific models, hypoxia-iCA845 and normoxia-iCA845, to study the metabolic reprogramming in C.acnes under anaerobic conditions.
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The identification of systems-level metabolic perturbations indicated a reprogrammed metabolism in C. acnes. To understand the purpose of this adapted response towards the anaerobic environment, an in-silico based modeling approach was opted to investigate the genome-wide metabolic adjustments. After the consolidation of the two GSMs, iCA843 and iCAcnesBP475, the resulted model, iCA845 (845 metabolic genes, 1 spontaneous gene) was integrated with transcriptome (hypoxia vs normoxia) data to make context-specific models, followed by FBA simulation (with biomass maximization). The magnitude [ΔFlux = Flux(Hypoxia-iCA845)-Flux(normoxia-iCA845)] and direction of the flux were analyzed to study the metabolism of C. acnes in hypoxia. An overall increase in flux through the Pentose Phosphate Pathway, lower parts of the glycolysis, along with alternate carbon metaboism was observed. The flux enters the reverse TCA cycle and supports anaerobic respiration (activation of fumarate reductase) in hypoxia. An increase in flux through the Wood-Werkman cycle/ succinate pathway indicated an increase in propionate production. Overall the study showed the coordinated set of metabolic adjustments carried out by the C. acnes.
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C. acnes is an aerotolerant-to-anaerobe, and hence, this feature was utilized to study the anaerobic adaptations at phenotypic, genetic, and systems levels. The bacteria were cultured in anaerobic (hypoxia) and aerobic (normoxia) in-vitro lab conditions, and the growth curves were studied. To analyze the genetic level adjustments, RNA was isolated from the mid-log phase, stabilized, and high-throughput sequencing (RNAseq) was carried out. Genome-wide transcritpomic profiles of C. acnes in hypoxia and normoxia resulted in 407 differentially expressed genes (DEGs). To obtain a systems perspective of the functional implications of these expression alterations, a transcriptome-integrated functional interactome was constructed. By using in-house developed network mining and path tracing algorithms, top-ranked perturbed paths were identified.
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Overall, the work achieves multi-omics data acquisition and presents it in an accessible biological database- CAcnesDB. The 'dry'-lab generated multi-omics data, such as structural proteome, pocketome, ligandome, and 'wet'-lab generated transcriptome data, are computationally integrated at multiple stages. It also demonstrates the applicability of integrated structural bioinformatics approaches to study the genome-wide perturbations in a given system. Broadly, this work provides genome-wide structural, transcriptional, and pathway-level insights into the perturbed activity in hypoxia. The presented data are explored with the common goal of elucidating the genome-wide adjustments carried out by C. acnes in anaerobic conditions.