Biology subjects

Potgieter, M. G.

Publications and source records attributed to Potgieter, M. G..

3 recordsLinked to original sources

bioRxiv2021

The role of copper resistance in Mycobacterium tuberculosis pathogenesis

Despite the development of new drugs and social interventions, tuberculosis remains a leading cause of mortality. This burden falls disproportionately on developing countries, particularly those where the incidence of HIV is high. In the Western Cape, South Africa, we have identified and isolated two Beijing family strains of Mycobacterium tuberculosis that, despite few differences at a genomic level, differ greatly in their severity of disease caused, providing an opportunity to study virulence in this organism. The aim of this study was to identify differences at a genomic and transcriptomic level that may identify the cause of the different virulence levels observed in the two isolates. The isolates were compared at the transcriptome level under four different growth conditions including oxidative stress. In comparing the transcriptome of the two isolates, an operon containing genes involved in the production of molybdenum cofactor that showed consistently lower levels of expression in the hypervirulent isolate was identified. A copper sensing transcriptional regulator was identified as the most probable regulator, and we found that the Cso operon which it is known to regulate was similarly differentially expressed in the strains. The production of molybdenum cofactor is effected in two ways by copper levels. Through the independent insertion of copper into molybdopterin (MPT), and destabilisation of Fe-S clusters. As MoaA3 contains a Fe-S cluster that is known to be destabilised by copper, and a number of copper sensitive genes are likewise found differentially expressed, it is likely that the strains differ in terms of their levels of resistance to copper. It is therefore hypothesised that the differences in virulence are as a result of different levels of resistance to phagosome copper overload, and the mechanism by which copper levels are linked to the production of molybdenum cofactor is described. Author summaryIn this article, we describe the differences in gene expression of two closely related strains of Mycobacterium tuberculosis isolated in the Western Cape of South Africa that differ in the severity of disease that they cause. We compared the strains at a genomic and transcriptomic level, and in doing so, we discovered a set of molybdenum cofactor genes regulated by a copper sensing transcription factor that came up in all datasets. Further genes linked to copper response were identified, providing greater evidence that the difference between the two strains was the manner in which they responded to copper stress. Phagocytes are known to exploit high levels of copper to kill intracellular bacteria, suggesting an important link between copper and disease. We conclude that resistance to copper toxicity is the most probable reason for the relative increase in virulence, and describe the regulatory relationship between copper levels and molybdenum cofactor synthesis.

microbiology↗

bioRxiv2020

Microbial function and genital inflammation in young South African women at high risk of HIV infection

BackgroundFemale genital tract (FGT) inflammation is an important risk factor for HIV acquisition. The FGT microbiome is closely associated with inflammatory profile, however, the relative importance of microbial activities has not been established. Since proteins are key elements representing actual microbial functions, this study utilized metaproteomics to evaluate the relationship between FGT microbial function and inflammation in 113 young and adolescent South African women at high risk of HIV infection. Women were grouped as having low, medium or high FGT inflammation by K-means clustering according to pro-inflammatory cytokine concentrations. ResultsA total of 3,186 microbial and human proteins were identified in lateral vaginal wall swabs using liquid chromatography-tandem mass spectrometry, while 94 microbial taxa were included in the taxonomic analysis. Both metaproteomics and 16S rRNA gene sequencing analyses showed increased non-optimal bacteria and decreased lactobacilli in women with FGT inflammatory profiles. However, differences in the predicted relative abundance of most bacteria were observed between 16S rRNA gene sequencing and metaproteomics analyses. Bacterial protein functional annotations (gene ontology) predicted inflammatory cytokine profiles more accurately than bacterial relative abundance determined by 16S rRNA gene sequence analysis, as well as functional predictions based on 16S rRNA gene sequence data (p<0.0001). The majority of microbial biological processes were underrepresented in women with high inflammation compared to those with low inflammation, including a Lactobacillus-associated signature of reduced cell wall organization and peptidoglycan biosynthesis. This signature remained associated with high FGT inflammation in a subset of 74 women nine weeks later, was upheld after adjusting for Lactobacillus relative abundance, and was associated with in vitro inflammatory cytokine responses to Lactobacillus isolates from the same women. Reduced cell wall organization and peptidoglycan biosynthesis were also associated with high FGT inflammation in an independent sample of ten women. ConclusionsBoth the presence of specific microbial taxa in the FGT and their properties and activities are critical determinants of FGT inflammation. Our findings support those of previous studies suggesting that peptidoglycan is directly immunosuppressive, and identify a possible avenue for biotherapeutic development to reduce inflammation in the FGT. To facilitate further investigations of microbial activities, we have developed the FGT-METAP application that is available at (http://immunodb.org/FGTMetap/).

microbiology↗

bioRxiv2019

MetaNovo: a probabilistic approach to peptide and polymorphism discovery in complex mass spectrometry datasets

BackgroundMicrobiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focussed search libraries based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing will only target the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. We describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored databases for target-decoy searches directly at the proteome level, enabling analyses without prior expectation of sample composition or metagenomic data generation, and compatible with standard downstream analysis pipelines. ResultsWe compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome database - but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying a known sample contaminant without prior expectation. ConclusionsBy estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence search databases. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself. The pipeline source code is available on GitHub1 and documentation is provided to run the software as a singularity-compatible docker image available from the Docker Hub2.

bioinformatics↗