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Ambler, J. M.

Publications and source records attributed to Ambler, J. M..

2 recordsLinked to original sources

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↗

GenGraph: a python module for the simple generation and manipulation of genome graphs.

BackgroundAs sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promising solution to this problem is through the graph based representation of collections of genomes as a single genome graph. Though there are currently a handful of tools that can create genome graphs and have demonstrated the advantages of this new paradigm, there still exists a need for flexible tools that can be used by researchers to overcome challenges in genomics studies.\n\nResultsWe present the GenGraph toolkit, a tool that uses existing multiple sequence alignment tools to create genome graphs. It is written in Python, one of the most popular coding languages for the biological sciences, and creates the genome graphs as Python NetworkX graph objects. The conceptual model is highly intuitive, and as much as possible represents the biological relationship between the genomes. This design means that users will quickly be able to start creating genome graphs and using them in their own projects.\n\nWe outline the methods used in the generation of the graphs, and give some examples of how the created graphs may be used. GenGraph utilises existing file formats and methods in the generation of these graphs, allowing graphs to be visualised and imported with widely used applications, including Cytoscape, R, and Java Script.\n\nConclusionGenGraph provides a set of tools for generating graph based representations of sets of sequences with a simple conceptual model in a widely used coding language. It is publicly available on Github (https://github.com/jambler24/GenGraph).

bioinformatics↗