Close Related Drug-Resistance Beijing Isolates of Mycobacterium tuberculosis Reveal a Different Transcriptomic Signature in a Murine Disease Progression Model.
María Irene Cerezo-CortésRodríguez-Castillo Juan GermánDulce Adriana Mata-EspinosaEstela Isabel BiniJorge Barrios-PayanZyanya Lucia Zatarain-BarrónJuan Manuel AnzolaFernanda Cornejo-GranadosOchoa-Leyva AdrianPatricia Del PortilloMartha Isabel MurciaRogelio Hernández-PandoPublished in: International journal of molecular sciences (2022)
Mycobacterium tuberculosis (MTB) lineage 2/Beijing is associated with high virulence and drug resistance worldwide. In Colombia, the Beijing genotype has circulated since 1997, predominantly on the pacific coast, with the Beijing-Like SIT-190 being more prevalent. This genotype conforms to a drug-resistant cluster and shows a fatal outcome in patients. To better understand virulence determinants, we performed a transcriptomic analysis with a Beijing-Like SIT-190 isolate (BL-323), and Beijing-Classic SIT-1 isolate (BC-391) in progressive tuberculosis (TB) murine model. Bacterial RNA was extracted from mice lungs on days 3, 14, 28, and 60. On average, 0.6% of the total reads mapped against MTB genomes and of those, 90% against coding genes. The strains were independently associated as determined by hierarchical cluster and multidimensional scaling analysis. Gene ontology showed that in strain BL-323 enriched functions were related to host immune response and hypoxia, while proteolysis and protein folding were enriched in the BC-391 strain. Altogether, our results suggested a differential bacterial transcriptional program when evaluating these two closely related strains. The data presented here could potentially impact the control of this emerging, highly virulent, and drug-resistant genotype.
Keyphrases
- mycobacterium tuberculosis
- drug resistant
- air pollution
- particulate matter
- multidrug resistant
- pulmonary tuberculosis
- escherichia coli
- acinetobacter baumannii
- immune response
- genome wide
- staphylococcus aureus
- multiple sclerosis
- pseudomonas aeruginosa
- single cell
- ejection fraction
- end stage renal disease
- antimicrobial resistance
- gene expression
- electronic health record
- prognostic factors
- newly diagnosed
- single molecule
- quality improvement
- metabolic syndrome
- deep learning
- inflammatory response
- oxidative stress
- hiv infected
- toll like receptor
- african american
- insulin resistance