Biology subjects

Gygli, S. M.

Publications and source records attributed to Gygli, S. M..

5 recordsLinked to original sources

bioRxiv2020

Local adaptation in populations of Mycobacterium tuberculosis endemic to the Indian Ocean Rim

Lineage 1 (L1) and 3 (L3) are two lineages of the Mycobacterium tuberculosis complex (MTBC), causing tuberculosis (TB) in humans. L1 and L3 are endemic to the Rim of the Indian Ocean, the region that accounts for most of the worlds new TB cases. Despite their relevance for this region, L1 and L3 remain understudied. Here we analyzed 2,938 L1 and 2,030 L3 whole genome sequences originating from 69 countries. We show that South Asia played a central role in the dispersion of these two lineages to neighboring regions. Moreover, we found that L1 exhibits signatures of local adaptation at the esxH locus, a gene coding for a secreted effector that targets the human endosomal sorting complex, and is included in several vaccine candidates. Our study highlights the importance of genetic diversity in the MTBC, and sheds new light on two of the most important MTBC lineages affecting humans.

genomics↗

bioRxiv2020

Network analysis identifies regulators of lineage-specific phenotypes in Mycobacterium tuberculosis

The Mycobacterium tuberculosis (Mtb) complex includes ten phylogenetically distinct human-adapted lineages with varying geographical distributions and pathogenicity. Lineage 1 (L1) is associated with low virulence, while Lineage 2 (L2) is linked to hyper-virulence, increased transmission, and drug resistance. We performed multi-layer comparative analyses integrating whole-genome sequencing with quantitative transcriptomic and proteomic profiling of a panel of L1 and L2 clinical strains, each grown under two in vitro conditions. Our data revealed variable correlations between transcript and protein levels across strains and gene categories, indicating lineage-specific post-translational regulation. Transcriptional and translational differences scaled with phylogenetic distance, with one in three SNPs on average leading to gene expression changes. A newly developed genome-scale transcriptional regulatory model identified master transcription factors--closely linked to the sigma factor network--whose targets were differentially expressed between L1 and L2. Notably, DosR proteins showed higher basal levels and a stronger nitric oxide (NO) response in L2. Time-course validation using an Rv1985c induction and wild-type H37Rv under hypoxia and reaeration confirmed the role of Rv1985c in the differentially expressed genes between L1 and L2. These findings suggest that limited genetic variation can translate into significant phenotypic differences via differential regulation of key transcriptional networks. HighlightsO_LIProteomic and transcriptomic characterization of fully sequenced diverse L1 and L2 clinical strains of Mtb. C_LIO_LIPost translational control mechanisms for regulatory and virulence genes are mitigated in Mtb L2. C_LIO_LIA genome-scale transcriptional framework identifies DosR, Rv1985c, Lsr2 and Rv0691c as master transcription factors responsible for differential target gene expression in L2 compared to L1 strains. C_LIO_LIL1 and L2 DosR proteins respond differently to nitric oxide stress, thus determining a relevant phenotype. C_LIO_LITime-course phenotypic and transcriptomic data under hypoxia and reaeration validate Rv1985c as a key transcription factor differentiating L2 and L1 strains. C_LI

systems biology↗

bioRxiv2018

Resource misallocation as a mediator of fitness costs in antibiotic resistance.

Antimicrobial resistance poses a threat to global health and the economy. It is widely accepted that, in the absence of antibiotics, drug resistance mutations carry a fitness cost. In the case of rifampicin resistance in fast-growing bacteria, this cost stems from a reduced transcription rate of the RNA polymerase resulting in slower ribosome biosynthesis. However, this relationship does not apply in the slow-growing Mycobacterium tuberculosis, where the true mechanism of fitness cost of rifampicin resistance as well as the impact of compensatory evolution remain unknown. Here we show, using global transcriptomic and proteomic profiling of selected M. tuberculosis mutants and clinical strains, that the fitness cost of rifampicin resistance in M. tuberculosis is the result of the physiological burden caused by aberrant gene expression. We further show that the perceived burden can be increased, effectively suppressing the emergence of drug resistance.

microbiology↗

bioRxiv2018

Multiple Introductions of the Mycobacterium tuberculosis Lineage 2 Beijing into Africa over centuries

The Lineage 2-Beijing (L2-Beijing) sub-lineage of Mycobacterium tuberculosis has received much attention due to its high virulence, fast disease progression, and association with antibiotic resistance. Despite several reports of the recent emergence of L2-Beijing in Africa, no study has investigated the evolutionary history of this sub-lineage on the continent. In this study, we used whole genome sequences of 817 L2 clinical strains from 14 geographical regions globally distributed to investigate the origins and onward spread of this lineage in Africa. Our results reveal multiple introductions of L2-Beijing into Africa linked to independent bacterial populations from East-and Southeast Asia. Bayesian analyses further indicate that these introductions occurred during the past 300 years, with most of these events pre-dating the antibiotic era. Hence, the success of L2-Beijing in Africa is most likely due to its hypervirulence and high transmissibility rather than drug resistance.

evolutionary biology↗

bioRxiv2018

Whole genome sequencing for drug resistance profile prediction in Mycobacterium tuberculosis

Whole genome sequencing allows rapid detection of drug-resistant M. tuberculosis isolates. However, high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been lacking.\n\nWe determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from Democratic Republic of the Congo, Ivory Coast, Peru, Thailand and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD BACTEC MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared phenotypic drug susceptibility results with predicted drug resistance profiles inferred by whole genome sequencing.\n\nBoth phenotypic DST methods identically classified the strains into resistant/susceptible in 73-99% of the cases, depending on the drug. Changes in minimal inhibitory concentrations were readily explained by mutations identified by whole genome sequencing. Using the whole genome sequences we were able to predict quantitative drug resistance levels where wild type and mutant MIC distributions did not overlap. The utility of genome sequences to predict quantitative levels of drug resistance was partially limited due to incompletely understood mechanisms influencing the expression of phenotypic drug resistance. The overall sensitivity and specificity of whole genome-based DST were 86.8% and 94.5%, respectively.\n\nDespite some limitations, whole genome sequencing has high predictive power to infer resistance profiles without the need for time-consuming phenotypic methods.\n\nOne sentence summaryWhole genome sequencing of clinical M. tuberculosis isolates accurately predicts drug resistance profiles and may replace culture-based drug susceptibility testing in the future.

microbiology↗