Biology subjects

Meehan, C. J.

Publications and source records attributed to Meehan, C. J..

23 records · Page 2Linked to original sources

bioRxiv2019

Bridging the TB data gap: in silico extraction of rifampicin-resistant tuberculosis diagnostic test results from whole genome sequence data

BackgroundMycobacterium tuberculosis rapid diagnostic tests (RDTs) are widely employed in routine laboratories and national surveys for detection of rifampicin-resistant (RR)-TB. However, as next generation sequencing technologies have become more commonplace in research and surveillance programs, RDTs are being increasingly complemented by whole genome sequencing (WGS). While comparison between RDTs is difficult, all RDT results can be derived from WGS data. This can facilitate continuous analysis of RR-TB burden regardless of the data generation technology employed. By converting WGS to RDT results, we enable comparison of data with different formats and sources particularly for low and middle income high TB burden countries that employ different diagnostic algorithms for drug resistance surveys. This allows national TB control programs (NTPs) and epidemiologists to utilize all available data in the setting for improved RR-TB surveillance.\n\nMethodsWe developed the Python-based MTB Genome to Test (MTBGT) tool that transforms WGS-derived data into laboratory-validated results of the primary RDTs - Xpert MTB/RIF, XpertMTB/RIF Ultra, GenoType MDRTBplus v2.0, and GenoscholarNTM+MDRTB II. The tool was validated through RDT results of RR-TB strains with diverse resistance patterns and geographic origins and applied on routine-derived WGS data.\n\nResultsThe MTBGT tool correctly transformed the SNP data into the RDT results and generated tabulated frequencies of the RDT probes as well as rifampicin susceptible cases. The tool supplemented the RDT probe reactions output with the RR-conferring mutation based on identified SNPs. The MTBGT tool facilitated continuous analysis of RR-TB and Xpert probe reactions from different platforms and collection periods in Rwanda.\n\nConclusionOverall, the MTBGT tool allows low and middle income countries to make sense of the increasingly generated WGS in light of the readily available RDT results, and assess whether currently implemented RDTs adequately detect RR-TB in their setting. With its feature to transform WGS to RDT results and facilitate continuous RR-TB data analysis, the MTBGT tool may bridge the gap between and among data from periodic surveys, continuous surveillance, research, and routine tests, and may be integrated within the existing national connectivity platform for use by the NTP and epidemiologists to improve setting-specific RR-TB control. The MTBGT source code and accompanying documentation is available at https://github.com/KamelaNg/MTBGT.

bioinformatics↗

bioRxiv2019

A genome-based species taxonomy of the Lactobacillus Genus Complex

BackgroundThere are over 200 published species within the Lactobacillus Genus Complex (LGC), the majority of which have sequenced type strain genomes available. Although gold standard, genome-based species delimitation cutoffs are accepted by the community, they are seldom checked against currently available genome data. In addition, there are many species-level misclassification issues within the LGC. We constructed a de novo species taxonomy for the LGC based on 2,459 publicly available, decent-quality genomes and using a 94% core nucleotide identity threshold. We reconciled these de novo species with published species and subspecies names by (i) identifying genomes of type strains in our dataset and (ii) performing comparisons based on 16S rRNA sequence identity against type strains. ResultsWe found that genomes within the LGC could be divided into 239 clusters (de novo species) that were discontinuous and exclusive. Comparison of these de novo species to published species lead to the identification of ten sets of published species that can be merged and one species that can be split. Further, we found at least eight genome clusters that constitute new species. Finally, we were able to accurately classify 98 unclassified genomes and reclassify 74 wrongly classified genomes. ConclusionsThe current state of LGC species taxonomy is largely consistent with genome data, but there are some inconsistencies as well as genome misclassifications. These inconsistencies should be resolved to evolve towards a meaningful taxonomy where species have a consistent size in terms of sequence divergence.

bioinformatics↗

bioRxiv2018

Genome wide association with quantitative resistance phenotypes in Mycobacterium tuberculosis reveals novel resistance genes and regulatory regions

Drug resistance is threatening attempts at tuberculosis epidemic control. Molecular diagnostics for drug resistance that rely on the detection of resistance-related mutations could expedite patient care and accelerate progress in TB eradication. We performed minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We then used a linear mixed model to evaluate genome wide associations between mutations in MTB genes or noncoding regions and drug resistance, followed by validation of our findings in an independent dataset of 792 patient isolates. Novel associations at 13 genomic loci were confirmed in the validation set, with 2 involving noncoding regions. We found promoter mutations to have smaller average effects on resistance levels than gene body mutations in genes where both can contribute to resistance. Enabled by a quantitative measure of resistance, we estimated the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. We also report the proportion of variation in resistance levels explained by the novel loci identified here. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causative or compensatory loci, and emphasizes the contribution of the noncoding portion of the genome.

evolutionary biology↗

bioRxiv2018

Xpert Ultra can unambiguously identify specific rifampicin resistance-conferring mutations

Introduction Introduction Methods Microorganisms Results Conclusions References The deluge of data produced by XpertMTB/RIF (Cepheid) can help improve global rifampicin-resistant tuberculosis (RR-TB) control strategies through molecular epidemiological surveillance (1, 2). Recently, a new version of the test - Xpert Ultra (hereinafter called Ultra) was released (3). Determining the relationship between RR-conferring rpoB mutations, Ultra probes, and melting temperature shifts ({Delta}Tm) - the difference between mutant and wildtype melting temperatures - allows Ultra results to be utilized for rapid detection of RR-TB strains and related underlying rpoB mutations. ...

microbiology↗

bioRxiv2018

The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

BackgroundTracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult.\n\nMethodsThis study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005-2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated.\n\nFindingsOur results suggest that clusters based on Spoligotyping could encompass transmission events that occurred over 70 years prior to sampling while 24-loci-MIRU-VNTR often represented two or more decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events in timespans of up to 10 years e.g. for a 5 SNP/allele cut-off.\n\nInterpretationWith the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.

epidemiology↗