scholarly journals Genome-based transmission modeling separates imported tuberculosis from recent transmission within an immigrant population

2017 ◽  
Author(s):  
Diepreye Ayabina ◽  
Janne O Rønning ◽  
Kristian Alfsnes ◽  
Nadia Debech ◽  
Ola B Brynildsrud ◽  
...  
Keyword(s):  
Sequence Data ◽  
Whole Genome Sequence ◽  
Time Of Arrival ◽  
Immigrant Community ◽  
Tb Control ◽  
Control Programs ◽  
Rates Of Evolution ◽  
Recent Transmission ◽  
Genotype Cluster ◽  
Low Incidence

AbstractBackgroundIn many countries tuberculosis incidence is low and largely shaped by immigrant populations from high-burden countries. This is the case in Norway, where more than 80 per cent of TB cases are found among immigrants from high-incidence countries. A variable latent period, low rates of evolution and structured social networks make separating import from within-border transmission a major conundrum to TB-control efforts in many low-incidence countries.MethodsClinical Mycobacterium tuberculosis isolates belonging to an unusually large genotype cluster associated with people born in the Horn of Africa, have been identified in Norway over the last two decades. We applied modeled transmission based on whole-genome sequence data to estimate infection times for individual patients. By contrasting these estimates with time of arrival in Norway, we estimate on a case-by-case basis whether patients were likely to have been infected before or after arrival.ResultsIndependent import was responsible for the majority of cases, but we estimate that about a quarter of the patients had contracted TB in Norway.ConclusionsThis study illuminates the transmission dynamics within an immigrant community. Our approach is broadly applicable to many settings where TB control programs can benefit from understanding when and where patients acquired tuberculosis.

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

2019 ◽  
Author(s):  
Kamela Charmaine S. Ng ◽  
Jean Claude S. Ngabonziza ◽  
Pauline Lempens ◽  
Bouke Catherine de Jong ◽  
Frank van Leth ◽  
...  
Keyword(s):  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Data Generation ◽  
Continuous Analysis ◽  
Middle Income ◽  
Tb Control ◽  
Sequencing Technologies ◽  
Surveillance Programs ◽  
Low And Middle Income

AbstractBackgroundMycobacterium 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.MethodsWe 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.ResultsThe 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.ConclusionOverall, 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.

scholarly journals Evolution and emergence of multidrug-resistant Mycobacterium tuberculosis in Chisinau, Moldova

2021 ◽  
Author(s):  
Tyler S. Brown ◽  
Vegard Eldholm ◽  
Ola Brynildsrud ◽  
Magnus Osnes ◽  
Natalie Stennis ◽  
...  
Keyword(s):  
Public Health ◽  
Population Size ◽  
Sequence Data ◽  
Multidrug Resistant ◽  
Capital City ◽  
Whole Genome Sequence ◽  
Hospital Treatment ◽  
Drug Resistant ◽  
National Guidelines ◽  
Tb Control

1.ABSTRACTBackgroundDrug-resistant tuberculosis is a high priority threat to global public health. There are still critical gaps in understanding how novel drug-resistant M. tuberculosis strains emerge and, once emergent, what drives the differential propagation of certain epidemiologically-successful strains over others. This study sought to describe the joint evolutionary and epidemiological histories of a novel multidrug-resistant M. tuberculosis strain recently identified in the capital city of the Republic of Moldova (MDR Ural/4.2).MethodsUsing whole genome sequence data and Bayesian phylogenomic methods, we reconstruct the stepwise acquisition of drug-resistance mutations in the MDR Ural/4.2 strain, estimate its historical bacterial population size over time, and infer the migration history of this strain between Eastern European countries.ResultsWe infer that MDR Ural/4.2 likely evolved (via acquisition of rpoB S450L, which confers resistance to rifampin) in the early 1990s, during a period of social turmoil following Moldovan independence from the Soviet Union. This strain subsequently underwent substantial population size expansion in the early 2000s, at a time when national guidelines encouraged in hospital treatment of TB patients. We infer exportation of this strain and its INH-resistant ancestral precursor from Moldova to neighboring countries starting as early as 1985.ConclusionsOur findings underscore how public health practice and social determinants of health shape the conditions under which M. tuberculosis evolves, and demonstrates how historical changes in these conditions shape present-day challenges in TB control. These findings underscore the need for regional coordination in TB control across Eastern Europe.

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

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7564
Author(s):  
Kamela C. S. Ng ◽  
Jean Claude S. Ngabonziza ◽  
Pauline Lempens ◽  
Bouke C. de Jong ◽  
Frank van Leth ◽  
...  
Keyword(s):  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Data Generation ◽  
Continuous Analysis ◽  
Middle Income ◽  
Tb Control ◽  
Sequencing Technologies ◽  
Surveillance Programs ◽  
Low And Middle Income

Background Mycobacterium 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. Methods We developed the Python-based MycTB 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. Results The MTBGT tool correctly transformed the single nucleotide polymorphism (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. Conclusion Overall, 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 national information system for use by the NTP and epidemiologists to improve setting-specific RR-TB control. The MTBGT source code and accompanying documentation are available at https://github.com/KamelaNg/MTBGT.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

scholarly journals Whole genome sequence data of Mycobacterium tuberculosis XDR strain, isolated from patient in Kazakhstan

Data in Brief ◽  
2020 ◽  
Vol 33 ◽  
pp. 106416
Author(s):  
Asset Daniyarov ◽  
Askhat Molkenov ◽  
Saule Rakhimova ◽  
Ainur Akhmetova ◽  
Zhannur Nurkina ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

scholarly journals Whole-genome sequence data suggests environmental adaptation of Ethiopian sheep populations

2021 ◽  
Author(s):  
Pamela Wiener ◽  
Christelle Robert ◽  
Abulgasim Ahbara ◽  
Mazdak Salavati ◽  
Ayele Abebe ◽  
...  
Keyword(s):  
High Altitude ◽  
Environmental Variables ◽  
Large Scale ◽  
Sequence Data ◽  
Strong Association ◽  
Environmental Adaptation ◽  
Whole Genome Sequence ◽  
Single Nucleotide Variants ◽  
High Altitude Adaptation ◽  
Altitude Adaptation

Abstract Great progress has been made over recent years in the identification of selection signatures in the genomes of livestock species. This work has primarily been carried out in commercial breeds for which the dominant selection pressures, are associated with artificial selection. As agriculture and food security are likely to be strongly affected by climate change, a better understanding of environment-imposed selection on agricultural species is warranted. Ethiopia is an ideal setting to investigate environmental adaptation in livestock due to its wide variation in geo-climatic characteristics and the extensive genetic and phenotypic variation of its livestock. Here, we identified over three million single nucleotide variants across 12 Ethiopian sheep populations and applied landscape genomics approaches to investigate the association between these variants and environmental variables. Our results suggest that environmental adaptation for precipitation-related variables is stronger than that related to altitude or temperature, consistent with large-scale meta-analyses of selection pressure across species. The set of genes showing association with environmental variables was enriched for genes highly expressed in human blood and nerve tissues. There was also evidence of enrichment for genes associated with high-altitude adaptation although no strong association was identified with hypoxia-inducible-factor (HIF) genes. One of the strongest altitude-related signals was for a collagen gene, consistent with previous studies of high-altitude adaptation. Several altitude-associated genes also showed evidence of adaptation with temperature, suggesting a relationship between responses to these environmental factors. These results provide a foundation to investigate further the effects of climatic variables on small ruminant populations.

scholarly journals Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Lynsey K. Whitacre ◽  
Jesse L. Hoff ◽  
Robert D. Schnabel ◽  
Sara Albarella ◽  
Francesca Ciotola ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Birth Defect ◽  
Genetic Basis ◽  
Sequence Data ◽  
Model Organism ◽  
Bubalus Bubalis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

scholarly journals Whole genome characterization of strains belonging to the Ralstonia solanacearum species complex and in silico analysis of TaqMan assays for detection in this heterogenous species complex

2021 ◽  
Author(s):  
Viola Kurm ◽  
Ilse Houwers ◽  
Claudia E. Coipan ◽  
Peter Bonants ◽  
Cees Waalwijk ◽  
...  
Keyword(s):  
Ralstonia Solanacearum ◽  
In Silico ◽  
Species Complex ◽  
Sequence Data ◽  
In Silico Analysis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequences ◽  
Pcr Assays

AbstractIdentification and classification of members of the Ralstonia solanacearum species complex (RSSC) is challenging due to the heterogeneity of this complex. Whole genome sequence data of 225 strains were used to classify strains based on average nucleotide identity (ANI) and multilocus sequence analysis (MLSA). Based on the ANI score (>95%), 191 out of 192(99.5%) RSSC strains could be grouped into the three species R. solanacearum, R. pseudosolanacearum, and R. syzygii, and into the four phylotypes within the RSSC (I,II, III, and IV). R. solanacearum phylotype II could be split in two groups (IIA and IIB), from which IIB clustered in three subgroups (IIBa, IIBb and IIBc). This division by ANI was in accordance with MLSA. The IIB subgroups found by ANI and MLSA also differed in the number of SNPs in the primer and probe sites of various assays. An in-silico analysis of eight TaqMan and 11 conventional PCR assays was performed using the whole genome sequences. Based on this analysis several cases of potential false positives or false negatives can be expected upon the use of these assays for their intended target organisms. Two TaqMan assays and two PCR assays targeting the 16S rDNA sequence should be able to detect all phylotypes of the RSSC. We conclude that the increasing availability of whole genome sequences is not only useful for classification of strains, but also shows potential for selection and evaluation of clade specific nucleic acid-based amplification methods within the RSSC.

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