Overview on current WGS projects TB sequencing projects, resistance mutations and phenotypic correlation Stefan Niemann Research Center Borstel German Center for Infection Research Publications “We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. “ “72 new genes, 28 intergenic regions (IGRs), 11 nonsynonymous SNPs and 10 IGR SNPs with strong, consistent associations with drug resistance.” Publications Figure 2 Maximum-likelihood phylogeny of 1,035 M. tuberculosis isolates based on 32,445 variable sites. Publications Ongoing projects NDWG meeting participants feedback Borstel Lab – Ongoing sequencing of Mtb strains from different settings – 3000 finished Daniela Cirillo – Ongoing projects on 2000 strains from different countries – including the WHO PZA resistance project Maha Farhat, Megan Murray – 150 done (Nat. Gen.), furhter 2000 strains planned Claudio Köser - 1000 strains from China, South Africa, Sweden and Peru Dick van Soolingen – 350 strains from the Netherlands Phil Butcher – NGS directly from sputum Tim Rodwell, Antonino Catanzaro - sensitivity and specificity of SNPs for predicting M/XDR phenotypes in 416 isolates from India, Moldova, South Africa and Philippines - further 1100 pts at risk for M/XDR in India, Moldova and Western Cape - 300 PZA resistant M/XDR isolates to examine the relationship of pncA Excuse for anyone not correctly mentioned MDR TB epidemic in Eastern Europe NGS analysis of 700 MDR strains from Samara and Karakalpakstan Merker et al. in preparation MDR TB epidemic in Eastern Europe E Resistant susceptible embB Cm/Am resistant susceptible rrs_copy wt 48 69 wt 39 368 M306L 4 1 1401 a>g 64 7 M306I 53 39 514 a>c 1402 c>t 2 1 M306V 158 50 1402 c>t 1 1 L74R D328G 14 4 514 a>c 1401 a>g 8 0 Q497R 17 12 1325 a>c 0 1 N296H 1 0 906 a>g 1401 a>g 2 0 G406D 5 8 1484 g>t 1 0 D328Y 1 1 514 a>c 1401 a>n 1 0 M306I T1027T 0 1 1401 a>n 0 1 S347T 1 0 eis D354A 91 80 wt 97 278 G406S 1 0 -12 g>a 12 56 M306V T1027T 1 0 -16 g>a 1 7 H1002R 1 2 -10 c>t 6 47 D328H 0 1 -17 g>c 0 2 T1027T 0 2 -10 c>g 0 1 -8 g>t 0 1 -37 c>a 25 150 -37 c>a -12 g>a 0 1 -14 g>a 1 6 -14 g>a -2 g>c 0 1 -15 g>c -12g>a 0 1 -15 g>c 1 4 -14 g>a -9 a>g 0 1 -12 g>n 0 1 Merker et al. in preparation PreDict – NGS for M. tuberculosis DST • • • • Large Scale genotype – phenotype study 5 sites: England, Germany, South Africa, Sierra Leone NGS analysis of 2153 strains for SNP definition NGS analysis of 1500 strains for pipeline performance validation INH RIF EMB PZA SM CIP MOX OFX AK CAP KAN Total Sensitive 1,618 1,658 1,754 1,701 404 251 116 114 106 99 95 7,916 UKCRC Modernising Medical Microbiology Borderline 2 1 3 1 1 4 0 0 0 0 0 12 Resistant 274 100 55 62 73 20 15 16 6 7 9 637 Total 1,894 1,759 1,812 1,764 478 275 131 130 112 106 104 8,565 PreDICT – NGS for M. tuberculosis DST • • • Phyogenetic tree 2153 isolates - 150.000 SNP UKCRC Modernising Medical Microbiology 23 resistance targets analysed 80% of susceptible strains without mutation 80% of resistant strains with one mutation Delhi / Central Asian Bejing Africanum 1a/1b and II Bovis East Asian Indian European/American TB PANNET PZA resistance study Large study assessing pncA sequence variations in 1950 clinical isolates, including 1142 MDR and 483 fully susceptible strains: 280 genetic variants Miotto et al. in press NGS - automated data analysis PhyResSE Feuerriegel et al. in preparation NGS - automated data analysis • 96 strains analysed 75 MDR, 21 INH or RIF resistant PhyResSE • Sanger sequencing of resistance genes (katG, rpoB, pncA, embB) • All mutations determined by automated NGS analysis • Phylogenetic strain classification fully concordant with classical typing data gene # SNPs sanger sequencing # SNPs WGS analysis katG 77 77 rpoB 88 88 pncA 72 72 embB 73 73 Feuerriegel et al. in preparation NGS - automated data analysis PhyResSE Feuerriegel et al. in preparation Vision Conclusions Problems NGS initiatives are largely fragmented Data generation and analysis is not standardized NGS allows for a paradigm change in Mtb diagnostics and epidemiology Genotype phenotype correlation difficult No easy read out systems for relevant data Way forward Join forces and use the actual momentum Found the international online MTB encyclopedia initiative With relevant partners TODAY Develop easy interpretation tools for NGS data Build international consortia that work on genotype – phenotype correlation Thanks to Molekluare Mykobakteriologie Stefan Niemann Silke Feuerriegel Christiane Gerlach Susanne Homolka Thomas Kohl Sven Malm Judith Petersen Anja Lüdemann Matthias Merker Silvia Maaß Molecular Mycobacteriology Stefan Niemann Silke Feuerriegel Anna Engstrom Christiane Gerlach Susanne Homolka Barbara Tizzano Judith Petersen Thomas Kohl Sven Malm Glennah Kerubi Leila Jeljeli Ecaterina Noroc Patrick Beckert Matthias Merker Doreen Beyer Anja Lüdemann Silvia Maaß Tanja Ubben Julia Zallet Tanja Struwe-Sonnenschein Thanks to E. Sanchez Epicentre, Paris M. Bonnet MSF, Geneva S. Rüsch-Gerdes, E. Richter NRC Mykobacteria Borstel P. Supply Institute Pasteur Lille K. Fellenberg V. Schleusener Bioinformatik Borstel T. Wirth Muséum National d'Histoire Naturelle Paris I. Comas Genomics and Health Unit CSISP, Valencia S. Gagneux Tuberculosis Research Unit Swiss TPHI Basel Global Beijing study group* *25 researchers supporting this study with 24 loci MIRU-VNTR and DST data D. Cirillo TB PANNET coordinator San Rafaele, Milan All other cooperation partners
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