Planning a future with expanded molecular DST

Transcription

1 Planning a future with expanded molecular DST Find Symposium Daniela M. Cirillo Emerging Bacterial Pathogens Unit (EBPU), San Raffaele Scientific Institute, Milan, Italy

2 Outline Where we come from Needs for sensitivity tests Available tests Current knowledge on molecular tests Need for large data bases and where we would like to go Molecular tests for key drugs with an impact on patient management Automated molecular prediction for response to therapy

3 Where we come from: MDR-TB continues to grow globally: role of DST fewer than 5% of newly diagnosed or previously treated patients are tested for drug resistance. only 19% of the estimated MDR-TB burden are reported globally Role of DST: early detection of DR-TB for: Shift of treatment Infection control Individualized regimens

4 Phenotypic tests Large scale implementation by Costly for infrastructure, equipments,maintenance,staff and training MDRTB : 3-6 weeks; XDRTB : 6-9 weeks Reproducibility and accuracy of results are drugs dependent Correlation of sensitivity test results and clinical outcome is difficult to evaluate and we have very limited or no evidence for Pyr,E, and 2 nd line drugs other than INJ and FQs on MDR cases Van Deun A. et al IJTLD 15(1):

5 Molecular tests Semi-Automated, 2. Fast detection of MDR-TB Good infrastructure required Automated, 2. User friendly, 3. Low biosafety requirements, 4. Fast detection of Rif Resistant TB

6 Knowledge of DR mechanisms and molecular tests One gene/ NO hot spot: PYR Few genes single mutations correlation to R unproven Few genes /single mutations/ crossres unclear :INJ One gene/ single mutation correlation questioned: E Few genes/ hot spot: FQ One gene/ one hot spot covering the majority RIF Mechanism of resistance Few genes/single mutations:inh

7 Low hanging fruit : 1) Rifampicin testing Bactericidal antibiotic that inhibits the bacterial DNA-dependent RNA polymerase. Target: β-subunit of the RNA polymerase (encoded by rpob), blocking elongation of the RNA chain. Absence of WT associated to failure despite a sensitive DST Mutations resulting in a sensitive DST Mutations in a hot-spot region of 81 bp of rpob gene (Rifampin resistance-determining region) RIF resistance (> 95%) Cod. 526 and 531: high level resistance to rifampicin, rifabutin e rifapentin Cod. 516 and 522: associated to rifabutin sensitivity

8 2) Isoniazid targeting mycolic acid biosynthesis Mutations in KatG gene prevent INH activation (cod. 315, 60-90%) Mutations in the direct target inha (inha belongs to the family of short-chain dehydrogenases/reductases. It is essential in MTB) Mutations in the promoter of inha gene leading to drug tritration (direct target over-production) KatG cod. 315 and -8 /-15 inha promoter region are included in current diagnostic tests Rattan A et al. EID 1998

9 Fluoroquinolones Interference with changes in DNA supercoiling by binding to topoisomerase II (DNA gyrase subunits A and B, encoded by gyra and gyrb genes). Amino acid substitutions in gyra-gyrb resistance Kohanski M et al., Nature Reviews 2010 Ofloxacin Levofloxacin Moxifloxacin Ciprofloxacin Gatifloxacin Full cross-resistance is commonly assumed among fluoroquinolones mutated in gyra hot spot However, analysis of different mutations in gyra and gyrb has shown discordant phenotypic results among the fluoroquinolones

10 Fluoroquinolones Candidate genes evaluated (3 genes) DNA gyrase: gyra, gyrb transcription factor: card Relevant genes: gyra, gyrb 224 FQ-R FQ-S sequenced for gyra and gyrb genes FQ-R most frequent MUT: gyra cod. D %; A90V, 24.2% gyrb D510D, 4.8% Targeting most frequent MUT R detection = 70% Targeting gyra+gyrb all gene R detection > 85% gyra MUT E21Q+G668D associated to FQ-R only in combination with additional mutations FQ-S only 1 case non-mdr strain harbouring S91A >mic for OFL

11 Fluoroquinolones

12 Multiple genes: second-line injectable drugs Kohanski M et al., Nature Reviews 2010 Aminoglycosides: binding to the 30S subunit of the ribosome and misincorporation of amino acids into elongating peptides (streptomycin, kanamycin, amikacin) Mutations in the rrs gene coding for 16S rrna AGs resistance Mutations in the promoter region of eis kanamycin resistance Mutations in rpsl gene (ribosomal S12 protein) streptomycin resistance Polypeptides: inhibition of the translocation of peptidyl trna and block of initiation of protein synthesis (capreomycin, viomycin) Eis acetylates multiple amines of many AGs. Upregulation of the eis gene (mutations in the promoter region) confers resistance to Kanamycin Mutations in the rrs gene coding for 16S rrna resistance Mutations in the tlya gene coding for a 2-O-methyltransferase polypeptides resistance?

13 Second-line injectable drugs Candidate genes evaluated (18 genes) rrna: rrs (16S) rrna metyltransferases: ksga, tsnr, gidb, tlya transcription factor: whib7 N-acetyltransferases: eis, Rv0262c, Rv0428c, Rv0730, Rv802c, Rv0919, Rv2170, Rv2775, Rv2851c, Rv2867c, Rv3027c, Rv3225c Relevant genes: rrs, eis, gidb, tlya 228 AG-R +192 AG-S sequenced for rrs and eis genes AG-R most frequent MUT: rrs a1401g, 21.9% eis g-14a, 36.8%; c-14t, 17.1% Targeting most frequent MUT R detection = 75% Targeting rrs+eis all gene R detection > 85% tlya CAP-R only; marginal role gidb Further studies needed. Variations in gidb appear to be phylogenetically restricted rather than being involved in drug resistance development 70% Beijing lineage (AG-S 100% WT)

14 Second-line injectables eiswt eismut Beijing clones resistant to Kan (eis mutation) Role of tlya?

15 Evaluation of Genetic Mutations Associated with Mycobacterium tuberculosis Resistance to Amikacin,Kanamycin and Capreomycin: A Systematic Review Sophia B. Georghiou et al PlosOne 2012 Need for large data bases combining clinical, phenotypic and genotypic information

16 Single mutation, correlation questioned: ethambutol Interferes in the biosynthesis of cell wall arabinogalactan Active against multiplying bacilli Poor performance of MGIT phenotypic test 50% of mutations occurs in codon 306 of embb, component of a 10 kbp operon encoding for mycobacterial arabinosyl transferase Compared to MIC mutation in embb Codon 306 detected by MTBDRsl has a specificity of 96.2% and sensitivity of 69.7%, and the PPV of 97.7% in clinical isolates Plinke et al AAC 2006, Miotto et al ERJ 2012 Van Deun A. et al IJTLD 15(1):

17 One gene (?), scattered mutations, questionable DST: pyrazinamide A. Membrane transport systems B. PZase activity C. Acid ph D. In acid conditions, POA is converted to HPOA that kills the bacterial cell by reducing membrane potential and affecting membrane transport E. Sept 2011 Trans-translation inhibition by direct targeting rpsa gene (30S ribosomal protein S1) Target for molecular tests A. 2. B. Pro-drug C Interspersed mutations in pnca gene (encoding the PZase enzyme) 72-98% 2. Failure of PZA uptake by resistant strains 3. Mutations in the direct target (preliminary data) Potential target for molecular tests E. 3. Active compound D. Modified from Zhang Y et al. IJTLD 2003, 7(1):6-21

18 PZA database 70% of mutations 808 strains 696 clinical isolates 112 spontaneous mutants Retesting with a reduced inoculum 530 MDR 166 non-mdr 112 PZA-R 352 PZA-R 77% pnca MUT 23% pnca WT 178 PZA-S 84%pncAWT 16%mut 60 PZA-R 106 PZA-S 35% PZAse neg

19 Where we want to go: universal access to DST by 2015 Implementation of R and INH testing Fast testing for key drugs: FQ,INJ Intention to test intention to use the results for treatment readjustment or infection control purposes A low density microarray may accommodate a larger number of mutations for testing simultaneously several genes with the possibility to accommodate determinants for NEW drugs

20 Major bottlenecks for an expanded molecular DST STRAINS Systematic molecular databases analysis and correlation of SNPs/ mutations/phylogenetic markers with clinical data SAMPLES Sample processing (from collection, processing, concentration to NAs extraction) Selective detection of metabolically viable bacteria (treatment monitoring)

21 Conclusions Molecular testing for Rifampin has fully shown the potential (and limitation) of molecular approaches. The Xpert format has shown: Sample preparation and volume are crucial factors Full Automation is highly appreciated by the lab staff Training of clinicians on interpretation and clinical application of results is crucial for success Phenotypic tests are an imperfect gold standard for some drugs. Mutations should be considered for patients management Implementation of tests for FQs and Inj should be performed in a near future (existing and/or novel testing format) Existing technology allows screening for multiple determinants of drug resistance in few hours (fast DST on strains)

22 And the Future What bacteria are is written on their genome, coding and NON- CODING New generation of test based on full genome analysis may change our approach to DST by the integration of different data (SNPs, phylogenetic markers, compensatory mutations, regulatory mechanisms) providing a global approach at strain level Improving capacity to integrate and interpret genomic sequences into information able to predict the response to therapy may open a completely new scenario for individualized treatment

23 Acknowledgments Emanuele Borroni Andrea M. Cabibbe Irene Festoso Paola Mantegani Paolo Miotto Luca Norbis Fulvio Salvo Elisa Tagliani Enrico Tortoli Ilaria Valente Diego Zallocco Emerging Bacterial Pathogens Unit San Raffaele Scientific Institute TB PAN-NET EU FP7 Consortium TM-REST EU FP7 Consortium TB-Child EDCTP Consortium