The goal of this proposal is to develop and implement a whole-genome sequencing (WGS) approach that will allow direct detection, identification and prediction of drug resistance profiles for Mycobacterium tuberculosis (Mtb) directly from sputum samples prior to culture. Mtb latently infects one-third of the world's population and kills 1.4 million people annually. Its deadly synergistic association with HIV and the ascendance of multi-drug-resistant strains has exacerbated this global health crisis. The length of treatment times, combined with the lack of adherence to drug regimens has caused this devastating increase in drug resistant TB cases. One of the most effective ways to address this problem is to develop rapid diagnostic tests that can accurately identify mutations associated with drug resistance. We propose the innovative step of performing WGS directly from sputum samples, which would dramatically reduce turn-around-times to days rather than weeks. In preliminary studies, we demonstrated the feasibility of such an approach, by showing that we can generate significant numbers of Mtb sequence reads directly from sputum samples using Illumina technology and customized bioinformatics pipelines. As expected, a majority of sequence reads were of human DNA. We hypothesize that simple chemical and enzymatic treatments can remove the majority of this contaminating DNA thereby enhancing the coverage for accurate Mtb genome analysis. The goal of this R03 proposal is to develop protocols to optimize DNA extraction methods from sputum samples, to enrich for Mtb DNA and to eliminate contaminating human DNA. Successful completion of these objectives will allow us to introduce this technology into clinical laboratorie to facilitate the rapid detection of mutations leading to drug-resistance. We will initially perfor a series of pilot experiments aimed at optimizing DNA extraction from sputum samples spiked with Mtb. This will involve pre-treatment with enzymatic and chemical cocktails to lyse human cells and degrade human DNA - the major contaminant. We will also assess the use of magnetic beads to purify Mtb cells from the other bacteria present as normal flora. We will use qPCR assays to assess purification and enrichment before validating the use of WGS directly on clinical sputum samples in parallel with testing methods currently used in our laboratory. This innovative approach exploits our documented expertise in clinical TB research, whole genome sequencing and development of high throughput bio-informatic pipelines, combined with our access to a unique collection of clinical isolates and specimens for direct testing. Upon completion of this work, we will have developed a new methodology for rapid detection of drug-resistant Mtb strains that will dramatically enhance TB treatments by allowing early implementation of optimized antibiotic therapy. It will also permit timely implementation of preventive measures to minimize the spread of the disease by identifying patients harboring the most dangerous strains.
The goal of this proposal is to develop and implement a whole-genome sequencing approach that will allow direct detection, identification and prediction of drug resistance profiles for Mycobacterium tuberculosis (Mtb) directly from sputum samples prior to culture. Upon completion of this work, we will have developed a new methodology for rapid detection of drug-resistant Mtb strains that will dramatically enhance tuberculosis treatments by allowing early implementation of optimized antibiotic therapy. It will also permit timely implementation of preventive measures to minimize the spread of the disease by identifying patients harboring the most dangerous strains.
| Shea, Joseph; Halse, Tanya A; Lapierre, Pascal et al. (2017) Comprehensive Whole-Genome Sequencing and Reporting of Drug Resistance Profiles on Clinical Cases of Mycobacterium tuberculosis in New York State. J Clin Microbiol 55:1871-1882 |
| Lapierre, Pascal; Halse, Tanya A; Shea, Joseph et al. (2016) Draft Genome Sequence of Branchiibius sp. NY16-3462-2, Isolated from a Mixed Clinical Sample. Genome Announc 4: |
