TB Resistance Collaboration with K-RITH
Characterization of M. tuberculosis Resistance Through Whole Genome Sequence Analysis to Support Diagnostic Development, Drug Discovery, and Molecular Epidemiology.
A Collaboration with K-RITH, KwaZulu-Natal Research Institute for Tuberculosis and HIV
This collaborative sequencing project is designed to close the gap on critical deficiencies in data for the MTB genome with emphasis upon MDR, XDR, and TDR strains. The goal for this work is to obtain full genome sequence data from well characterized DR, MDR, XDR, and TDR TB strains to understand the genomic patterns of drug resistance in support of (1) predictive analytics platforms and services to support patient treatment, (2) development of new diagnostics, (3) new drug discovery and (4) molecular epidemiology for population control programs including drug supply chain management. Progress in any one of these four areas will have an immediate and positive impact on the global TB burden by providing clinicians with real-time information and better treatment options for new cases of TB.
Key to describing genomic resistance patterns in MTB is the generation of high quality genome sequence from clinical isolates that have undergone rigorous and systematic clinical laboratory drug sensitivity testing (DST). To date, these essential data are not available. A review of several public domain repositories (including GenBank, TBDB and PATRIC as well as the Genome Sequencing Centers at the Broad Institute and the Sanger Center) revealed that only a few of the more than 70 MTB genomes sequenced, assembled and placed into the public domain, are from drug resistant strains (Mardassi, 2005; Ioerger, 2009; Ioerger, 2011; Jassal, 2009; Sandegren, 2011, Zhang, 2011). Furthermore, many publicly available MTB genomes are lacking significant meta-data (both clinical and phenotypic), hampering their usability for developing genomic sequence-based tools for public health applications. As such, this project represents the first truly large scale MTB sequencing effort designed to elucidate sequence variation and novel drug resistant loci.
We propose to sequence strains from two patient cohorts from the province of KwaZulu-Natal (KZN) in South Africa: (1) PROX, (2) KZSUR (described below). Each strain has been characterized by clinical laboratory DST, confirmed by at least one other laboratory, and is accompanied by other required minimum metadata. Sequence polymorphisms will be identified and compared across genomes derived from both cohorts to identify the suite of polymorphisms corresponding to each drug resistance profile. This analysis will also allow for an assessment of how many genomes are needed to saturate the view of drug resistance polymorphisms from any one geographic locale, like KZN. This information will inform future work to sequence MTB from patient cohorts in this and other locales. In addition, the PROX study will identify polymorphisms from each PROX strain pair (isolated at admission and at eight weeks following treatment as described below) that will be directly compared to identify polymorphisms that arise in MTB strains of antibiotic treated patients over time.
PROX isolates were collected from patients enrolled in the Prospective Study of Extensively Drug Resistant Tuberculosis (XDRTB) study (PROX) of Dr. Max O’Donnell from the Albert Einstein College of Medicine in New York. Patients over the age of 18 admitted to King George V hospital in Durban, South Africa from August 2009 until the present are eligible. All of these patients have clinically confirmed XDRTB (by DST), which is stated in the PROX protocol. For the first 90 enrollees (August 2009 – August 2011), patients were followed monthly for up to two years, including a follow-up questionnaire and sputum sample. For patients admitted after August 2011, study logistics dictate that patients be seen monthly through the first six months and then periodically through up to two years. Clinical data collected in each patient’s Case Report Form (provided for reference), including patient outcomes and treatment regimens will be provided when available. We will sequence 80 XDR MTB strains from this collection.
Among the strains isolated from PROX patient sputum samples are 20 “sequential isolates”, representing 42 strains, taken at the time of admission to King George V and then at eight weeks after admission (two patients had one additional sample taken). Data from these strains will allow us to examine how XDRTB therapy influences the genomic evolution of the tubercle bacilli under antibiotic pressure and against key clinical variables. This information can be greatly useful in understanding the mechanisms of resistance and virulence in MTB.
Cohort: KZSUR (KZN Survey)
MTB clinical isolates will also be sourced from two drug-resistance surveillance projects that have been carried out in KZN since 2006. The first screened TB outpatient suspects from sequentially selected hospitals from across the province. To date, the project has screened over 5,000 subjects at 12 sites with an MTB isolation rate of approximately 25%. MDRTB rates from these outpatient sites ranged from 4% to 12% with XDRTB at below 2%. The second project was an inpatient drug resistance survey that involved two rounds of screening all patients admitted to acute medical wards in 20 hospitals KZN. In total, there were 2,964 inpatients on wards where sampling was done and 53% had a current cough and sufficient microbiological and clinical data for inclusion in the study. MTB was isolated from 543 inpatients, 15% of which were found to be MDRTB infected and 3% had XDRTB. We will sequence 97 strains from the inpatient and outpatient cohorts from the KZN Survey.
Combined, these two studies provide an excellent source of drug resistant strains for sequencing for a number of reasons. The strains were collected with written patient consent for isolate analysis, have been characterized phenotypically for susceptibility to eight drugs, and have patient clinical data obtained through interview and chart review at the time of sample collection. The profile of the strains represents the full spectrum of resistance from mono-resistance and poly-resistance through MDRTB, to pre XDRTB and XDRTB. In addition the wide geographical sampling frame and collection from TB suspects rather than confirmed cases at a single treatment center will increase the chance of capturing the full diversity of drug resistant strains.