Non-invasive diagnosis of pediatric tuberculosis

Thesis (Master's)--University of Washington, 2016-08Pulmonary tuberculosis (TB) is typically diagnosed by analysis of sputum samples. Sputum is a reliable specimen for TB diagnosis, but it has limitations. Requiring ill patients to cough up sputum can put health care workers at risk. The viscosity of sputum makes it difficult to work with. There are also patients, such as young children, who may have difficulty producing sputum on demand. Oral swabs could provide a quick, simple, non-invasive alternative to sputum sampling. In a preliminary study, swabs were collected from 20 adult TB cases confirmed by Cepheid’s GeneXpert (PCR) analysis of sputum. Eighteen of these subjects yielded swabs that were positive for Mycobacterium tuberculosis (MTB) DNA in a manual quantitative PCR (qPCR) analysis. Control samples from 20 healthy adults were 100% negative. The current study pursued two Aims. The first was to improve the sensitivity of oral swab analysis (OSA) by evaluating alternatives to the qPCR method used in the pilot study. Swabs were “spiked” with cultured MTB cells. Three systems were compared for their abilities to detect MTB: Qiagen’s QIAamp DNA Mini Kit followed by manual qPCR, Claremont BioSolution’s semi-automated Purelyse Kit followed by manual qPCR, and Cepheid’s fully automated GeneXpert. After adjustments to improve sensitivity, the Qiagen kit was chosen as the best method for use in the second Aim based on its sensitivity. The second Aim was to complete a pilot evaluation of OSA applied to children with suspected TB in a high TB-burden setting. Oral swab samples were collected from children aged 0-12 years with TB-like symptoms who visited a clinic in South Africa. The children were clinically diagnosed with definite TB (sputum culture or GeneXpert confirmed, N=21), possible TB (negative by sputum testing but improved after TB treatment, N=42), or not TB (negative by sputum testing and improved without TB treatment, N=22). Swabs were analyzed using the optimized Qiagen protocol. MTB was detected in approximately 24% of the definite TB subjects, while in children above the age of 59 months, MTB was detected in 50% of the definite TB subjects. In these same populations, PCR analysis by GeneXpert of induced sputum detected 52% and 63% respectively. The results show that M. tuberculosis can be detected on oral swabs using a variety of popular molecular analytical platforms. OSA may be most effective in children and adults aged five years and older

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Transcriptomic Signatures Predict Regulators of Drug Synergy and Clinical Regimen Efficacy against Tuberculosis

Multidrug combination therapy is an important strategy for treating tuberculosis, the world’s deadliest bacterial infection. Long treatment durations and growing rates of drug resistance have created an urgent need for new approaches to prioritize effective drug regimens. Hence, we developed a computational model called INDIGO-MTB that identifies synergistic drug regimens from an immense set of possible drug combinations using the pathogen response transcriptome elicited by individual drugs. Although the underlying input data for INDIGO-MTB was generated under in vitro broth culture conditions, the predictions from INDIGO-MTB correlated significantly with in vivo drug regimen efficacy from clinical trials. INDIGO-MTB also identified the transcription factor Rv1353c as a regulator of multiple drug interaction outcomes, which could be targeted for rationally enhancing drug synergy.The rapid spread of multidrug-resistant strains has created a pressing need for new drug regimens to treat tuberculosis (TB), which kills 1.8 million people each year. Identifying new regimens has been challenging due to the slow growth of the pathogen Mycobacterium tuberculosis (MTB), coupled with the large number of possible drug combinations. Here we present a computational model (INDIGO-MTB) that identified synergistic regimens featuring existing and emerging anti-TB drugs after screening in silico more than 1 million potential drug combinations using MTB drug transcriptomic profiles. INDIGO-MTB further predicted the gene Rv1353c as a key transcriptional regulator of multiple drug interactions, and we confirmed experimentally that Rv1353c upregulation reduces the antagonism of the bedaquiline-streptomycin combination. A retrospective analysis of 57 clinical trials of TB regimens using INDIGO-MTB revealed that synergistic combinations were significantly more efficacious than antagonistic combinations (P value = 1 × 10−4) based on the percentage of patients with negative sputum cultures after 8 weeks of treatment. Our study establishes a framework for rapid assessment of TB drug combinations and is also applicable to other bacterial pathogens