Autoluminescent Mycobacterium tuberculosis for Rapid, Real-Time, Non-Invasive Assessment of Drug and Vaccine Efficacy

Preclinical efforts to discover and develop new drugs and vaccines for tuberculosis are hampered by the reliance on colony-forming unit (CFU) counts as primary outcomes for in vivo efficacy studies and the slow growth of Mycobacterium tuberculosis. The utility of bioluminescent M. tuberculosis reporter strains for real-time in vitro and ex vivo assessment of drug and vaccine activity has been demonstrated but a simple, non-invasive, real-time surrogate marker to replace CFU counts for real-time evaluation of drug and vaccine efficacy in vivo has not been described. We describe the development of a fully virulent and stable autoluminescent strain of M. tuberculosis and proof-of-concept experiments demonstrating its utility for in vivo bioluminescence imaging to assess the efficacy of new drugs and vaccines for tuberculosis in a mouse model. Relative light unit (RLU) counts paralleled CFU counts during the active phase of bacterial growth, with a lower limit of detection of approximately 106 CFU in live, anesthetized mice. Experiments distinguishing active from inactive anti-tuberculosis drugs and bacteriostatic drug effects from bactericidal effects were completed in less than 5 days. The ability of a recombinant BCG vaccine to limit bacterial growth was demonstrated within 3 weeks. Use of this autoluminescent reporter strain has the potential to drastically reduce the time, effort, animals and costs consumed in the evaluation of drug activity in vitro and the in vivo assessment of drug and vaccine efficacy

SPARCS: a web server to analyze (un)structured regions in coding RNA sequences.

International audienceMore than a simple carrier of the genetic information, messenger RNA (mRNA) coding regions can also harbor functional elements that evolved to control different post-transcriptional processes, such as mRNA splicing, localization and translation. Functional elements in RNA molecules are often encoded by secondary structure elements. In this aticle, we introduce Structural Profile Assignment of RNA Coding Sequences (SPARCS), an efficient method to analyze the (secondary) structure profile of protein-coding regions in mRNAs. First, we develop a novel algorithm that enables us to sample uniformly the sequence landscape preserving the dinucleotide frequency and the encoded amino acid sequence of the input mRNA. Then, we use this algorithm to generate a set of artificial sequences that is used to estimate the Z-score of classical structural metrics such as the sum of base pairing probabilities and the base pairing entropy. Finally, we use these metrics to predict structured and unstructured regions in the input mRNA sequence. We applied our methods to study the structural profile of the ASH1 genes and recovered key structural elements. A web server implementing this discovery pipeline is available at http://csb.cs.mcgill.ca/sparcs together with the source code of the sampling algorithm