MUBII-TB-DB: a database of mutations associated with antibiotic resistance in Mycobacterium tuberculosis

Abstract

Background: Tuberculosis is an infectious bacterial disease caused by Mycobacterium tuberculosis. It remains a major health threat, killing over one million people every year worldwide. An early antibiotic therapy is the basis of the treatment, and the emergence and spread of multidrug and extensively drug-resistant mutant strains raise significant challenges. As these bacteria grow very slowly, drug resistance mutations are currently detected using molecular biology techniques. Resistance mutations are identified by sequencing the resistance-linked genes followed by a comparison with the literature data. The only online database is the TB Drug Resistance Mutation database (TBDReaM database); however, it requires mutation detection before use, and its interrogation is complex due to its loose syntax and grammar.

Description: The MUBII-TB-DB database is a simple, highly structured text-based database that contains a set of Mycobacterium tuberculosis mutations (DNA and proteins) occurring at seven loci: rpoB, pncA, katG; mabA(fabG1)-inhA, gyrA, gyrB, and rrs. Resistance mutation data were extracted after the systematic review of MEDLINE referenced publications before March 2013. MUBII analyzes the query sequence obtained by PCR-sequencing using two parallel strategies: i) a BLAST search against a set of previously reconstructed mutated sequences and ii) the alignment of the query sequences (DNA and its protein translation) with the wild-type sequences. The post-treatment includes the extraction of the aligned sequences together with their descriptors (position and nature of mutations). The whole procedure is performed using the internet. The results are graphs (alignments) and text (description of the mutation, therapeutic significance). The system is quick and easy to use, even for technicians without bioinformatics training.

Conclusion: MUBII-TB-DB is a structured database of the mutations occurring at seven loci of major therapeutic value in tuberculosis management. Moreover, the system provides interpretation of the mutations in biological and therapeutic terms and can evolve by the addition of newly described mutations. Its goal is to provide easy and comprehensive access through a client-server model over the Web to an up-to-date database of mutations that lead to the resistance of M. tuberculosis to antibiotics.

Figure 1

Study selection process and reasons for the exclusion of studies.

Figure 2

MUBII general organization. The MUBII-TB-DB database and the de novo constructed mutation database (orange frame) are built before the query session. The mutation database is used for the results interpretation and for the construction of the BLAST mutation database. Ovals indicate the use of external software (dark green) or of MUBII routines (pale green). The query analysis process (green frame) combines the BLAST result and the expertise of the alignment using the mutation database. Outputs are in blue.

Figure 3

Screen capture of an rpoB query: DNA alignment and detected mutations. The figure shows an example of the detection of a mutation. The whole nucleotide alignment can be observed by horizontally scrolling the alignment window. In the case of the rpoB gene mutation, the nucleotide positions in M. tuberculosis and E. coli are indicated. The protein scheme compares the wild-type and query sequences for a given position. This scheme describes the changes along the protein sequence and emphasizes the effect of the mutation on the protein chain.

Figure 4

Protein alignment and detected mutations. A shows the detection of a mutation. B shows frameshift creation. C shows stop-codon creation. The whole alignment can be observed by horizontally scrolling the alignment window. These representations emphasize the effect of the mutation on the protein chain to provide solid understanding in terms of establishing therapy and monitoring.