Non Mycobacterial Virulence Genes in the Genome of the Emerging Pathogen Mycobacterium abscessus

Mycobacterium abscessus is an emerging rapidly growing mycobacterium (RGM) causing a pseudotuberculous lung disease to which patients with cystic fibrosis (CF) are particularly susceptible. We report here its complete genome sequence. The genome of M. abscessus (CIP 104536T) consists of a 5,067,172-bp circular chromosome including 4920 predicted coding sequences (CDS), an 81-kb full-length prophage and 5 IS elements, and a 23-kb mercury resistance plasmid almost identical to pMM23 from Mycobacterium marinum. The chromosome encodes many virulence proteins and virulence protein families absent or present in only small numbers in the model RGM species Mycobacterium smegmatis. Many of these proteins are encoded by genes belonging to a “mycobacterial” gene pool (e.g. PE and PPE proteins, MCE and YrbE proteins, lipoprotein LpqH precursors). However, many others (e.g. phospholipase C, MgtC, MsrA, ABC Fe(3+) transporter) appear to have been horizontally acquired from distantly related environmental bacteria with a high G+C content, mostly actinobacteria (e.g. Rhodococcus sp., Streptomyces sp.) and pseudomonads. We also identified several metabolic regions acquired from actinobacteria and pseudomonads (relating to phenazine biosynthesis, homogentisate catabolism, phenylacetic acid degradation, DNA degradation) not present in the M. smegmatis genome. Many of the “non mycobacterial” factors detected in M. abscessus are also present in two of the pathogens most frequently isolated from CF patients, Pseudomonas aeruginosa and Burkholderia cepacia. This study elucidates the genetic basis of the unique pathogenicity of M. abscessus among RGM, and raises the question of similar mechanisms of pathogenicity shared by unrelated organisms in CF patients

Updating the approaches to define susceptibility and resistance to anti-tuberculosis agents: implications for diagnosis and treatment

11 páginas, 2 figuras, 1 tablaInappropriately high breakpoints have resulted in systematic false-susceptible AST results to anti-TB drugs. MIC, PK/PD and clinical outcome data should be combined when setting breakpoints to minimise the emergence and spread of antimicrobial resistance.I. Comas was supported by PID2019-104477RB-I00 from the Spanish Science Ministry and by ERC (CoG 101001038)Peer reviewe