The quality of multiple sequence alignments plays an important role in the accuracy of phylogenetic inference. It has been shown that removing ambiguously aligned regions, but also other sources of bias such as highly variable (saturated) characters, can improve the overall performance of many phylogenetic reconstruction methods. A current scientific trend is to build phylogenetic trees from a large number of sequence datasets (semi-)automatically extracted from numerous complete genomes. Because these approaches do not allow a precise manual curation of each dataset, there exists a real need for efficient bioinformatic tools dedicated to this alignment character trimming step.
Artemisinin resistance (delayed P. falciparum clearance following artemisinin-based combination therapy), is widespread across Southeast Asia but to date has not been reported in Africa1–4. Here we genotyped the P. falciparum K13 (Pfkelch13) propeller domain, mutations in which can mediate artemisinin resistance5,6, in pretreatment samples collected from recent dihydroarteminisin-piperaquine and artemether-lumefantrine efficacy trials in Rwanda7. While cure rates were >95% in both treatment arms, the Pfkelch13 R561H mutation was identified in 19 of 257 (7.4%) patients at Masaka. Phylogenetic analysis revealed the expansion of an indigenous R561H lineage. Gene editing confirmed that this mutation can drive artemisinin resistance in vitro. This study provides evidence for the de novo emergence of Pfkelch13-mediated artemisinin resistance in Rwanda, potentially compromising the continued success of antimalarial chemotherapy in Africa.
Marc Lecuit, Sylvain Brisse and colleagues combine Listeria monocytogenes population genomic data with human epidemiological and clinical data to study human listeriosis. They report new putative virulence factors and demonstrate that some clones are hypervirulent in a humanized mouse model of listeriosis and have enhanced neural and placental tropism. Microbial pathogenesis studies are typically performed with reference strains, thereby overlooking within-species heterogeneity in microbial virulence. Here we integrated human epidemiological and clinical data with bacterial population genomics to harness the biodiversity of the model foodborne pathogen Listeria monocytogenes and decipher the basis of its neural and placental tropisms. Taking advantage of the clonal structure of this bacterial species, we identify clones epidemiologically associated either with food or with human central nervous system (CNS) or maternal-neonatal (MN) listeriosis. The latter clones are also most prevalent in patients without immunosuppressive comorbidities. Strikingly, CNS- and MN-associated clones are hypervirulent in a humanized mouse model of listeriosis. By integrating epidemiological data and comparative genomics, we have uncovered multiple new putative virulence factors and demonstrate experimentally the contribution of the first gene cluster mediating L. monocytogenes neural and placental tropisms. This study illustrates the exceptional power in harnessing microbial biodiversity to identify clinically relevant microbial virulence attributes.
Listeria monocytogenes (Lm) is a major human foodborne pathogen. Numerous Lm outbreaks have been reported worldwide and associated with a high case fatality rate, reinforcing the need for strongly coordinated surveillance and outbreak control. We developed a universally applicable genome-wide strain genotyping approach and investigated the population diversity of Lm using 1,696 isolates from diverse sources and geographical locations. We define, with unprecedented precision, the population structure of Lm, demonstrate the occurrence of international circulation of strains and reveal the extent of heterogeneity in virulence and stress resistance genomic features among clinical and food isolates. Using historical isolates, we show that the evolutionary rate of Lm from lineage I and lineage II is low (∼2.5 × 10−7 substitutions per site per year, as inferred from the core genome) and that major sublineages (corresponding to so-called ‘epidemic clones’) are estimated to be at least 50–150 years old. This work demonstrates the urgent need to monitor Lm strains at the global level and provides the unified approach needed for global harmonization of Lm genome-based typing and population biology.
Multidrug-resistant and highly virulent Klebsiella pneumoniae isolates are emerging, but the clonal groups (CGs) corresponding to these high-risk strains have remained imprecisely defined. We aimed to identify K. pneumoniae CGs on the basis of genome-wide sequence variation and to provide a simple bioinformatics tool to extract virulence and resistance gene data from genomic data. We sequenced 48 K. pneumoniae isolates, mostly of serotypes K1 and K2, and compared the genomes with 119 publicly available genomes. A total of 694 highly conserved genes were included in a core-genome multilocus sequence typing scheme, and cluster analysis of the data enabled precise definition of globally distributed hypervirulent and multidrug-resistant CGs. In addition, we created a freely accessible database, BIGSdb-Kp, to enable rapid extraction of medically and epidemiologically relevant information from genomic sequences of K. pneumoniae. Although drug-resistant and virulent K. pneumoniae populations were largely nonoverlapping, isolates with combined virulence and resistance features were detected.
1 April 2010 in The Journal of Infectious Diseases