The causative agents of leptospirosis are responsible for an emerging zoonotic disease worldwide. One of the major routes of transmission for leptospirosis is the natural environment contaminated with the urine of a wide range of reservoir animals. Soils and surface waters also host a high diversity of non-pathogenic Leptospira and species for which the virulence status is not clearly established. The genus Leptospira is currently divided into 35 species classified into three phylogenetic clusters, which supposedly correlate with the virulence of the bacteria. In this study, a total of 90 Leptospira strains isolated from different environments worldwide including Japan, Malaysia, New Caledonia, Algeria, mainland France, and the island of Mayotte in the Indian Ocean were sequenced. A comparison of average nucleotide identity (ANI) values of genomes of the 90 isolates and representative genomes of known species revealed 30 new Leptospira species. These data also supported the existence of two clades and 4 subclades. To avoid classification that strongly implies assumption on the virulence status of the lineages, we called them P1, P2, S1, S2. One of these subclades has not yet been described and is composed of Leptospira idonii and 4 novel species that are phylogenetically related to the saprophytes. We then investigated genome diversity and evolutionary relationships among members of the genus Leptospira by studying the pangenome and core gene sets. Our data enable the identification of genome features, genes and domains that are important for each subclade, thereby laying the foundation for refining the classification of this complex bacterial genus. We also shed light on atypical genomic features of a group of species that includes the species often associated with human infection, suggesting a specific and ongoing evolution of this group of species that will require more attention. In conclusion, we have uncovered a massive species diversity and revealed a novel subclade in environmental samples collected worldwide and we have redefined the classification of species in the genus. The implication of several new potentially infectious Leptospira species for human and animal health remains to be determined but our data also provide new insights into the emergence of virulence in the pathogenic species. Leptospirosis which is an emerging zoonotic disease worldwide, is transmitted to humans through contact with soils or surface waters contaminated with the urine of reservoir animals. Species of Leptospira, which include infectious and non-infectious strains, are ubiquitous in the environment. In this study we have sequenced the genomes of strains of Leptospira isolated from several environmental sources worldwide. Comparison of these genomes with other members of the Leptospira genus revealed the existence of 30 novel Leptospira species. A comparative genomic analysis of species of the genus allowed us to identify genes or genome features that are specific of infectious species, providing insights into virulence evolution in these atypical bacteria but also allow refinement of the Leptospira classification.

The huge increase in the availability of bacterial genomes led us to a point in which we can investigate and query pan-genomes, for example, the full set of genes of a given bacterial species or clade. Here, we used a data set of 1,311 high-quality genomes from the human pathogen Pseudomonas aeruginosa, 619 of which were newly sequenced, to show that a pan-genomic approach can greatly refine the population structure of bacterial species, provide new insights to define species boundaries, and generate hypotheses on the evolution of pathogenicity. The 665-gene P. aeruginosa core genome presented here, which constitutes only 1% of the entire pan-genome, is the first to be in the same order of magnitude as the minimal bacterial genome and represents a conservative estimate of the actual core genome. Moreover, the phylogeny based on this core genome provides strong evidence for a five-group population structure that includes two previously undescribed groups of isolates. Comparative genomics focusing on antimicrobial resistance and virulence genes showed that variation among isolates was partly linked to this population structure. Finally, we hypothesized that horizontal gene transfer had an important role in this respect, and found a total of 3,010 putative complete and fragmented plasmids, 5% and 12% of which contained resistance or virulence genes, respectively. This work provides data and strategies to study the evolutionary trajectories of resistance and virulence in P. aeruginosa.

It is easy for today’s students and researchers to believe that modern bioinformatics emerged recently to assist next-generation sequencing data analysis. However, the very beginnings of bioinformatics occurred more than 50 years ago, when desktop computers were still a hypothesis and DNA could not yet be sequenced. The foundations of bioinformatics were laid in the early 1960s with the application of computational methods to protein sequence analysis (notably, de novo sequence assembly, biological sequence databases and substitution models). Later on, DNA analysis also emerged due to parallel advances in (i) molecular biology methods, which allowed easier manipulation of DNA, as well as its sequencing, and (ii) computer science, which saw the rise of increasingly miniaturized and more powerful computers, as well as novel software better suited to handle bioinformatics tasks. In the 1990s through the 2000s, major improvements in sequencing technology, along with reduced costs, gave rise to an exponential increase of data. The arrival of ‘Big Data’ has laid out new challenges in terms of data mining and management, calling for more expertise from computer science into the field. Coupled with an ever-increasing amount of bioinformatics tools, biological Big Data had (and continues to have) profound implications on the predictive power and reproducibility of bioinformatics results. To overcome this issue, universities are now fully integrating this discipline into the curriculum of biology students. Recent subdisciplines such as synthetic biology, systems biology and whole-cell modeling have emerged from the ever-increasing complementarity between computer science and biology.

Pork meat is in high demand worldwide and this is expected to increase. Pork is often raised in intensive conditions, which is conducive to the spread of infectious diseases. Vaccines, antibiotics, and other biosafety measures help mitigate the impact of infectious diseases. However, bacterial strains resistant to antibiotics are more and more frequently found in pig farms, animals, and the environment. It is now recognized that a holistic perspective is needed to sustainably fight antibiotic resistance, and that an integrated One Health approach is essential. With this in mind, this review tackles antibiotic resistance throughout the pork raising process, including their microbiome; many factors of their environment (agricultural workers, farms, rivers, etc.); and an overview of the impact of antibiotic resistance on pork meat, which is the end product available to consumers. Antibiotic resistance, while a natural process, is a public health concern. If we react, and act, collectively, it is expected to be, at least partially, reversible with judicious antibiotic usage and the development of innovative strategies and tools to foster animal health.

Background: The class Chlorophyceae (Chlorophyta) includes morphologically and ecologically diverse green algae. Most of the documented species belong to the clade formed by the Chlamydomonadales (also called Volvocales) and Sphaeropleales. Although studies based on the nuclear 18S rRNA gene or a few combined genes have shed light on the diversity and phylogenetic structure of the Chlamydomonadales, the positions of many of the monophyletic groups identified remain uncertain. Here, we used a chloroplast phylogenomic approach to delineate the relationships among these lineages.Results: To generate the analyzed amino acid and nucleotide data sets, we sequenced the chloroplast DNAs (cpDNAs) of 24 chlorophycean taxa; these included representatives from 16 of the 21 primary clades previously recognized in the Chlamydomonadales, two taxa from a coccoid lineage (Jenufa) that was suspected to be sister to the Golenkiniaceae, and two sphaeroplealeans. Using Bayesian and/or maximum likelihood inference methods, we analyzed an amino acid data set that was assembled from 69 cpDNA-encoded proteins of 73 core chlorophyte (including 33 chlorophyceans), as well as two nucleotide data sets that were generated from the 69 genes coding for these proteins and 29 RNA-coding genes. The protein and gene phylogenies were congruent and robustly resolved the branching order of most of the investigated lineages. Within the Chlamydomonadales, 22 taxa formed an assemblage of five major clades/lineages. The earliest-diverging clade displayedHafniomonas laevisand theCrucicarteria,and was followed by theRadicarteriaand then by theChloromonadinia. The latter lineage was sister to two superclades, one consisting of theOogamochlamydiniaandReinhardtiniaand the other of theCaudivolvoxaandXenovolvoxa. To our surprise, theJenufaspecies and the two spine-bearing green algae belonging to theGolenkiniaandTreubariagenera were recovered in a highly supported monophyletic group that also included three taxa representing distinct families of the Sphaeropleales (Bracteacoccaceae, Mychonastaceae, and Scenedesmaceae).Conclusions: Our phylogenomic study advances our knowledge regarding the circumscription and internal structure of the Chlamydomonadales, suggesting that a previously unrecognized lineage is sister to the Sphaeropleales. In addition, it offers new insights into the flagellar structures of the founding members of both the Chlamydomonadales and Sphaeropleales.