Revisiting the taxonomy and evolution of pathogenicity of the genus Leptospira through the prism of genomics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".