Genome sequences of lower Great Lakes Microcystis sp. reveal strain-specific genes that are present and expressed in western Lake Erie blooms
Bibliographic record
Abstract
Blooms of the potentially toxic cyanobacterium Microcystis are increasing worldwide. In the Laurentian Great Lakes they pose major socioeconomic, ecological, and human health threats, particularly in western Lake Erie. However, the interpretation of "omics" data is constrained by the highly variable genome of Microcystis and the small number of reference genome sequences from strains isolated from the Great Lakes. To address this, we sequenced two Microcystis isolates from Lake Erie (Microcystis aeruginosa LE3 and M. wesenbergii LE013-01) and one from upstream Lake St. Clair (M. cf aeruginosa LSC13-02), and compared these data to the genomes of seventeen Microcystis spp. from across the globe as well as one metagenome and seven metatranscriptomes from a 2014 Lake Erie Microcystis bloom. For the publically available strains analyzed, the core genome is ~1900 genes, representing ~11% of total genes in the pan-genome and ~45% of each strain's genome. The flexible genome content was related to Microcystis subclades defined by phylogenetic analysis of both housekeeping genes and total core genes. To our knowledge this is the first evidence that the flexible genome is linked to the core genome of the Microcystis species complex. The majority of strain-specific genes were present and expressed in bloom communities in Lake Erie. Roughly 8% of these genes from the lower Great Lakes are involved in genome plasticity (rapid gain, loss, or rearrangement of genes) and resistance to foreign genetic elements (such as CRISPR-Cas systems). Intriguingly, strain-specific genes from Microcystis cultured from around the world were also present and expressed in the Lake Erie blooms, suggesting that the Microcystis pangenome is truly global. The presence and expression of flexible genes, including strain-specific genes, suggests that strain-level genomic diversity may be important in maintaining Microcystis abundance during bloom events.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".