Metagenomic assembly of new (sub)polar Cyanobacteria and their associated microbiome from non-axenic cultures
Bibliographic record
Abstract
Abstract Cyanobacteria form one of the most diversified phylum of Bacteria. They are important ecologically as primary producers, for Earth evolution and biotechnological applications. Yet, Cyanobacteria are notably difficult to purify and grow axenically, and most strains in culture collections contain heterotrophic bacteria that were likely associated to Cyanobacteria in the environment. Obtaining cyanobacterial DNA without contaminant sequences is thus a challenging and time-consuming task. Here, we deploy a metagenomic pipeline that enables the easy recovery of high-quality genomes from non-axenic cultures. We tested this pipeline on 17 cyanobacterial cultures from the BCCM/ULC public collection and generated novel genome sequences for 15 arctic or subarctic strains, of which 14 early-branching organisms that will be useful for cyanobacterial phylogenomics. In parallel, we managed to assemble 31 co-cultivated bacteria from the same cultures and showed that they mostly belong to Bacteroidetes and Proteobacteria, some of them being very closely related in spite of geographically distant sampling sites. Importance Complete genomes of cold-adapted Cyanobacteria are underrepresented in databases, due to the difficulty to grow them axenically. In this work, we report the genome sequencing of 12 (sub)arctic and 3 temperate Cyanobacteria, along with 21 Proteobacteria and 5 Bacteroidetes recovered from their microbiome. Following the use of a state-of-the-art metagenomic pipeline, 12 of our new cyanobacterial genome assemblies are of high-quality, which indicates that even non-axenic cultures can yield complete genomes suitable for phylogenomics and comparative genomics. From a methodological point of view, we investigate the fate of SSU rRNA (16S) genes during metagenomic binning and observe that multi-copy rRNA operons are lost because of higher sequencing coverage and divergent tetranucleotide frequencies. Moreover, we devised a measure of genomic identity to compare metagenomic bins of different completeness, which allowed us to show that Cyanobacteria-associated bacteria can be highly related in spite of considerable distance between collection points.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.001 |
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".