Genome-wide screen identifies host colonization determinants in a bacterial gut symbiont
Bibliographic record
Abstract
Animal guts are often colonized by host-specialized bacterial species to the exclusion of other transient microorganisms, but the genetic basis of colonization ability is largely unknown. The bacterium Snodgrassella alvi is a dominant gut symbiont in honey bees, specialized in colonizing the hindgut epithelium. We developed methods for transposon-based mutagenesis in S. alvi and, using high-throughput DNA sequencing, screened genome-wide transposon insertion (Tn-seq) and transcriptome (RNA-seq) libraries to characterize both the essential genome and the genes facilitating host colonization. Comparison of Tn-seq results from laboratory cultures and from monoinoculated worker bees reveal that 519 of 2,226 protein-coding genes in S. alvi are essential in culture, whereas 399 are not essential but are beneficial for gut colonization. Genes facilitating colonization fall into three broad functional categories: extracellular interactions, metabolism, and stress responses. Extracellular components with strong fitness benefits in vivo include trimeric autotransporter adhesins, O antigens, and type IV pili (T4P). Experiments with T4P mutants establish that T4P in S. alvi likely function in attachment and biofilm formation, with knockouts experiencing a competitive disadvantage in vivo. Metabolic processes promoting colonization include essential amino acid biosynthesis and iron acquisition pathways, implying nutrient scarcity within the hindgut environment. Mechanisms to deal with various stressors, such as for the repair of double-stranded DNA breaks and protein quality control, are also critical in vivo. This genome-wide study identifies numerous genetic networks underlying colonization by a gut commensal in its native host environment, including some known from more targeted studies in other host-microbe symbioses.
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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) | 0.001 | 0.001 |
| 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".