Functional Characterization of Outer Membrane Proteins (OMPs) in <em>Xenorhabdus nematophila</em> and <em>Photorhabdus luminescens</em> through Insect Immune Defense Reactions<strong> </strong>
Bibliographic record
Abstract
Xenorhabdus nematophila and Photorhabdus luminescens are entomopathogenic symbionts that produce several toxic proteins that can interfere with the immune system of insects. Here, we showed that outer membrane proteins (OMPs) could be involved as virulence factors during bacterial symbiont pathogenesis. Purified OMPs from bacterial culture were injected fifth instar larvae of Spodoptera exigua Hübner. Larvae were surveyed for fluctuations in total haemocyte counts (THC), granulocyte percentage (cellular defence), protease, phospholipase A2 (PLA2), and phenoloxidase (PO) activities (humoral defence) at specific time intervals. Changes in the expression of the three antimicrobial peptides (AMPs), cecropin, attacin, and spodoptericin, were also measured. Larvae treated with both types of OMPs had more haemocytes than did the negative controls. OMPs of X. nematophila caused more haemocyte destruction than did the OMPs of P. luminescens. The OMPs of both bacterial species initially activated insect defensive enzymes post-injection, their activating fluctuated in different ways. Attacin, cecropin and spodoptericin were up-regulated by OMP injections more than in normal larvae. The expression of these three AMPs was maximal at four hpi with P. luminescens OMPs treatment. Expression of the three AMPs in X. nematophila treatment was irregular and lower than in the P. luminescens OMPs treatment. These findings provide insights into the role of OMPs of entomopathogenic nematode bacterial symbionts in countering the physiological defenses of insects.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".