Characterization of Slam-mediated Surface Lipoprotein Translocation across the Bacterial Outer Membrane
Bibliographic record
Abstract
Surfaces of many Gram-negative bacteria are decorated by peripheral membrane proteins that are anchored in the membrane by a lipid group, commonly referred to as surface lipoproteins or SLPs. SLPs play key role in nutrient acquisition, immune evasion and have been proposed as excellent vaccine antigens. Previously our lab had shown that the proper display of host transferrin binding SLP TbpB in Neisseria meningitidis required an outer membrane protein called Slam. The aim of the present study was to investigate the role Slam plays in SLP biogenesis. Using bioinformatic analysis, we show that Slams are present in a number of Gram-negative bacteria. Putative Slam genes are often found adjacent to their putative SLP substrates. In N. meningitidis, we discovered two Slam paralogs, Slam1 and Slam2, that are specific for SLPs TbpB and HpuA respectively. All putative Slam-dependent SLPs contain a C-terminal 8-stranded soluble barrel domain. The last two strands of the SLP were found to be essential for TbpB translocation and the C-terminal 8-stranded barrel domain mediated Slam specificity. Using GST-fused TbpB, we showed that the Slam-dependent translocation occurs from the C-terminus to the N-terminus. To investigate Slam mechanism, we developed an in vitro translocation system. Upon the addition of the periplasmic chaperone LolA, SLPs can be released from spheroplasts into the supernatant. We discovered that Slam containing proteoliposomes can successfully translocate spheroplast released SLPs into the liposomal lumen. Addition of other outer membrane factors such as the Bam complex did not increase the efficiency of SLP insertion and Slam12 retained their specificity in the assay. Interestingly, Slam1 proteoliposomes were also able to translocate purified unfolded TbpB into the lumen. Collectively, these findings show that Slams are both necessary and sufficient for the translocation of SLPs across the outer membrane, indicating that they act as translocons.
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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".