Structural and mechanistic analysis of a tripartite ATP-independent periplasmic TRAP transporter
Bibliographic record
Abstract
Tripartite ATP-independent periplasmic (TRAP) transporters are found widely in bacteria and archaea and consist of three structural domains, a soluble substrate-binding protein (P-domain), and two transmembrane domains (Q- and M-domains). HiSiaPQM and its homologs are TRAP transporters for sialic acid and are essential for host colonization by pathogenic bacteria. Here, we reconstitute HiSiaQM into lipid nanodiscs and use cryo-EM to reveal the structure of a TRAP transporter. It is composed of 16 transmembrane helices that are unexpectedly structurally related to multimeric elevator-type transporters. The idiosyncratic Q-domain of TRAP transporters enables the formation of a monomeric elevator architecture. A model of the tripartite PQM complex is experimentally validated and reveals the coupling of the substrate-binding protein to the transporter domains. We use single-molecule total internal reflection fluorescence (TIRF) microscopy in solid-supported lipid bilayers and surface plasmon resonance to study the formation of the tripartite complex and to investigate the impact of interface mutants. Furthermore, we characterize high-affinity single variable domains on heavy chain (VHH) antibodies that bind to the periplasmic side of HiSiaQM and inhibit sialic acid uptake, providing insight into how TRAP transporter function might be inhibited in vivo.
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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".