A chemical and biological toolbox for Type Vd secretion: Characterization of the phospholipase A1 autotransporter FplA from Fusobacterium nucleatum
Bibliographic record
Abstract
Fusobacterium nucleatum is an oral pathogen that is linked to multiple human infections and colorectal cancer. Strikingly, F. nucleatum achieves virulence in the absence of large, multiprotein secretion systems (Types I, II, III, IV, and VI), which are widely used by Gram-negative bacteria for pathogenesis. By contrast, F. nucleatum strains contain genomic expansions of Type V secreted effectors (autotransporters) that are critical for host cell adherence, invasion, and biofilm formation. Here, we present the first characterization of an F. nucleatum Type Vd phospholipase class A1 autotransporter (strain ATCC 25586, gene FN1704) that we hereby rename Fusobacterium phospholipase autotransporter (FplA). Biochemical analysis of multiple Fusobacterium strains revealed that FplA is expressed as a full-length 85-kDa outer membrane–embedded protein or as a truncated phospholipase domain that remains associated with the outer membrane. Whereas the role of Type Vd secretion in bacteria remains unidentified, we show that FplA binds with high affinity to host phosphoinositide-signaling lipids, revealing a potential role for this enzyme in establishing an F. nucleatum intracellular niche. To further analyze the role of FplA, we developed an fplA gene knock-out strain, which will guide future in vivo studies to determine its potential role in F. nucleatum pathogenesis. In summary, using recombinant FplA constructs, we have identified a biochemical toolbox that includes lipid substrates for enzymatic assays, potent inhibitors, and chemical probes to detect, track, and characterize the role of Type Vd secreted phospholipases in Gram-negative bacteria.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".