Analysis of Membrane-Enriched and High Molecular Weight Proteins in <i>Leishmania infantum</i> Promastigotes and Axenic Amastigotes
Bibliographic record
Abstract
Membrane and high molecular weight (HMW) proteins tend to be underrepresented in proteome analyses. Here, we optimized a protocol designed for the extraction and purification of membranes from the protozoan parasite Leishmania using a combination of serial centrifugation and free-flow zone electrophoresis (ZE-FFE). We also enriched for Leishmania HMW proteins from total extracts using the Gelfree 8100 fractionation system. This allowed the study of expression of both membrane-enriched and HMW proteins in Leishmania infantum promastigotes and amastigotes. We identified 194 proteins with at least one transmembrane domain (TMD) and 171 HMW proteins (≥100 kDa) in the invertebrate promastigote stage and 66 proteins with at least one TMD and 154 HMW proteins in the mammalian amastigote stage. Several of the proteins identified in one of the stages are part of pathways consistent with the known biology of the parasite, with many proteins involved in lipid synthesis, numerous dynein heavy chains, and some surface antigen proteins 2 detected in the promastigote stage. Notably, some proteins involved in transport and proteolysis were detected either in promastigote or amastigote. The present study is using improved proteomic methods for studying membrane-enriched and HMW proteins helping to achieve a better understanding of the parasite life cycle.
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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".