Application of Capillary Electrophoresis Mass Spectrometry and Liquid Chromatography Multiple-Step Tandem Electrospray Mass Spectrometry To Profile Glycoform Expression during <i>Haemophilus influenzae</i> Pathogenesis in the Chinchilla Model of Experimental Otitis Media
Bibliographic record
Abstract
Otitis media caused by nontypeable Haemophilus influenzae (NTHi) is a common and recurrent bacterial infection of childhood. The structural variability and diversity of H. influenzae lipopolysaccharide (LPS) glycoforms are known to play a significant role in the commensal and disease-causing behavior of this pathogen. In this study, we determined LPS glycoform populations from NTHi strain 1003 during the course of experimental otitis media in the chinchilla model of infection by mass spectrometric techniques. Building on an established structural model of the major LPS glycoforms expressed by this NTHi strain in vitro (M. Månsson, W. Hood, J. Li, J. C. Richards, E. R. Moxon, and E. K. Schweda, Eur. J. Biochem. 269:808-818, 2002), minor isomeric glycoform populations were determined by liquid chromatography multiple-step tandem electrospray mass spectrometry (LC-ESI-MS(n)). Using capillary electrophoresis ESI-MS (CE-ESI-MS), we determined glycoform profiles for bacteria from direct middle ear fluid (MEF) samples. The LPS glycan profiles were essentially the same when the MEF samples of 7 of 10 animals were passaged on solid medium (chocolate agar). LC-ESI-MS(n) provided a sensitive method for determining the isomeric distribution of LPS glycoforms in MEF and passaged specimens. To investigate changes in LPS glycoform distribution during the course of infection, MEF samples were analyzed at 2, 5, and 9 days postinfection by CE-ESI-MS following minimal passage on chocolate agar. As previously observed, sialic acid-containing glycoforms were detected during the early stages of infection, but a trend toward more-truncated and less-complex LPS glycoforms that lacked sialic acid was found as disease progressed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".