Identification and Expression Characterization of Surface Proteins for the Detection and Isolation of Listeria monocytogenes
Bibliographic record
Abstract
Listeria monocytogenes causes a serious foodborne illness (listeriosis) with a fatality rate of about 30% in susceptible individuals (1). Timely identification of foods and food processing environments carrying this deadly bacterium is crucial for implementing effective interventions but remains a practical challenge due to the complexity of test samples, low level of bacterial contamination, and the ubiquity and the genetic diversity of Listeria isolates. The purpose of this work was to identify and assess surface proteins of L. monocytogenes that can serve as diagnostic biomarkers for pathogen isolation and detection using antibody-based methods. Bioinformatics analysis of 130 putative surface proteins encoded by the genome of L. monocytogenes F2365 (serotype 4b) revealed four uncharacterized proteins with extensive amino acid sequences unique to L. monocytogenes. These proteins did not contain identifiable PrfA-controlled promoter elements. The four proteins were expressed at the transcriptional level in vitro, as demonstrated by RT-PCR, but only one of the four proteins, LMOf2365_0639, was detected on the cell surface by immunofluorescence microscopy (IFM) using rabbit polyclonal antibodies (PAbs) raised against corresponding recombinant proteins. Transcription start site mapping and promoter prediction analysis provided evidence that the LMOf2365_0639 gene was expressed under the control of a sigma B factor-dependent promoter, an alternative sigma factor involved in stress response. Non-gel based proteomics analysis of L. monocytogenes surface proteins identified 36 surface proteins in at least one of the three trials performed. IFM with PAbs raised against each of the five candidate surface proteins identified from the proteomics study revealed a strong fluorescence signal on the surface of live L. monocytogenes cells with LMOf2365_0148 specific PAbs, indicating a good level of expression of this protein. These results suggested the potential of the surface proteins LMOf2365_0639 and LMOf2365_0148 as diagnostic biomarkers for L. monocytogenes. Thirty-five and 24 monoclonal antibodies (MAbs) were developed against purified recombinant LMOf2365_0639 and LMOf2365_0148, respectively. Three MAbs against LMOf2365_0639 and five MAbs against LMOf2365_0148 were selected and evaluated for their potential in L. monocytogenes detection and isolation based on the observation that these MAbs recognized the highest number of the 53 L. monocytogenes isolates and the lowest number of the 10 other Listeria species isolates tested. None of these MAbs reacted with the four foodborne pathogens (Campylobacter jejuni, Samonella enterica serovar Typhimurium, Escherichia coli O157:H7 and Bacillus cereus) tested. All three MAbs to LMOf2365_0639 were specific for lineage I and II isolates of L. monocytogenes commonly found in clinical and food isolates respectively and recognized the N-terminal region of LMOf2365_0639. Anti-LMOf2365_0148 MAbs were reactive to lineage I and lineages III L. monocytogenes isolates commonly found in clinical and animal isolates respectively. Both LMOf2365_0639 and LMOf2365_0148 were expressed in standard enrichment culture conditions according to Health Canada’s MFHPB-30 and MFHPB-07 methods. In addition, MAbs against LMOf2365_0148 could specifically isolate live L. monocytogenes by immunomagnetic separation even in a mixture of L. monocytogenes and non-target L. innocua. The dissociation constants of the MAbs capable of capturing L. monocytogenes ranged from 2.58 x 10-8 M to 8.87 x 10-10 M. In conclusion, two novel surface proteins LMOf2365_0639 and LMOf2365_0148 were identified, were shown to be expressed in L. monocytogenes grown in standard selective enrichment cultures, and can be explored as surface biomarkers for the isolation and detection of L. monocytogenes with specific MAbs developed in this study.
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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".