Evidence map›Paper›PMID 39852815›Full record

ReviewVaccines2025

Lipoprotein Signal Peptide as Adjuvants: Leveraging Lipobox-Driven TLR2 Activation in Modern Vaccine Design.

Muhammad Umar, Haroon Afzal, Asad Murtaza, Li-Ting Cheng

Abstract readReview
In one paragraph

Review in Vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Muhammad UmarGraduate Institute of Animal Vaccine Technology, College of Veterinary Medicine, National Pingtung University of Science and Technology, Pingtung 91201, Taiwan.
Haroon AfzalInternational Program in Animal Vaccine Technology, International College, National Pingtung University of Science and Technology, Pingtung 91201, Taiwan.ORCID 0000-0002-5256-3265
Asad MurtazaFaculty of Biosciences, Fisheries and Economics, Norwegian College of Fishery Science, UiT-The Arctic University of Norway, P.O. Box 6050 Tromsø, Norway.
Li-Ting ChengGraduate Institute of Animal Vaccine Technology, College of Veterinary Medicine, National Pingtung University of Science and Technology, Pingtung 91201, Taiwan.ORCID 0000-0002-9832-2424

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toll-like receptor 2 (TLR2) signaling is a pivotal component of immune system activation, and it is closely linked to the lipidation of bacterial proteins. This lipidation is guided by bacterial signal peptides (SPs), which ensure the precise targeting and membrane anchoring of these proteins. The lipidation process is essential for TLR2 recognition and the activation of robust immune responses, positioning lipidated bacterial proteins as potent immunomodulators and adjuvants for vaccines against bacterial-, viral-, and cancer-related antigens. The structural diversity and cleavage pathways of bacterial SPs are critical in determining lipidation efficiency and protein localization, influencing their immunogenic potential. Recent advances in bioinformatics have significantly improved the prediction of SP structures and cleavage sites, facilitating the rational design of recombinant lipoproteins optimized for immune activation. Moreover, the use of SP-containing lipobox motifs, as adjuvants to lipidate heterologous proteins, has expanded the potential of vaccines targeting a broad range of pathogens. However, challenges persist in expressing lipidated proteins, particularly within heterologous systems. These challenges can be addressed by optimizing expression systems, such as engineering

Indexed as

adjuvantbacterial lipoproteinlipoboxSPTLR2

Identifiers

PMID39852815
PMCPMC11769378

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.