Evidence map›Paper›PMID 30166569›Full record

ArticleScientific reports2018

Predictions of novel Schistosoma mansoni - human protein interactions consistent with experimental data.

J White Bear, Thavy Long, Danielle Skinner, James H McKerrow

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 25% of its field
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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. A comprehensive and critical overview of schistosomiasis vaccine candidates.Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2021
    Review
  7. São Paulo School of Advanced Sciences on Vaccines: an overview.The journal of venomous animals and toxins including tropical diseases · 2020
    Review
  8. Article
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 at 3 institutions in 2 countries.

J White BearDepartment of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California, San Francisco, CA, 94158, USA. jwbear15@gmail.com.
Thavy LongDepartment of Pathology and Sandler Center for Basic Research in Parasitic Diseases, University of California at San Francisco, San Francisco, California, 94158, USA.
Danielle SkinnerSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego 9500 Gilman Dr, La Jolla, CA, 92093, USA.
James H McKerrowDepartment of Pathology and Sandler Center for Basic Research in Parasitic Diseases, University of California at San Francisco, San Francisco, California, 94158, USA.
University of Montana · USCNR de la Résistance aux Antibiotiques · FRMIT Lincoln Laboratory · US

Funding

BMI Bioinformatics Training GrantsT32GM067547 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HERNANDEZ, RYAN D. · 2003 to 2022
$6.6M
NIGMS NIH HHS T32 GM067547
6 · The paper itself

Abstract

Infection by the human blood fluke, Schistosoma mansoni involves a variety of cross-species protein- protein interactions. The pathogen expresses a diverse arsenal of proteins that facilitate the breach of physical and biochemical barriers present in skin evasion of the immune system, and digestion of human plasma proteins including albumin and hemoglobin, allowing schistosomes to reside in the host for years. However, only a small number of specific interactions between S. mansoni and human proteins have been identified. We present and apply a protocol that generates testable predictions of S. mansoni-human protein interactions. In this study, we have preliminary predictions of novel interactions between schistosome and human proteins relevant to infection and the ability of the parasite to evade the immune system. We applied a computational whole-genome comparative approach to predict potential S. mansoni-human protein interactions based on similarity to known protein complexes. We first predict S. mansoni -human protein interactions based on similarity to known protein complexes. Putative interactions were then scored and assessed using several contextual filters, including the use of annotation automatically derived from literature using a simple natural language processing methodology. Next, in vitro experiments were carried out between schistosome and host proteins to validate several prospective predictions. Our method predicted 7 out of the 10 previously known cross-species interactions involved in pathogenesis between S. mansoni and its human host. Interestingly, two novel putative interactions involving Schistosoma proteins, the cercarial elastase SmCE, and the adult tegument surface protein Sm29, were also predicted and experimentally characterized. Preliminary data suggest that elafin, a host endogenous serine protease inhibitor, may be a novel substrate for SmCE. Additionally, CD59, an inhibitor of the membrane attack complex, could interact with Sm29. Furthermore, the application framework provides an integrated methodology for investigation of host-pathogen interactions and an extensive source of orthogonal data for experimental analysis. We have made the predictions available for community perusal.

Indexed as

Protein Interaction MappingAnimalsAntigens, HelminthCD59 AntigensCercariaHelminth ProteinsHumansLife Cycle StagesMesocricetusModels, MolecularPancreatic ElastaseSchistosoma mansoniSchistosomiasis mansoniSubstrate SpecificityVaccinesAntigens, HelminthCD59 AntigensHelminth ProteinsPancreatic ElastaseVaccines

Identifiers

PMID30166569
PMCPMC6117258
OpenAlexW2888328846

What OpenQuestion holds

Textmetadata
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.