Evidence map›Paper›PMID 19885392›Full record

ArticlePLoS neglected tropical diseases2009

Anti-schistosomal intervention targets identified by lifecycle transcriptomic analyses.

Jennifer M Fitzpatrick, Emily Peak, Samirah Perally, Iain W Chalmers, John Barrett, Timothy P Yoshino, Alasdair C Ivens, Karl F Hoffmann

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
9.1field-weighted citation impact, top 1% 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

76 citing papers in PubMed, 128 citations in OpenAlex.

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  11. Revisiting the Mechanisms of Immune Evasion Employed by Human Parasites.Frontiers in cellular and infection microbiology · 2021
    Review
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16 more citing papers are in PubMed but not listed here.

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

8 authors at 5 institutions in 2 countries.

Jennifer M FitzpatrickDepartment of Pathology, University of Cambridge, Cambridge, United Kingdom.
Emily Peak
Samirah Perally
Iain W Chalmers
John Barrett
Timothy P Yoshino
Alasdair C Ivens
Karl F Hoffmann
Aberystwyth University · GBInstitute of Biological, Environmental and Rural Sciences · GBFios Genomics (United Kingdom) · GBUniversity of Cambridge · GBUniversity of Wisconsin–Madison · US

Funding

Functional genomics of molluscan schistosome developmentR01AI061436 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI YOSHINO, TIMOTHY P. · 2005 to 2009
$1.7M
NIAID NIH HHS AI061436NIAID NIH HHS R01 AI061436Wellcome TrustWellcome Trust WT078317Wellcome Trust WT084273
6 · The paper itself

Abstract

backgroundNovel methods to identify anthelmintic drug and vaccine targets are urgently needed, especially for those parasite species currently being controlled by singular, often limited strategies. A clearer understanding of the transcriptional components underpinning helminth development will enable identification of exploitable molecules essential for successful parasite/host interactions. Towards this end, we present a combinatorial, bioinformatics-led approach, employing both statistical and network analyses of transcriptomic data, for identifying new immunoprophylactic and therapeutic lead targets to combat schistosomiasis. METHODOLOGY/PRINCIPAL

findingsUtilisation of a Schistosoma mansoni oligonucleotide DNA microarray consisting of 37,632 elements enabled gene expression profiling from 15 distinct parasite lifecycle stages, spanning three unique ecological niches. Statistical approaches of data analysis revealed differential expression of 973 gene products that minimally describe the three major characteristics of schistosome development: asexual processes within intermediate snail hosts, sexual maturation within definitive vertebrate hosts and sexual dimorphism amongst adult male and female worms. Furthermore, we identified a group of 338 constitutively expressed schistosome gene products (including 41 transcripts sharing no sequence similarity outside the Platyhelminthes), which are likely to be essential for schistosome lifecycle progression. While highly informative, statistics-led bioinformatics mining of the transcriptional dataset has limitations, including the inability to identify higher order relationships between differentially expressed transcripts and lifecycle stages. Network analysis, coupled to Gene Ontology enrichment investigations, facilitated a re-examination of the dataset and identified 387 clusters (containing 12,132 gene products) displaying novel examples of developmentally regulated classes (including 294 schistosomula and/or adult transcripts with no known sequence similarity outside the Platyhelminthes), which were undetectable by the statistical comparisons. CONCLUSIONS/SIGNIFICANCE: Collectively, statistical and network-based exploratory analyses of transcriptomic datasets have led to a thorough characterisation of schistosome development. Information obtained from these experiments highlighted key transcriptional programs associated with lifecycle progression and identified numerous anti-schistosomal candidate molecules including G-protein coupled receptors, tetraspanins, Dyp-type peroxidases, fucosyltransferases, leishmanolysins and the netrin/netrin receptor complex.

Indexed as

Gene Expression ProfilingGene Expression Regulation, DevelopmentalLife Cycle StagesAnimalsFemaleHelminth ProteinsHumansMaleMiceOligonucleotide Array Sequence AnalysisSchistosoma mansoniSchistosomiasis mansoniHelminth Proteins

Identifiers

PMID19885392
PMCPMC2764848
OpenAlexW2154744452

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.