Evidence map›Paper›PMID 29232402›Full record

ArticlePloS one2017

Chagas disease vector blood meal sources identified by protein mass spectrometry.

Judith I Keller, Bryan A Ballif, Riley M St Clair, James J Vincent, M Carlota Monroy, Lori Stevens

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Protein mass spectrometry detects multiple bloodmeals for enhanced Chagas disease vector ecology.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2019
    Article
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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

6 authors at 1 institution in 2 countries.

Judith I KellerDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
Bryan A BallifDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
Riley M St ClairDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
James J VincentDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
M Carlota MonroyDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.
Lori StevensDepartment of Biology, University of Vermont, Burlington, Vermont, United States of America.ORCID http://orcid.org/0000-0003-3847-5979
University of Vermont · US

Funding

Vermont INBRE Administrative Supplement 2024 AWD 118P20GM103449 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI CHRISTOPHER S FRANCKLYN · 2012 to 2026
$58.4M
Chagas disease transmission: Genomic studies of the kissing bug Triatoma infestans to enhance control strategies for a neglected tropical diseaseR03AI126268 · NIAID · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI CAHAN, SARA, STEVENS, LORI · 2016 to 2017
$155k
NIAID NIH HHS R03 AI126268NIGMS NIH HHS P20 GM103449
6 · The paper itself

Abstract

Chagas disease is a complex vector borne parasitic disease involving blood feeding Triatominae (Hemiptera: Reduviidae) insects, also known as kissing bugs, and the vertebrates they feed on. This disease has tremendous impacts on millions of people and is a global health problem. The etiological agent of Chagas disease, Trypanosoma cruzi (Kinetoplastea: Trypanosomatida: Trypanosomatidae), is deposited on the mammalian host in the insect's feces during a blood meal, and enters the host's blood stream through mucous membranes or a break in the skin. Identifying the blood meal sources of triatomine vectors is critical in understanding Chagas disease transmission dynamics, can lead to identification of other vertebrates important in the transmission cycle, and aids management decisions. The latter is particularly important as there is little in the way of effective therapeutics for Chagas disease. Several techniques, mostly DNA-based, are available for blood meal identification. However, further methods are needed, particularly when sample conditions lead to low-quality DNA or to assess the risk of human cross-contamination. We demonstrate a proteomics-based approach, using liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify host-specific hemoglobin peptides for blood meal identification in mouse blood control samples and apply LC-MS/MS for the first time to Triatoma dimidiata insect vectors, tracing blood sources to species. In contrast to most proteins, hemoglobin, stabilized by iron, is incredibly stable even being preserved through geologic time. We compared blood stored with and without an anticoagulant and examined field-collected insect specimens stored in suboptimal conditions such as at room temperature for long periods of time. To our knowledge, this is the first study using LC-MS/MS on field-collected arthropod disease vectors to identify blood meal composition, and where blood meal identification was confirmed with more traditional DNA-based methods. We also demonstrate the potential of synthetic peptide standards to estimate relative amounts of hemoglobin acquired when insects feed on multiple blood sources. These LC-MS/MS methods can contribute to developing Ecohealth control strategies for Chagas disease transmission and can be applied to other arthropod disease vectors.

Indexed as

AnimalsChagas DiseaseChromatography, LiquidDietary ProteinsElectrophoresis, Polyacrylamide GelHumansMiceTandem Mass SpectrometryTriatominaeDietary Proteins

Identifiers

PMID29232402
PMCPMC5726658
OpenAlexW2774063894

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.