Evidence map›Paper›PMID 31388077›Full record

ArticleScientific reports2019

Metabolomics-based biomarker discovery for bee health monitoring: A proof of concept study concerning nutritional stress in Bombus terrestris.

Luoluo Wang, Ivan Meeus, Caroline Rombouts, Lieven Van Meulebroek, Lynn Vanhaecke, Guy Smagghe

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. MappingFoods (Basel, Switzerland) · 2021
    Article
  12. Article
  13. Article
  14. Improving bee health through genomics.Nature reviews. Genetics · 2020
    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

6 authors.

Luoluo WangDepartment of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.ORCID http://orcid.org/0000-0001-5125-8149
Ivan MeeusDepartment of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Caroline RomboutsLaboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Ghent University, Ghent, Belgium.
Lieven Van MeulebroekLaboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Ghent University, Ghent, Belgium.
Lynn VanhaeckeLaboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Ghent University, Ghent, Belgium.
Guy SmaggheDepartment of Plants and Crops, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium. Guy.Smagghe@UGent.be.ORCID http://orcid.org/0000-0001-8334-3313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bee pollinators are exposed to multiple natural and anthropogenic stressors. Understanding the effects of a single stressor in the complex environmental context of antagonistic/synergistic interactions is critical to pollinator monitoring and may serve as early warning system before a pollination crisis. This study aimed to methodically improve the diagnosis of bee stressors using a simultaneous untargeted and targeted metabolomics-based approach. Analysis of 84 Bombus terrestris hemolymph samples found 8 metabolites retained as potential biomarkers that showed excellent discrimination for nutritional stress. In parallel, 8 significantly altered metabolites, as revealed by targeted profiling, were also assigned as candidate biomarkers. Furthermore, machine learning algorithms were applied to the above-described two biomarker sets, whereby the untargeted eight components showed the best classification performance with sensitivity and specificity up to 99% and 100%, respectively. Based on pathway and biochemistry analysis, we propose that gluconeogenesis contributed significantly to blood sugar stability in bumblebees maintained on a low carbohydrate diet. Taken together, this study demonstrates that metabolomics-based biomarker discovery holds promising potential for improving bee health monitoring and to identify stressor related to energy intake and other environmental stressors.

Indexed as

Stress, PhysiologicalAnimalsBeesBiomarkersBlood GlucoseEcological Parameter MonitoringGluconeogenesisHealth StatusHemolymphMachine LearningMetabolomicsPollinationProof of Concept StudyBiomarkersBlood Glucose

Identifiers

PMID31388077
PMCPMC6684606

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.