Evidence map›Paper›PMID 30373673›Full record

ArticleMicrobiome2018

A high-throughput sequencing assay to comprehensively detect and characterize unicellular eukaryotes and helminths from biological and environmental samples.

Matthew V Cannon, Haikel Bogale, Lindsay Rutt, Michael Humphrys, Poonum Korpe, Priya Duggal, Jacques Ravel, David Serre

Open access · goldAbstract read
In one paragraph

Article in Microbiome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 37 citations in OpenAlex.

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  12. High Frequency ofJournal of fungi (Basel, Switzerland) · 2021
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  14. Haemoprotozoan surveillance in peri-urban native and introduced wildlife from Australia.Current research in parasitology & vector-borne diseases · 2021
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  15. Article
  16. SPDB: a specialized database and web-based analysis platform for swine pathogens.Database : the journal of biological databases and curation · 2020
    Article
  17. 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

8 authors at 2 institutions in 1 country.

Matthew V CannonInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.ORCID 0000-0002-3035-9490
Haikel BogaleInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
Lindsay RuttInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
Michael HumphrysInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
Poonum KorpeDepartment of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
Priya DuggalDepartment of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
Jacques RavelInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
David SerreInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA. dserre@som.umaryland.edu.
University of Maryland, Baltimore · USJohns Hopkins University · US

Funding

EXPAND PARTICIPATION BY MINORITIES IN BIOMEDICAL SCIENCER25GM055036 · NIGMS · UNIVERSITY OF MARYLAND BALTIMORE COUNTY · PI SUMMERS, MICHAEL FINLEY · 1996 to 2021
$16.9M
NIGMS NIH HHS R25 GM055036
6 · The paper itself

Abstract

backgroundSeveral of the most devastating human diseases are caused by eukaryotic parasites transmitted by arthropod vectors or through food and water contamination. These pathogens only represent a fraction of all unicellular eukaryotes and helminths that are present in the environment and many uncharacterized organisms might have subtle but pervasive effects on health, including by modifying the microbiome where they reside. Unfortunately, while we have modern molecular tools to characterize bacterial and, to a lesser extent, fungal communities, we lack suitable methods to comprehensively investigate and characterize most unicellular eukaryotes and helminths: the detection of these organisms often relies on microscopy that cannot differentiate related organisms, while molecular assays can only detect the pathogens specifically tested.

resultsHere, we describe a novel sequencing-based assay, akin to bacterial 16S rRNA sequencing, that enables high-throughput detection and characterization of a wide range of unicellular eukaryotes and helminths, including those from taxonomical groups containing all common human parasites. We designed and evaluated taxon-specific PCR primer pairs that selectively amplify all species from eight taxonomical groups (Apicomplexa, Amoeba, Diplomonadida, Kinetoplastida, Parabasalia, Nematoda, Platyhelminthes, and Microsporidia). We then used these primers to screen DNA extracted from clinical, biological, and environmental samples, and after next-generation sequencing, identified both known and previously undescribed organisms from most taxa targeted.

conclusionsThis novel high-throughput assay enables comprehensive detection and identification of eukaryotic parasites and related organisms, from a wide range of complex biological and environmental samples. This approach can be easily deployed to many settings and will efficiently complement existing methods and provide a holistic perspective on the microbiome.

Indexed as

AnimalsArthropod VectorsDNA, ProtozoanFood ContaminationFood ParasitologyHelminthsHigh-Throughput Nucleotide SequencingHumansParasitesPolymerase Chain ReactionWater PollutionDNA, ProtozoanEukaryotic pathogensFood and water safetyHigh-throughput screeningInfectious diseasesMicrobiomerRNA sequencing

Identifiers

PMID30373673
PMCPMC6206884
OpenAlexW2899403585

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.