Transcript and blood-microbiome analysis towards a blood diagnostic tool for goats affected by Haemonchus contortus.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
30 03 2022
Historique:
received: 22 08 2021
accepted: 10 03 2022
entrez: 31 3 2022
pubmed: 1 4 2022
medline: 2 4 2022
Statut: epublish

Résumé

The Alpine goat (Capra aegagrus hircus) is parasitized by the barber pole worm (Haemonchus contortus). Hematological parameters from transcript and metagenome analysis in the host are reflective of infestation. We explored comparisons between blood samples of control, infected, infected zoledronic acid-treated, and infected antibody (anti-γδ T cells) treated wethers under controlled conditions. Seven days post-inoculation (dpi), we identified 7,627 transcripts associated with the different treatment types. Microbiome measurements at 7 dpi revealed fewer raw read counts across all treatments and a less diverse microbial flora than at 21 dpi. This study identifies treatment specific transcripts and an increase in microflora abundance and diversity as wethers age. Further, F/B ratio reflect health, based on depression or elevation above thresholds defined by the baseline of non-infected controls. Forty Alpine wethers were studied where blood samples were collected from five goats in four treatment groups on 7 dpi and 21 dpi. Transcript and microbiome profiles were obtained using the Partek Flow (St. Louis, Missouri, USA) software suites pipelines. Inflammation comparisons were based on the Firmicutes/Bacteriodetes ratios that are calculated as well as the reduction of microbial diversity.

Identifiants

pubmed: 35354850
doi: 10.1038/s41598-022-08939-x
pii: 10.1038/s41598-022-08939-x
pmc: PMC8967894
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5362

Informations de copyright

© 2022. The Author(s).

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Auteurs

Yonathan Tilahun (Y)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA. yonathan.tilahun@langston.edu.

Jessica Quijada Pinango (JQ)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

Felicia Johnson (F)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

Charles Lett (C)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

Kayla Smith (K)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

Terry Gipson (T)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

Malcolm McCallum (M)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

Peter Hoyt (P)

Institute for Biosecurity and Microbial Forensics, Oklahoma State University, Stillwater, OK, 74078, USA.

Andrew Tritt (A)

Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.

Archana Yadav (A)

Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, OK, 74078, USA.

Mostafa Elshahed (M)

Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, OK, 74078, USA.

Zaisen Wang (Z)

School of Agriculture and Applied Sciences, Langston University, Langston, OK, 73050, USA.

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