Immune-mediated hematological disease in dogs is associated with alterations of the fecal microbiota: a pilot study

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Abstract

Background

The dog is the most popular companion animal and is a valuable large animal model for several human diseases. Canine immune-mediated hematological diseases, including immune-mediated hemolytic anemia (IMHA) and immune thrombocytopenia (ITP), share many features in common with autoimmune hematological diseases of humans. The gut microbiome has been linked to systemic illness, but few studies have evaluated its association with immune-mediated hematological disease. To address this knowledge gap, 16S rRNA gene sequencing was used to profile the fecal microbiota of dogs with spontaneous IMHA and ITP at presentation and following successful treatment. In total, 21 affected and 13 healthy control dogs were included in the study.

Results

IMHA/ITP is associated with remodeling of fecal microbiota, marked by decreased relative abundance of the spirochete Treponema spp., increased relative abundance of the pathobionts Clostridium septicum and Escherichia coli, and increased overall microbial diversity. Logistic regression analysis demonstrated that Treponema spp. were associated with decreased risk of IMHA/ITP (odds ratio [OR] 0.24–0.34), while Ruminococcaceae UCG-009 and Christensenellaceae R-7 group were associated with increased risk of disease (OR = 6.84 [95% CI 2–32.74] and 8.36 [95% CI 1.85–71.88] respectively).

Conclusions

This study demonstrates an association of immune-mediated hematological diseases in dogs with fecal dysbiosis, and points to specific bacterial genera as biomarkers of disease. Microbes identified as positive or negative risk factors for IMHA/ITP represent an area for future research as potential targets for new diagnostic assays and/or therapeutic applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-023-00268-2.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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DADA2: High resolution sample inference from Illumina amplicon data

Benjamin J. Callahan, Paul McMurdie, Michael Rosen … (2016)

We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

Christian Quast, Elmar Pruesse, Pelin Yilmaz … (2012)

SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

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Author and article information

Contributors

O. A. Garden:

ORCID: https://orcid.org/0000-0002-4133-9487

ogarden@lsu.edu

Journal

Journal ID (nlm-ta): Anim Microbiome

Journal ID (iso-abbrev): Anim Microbiome

Title: Animal Microbiome

Publisher: BioMed Central (London )

ISSN (Electronic): 2524-4671

Publication date (Electronic): 29 September 2023

Publication date PMC-release: 29 September 2023

Publication date Collection: 2023

Volume: 5

Electronic Location Identifier: 46

Affiliations

[1 ]Department of Pathobiology and Population Sciences, The Royal Veterinary College, ( https://ror.org/01wka8n18) Royal College Street, London, NW1 0TU UK

[2 ]School of Medicine, College of Medicine, National Sun Yat-sen University, ( https://ror.org/00mjawt10) Kaohsiung, 804201 Taiwan

[3 ]Department of Clinical Sciences and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, ( https://ror.org/00b30xv10) 3900 Spruce Street, Philadelphia, PA 19104 USA

[4 ]Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, ( https://ror.org/00b30xv10) 380 South University Avenue, Philadelphia, 19104 USA

[5 ]GRID grid.34421.30, ISNI 0000 0004 1936 7312, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, , Iowa State University, ; 1809 South Riverside Drive, Ames, IA 50011 USA

[6 ]GRID grid.252546.2, ISNI 0000 0001 2297 8753, Department of Clinical Sciences, College of Veterinary Medicine, , Auburn University, ; 1220 Wire Road, Auburn, AL 36849 USA

[7 ]Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University, ( https://ror.org/05wvpxv85) North Grafton, MA 01536 USA

[8 ]GRID grid.5386.8, ISNI 000000041936877X, Department of Clinical Sciences, College of Veterinary Medicine, , Cornell University, ; 930 Campus Road, Box 31, Ithaca, NY 14853 USA

[9 ]Present Address: Dean’s Office, School of Veterinary Medicine, Louisiana State University, ( https://ror.org/05ect4e57) Skip Bertman Drive, Baton Rouge, LA 70803 USA

Author information

P.-Y. Liu https://orcid.org/0000-0003-0850-5030

D. Xia https://orcid.org/0000-0003-4571-2776

C. L. Fellman https://orcid.org/0000-0003-4799-3372

D. P. Beiting https://orcid.org/0000-0002-2865-4589

O. A. Garden https://orcid.org/0000-0002-4133-9487

Article

Publisher ID: 268

DOI: 10.1186/s42523-023-00268-2

PMC ID: 10540429

PubMed ID: 37770990

SO-VID: 1d1ca69a-da79-4626-87c5-0ee8976b89b3

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 29 March 2023

Date accepted : 20 September 2023

Funding

Funded by: The Center for Host-Microbial Interactions at the School of Veterinary Medicine, University of Pennsylvania

Custom metadata

Keywords: hemolytic anemia,thrombocytopenia,biomarker,treponema,clostridium septicum,escherichia coli,immune-mediated disease,dog,microbiome

Data availability:

Keywords: hemolytic anemia, thrombocytopenia, biomarker, treponema, clostridium septicum, escherichia coli, immune-mediated disease, dog, microbiome

Immune-mediated hematological disease in dogs is associated with alterations of the fecal microbiota: a pilot study

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Abstract

Background

Results

Conclusions

Supplementary Information

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Tick microbiome

Most cited references 114

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

DADA2: High resolution sample inference from Illumina amplicon data

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

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