Evidence map›Paper›PMID 38719878›Full record

ArticleScientific reports2024

Characterizing the blood microbiota in healthy and febrile domestic cats via 16s rRNA sequencing.

Liam Kitson, Anne A M J Becker, Katrin Hartmann, Michèle Bergmann, Paulina Sepulveda-Garcia, Nivia Canales, Ananda Muller

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

7 authors.

Liam KitsonGraduate Program, Ross University School of Veterinary Medicine, West Farm, West Indies, Saint Kitts and Nevis.
Anne A M J BeckerOne Health Center for Zoonoses and Tropical Veterinary Medicine, Biomedical Sciences Department, Ross University School of Veterinary Medicine, West Farm, West Indies, Saint Kitts and Nevis.
Katrin HartmannLMU Small Animal Clinic, Centre for Clinical Veterinary Medicine, LMU Munich, Munich, Germany.
Michèle BergmannLMU Small Animal Clinic, Centre for Clinical Veterinary Medicine, LMU Munich, Munich, Germany.
Paulina Sepulveda-GarciaInstituto de Medicina Preventiva Veterinaria, Facultad de Ciencias Veterinarias, Universidad Austral de Chile, Valdivia, Chile.
Nivia CanalesInstituto de Bioquímica y Microbiología, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile.
Ananda MullerOne Health Center for Zoonoses and Tropical Veterinary Medicine, Biomedical Sciences Department, Ross University School of Veterinary Medicine, West Farm, West Indies, Saint Kitts and Nevis. AMuller@rossvet.edu.kn.

Funding

EveryCat Health Foundation No EC22-028.
6 · The paper itself

Abstract

This study aimed to evaluate the blood bacterial microbiota in healthy and febrile cats. High-quality sequencing reads from the 16S rRNA gene variable region V3-V4 were obtained from genomic blood DNA belonging to 145 healthy cats, and 140 febrile cats. Comparisons between the blood microbiota of healthy and febrile cats revealed dominant presence of Actinobacteria, followed by Firmicutes and Proteobacteria, and a lower relative abundance of Bacteroidetes. Upon lower taxonomic levels, the bacterial composition was significantly different between healthy and febrile cats. The families Faecalibacterium and Kineothrix (Firmicutes), and Phyllobacterium (Proteobacteria) experienced increased abundance in febrile samples. Whereas Thioprofundum (Proteobacteria) demonstrated a significant decrease in abundance in febrile. The bacterial composition and beta diversity within febrile cats was different according to the affected body system (Oral/GI, systemic, skin, and respiratory) at both family and genus levels. Sex and age were not significant factors affecting the blood microbiota of febrile cats nor healthy ones. Age was different between young adult and mature adult healthy cats. Alpha diversity was unaffected by any factors. Overall, the findings suggest that age, health status and nature of disease are significant factors affecting blood microbiota diversity and composition in cats, but sex is not.

Indexed as

MicrobiotaRNA, Ribosomal, 16SAnimalsBacteriaCat DiseasesCatsFemaleFeverMaleRNA, Ribosomal, 16S16S V3-V4 regionFeline microbiotaFeverInfectious disease

Identifiers

PMID38719878
PMCPMC11079020

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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.