Natural infection with <i>Giardia</i> is associated with altered community structure of the human and canine gut microbiome

Berry, Alexander S. F.; Johnson, Keegan S.; Martins, Rene; Sullivan, Megan C.; Amorim, Camila Farias; Putre, Alexandra; Scott, Aiysha; Wang, Shuai; Lindsay, Brianna; Baldassano, Robert N.; Nolan, Thomas J.; Beiting, Daniel P.

doi:10.1101/2020.01.13.905604

Cited by 5 publications

(6 citation statements)

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“…In mouse model, rotavirus infection resulted in increased Bacteroides and Akkermansia populations (both with mucin-degrading capability) only in the ileal microbiome [ 37 • ], but evidence for the overgrowth of these two taxa in human rotavirus infections has been inconclusive [ 21 , 26 , 34 , 39 ]. On the other hand, Giardia -induced diarrhea was consistently linked to a decrease in Gammaproteobacteria and an enrichment of Prevotella [ 40 ]. Dysentery (mucoid/bloody diarrhea) is a severe form of infectious diarrhea with heightened gut inflammation, which requires antimicrobial treatments and longer hospitalization [ 10 , 41 ].…”

Section: Dysbiosis In the Early Phase Of Diarrheamentioning

confidence: 99%

Dynamic of the human gut microbiome under infectious diarrhea

The

2022

Current Opinion in Microbiology

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Section: Dysbiosis In the Early Phase Of Diarrheamentioning

confidence: 99%

Dynamic of the human gut microbiome under infectious diarrhea

The

2022

Current Opinion in Microbiology

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“…In recent years, hypotheses regarding the association of opportunistic protists with distinct microbial profiles have been brought forth [ 59 , 60 , 61 , 62 , 63 ]. Among those, the most-studied protist is Blastocystis , which has been suggested to be an “ecosystem engineer” [ 64 ].…”

Section: Discussionmentioning

confidence: 99%

Parasites, Drugs and Captivity: Blastocystis-Microbiome Associations in Captive Water Voles

Betts

Hoque

Torbe

et al. 2021

Biology

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(1) Background: Blastocystis is a microbial eukaryote inhabiting the gastrointestinal tract of a broad range of animals including humans. Several studies have shown that the organism is associated with specific microbial profiles and bacterial taxa that have been deemed beneficial to intestinal and overall health. Nonetheless, these studies are focused almost exclusively on humans, while there is no similar information on other animals. (2) Methods: Using a combination of conventional PCR, cloning and sequencing, we investigated presence of Blastocystis along with Giardia and Cryptosporidium in 16 captive water voles sampled twice from a wildlife park. We also characterised their bacterial gut communities. (3) Results: Overall, alpha and beta diversities between water voles with and without Blastocystis did not differ significantly. Differences were noted only on individual taxa with Treponema and Kineothrix being significantly reduced in Blastocystis positive water voles. Grouping according to antiprotozoal treatment and presence of other protists did not reveal any differences in the bacterial community composition either. (4) Conclusion: Unlike human investigations, Blastocystis does not seem to be associated with specific gut microbial profiles in water voles.

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“…Some of the detected taxa have been reported by previous studies. For example, bacteria of the genus Bacteroides were detected as differentially abundant with low relative abundance in infected dogs, and bacteria of the genera Megamonas and Prevotella were significantly associated with the infection status of dogs in studies of the effect of parasite-induced infections on gut microbiome composition [6,33].…”

Section: Camp Study Canine Datamentioning

confidence: 99%

A zero-inflated Bayesian nonparametric approach for identifying differentially abundant taxa in multigroup microbiome data with covariates

Sachdeva¹,

Datta²,

Guha³

2022

Preprint

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Scientific studies conducted during the last two decades have established the central role of the microbiome in disease and health. Differential abundance analysis aims to identify microbial taxa associated with two or more sample groups defined by attributes such as disease subtype, geography, or environmental condition. The results, in turn, help clinical practitioners and researchers diagnose disease and develop new treatments more effectively. However, detecting differential abundance is uniquely challenging due to the high dimensionality, collinearity, sparsity, and compositionality of microbiome data. Further, there is a critical need for unified statistical approaches that can directly compare more than two groups and appropriately adjust for covariates. We develop a zero-inflated Bayesian nonparametric (ZIBNP) methodology that meets the multipronged challenges posed by microbiome data and identifies differentially abundant taxa in two or more groups, while also accounting for sample-specific covariates. The proposed hierarchical model flexibly adapts to unique data characteristics, casts the typically high proportion of zeros in a censoring framework, and mitigates high dimensionality and collinearity issues by utilizing the dimension reducing property of the semiparametric Chinese restaurant process. The approach relates the microbiome sampling depths to inferential precision and conforms with the compositional nature of microbiome data. In simulation studies and in the analyses of the CAnine Microbiome during Parasitism (CAMP) data on infected and uninfected dogs, and the Global Gut microbiome data on human subjects belonging to three geographical regions, we compare ZIBNP with established statistical methods for differential abundance analysis in the presence of covariates.

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Natural infection with Giardia is associated with altered community structure of the human and canine gut microbiome

Abstract: word count: 249 Main text word count: 3711 Abstract

Cited by 5 publications

References 76 publications

Dynamic of the human gut microbiome under infectious diarrhea

Dynamic of the human gut microbiome under infectious diarrhea

Parasites, Drugs and Captivity: Blastocystis-Microbiome Associations in Captive Water Voles

A zero-inflated Bayesian nonparametric approach for identifying differentially abundant taxa in multigroup microbiome data with covariates

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