Reduced housing density improves statistical power of murine gut microbiota studies.
Ontology highlight
ABSTRACT:
SUBMITTER: Russell A
PROVIDER: S-EPMC9161176 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
Publications
Reduced housing density improves statistical power of murine gut microbiota studies.
Russell Amber A Copio Joanna N JN Shi Yushu Y Kang Sumin S Franklin Craig L CL Ericsson Aaron C AC
Cell reports 20220501 6
The gut microbiome of humans and animals is critical to host health. Mice are used to investigate the microbiome and its influences; however, the predictive value of such studies is hindered by cage effects due to coprophagy. Our objectives were to evaluate the influence of cage density on the statistical power to detect treatment-dependent effects of a selective pressure on microbiome composition. C57BL/6 mice were separated into groups of 2 or 4 mice per cage and then assigned to groups receiv ...[more]
Similar Datasets
Project description:PurposeIn vivo MRS is often characterized by a spectral signal-to-noise ratio (SNR) that varies highly between experiments. A common design for spectroscopic studies is to compare the ratio of two spectral peak amplitudes between groups, e.g. individual PCr/γ-ATP ratios in 31 P-MRS. The uncertainty on this ratio is often neglected. We wished to explore this assumption.TheoryThe canonical theory for the propagation of uncertainty on the ratio of two spectral peaks and its incorporation in the Frequentist hypothesis testing framework by weighted averaging is presented.MethodsTwo retrospective re-analyses of studies comparing spectral peak ratios and one prospective simulation were performed using both the weighted and unweighted methods.ResultsIt was found that propagating uncertainty correctly improved statistical power in all cases considered, which could be used to reduce the number of subjects required to perform an MR study.ConclusionThe variability of in vivo spectroscopy data is often accounted for by requiring it to meet an SNR threshold. A theoretically sound propagation of the variable uncertainty caused by quantifying spectra of differing SNR is therefore likely to improve the power of in vivo spectroscopy studies. Magn Reson Med 78:2082-2094, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
| S-EPMC5697704 | biostudies-literature
Project description:Specific-pathogen-free (SPF) mice have improved hematopoietic characteristics relative to germ-free mice, however, it is not clear whether improvements in hematopoietic traits will continue when the level of microorganism exposure is further increased. We co-housed SPF C57BL/6 mice in a conventional facility (CVT) and found a significant increase in gut microbiota diversity along with increased levels of myeloid cells and T cells, especially effector memory T cells. Through single cell RNA sequencing of sorted KL (c-Kit+Lin-) cells, we imputed a decline in long-term hematopoietic stem cells and an increase in granulocyte-monocyte progenitors in CVT mice with up-regulation of genes associated with cell survival. Bone marrow transplantation through competitive repopulation revealed a significant increase in KSL (c-Kit+Sca-1+Lin-) cell reconstitution in recipients of CVT donor cells which occurred when donors were co-housed for both one and twelve months. However, there was minimal to no gain in mature blood cell engraftment in recipients of CVT donor cells relative to those receiving SPF donor cells. We conclude that co-housing SPF mice with mice born in a conventional facility increased gut microbiota diversity, augmented myeloid cell production and T cell activation, stimulated KSL cell reconstitution, and altered hematopoietic gene expression.
| S-EPMC7503692 | biostudies-literature
Project description:BackgroundAccumulating evidence indicates interactions between human milk composition, particularly sugars (human milk oligosaccharides or HMO), the gut microbiota of human infants, and behavioral effects. Some HMO secreted in human milk are unable to be endogenously digested by the human infant but are able to be metabolized by certain species of gut microbiota, including Bifidobacterium longum subsp. infantis (B. infantis), a species sensitive to host stress (Bailey & Coe, 2004). Exposure to gut bacteria like B. infantisduring critical neurodevelopment windows in early life appears to have behavioral consequences; however, environmental, physical, and social stress during this period can also have behavioral and microbial consequences. While rodent models are a useful method for determining causal relationships between HMO, gut microbiota, and behavior, murine studies of gut microbiota usually employ oral gavage, a technique stressful to the mouse. Our aim was to develop a less-invasive technique for HMO administration to remove the potential confound of gavage stress. Under the hypothesis that stress affects gut microbiota, particularly B. infantis, we predicted the pups receiving a prebiotic solution in a less-invasive manner would have the highest amount of Bifidobacteria in their gut.MethodsThis study was designed to test two methods, active and passive, of solution administration to mice and the effects on their gut microbiome. Neonatal C57BL/6J mice housed in a specific-pathogen free facility received increasing doses of fructooligosaccharide (FOS) solution or deionized, distilled water. Gastrointestinal (GI) tracts were collected from five dams, six sires, and 41 pups over four time points. Seven fecal pellets from unhandled pups and two pellets from unhandled dams were also collected. Qualitative real-time polymerase chain reaction (qRT-PCR) was used to quantify and compare the amount of Bifidobacterium, Bacteroides, Bacteroidetes, and Firmicutes.ResultsOur results demonstrate a significant difference between the amount of Firmicutes in pups receiving water passively and those receiving FOS actively (p-value = 0.009). Additionally, we found significant differences between the fecal microbiota from handled and non-handled mouse pups.DiscussionFrom our results, we conclude even handling pups for experimental purposes, without gavage, may induce enough stress to alter the murine gut microbiota profile. We suggest further studies to examine potential stress effects on gut microbiota caused by experimental techniques. Stress from experimental techniques may need to be accounted for in future gut microbiota studies.
| S-EPMC5234434 | biostudies-literature
Project description:ObjectiveTo investigate compositional differences in the gut microbiota associated with bone homeostasis and fractures in a cohort of older adults.MethodsFaecal microbiota profiles were determined from 181 individuals with osteopenia (n = 61) or osteoporosis (n = 60), and an age- and gender-matched group with normal BMD (n = 60). Analysis of the 16S (V3-V4 region) amplicon dataset classified to the genus level was used to identify significantly differentially abundant taxa. Adjustments were made for potential confounding variables identified from the literature using several statistical models.ResultsWe identified six genera that were significantly altered in abundance in the osteoporosis or osteopenic groups compared with age- and gender-matched controls. A detailed study of microbiota associations with meta-data variables that included BMI, health status, diet and medication revealed that these meta-data explained 15-17% of the variance within the microbiota dataset. BMD measurements were significantly associated with alterations in the microbiota. After controlling for known biological confounders, five of the six taxa remained significant. Overall microbiota alpha diversity did not correlate to BMD in this study.ConclusionReduced BMD in osteopenia and osteoporosis is associated with an altered microbiota. These alterations may be useful as biomarkers or therapeutic targets in individuals at high risk of reductions in BMD. These observations will lead to a better understanding of the relationship between the microbiota and bone homeostasis.
| S-EPMC6880854 | biostudies-literature
Project description:Disorders of bile acids (BAs) are closely related to the development of liver and intestinal diseases, including acute pancreatitis (AP). However, the mechanism underlying the involvement of BAs in AP development remains unclear. We used intraperitoneal injection of cerulein to construct AP mouse models. These mice had significantly reduced tauroursodeoxycholic acid (TUDCA) and an imbalance of intestinal microbiota, based on 16S rDNA gene sequencing. To explore the role of AP-induced intestinal microbiota changes in the development of AP, we transplanted the stool obtained from AP mice to antibiotic-treated, microbiota-depleted healthy mice. Microbiota-depleted mice presented injury to the intestinal barrier function and pancreas. Additionally, microbiota depletion reduced AP-associated pancreatic injury. This indicated that the gut microbiota may worsen AP. As TUDCA was deficient in AP mice, we gavaged AP mice with it, and evaluated subsequent expression changes in the bile acid signaling receptors farnesoid-x-receptor (FXR) and its target gene fibroblast growth factor (FGF) 15. These were downregulated, and pancreatic and intestinal barrier function injury were mitigated. The gut microbiota is known to regulate bile acid production and signaling, and our analysis of changes to the gut microbiota in AP indicated that Lactobacilli may be the key contributors of TUDCA. Taken together, our study shows that supplementation with BAs could reduce pancreatic and intestinal injury, and that this effect may be associated with the gut microbiota.
| S-EPMC7309677 | biostudies-literature
Project description:Statistical power is key for robust, replicable science. Here, we systematically explored how numbers of trials and subjects affect statistical power in MEG sensor-level data. More specifically, we simulated "experiments" using the MEG resting-state dataset of the Human Connectome Project (HCP). We divided the data in two conditions, injected a dipolar source at a known anatomical location in the "signal condition", but not in the "noise condition", and detected significant differences at sensor level with classical paired t-tests across subjects, using amplitude, squared amplitude, and global field power (GFP) measures. Group-level detectability of these simulated effects varied drastically with anatomical origin. We thus examined in detail which spatial properties of the sources affected detectability, looking specifically at the distance from closest sensor and orientation of the source, and at the variability of these parameters across subjects. In line with previous single-subject studies, we found that the most detectable effects originate from source locations that are closest to the sensors and oriented tangentially with respect to the head surface. In addition, cross-subject variability in orientation also affected group-level detectability, boosting detection in regions where this variability was small and hindering detection in regions where it was large. Incidentally, we observed a considerable covariation of source position, orientation, and their cross-subject variability in individual brain anatomical space, making it difficult to assess the impact of each of these variables independently of one another. We thus also performed simulations where we controlled spatial properties independently of individual anatomy. These additional simulations confirmed the strong impact of distance and orientation and further showed that orientation variability across subjects affects detectability, whereas position variability does not. Importantly, our study indicates that strict unequivocal recommendations as to the ideal number of trials and subjects for any experiment cannot be realistically provided for neurophysiological studies and should be adapted according to the brain regions under study.
| S-EPMC8148377 | biostudies-literature
Project description:This study aimed to investigate whether class A1 scavenger receptor (SR-A1) regulated macrophage polarization and gut microbial alteration during intestinal inflammation of colitis. A murine colitis model was established by feeding with dextran sulfate sodium (DSS), and treatment groups were injected intravenously with SR-A1 antibody. Results showed a preventive effect on colitis symptoms and fewer inflammatory cell infiltrates in treatment groups. Down-regulation of inflammatory cytokines and up-regulation of anti-inflammatory cytokine related to macrophages were seen in murine PBMC and LPMC after injected with SR-A1 antibody. The percentage of M2 macrophages was also elevated in treatment groups. In addition, SR-A1 antibody treatment resulted in the decreased apoptosis and increased proliferation of colonic epithelial cells. Other findings indicated that SR-A1 antibody injection could mediate its anti-inflammatory effect via inhibiting TLR4-MyD88-NF-kB signaling pathway and alterating the gut microbiota composition. Our research identified SR-A1 as a potential therapeutic target in inflammatory bowel disease (IBD).
| S-EPMC11316757 | biostudies-literature
Project description:Multiple-trait analysis typically employs models that associate a quantitative trait locus (QTL) with all of the traits. As a result, statistical power for QTL detection may not be optimal if the QTL contributes to the phenotypic variation in only a small proportion of the traits. Excluding QTL effects that contribute little to the test statistic can improve statistical power. In this article, we show that an optimal power can be achieved when the number of QTL effects is best estimated, and that a stringent criterion for QTL effect selection may improve power when the number of QTL effects is small but can reduce power otherwise. We investigate strategies for excluding trivial QTL effects, and propose a method that improves statistical power when the number of QTL effects is relatively small, and fairly maintains the power when the number of QTL effects is large. The proposed method first uses resampling techniques to determine the number of nontrivial QTL effects, and then selects QTL effects by the backward elimination procedure for significance test. We also propose a method for testing QTL-trait associations that are desired for biological interpretation in applications. We validate our methods using simulations and Arabidopsis thaliana transcript data.
| S-EPMC5345711 | biostudies-literature
Project description:Analysis of preclinical lifespan studies often assume that outcome data from co-housed animals are indepen-dent. In practice, treatments, such as controlled feeding or putative life-extending compounds, are applied to whole housing units, and as a result the outcomes are potentially correlated within housing units. We consider intra-class (here, intra-cage) correlation in three published and two unpublished lifespan studies of aged mice encompassing more than 20 thousand observations. We show that the independence assumption underlying common analytic techniques does not hold in these data, particularly for traits associated with frailty. We describe and demonstrate various analytical tools available to accommodate this study design and highlight a limitation of standard variance components models (i.e., linear mixed models) which are the usual statisti-cal tool for handling correlated errors. Through simulations, we examine the statistical biases resulting from intra-cage correlations with similar magnitudes as observed in these case studies and discuss implications for power and reproducibility.
| S-EPMC11326161 | biostudies-literature
Project description:Group level statistical maps of blood oxygenation level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) have become a basic measurement for much of systems, cognitive and social neuroscience. A challenge in making inferences from these statistical maps is the noise and potential confounds that arise from the head motion that occurs within and between acquisition volumes. This motion results in the scan plane being misaligned during acquisition, ultimately leading to reduced statistical power when maps are constructed at the group level. In most cases, an attempt is made to correct for this motion through the use of retrospective analysis methods. In this paper, we use a prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction. We show that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction. Analysis of our results indicates that the PRAMMO acquisition reduces the variance without decreasing the signal component of the BOLD (beta). Using PRAMMO could thus improve the overall statistical power of fMRI based BOLD measurements, leading to stronger inferences of the nature of processing in the human brain.
| S-EPMC3638742 | biostudies-literature