scholarly journals Consideration of Gut Microbiome in Murine Models of Diseases

2021 ◽  
Vol 9 (5) ◽  
pp. 1062
Author(s):  
Chunye Zhang ◽  
Craig L. Franklin ◽  
Aaron C. Ericsson
Keyword(s):  
Animal Models ◽  
Mouse Models ◽  
Biomedical Research ◽  
Gut Microbiome ◽  
Close Association ◽  
Disease Model ◽  
Potential Contributor ◽  
Potential Factors ◽  
Models Of Disease ◽  
The Impact

The gut microbiome (GM), a complex community of bacteria, viruses, protozoa, and fungi located in the gut of humans and animals, plays significant roles in host health and disease. Animal models are widely used to investigate human diseases in biomedical research and the GM within animal models can change due to the impact of many factors, such as the vendor, husbandry, and environment. Notably, variations in GM can contribute to differences in disease model phenotypes, which can result in poor reproducibility in biomedical research. Variation in the gut microbiome can also impact the translatability of animal models. For example, standard lab mice have different pathogen exposure experiences when compared to wild or pet store mice. As humans have antigen experiences that are more similar to the latter, the use of lab mice with more simplified microbiomes may not yield optimally translatable data. Additionally, the literature describes many methods to manipulate the GM and differences between these methods can also result in differing interpretations of outcomes measures. In this review, we focus on the GM as a potential contributor to the poor reproducibility and translatability of mouse models of disease. First, we summarize the important role of GM in host disease and health through different gut–organ axes and the close association between GM and disease susceptibility through colonization resistance, immune response, and metabolic pathways. Then, we focus on the variation in the microbiome in mouse models of disease and address how this variation can potentially impact disease phenotypes and subsequently influence research reproducibility and translatability. We also discuss the variations between genetic substrains as potential factors that cause poor reproducibility via their effects on the microbiome. In addition, we discuss the utility of complex microbiomes in prospective studies and how manipulation of the GM through differing transfer methods can impact model phenotypes. Lastly, we emphasize the need to explore appropriate methods of GM characterization and manipulation.

scholarly journals Methods Used and Application of the Mouse Grimace Scale in Biomedical Research 10 Years On: A Scoping Review

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 673
Author(s):  
Alexandra L. Whittaker ◽  
Yifan Liu ◽  
Timothy H. Barker
Keyword(s):  
Animal Models ◽  
Mouse Models ◽  
Biomedical Research ◽  
Scoping Review ◽  
Facial Features ◽  
Inclusion Criteria ◽  
Academic Literature ◽  
Research Fields ◽  
Neuroscience Research ◽  
Wide Range

The Mouse Grimace Scale (MGS) was developed 10 years ago as a method for assessing pain through the characterisation of changes in five facial features or action units. The strength of the technique is that it is proposed to be a measure of spontaneous or non-evoked pain. The time is opportune to map all of the research into the MGS, with a particular focus on the methods used and the technique’s utility across a range of mouse models. A comprehensive scoping review of the academic literature was performed. A total of 48 articles met our inclusion criteria and were included in this review. The MGS has been employed mainly in the evaluation of acute pain, particularly in the pain and neuroscience research fields. There has, however, been use of the technique in a wide range of fields, and based on limited study it does appear to have utility for pain assessment across a spectrum of animal models. Use of the method allows the detection of pain of a longer duration, up to a month post initial insult. There has been less use of the technique using real-time methods and this is an area in need of further research.

Of mice and models: improved animal models for biomedical research

2002 ◽  
Vol 11 (3) ◽  
pp. 115-132 ◽  
Author(s):  
Ernesto Bockamp ◽  
Marko Maringer ◽  
Christian Spangenberg ◽  
Stephan Fees ◽  
Stuart Fraser ◽  
...  
Keyword(s):  
Animal Models ◽  
Mouse Models ◽  
Biomedical Research ◽  
Applied Research ◽  
Mouse Genome ◽  
Gene Knockout ◽  
Genetic Disorders ◽  
Murine Models ◽  
Good State ◽  
Basic And Applied Research

The ability to engineer the mouse genome has profoundly transformed biomedical research. During the last decade, conventional transgenic and gene knockout technologies have become invaluable experimental tools for modeling genetic disorders, assigning functions to genes, evaluating drugs and toxins, and by and large helping to answer fundamental questions in basic and applied research. In addition, the growing demand for more sophisticated murine models has also become increasingly evident. Good state-of-principle knowledge about the enormous potential of second-generation conditional mouse technology will be beneficial for any researcher interested in using these experimental tools. In this review we will focus on practice, pivotal principles, and progress in the rapidly expanding area of conditional mouse technology. The review will also present an internet compilation of available tetracycline-inducible mouse models as tools for biomedical research ( http://www.zmg.uni-mainz.de/tetmouse/ ).

scholarly journals A Review of the Current Mammalian Models of Alzheimer’s Disease and Challenges That Need to Be Overcome

2021 ◽  
Vol 22 (23) ◽  
pp. 13168
Author(s):  
Natasha Elizabeth Mckean ◽  
Renee Robyn Handley ◽  
Russell Grant Snell
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Mouse Model ◽  
Mouse Models ◽  
Small Animal ◽  
Large Animal ◽  
Complex Disorders ◽  
Large Animal Models ◽  
The Impact

Alzheimer’s disease (AD) is one of the looming health crises of the near future. Increasing lifespans and better medical treatment for other conditions mean that the prevalence of this disease is expected to triple by 2050. The impact of AD includes both the large toll on individuals and their families as well as a large financial cost to society. So far, we have no way to prevent, slow, or cure the disease. Current medications can only alleviate some of the symptoms temporarily. Many animal models of AD have been created, with the first transgenic mouse model in 1995. Mouse models have been beset by challenges, and no mouse model fully captures the symptomatology of AD without multiple genetic mutations and/or transgenes, some of which have never been implicated in human AD. Over 25 years later, many mouse models have been given an AD-like disease and then ‘cured’ in the lab, only for the treatments to fail in clinical trials. This review argues that small animal models are insufficient for modelling complex disorders such as AD. In order to find effective treatments for AD, we need to create large animal models with brains and lifespan that are closer to humans, and underlying genetics that already predispose them to AD-like phenotypes.

scholarly journals Intermittent Hypoxia and Hypercapnia Reproducibly Change the Gut Microbiome and Metabolome across Rodent Model Systems

mSystems ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Anupriya Tripathi ◽  
Zhenjiang Zech Xu ◽  
Jin Xue ◽  
Orit Poulsen ◽  
Antonio Gonzalez ◽  
...  
Keyword(s):  
Time Series ◽  
Animal Models ◽  
Mouse Models ◽  
Intermittent Hypoxia ◽  
Model Systems ◽  
Supervised Machine Learning ◽  
Animal Models Of Disease ◽  
Obstructive Sleep ◽  
Data Layer ◽  
Models Of Disease

ABSTRACT Studying perturbations in the gut ecosystem using animal models of disease continues to provide valuable insights into the role of the microbiome in various pathological conditions. However, understanding whether these changes are consistent across animal models of different genetic backgrounds, and hence potentially translatable to human populations, remains a major unmet challenge in the field. Nonetheless, in relatively limited cases have the same interventions been studied in two animal models in the same laboratory. Moreover, such studies typically examine a single data layer and time point. Here, we show the power of utilizing time series microbiome (16S rRNA amplicon profiling) and metabolome (untargeted liquid chromatography-tandem mass spectrometry [LC-MS/MS]) data to relate two different mouse models of atherosclerosis—ApoE−/− (n = 24) and Ldlr−/− (n = 16)—that are exposed to intermittent hypoxia and hypercapnia (IHH) longitudinally (for 10 and 6 weeks, respectively) to model chronic obstructive sleep apnea. Using random forest classifiers trained on each data layer, we show excellent accuracy in predicting IHH exposure within ApoE−/− and Ldlr−/− knockout models and in cross-applying predictive features found in one animal model to the other. The key microbes and metabolites that reproducibly predicted IHH exposure included bacterial species from the families Mogibacteriaceae, Clostridiaceae, bile acids, and fatty acids, providing a refined set of biomarkers associated with IHH. The results highlight that time series multiomics data can be used to relate different animal models of disease using supervised machine learning techniques and can provide a pathway toward identifying robust microbiome and metabolome features that underpin translation from animal models to human disease. IMPORTANCE Reproducibility of microbiome research is a major topic of contemporary interest. Although it is often possible to distinguish individuals with specific diseases within a study, the differences are often inconsistent across cohorts, often due to systematic variation in analytical conditions. Here we study the same intervention in two different mouse models of cardiovascular disease (atherosclerosis) by profiling the microbiome and metabolome in stool specimens over time. We demonstrate that shared microbial and metabolic changes are involved in both models with the intervention. We then introduce a pipeline for finding similar results in other studies. This work will help find common features identified across different model systems that are most likely to apply in humans.

Implicit and explicit corrective feedback and feedback exposure conditions

2020 ◽  
Vol 4 (1) ◽  
pp. 3-48
Author(s):  
Takehiro Iizuka ◽  
Kimi Nakatsukasa
Keyword(s):  
Explicit Knowledge ◽  
Corrective Feedback ◽  
Significant Difference ◽  
Oral Corrective Feedback ◽  
Post Test ◽  
Picture Description ◽  
Potential Factors ◽  
Implicit And Explicit ◽  
Instructional Settings ◽  
The Impact

This exploratory study examined the impact of implicit and explicit oral corrective feedback (CF) on the development of implicit and explicit knowledge of Japanese locative particles (activity de, movement ni and location ni) for those who directly received CF and those who observed CF in the classroom. Thirty-six college students in a beginning Japanese language course received either recast (implicit), metalinguistic (explicit) or no feedback during an information-gap picture description activity, and completed a timed picture description test (implicit knowledge) and an untimed grammaticality judgement test (explicit knowledge) in a pre-test, immediate post-test and delayed post-test. The results showed that overall there was no significant difference between CF types, and that CF benefited direct and indirect recipients similarly. Potential factors that might influence the effectiveness of CF, such as instructional settings, complexity of target structures and pedagogy styles, are discussed.

scholarly journals The gut microbiome of laboratory mice: considerations and best practices for translational research

2021 ◽  
Author(s):  
Aaron C. Ericsson ◽  
Craig L. Franklin
Keyword(s):  
Human Physiology ◽  
Best Practices ◽  
Gut Microbiota ◽  
Translational Research ◽  
Mouse Models ◽  
Gut Microbiome ◽  
Predictive Power ◽  
Environmental Influences ◽  
Pharmacological Intervention ◽  
Laboratory Mice

AbstractJust as the gut microbiota (GM) is now recognized as an integral mediator of environmental influences on human physiology, susceptibility to disease, and response to pharmacological intervention, so too does the GM of laboratory mice affect the phenotype of research using mouse models. Multiple experimental factors have been shown to affect the composition of the GM in research mice, as well as the model phenotype, suggesting that the GM represents a major component in experimental reproducibility. Moreover, several recent studies suggest that manipulation of the GM of laboratory mice can substantially improve the predictive power or translatability of data generated in mouse models to the human conditions under investigation. This review provides readers with information related to these various factors and practices, and recommendations regarding methods by which issues with poor reproducibility or translatability can be transformed into discoveries.

scholarly journals A synbiotic intervention modulates meta-omics signatures of gut redox potential and acidity in elective caesarean born infants

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Christophe Lay ◽  
Collins Wenhan Chu ◽  
Rikky Wenang Purbojati ◽  
Enzo Acerbi ◽  
Daniela I. Drautz-Moses ◽  
...  
Keyword(s):  
Risk Factor ◽  
Gut Microbiome ◽  
Reference Group ◽  
Mode Of Delivery ◽  
Controlled Study ◽  
Double Blind ◽  
Lipopolysaccharide Biosynthesis ◽  
Infant Gut Microbiome ◽  
Stool Samples ◽  
The Impact

Abstract Background The compromised gut microbiome that results from C-section birth has been hypothesized as a risk factor for the development of non-communicable diseases (NCD). In a double-blind randomized controlled study, 153 infants born by elective C-section received an infant formula supplemented with either synbiotic, prebiotics, or unsupplemented from birth until 4 months old. Vaginally born infants were included as a reference group. Stool samples were collected from day 3 till week 22. Multi-omics were deployed to investigate the impact of mode of delivery and nutrition on the development of the infant gut microbiome, and uncover putative biological mechanisms underlying the role of a compromised microbiome as a risk factor for NCD. Results As early as day 3, infants born vaginally presented a hypoxic and acidic gut environment characterized by an enrichment of strict anaerobes (Bifidobacteriaceae). Infants born by C-section presented the hallmark of a compromised microbiome driven by an enrichment of Enterobacteriaceae. This was associated with meta-omics signatures characteristic of a microbiome adapted to a more oxygen-rich gut environment, enriched with genes associated with reactive oxygen species metabolism and lipopolysaccharide biosynthesis, and depleted in genes involved in the metabolism of milk carbohydrates. The synbiotic formula modulated expression of microbial genes involved in (oligo)saccharide metabolism, which emulates the eco-physiological gut environment observed in vaginally born infants. The resulting hypoxic and acidic milieu prevented the establishment of a compromised microbiome. Conclusions This study deciphers the putative functional hallmarks of a compromised microbiome acquired during C-section birth, and the impact of nutrition that may counteract disturbed microbiome development. Trial registration The study was registered in the Dutch Trial Register (Number: 2838) on 4th April 2011.

scholarly journals POS0329 GASTROINTESTINAL INVOLVEMENT IN SYSTEMIC SCLEROSIS: PATHOGENETIC ROLE OF GUT MICROBIOME, CYTOKINES AND ADIPOKINES

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 392.1-392
Author(s):  
E. Pigatto ◽  
M. Schiesaro ◽  
M. Caputo ◽  
M. Beggio ◽  
P. Galozzi ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Gut Microbiome ◽  
Serum Levels ◽  
High Serum ◽  
Healthy Population ◽  
Gastrointestinal Involvement ◽  
Degrading Bacteria ◽  
Gi Symptoms ◽  
Low Levels ◽  
The Impact

Background:Gastrointestinal (GI) involvement is very common in patients with Systemic Sclerosis (SSc). The pathophysiology of GI manifestations has not yet been defined. Cell-mediated immunological reactions appear to lead to endothelial damage resulting in fibrosis. The risk of developing malnutrition reinforces the need to better understand GI pathophysiology in these patients.Objectives:The study aimed to evaluate GI symptoms (GIT 2.0) and malnutrition status (MUST) and to determine specific bacterial changes in gut microbiome by investigating the possible presence of positive hot spots in bacterial species in SSc patients and their potential role in the disease progression. We also evaluated serum levels of adipokines and cytokines involved in the pathogenesis of SSc and their role, in addition to gut microbiome, in predicting the onset of GI involvement and malnutrition in SSc patients.Methods:We enrolled 25 scleroderma patients (EULAR/ACR 2013 criteria). UCLA-SCTC GIT 2.0 questionnaire to evaluate GI symptoms and MUST to investigate the risk of malnutrition were used. Gut microbiome was analyzed and the samples were subjected to extraction for the 16S rRNA gene (Earth Microbiome Project and the NIH-Human Microbiome Project). The microbiome was investigated at phenotypic and genotypic level. Serum levels of cytokines and adipokines (adiponectin and leptin) were evaluated by ELISA.Results:79.9% of patients had GERD and 63.5% abdominal distension at GIT 2.0 questionnaires. 48% of patients had moderate risk of malnutrition (MUST=2) and 12% had high risk (MUST=3). Gut microbioma: 19 patients (76%) had low similarity and 11 (44%) low diversity compared to the healthy population. The prevailing enterotypes of gut microbiome was Bacteroides (80%) and Prevotella (20%). The genotypic evaluation showed a reduced concentration of: gluten-digesting (Lactobacillus); lactose-digesting (Faecalibacterium); vitamin K-producing (Enterococcus, Desulfovibrio and Veillonella); acetaldehyde-degrading bacteria. 24 patients (96%) showed a reduction in bacteria devoted to maintaining weight control (Bifidobacterium and Ruminococcus). The patients had an altered intestinal permeability with less mucolytic bacteria (Bacteroides) and reduced production of LPS (Enterobacter and Escherichia). Low levels of butyrate (Eubacterium and Clostridium), acetate and propionate were found for SCFA-producing bacteria. Potentially pathogenic bacteria were also investigated: Salmonella was found in 14 (56%), Klebsiella in 9 (36%) and Enterococcus Faecalis in 3 (12%) patients. 11 (44%) patients had elevated serum levels of IL10 and IL12; 4 (16%) had high value of leptin. Correlation was found in patients who had a reduced concentration of gluten-digesting bacteria and MUST. Elevated MUST was correlated with serological increase in IL17A and IFN-α. Serum levels of IL12 and IL10 were found to correlate with specific bacteria alterations: high concentration of acetaldehyde-producing bacteria and low levels of acetaldehyde-degrade bacteria (also correlated with high serum levels of IL6), mucolytic bacteria and producers of hydrogen sulphide, acetate and propionate. Finally, reduced levels of mucolytic bacteria and acetate producing bacteria correlated with high serum leptin levels.Conclusion:The relationship between the gut microbiome and SSc seems to be multifactorial. In our study genotypic changes of gut microbioma might play a role in damaging the permeability of the mucosa and increasing risk of malnutrition. The evaluation of gut microbiome and cytokine profile is probably going to be of value in the follow-up of SSc. However, further studies are needed to clarify the impact of GI dysbiosis on the immune system in SSc.References:[1]Patrone V. et al. Gut microbiota profile in systemic sclerosis patients with and without clinical evidence of gastrointestinal involvement, Sci Rep. 2017; 7: 14874Disclosure of Interests:None declared

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