Vendor effects on murine gut microbiota and its influence on lipopolysaccharide-induced lung inflammation and Gram-negative pneumonia

Spatiotemporal dynamics during niche remodeling by super-colonizing microbiota in the mammalian gut

While fecal microbiota transplantation (FMT) has been shown to be effective in reversing gut dysbiosis, we lack an understanding of the fundamental processes underlying microbial engraftment in the mammalian gut. Here, we explored a murine gut colonization model leveraging natural inter-individual variations in gut microbiomes to elucidate the spatiotemporal dynamics of FMT. We identified a natural "super-donor" consortium that robustly engrafts into diverse recipients and resists reciprocal colonization. Temporal profiling of the gut microbiome showed an ordered succession of rapid engraftment by early colonizers within 72 h, followed by a slower emergence of late colonizers over 15-30 days. Moreover, engraftment was localized to distinct compartments of the gastrointestinal tract in a species-specific manner. Spatial metagenomic characterization suggested engraftment was mediated by simultaneous transfer of spatially co-localizing species from the super-donor consortia. These results offer a mechanism of super-donor colonization by which nutritional niches are expanded in a spatiotemporally dependent manner. A record of this paper's transparent peer review process is included in the supplemental information.

Influence of angiotensin II on the gut microbiome: modest effects in comparison to experimental factors

AIMS

Animal models are regularly used to test the role of the gut microbiome in hypertension. Small-scale pre-clinical studies have investigated changes to the gut microbiome in the angiotensin II hypertensive model. However, the gut microbiome is influenced by internal and external experimental factors, which are not regularly considered in the study design. Once these factors are accounted for, it is unclear if microbiome signatures are reproduceable. We aimed to determine the influence of angiotensin II treatment on the gut microbiome using a large and diverse cohort of mice and to quantify the magnitude by which other factors contribute to microbiome variations.

METHODS AND RESULTS

We conducted a retrospective study to establish a diverse mouse cohort resembling large human studies. We sequenced the V4 region of the 16S rRNA gene from 538 samples across the gastrointestinal tract of 303 male and female C57BL/6J mice randomized into sham or angiotensin II treatment from different genotypes, diets, animal facilities, and age groups. Analysing over 17 million sequencing reads, we observed that angiotensin II treatment influenced α-diversity (P = 0.0137) and β-diversity (i.e. composition of the microbiome, P < 0.001). Bacterial abundance analysis revealed patterns consistent with a reduction in short-chain fatty acid producers, microbial metabolites that lower blood pressure. Furthermore, animal facility, genotype, diet, age, sex, intestinal sampling site, and sequencing batch had significant effects on both α- and β-diversity (all P < 0.001). Sampling site (6.8%) and diet (6%) had the largest impact on the microbiome, while angiotensin II and sex had the smallest effect (each 0.4%).

CONCLUSION

Our large-scale data confirmed findings from small-scale studies that angiotensin II impacted the gut microbiome. However, this effect was modest relative to most of the other factors studied. Accounting for these factors in future pre-clinical hypertensive studies will increase the likelihood that microbiome findings are replicable and translatable.

The breath volatilome is shaped by the gut microbiota

The gut microbiota is widely implicated in host health and disease, inspiring translational efforts to implement our growing body of knowledge in clinical settings. However, the need to characterize gut microbiota by its genomic content limits the feasibility of rapid, point-of-care diagnostics. The microbiota produces a diverse array of xenobiotic metabolites that disseminate into tissues, including volatile organic compounds (VOCs) that may be excreted in breath. We hypothesize that breath contains gut microbe-derived VOCs that inform the composition and metabolic state of the microbiota. To explore this idea, we compared the breath volatilome and fecal gut microbiomes of 27 healthy children and found that breath VOC composition is correlated with gut microbiomes. To experimentally interrogate this finding, we devised a method for capturing exhaled breath from gnotobiotic mice. Breath volatiles are then profiled by gas-chromatography mass-spectrometry (GC-MS). Using this novel methodology, we found that the murine breath profile is markedly shaped by the composition of the gut microbiota. We also find that VOCs produced by gut microbes in pure culture can be identified in vivo in the breath of mice monocolonized with the same bacteria. Altogether, our studies identify microbe-derived VOCs excreted in breath and support a mechanism by which gut bacterial metabolism directly contributes to the mammalian breath VOC profiles.

Gut Microbiome Integration in Drug Discovery and Development of Small Molecules

Human microbiomes, particularly in the gut, could have a major impact on the efficacy and toxicity of drugs. However, gut microbial metabolism is often neglected in the drug discovery and development process. Medicen, a Paris-based human health innovation cluster, has gathered more than 30 international leading experts from pharma, academia, biotech, clinical research organizations, and regulatory science to develop proposals to facilitate the integration of microbiome science into drug discovery and development. Seven subteams were formed to cover the complementary expertise areas of 1) pharma experience and case studies, 2) in silico microbiome-drug interaction, 3) in vitro microbial stability screening, 4) gut fermentation models, 5) animal models, 6) microbiome integration in clinical and regulatory aspects, and 7) microbiome ecosystems and models. Each expert team produced a state-of-the-art report of their respective field highlighting existing microbiome-related tools at every stage of drug discovery and development. The most critical limitations are the growing, but still limited, drug-microbiome interaction data to produce predictive models and the lack of agreed-upon standards despite recent progress. In this paper we will report on and share proposals covering 1) how microbiome tools can support moving a compound from drug discovery to clinical proof-of-concept studies and alert early on potential undesired properties stemming from microbiome-induced drug metabolism and 2) how microbiome data can be generated and integrated in pharmacokinetic models that are predictive of the human situation. Examples of drugs metabolized by the microbiome will be discussed in detail to support recommendations from the working group. SIGNIFICANCE STATEMENT: Gut microbial metabolism is often neglected in the drug discovery and development process despite growing evidence of drugs' efficacy and safety impacted by their interaction with the microbiome. This paper will detail existing microbiome-related tools covering every stage of drug discovery and development, current progress, and limitations, as well as recommendations to integrate them into the drug discovery and development process.

Protective versus Pathogenic Type I Interferon Responses during Virus Infections

Following virus infections, type I interferons are synthesized to induce the expression of antiviral molecules and interfere with virus replication. The importance of early antiviral type I IFN response against virus invasion has been emphasized during COVID-19 as well as in studies on the microbiome. Further, type I IFNs can directly act on various immune cells to enhance protective host immune responses to viral infections. However, accumulating data indicate that IFN responses can be harmful to the host by instigating inflammatory responses or inducing T cell suppression during virus infections. Also, inhibition of lymphocyte and dendritic cell development can be caused by type I IFN, which is independent of the traditional signal transducer and activator of transcription 1 signaling. Additionally, IFNs were shown to impair airway epithelial cell proliferation, which may affect late-stage lung tissue recovery from the infection. As such, type I IFN-virus interaction research is diverse, including host antiviral innate immune mechanisms in cells, viral strategies of IFN evasion, protective immunity, excessive inflammation, immune suppression, and regulation of tissue repair. In this report, these IFN activities are summarized with an emphasis placed on the functions of type I IFNs recently observed during acute or chronic virus infections.

Guidelines for microbiome studies in renal physiology

Gut microbiome research has increased dramatically in the last decade, including in renal health and disease. The field is moving from experiments showing mere association to causation using both forward and reverse microbiome approaches, leveraging tools such as germ-free animals, treatment with antibiotics, and fecal microbiota transplantations. However, we are still seeing a gap between discovery and translation that needs to be addressed, so that patients can benefit from microbiome-based therapies. In this guideline paper, we discuss the key considerations that affect the gut microbiome of animals and clinical studies assessing renal function, many of which are often overlooked, resulting in false-positive results. For animal studies, these include suppliers, acclimatization, baseline microbiota and its normalization, littermates and cohort/cage effects, diet, sex differences, age, circadian differences, antibiotics and sweeteners, and models used. Clinical studies have some unique considerations, which include sampling, gut transit time, dietary records, medication, and renal phenotypes. We provide best-practice guidance on sampling, storage, DNA extraction, and methods for microbial DNA sequencing (both 16S rRNA and shotgun metagenome). Finally, we discuss follow-up analyses, including tools available, metrics, and their interpretation, and the key challenges ahead in the microbiome field. By standardizing study designs, methods, and reporting, we will accelerate the findings from discovery to translation and result in new microbiome-based therapies that may improve renal health.

Risk of bias assessment tool for systematic review and meta-analysis of the gut microbiome

Risk of bias assessment is a critical step of any meta-analysis or systematic review. Given the low sample count of many microbiome studies, especially observational or cohort studies involving human subjects, many microbiome studies have low power. This increases the importance of performing meta-analysis and systematic review for microbiome research in order to enhance the relevance and applicability of microbiome results. This work proposes a method based on the ROBINS-I tool to systematically consider sources of bias in microbiome research seeking to perform meta-analysis or systematic review for microbiome studies.

The BALB/c Mouse Model for the Evaluation of Therapies to Treat Infections with Aerosolized Burkholderia pseudomallei

Burkholderia pseudomallei, the causative agent of the disease melioidosis, has been isolated from the environment in 45 countries. The treatment of melioidosis is complex, requiring lengthy antibiotic regimens, which can result in the relapse of the disease following treatment cessation. It is important that novel therapies to treat infections with B. pseudomallei be assessed in appropriate animal models, and discussions regarding the different protocols used between laboratories are critical. A ‘deep dive’ was held in October 2020 focusing on the use of the BALB/c mouse model and the inhalational route of infection to evaluate new antibiotic therapies.

Resistant Potato Starch Alters the Cecal Microbiome and Gene Expression in Mice Fed a Western Diet Based on NHANES Data

Several studies indicate that the four major types of resistant starch (RS1-4) are fermented in the cecum and colon to produce short-chain fatty acids (SCFAs) and can alter the microbiome and host physiology. However, nearly all these studies were conducted in rodents fed with a diet that does not approximate what is typically consumed by humans. To address this, mice were fed a Total Western Diet (TWD) based on National Health and Nutrition Examination Survey (NHANES) data that mimics the macro and micronutrient composition of a typical American diet for 6 weeks and then supplemented with 0, 2, 5, or 10% of the RS2, resistant potato starch (RPS), for an additional 3 weeks. The cecal microbiome was analyzed by 16S sequencing. The alpha-diversity of the microbiome decreased with increasing consumption of RPS while a beta-diversity plot showed four discreet groupings based on the RPS level in the diet. The relative abundance of various genera was altered by feeding increasing levels of RPS. In particular, the genus Lachnospiraceae NK4A136 group was markedly increased. Cecal, proximal, and distal colon tissue mRNA abundance was analyzed by RNASeq. The cecal mRNA abundance principal component analysis showed clear segregation of the four dietary groups whose separation decreased in the proximal and distal colon. Differential expression of the genes was highest in the cecum, but substantially decreased in the proximal colon (PC) and distal colon (DC). Most differentially expressed genes were unique to each tissue with little overlap in between. The pattern of the observed gene expression suggests that RPS, likely through metabolic changes secondary to differences in microbial composition, appears to prime the host to respond to a range of pathogens, including viruses, bacteria, and parasites. In summary, consumption of dietary RPS led to significant changes to the microbiome and gene expression in the cecum and to a lesser extent in the proximal and distal colon.

Storage conditions of high-fat diets affect pulmonary inflammation

Obesity alters the risks and outcomes of inflammatory lung diseases. It is important to accurately recapitulate the obese state in animal models to understand these effects on the pathogenesis of disease. Diet-induced obesity is a commonly used model of obesity, but when applied to other disease models like acute respiratory distress syndrome, pneumonia, and asthma, it yields widely divergent. We hypothesized high-fat chow storage conditions would affect lipid oxidation and inflammatory response in the lungs of lipopolysaccharide (LPS)-challenged mice. For 6 weeks, C57BL/6crl mice were fed either a 10% (low-fat diet, LFD) or 60% (high-fat diet, HFD) stored at room temperature (RT, 23°C) for up to 7, 14, 21, or 42 days. Mice were treated with nebulized LPS to induce lung inflammation, and neutrophil levels in bronchoalveolar lavage were determined 24 h later. Lipid oxidation (malondialdehyde, MDA) was assayed by thiobarbituric acid reactive substances in chow and mouse plasma. Concentrations of MDA in chow and plasma rose in proportion to the duration of RT chow storage. Mice fed a HFD stored <2 weeks at RT had an attenuated response 24 h after LPS compared with mice fed an LFD. This effect was reversed after 2 weeks of chow storage at RT. Chow stored above freezing underwent lipid oxidation associated with significant alterations in the LPS-induced pulmonary inflammatory response. Our data show that storage conditions affect lipid peroxidation, which in turn affects pulmonary inflammatory responses in a mouse model of disease. It also suggests changes in the microbiome, although not significantly different suggests decreased variety and richness of bacteria in the gut, a large aspect of the immune system. Dietary composition and storage of chow may also affect pulmonary inflammation and the gut microbiome in humans.

The microbiome and rodent models of immune mediated diseases

Over the last six decades production of laboratory rodents have been refined with the aim of eliminating all pathogens, which could influence research results. This has, however, also created rodents with little diversity in their microbiota. Until 10 years ago the impact of the microbiota on the outcome of rodent studies was ignored, but today it is clear that the phenotype of rodent models differs essentially in relation to the environment of origin, i.e. different breeders or different rooms. In this review, we outline the mechanisms behind gut bacterial impact on rodent models of immune mediated diseases, and how differences in environment of origin leads to phenotypic model differences within research areas such as infectious diseases and vaccine development, the metabolic syndrome, gut immunity and inflammation, autoimmunity and allergy. Finally, we sum up some tools to handle this impact to increase reproducibility and translatability of rodent models.

Differences in Gut Microbiome Composition Between Sympatric Wild and Allopatric Laboratory Populations of Omnivorous Cockroaches

Gut microbiome composition is determined by a complex interplay of host genetics, founder’s effects, and host environment. We are using omnivorous cockroaches as a model to disentangle the relative contribution of these factors. Cockroaches are a useful model for host–gut microbiome interactions due to their rich hindgut microbial community, omnivorous diet, and gregarious lifestyle. In this study, we used 16S rRNA sequencing to compare the gut microbial community of allopatric laboratory populations of Periplaneta americana as well as sympatric, wild-caught populations of P. americana and Periplaneta fuliginosa, before and after a 14 day period of acclimatization to a common laboratory environment. Our results showed that the gut microbiome of cockroaches differed by both species and rearing environment. The gut microbiome from the sympatric population of wild-captured cockroaches showed strong separation based on host species. Laboratory-reared and wild-captured cockroaches from the same species also exhibited distinct gut microbiome profiles. Each group of cockroaches had a unique signature of differentially abundant uncharacterized taxa still present after laboratory cultivation. Transition to the laboratory environment resulted in decreased microbiome diversity for both species of wild-caught insects. Interestingly, although laboratory cultivation resulted in similar losses of microbial diversity for both species, it did not cause the gut microbiome of those species to become substantially more similar. These results demonstrate how competing factors impact the gut microbiome and highlight the need for a greater understanding of host–microbiome interactions.

Pulmonary and intestinal microbiota dynamics during Gram-negative pneumonia-derived sepsis

Background

The gut microbiome plays a protective role in the host defense against pneumonia. The composition of the lung microbiota has been shown to be predictive of clinical outcome in critically ill patients. However, the dynamics of the lung and gut microbiota composition over time during severe pneumonia remains ill defined. We used a mouse model of pneumonia-derived sepsis caused by Klebsiella pneumoniae in order to follow the pathogen burden as well as the composition of the lung, tongue and fecal microbiota from local infection towards systemic spread.

Results

Already at 6 h post-inoculation with K. pneumoniae, marked changes in the lung microbiota were seen. The alpha diversity of the lung microbiota did not change throughout the infection, whereas the beta diversity did. A shift between the prominent lung microbiota members of Streptococcus and Klebsiella was seen from 12 h onwards and was most pronounced at 18 h post-inoculation (PI) which was also reflected in the release of pro-inflammatory cytokines indicating severe pulmonary inflammation. Around 18 h PI, K. pneumoniae bacteremia was observed together with a systemic inflammatory response. The composition of the tongue microbiota was not affected during infection, even at 18–30 h PI when K. pneumoniae had become the dominant bacterium in the lung. Moreover, we observed differences in the gut microbiota during pulmonary infection. The gut microbiota contributed to the lung microbiota at 12 h PI, however, this decreased at a later stage of the infection.

Conclusions

At 18 h PI, K. pneumoniae was the dominant member in the lung microbiota. The lung microbiota profiles were significantly explained by the lung K. pneumoniae bacterial counts and Klebsiella and Streptococcus were correlating with the measured cytokine levels in the lung and/or blood. The oral microbiota in mice, however, was not influenced by the severity of murine pneumonia, whereas the gut microbiota was affected. This study is of significance for future studies investigating the role of the lung microbiota during pneumonia and sepsis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-021-00398-4.

From Klebsiella pneumoniae Colonization to Dissemination: An Overview of Studies Implementing Murine Models

Klebsiella pneumoniae is a Gram-negative pathogen responsible for community-acquired and nosocomial infections. The strains of this species belong to the opportunistic group, which is comprised of the multidrug-resistant strains, or the hypervirulent group, depending on their accessory genome, which determines bacterial pathogenicity and the host immune response. The aim of this survey is to present an overview of the murine models mimicking K. pneumoniae infectious processes (i.e., gastrointestinal colonization, urinary, pulmonary, and systemic infections), and the bacterial functions deployed to colonize and disseminate into the host. These in vivo approaches are pivotal to develop new therapeutics to limit K. pneumoniae infections via a modulation of the immune responses and/or microbiota.

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

Just 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.