Cage and maternal effects on the bacterial communities of the murine gut

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.

Gut Microbiota Regulation by Acupuncture and Moxibustion: A Systematic Review and Meta-Analysis

There have been numerous studies investigating the impact of acupuncture and/or moxibustion on the gut microbiota, but the results have been inconclusive. Therefore, we conducted a systematic review and meta-analysis that included both preclinical and clinical studies to assess the current evidence regarding the effects of acupuncture on gut microbiota changes. We collected relevant studies from EMBASE and PubMed, collected outcomes including diversity and relative abundance measures of the gut microbiome, and the summarized effect estimates were calculated using the ratio of means (ROM) with 95% confidence intervals. Our analysis identified three clinical studies and 20 preclinical studies, encompassing various diseases and models, including colitis and obesity. The pooled results indicated no significant difference in alpha diversity changes between treatment groups and controls, except for the Simpson index measure, which was significantly higher in the treatment groups. Additionally, the pooled results showed an increase in the Firmicutes and a decrease in the Bacteroidetes in the treatment groups, along with increases in the Lactobacillus and Ruminococcus genera. These findings suggest acupuncture treatment can target the modification of specific phyla and genera of gut microbiota. However, it is important to note that the effects of acupuncture on the gut microbiome are heterogeneous across studies, particularly in different disease models.

Genetic architecture and correlations between the gut microbiome and gut gene transcription in Chinook salmon (Oncorhynchus tshawytscha)

Population divergence through selection can drive local adaptation in natural populations which has implications for the effective restoration of declining and extirpated populations. However, adaptation to local environmental conditions is complicated when both the host and its associated microbiomes must respond via co-evolutionary change. Nevertheless, for adaptation to occur through selection, variation in both host and microbiome traits should include additive genetic effects. Here we focus on host immune function and quantify factors affecting variation in gut immune gene transcription and gut bacterial community composition in early life-stage Chinook salmon (Oncorhynchus tshawytscha). Specifically, we utilized a replicated factorial breeding design to determine the genetic architecture (sire, dam and sire-by-dam interaction) of gut immune gene transcription and microbiome composition. Furthermore, we explored correlations between host gut gene transcription and microbiota composition. Gene transcription was quantified using nanofluidic qPCR arrays (22 target genes) and microbiota composition using 16 S rRNA gene (V5-V6) amplicon sequencing. We discovered limited but significant genetic architecture in gut microbiota composition and transcriptional profiles. We also identified significant correlations between gut gene transcription and microbiota composition, highlighting potential mechanisms for functional interactions between the two. Overall, this study provides support for the co-evolution of host immune function and their gut microbiota in Chinook salmon, a species recognized as locally adapted. Thus, the inclusion of immune gene transcription profile and gut microbiome composition as factors in the development of conservation and commercial rearing practices may provide new and more effective approaches to captive rearing.

Hackflex library preparation enables low-cost metagenomic profiling

Shotgun metagenomic sequencing provides valuable insights into microbial communities, but the high cost of library preparation with standard kits and protocols is a barrier for many. New methods such as Hackflex use diluted commercially available reagents to greatly reduce library preparation costs. However, these methods have not been systematically validated for metagenomic sequencing. Here, we evaluate Hackflex performance by sequencing metagenomic libraries from known mock communities as well as mouse fecal samples prepared by Hackflex, Illumina DNA Prep, and Illumina TruSeq methods. Hackflex successfully recovered all members of the Zymo mock community, performing best for samples with DNA concentrations <1 ng/uL. Furthermore, Hackflex was able to delineate microbiota of individual inbred mice from the same breeding stock at the same mouse facility, and statistical modeling indicated that mouse ID explained a greater fraction of the variance in metagenomic composition than did library preparation method. These results show that Hackflex is suitable for generating inventories of bacterial communities through metagenomic sequencing.

Consumption of the Non-Nutritive Sweetener Stevia for 12 Weeks Does Not Alter the Composition of the Human Gut Microbiota

The use of non-nutritive sweeteners (NNSs) as an alternative to caloric sugars has increased in recent years. Stevia is an NNS that has demonstrated beneficial effects on appetite and energy intake. However, the impact on the gut microbiota is not well understood. Therefore, we investigated how regular consumption of stevia, for up to 12 weeks, impacts the human gut microbiota. Healthy subjects with a normal body mass index participated in our study; the stevia group (n = 14) was asked to consume five drops of stevia twice daily, compared to control participants (n = 13). Faecal samples collected before and after treatment were analysed by 16S rRNA gene sequencing. Stevia did not cause significant changes in the alpha or beta diversity when compared to the control groups. When the relative abundances of taxa were investigated, no clear differences were detected. Conversely, a random forest analysis correctly associated the gut microbiome with the control and stevia groups with an average of 75% accuracy, suggesting that there are intrinsic patterns that could discriminate between control and stevia use. However, large-scale changes in the gut microbiota were not apparent in this study, and, therefore, our data suggest that stevia does not significantly impact the gut microbiota.

Vaginal microbial dynamics and pathogen colonization in a humanized microbiota mouse model

Vaginal microbial composition is associated with differential risk of urogenital infection. Although Lactobacillus spp. are thought to confer protection against infection, the lack of in vivo models resembling the human vaginal microbiota remains a prominent barrier to mechanistic discovery. Using 16S rRNA amplicon sequencing of C57BL/6J female mice, we found that vaginal microbial composition varies within and between colonies across three vivaria. Noting vaginal microbial plasticity in conventional mice, we assessed the vaginal microbiome of humanized microbiota mice (HMbmice). Like the community structure in conventional mice, HMbmice vaginal microbiota clustered into community state types but, uniquely, HMbmice communities were frequently dominated by Lactobacillus or Enterobacteriaceae. Compared to conventional mice, HMbmice were less susceptible to uterine ascension by urogenital pathobionts group B Streptococcus (GBS) and Prevotella bivia. Although Escherichia and Lactobacillus both correlated with the absence of uterine GBS, vaginal pre-inoculation with exogenous HMbmouse-derived E. coli, but not Ligilactobacillus murinus, reduced vaginal GBS burden. Overall, HMbmice serve as a useful model to elucidate the role of endogenous microbes in conferring protection against urogenital pathogens.

Cross-alteration of murine skin and tick microbiome concomitant with pathogen transmission after Ixodes ricinus bite

BACKGROUND

Ticks are major vectors of diseases affecting humans such as Lyme disease or domestic animals such as anaplasmosis. Cross-alteration of the vertebrate host skin microbiome and the tick microbiome may be essential during the process of tick feeding and for the mechanism of pathogen transmission. However, it has been poorly investigated.

METHODS

We used mice bitten by field-collected ticks (nymphs and adult ticks) in different experimental conditions to investigate, by 16S rRNA gene metabarcoding, the impact of blood feeding on both the mouse skin microbiome and the tick microbiome. We also investigated by PCR and 16S rRNA gene metabarcoding, the diversity of microorganisms transmitted to the host during the process of tick bite at the skin interface and the dissemination of the pathogen in host tissues (blood, heart, and spleen).

RESULTS

Most of the commensal bacteria present in the skin of control mice were replaced during the blood-feeding process by bacteria originating from the ticks. The microbiome of the ticks was also impacted by the blood feeding. Several pathogens including tick-borne pathogens (Borrelia/Borreliella, Anaplasma, Neoehrlichia, Rickettsia) and opportunistic bacteria (Williamsia) were transmitted to the skin microbiome and some of them disseminated to the blood or spleen of the mice. In the different experiments of this study, skin microbiome alteration and Borrelia/Borreliella transmission were different depending on the tick stages (nymphs or adult female ticks).

CONCLUSIONS

Host skin microbiome at the bite site was deeply impacted by the tick bite, to an extent which suggests a role in the tick feeding, in the pathogen transmission, and a potentially important impact on the skin physiopathology. The diversified taxonomic profiles of the tick microbiome were also modified by the blood feeding. Video Abstract.

Host genomic variation shapes gut microbiome diversity in threespine stickleback fish

IMPORTANCE

A major focus of host-microbe research is to understand how genetic differences, of various magnitudes, among hosts translate to differences in their microbiomes. This has been challenging for animal hosts, including humans, because it is difficult to control environmental variables tightly enough to isolate direct genetic effects on the microbiome. Our work in stickleback fish is a significant contribution because our experimental approach allowed strict control over environmental factors, including standardization of the microbiome from the earliest stage of development and unrestricted co-housing of fish in a truly common environment. Furthermore, we measured host genetic variation over 2,000 regions of the stickleback genome, comparing this information and microbiome composition data among fish from very similar and very different genetic backgrounds. Our findings highlight how differences in the host genome influence microbiome diversity and make a case for future manipulative microbiome experiments that use host systems with naturally occurring genetic variation.

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.

metaSpectraST: an unsupervised and database-independent analysis workflow for metaproteomic MS/MS data using spectrum clustering

BACKGROUND

The high diversity and complexity of the microbial community make it a formidable challenge to identify and quantify the large number of proteins expressed in the community. Conventional metaproteomics approaches largely rely on accurate identification of the MS/MS spectra to their corresponding short peptides in the digested samples, followed by protein inference and subsequent taxonomic and functional analysis of the detected proteins. These approaches are dependent on the availability of protein sequence databases derived either from sample-specific metagenomic data or from public repositories. Due to the incompleteness and imperfections of these protein sequence databases, and the preponderance of homologous proteins expressed by different bacterial species in the community, this computational process of peptide identification and protein inference is challenging and error-prone, which hinders the comparison of metaproteomes across multiple samples.

RESULTS

We developed metaSpectraST, an unsupervised and database-independent metaproteomics workflow, which quantitatively profiles and compares metaproteomics samples by clustering experimentally observed MS/MS spectra based on their spectral similarity. We applied metaSpectraST to fecal samples collected from littermates of two different mother mice right after weaning. Quantitative proteome profiles of the microbial communities of different mice were obtained without any peptide-spectrum identification and used to evaluate the overall similarity between samples and highlight any differentiating markers. Compared to the conventional database-dependent metaproteomics analysis, metaSpectraST is more successful in classifying the samples and detecting the subtle microbiome changes of mouse gut microbiomes post-weaning. metaSpectraST could also be used as a tool to select the suitable biological replicates from samples with wide inter-individual variation.

CONCLUSIONS

metaSpectraST enables rapid profiling of metaproteomic samples quantitatively, without the need for constructing the protein sequence database or identification of the MS/MS spectra. It maximally preserves information contained in the experimental MS/MS spectra by clustering all of them first and thus is able to better profile the complex microbial communities and highlight their functional changes, as compared with conventional approaches. tag the videobyte in this section as ESM4 Video Abstract.

Effect of Oral Administration of Polyethylene Glycol 400 on Gut Microbiota Composition and Diet-Induced Obesity in Mice

Polyethylene glycol (PEG) is a commonly used dispersant for oral administration of hydrophobic agents. PEG is partly absorbed in the small intestine, and the unabsorbed fraction reaches the large intestine; thus, oral administration of PEG may impact the gut microbial community. However, to the best of our knowledge, no study evaluated the effects of PEG on gut commensal bacteria. Herein, we aimed to determine whether oral administration of PEG modifies the gut microbiota. Administration of PEG400 and PEG4000 altered gut microbial diversity in a concentration-dependent manner. Taxonomic analysis revealed that Akkermansia muciniphila and particularly Parabacteroides goldsteinii were overrepresented in mice administered with 40% PEG. PEG400 administration ameliorated the high-fat diet (HFD)-induced obesity and adipose tissue inflammation. Fecal microbiome transplantation from PEG400-administered donors counteracted the HFD-induced body and epididymal adipose tissue weight gain, indicating that PEG400-associated bacteria are responsible for the anti-obesity effect. Conversely, carboxymethyl cellulose, also used as a dispersant, did not affect the abundance of these two bacterial species or HFD-induced obesity. In conclusion, we demonstrated that oral administration of a high concentration of PEG400 (40%) alters the gut microbiota composition and ameliorates HFD-induced obesity.

Intestinal barrier dysfunction in murine sickle cell disease is associated with small intestine neutrophilic inflammation, oxidative stress, and dysbiosis

The intestinal microbiome has emerged as a potential contributor to the severity of sickle cell disease (SCD). We sought to determine whether SCD mice exhibit intestinal barrier dysfunction, inflammation, and dysbiosis. Using the Townes humanized sickle cell mouse model, we found a 3-fold increase in intestinal permeability as assessed via FITC-dextran (4 kDa) assay in SS (SCD) mice compared to AA (wild type) mice (n = 4, p < 0.05). This was associated with 25 to 50% decreases in claudin-1, 3, and 15 and zonula occludens-1 gene expression (n = 8-10, p < 0.05) in the small intestine. Increased Ly6G staining demonstrated more neutrophils in the SS small intestine (3-fold, n = 5, p < 0.05) associated with increased expression of TNFα, IL-17A, CXCL1, and CD68 (2.5 to 5-fold, n = 7-10, p < 0.05). In addition, we observed 30 to 55% decreases in superoxide dismutase-1, glutathione peroxidase-1, and catalase antioxidant enzyme expression (n = 7-8, p < 0.05) concomitant to an increase in superoxide (2-fold, n = 4, p < 0.05). Importantly, all significant observations of a leaky gut phenotype and inflammation were limited to the small intestine and not observed in the colon. Finally, characterization of the composition of the microbiome within the small intestine revealed dysbiosis in SS mice compared to their AA littermates with 47 phyla to species-level significant alterations in amplicon sequence variants. We conclude that the intestinal barrier is compromised in SCD, associated with decreased gene expression of tight junction proteins, enhanced inflammation, oxidative stress, and gut microbiome dysbiosis, all specific to the small intestine.

Predicting Neurodegenerative Disease Using Prepathology Gut Microbiota Composition: a Longitudinal Study in Mice Modeling Alzheimer's Disease Pathologies

The gut microbiota-brain axis is suspected to contribute to the development of Alzheimer's disease (AD), a neurodegenerative disease characterized by amyloid-β plaque deposition, neurofibrillary tangles, and neuroinflammation. To evaluate the role of the gut microbiota-brain axis in AD, we characterized the gut microbiota of female 3xTg-AD mice modeling amyloidosis and tauopathy and wild-type (WT) genetic controls. Fecal samples were collected fortnightly from 4 to 52 weeks, and the V4 region of the 16S rRNA gene was amplified and sequenced on an Illumina MiSeq. RNA was extracted from the colon and hippocampus, converted to cDNA, and used to measure immune gene expression using reverse transcriptase quantitative PCR (RT-qPCR). Diversity metrics were calculated using QIIME2, and a random forest classifier was applied to predict bacterial features that are important in predicting mouse genotype. Gene expression of glial fibrillary acidic protein (GFAP; indicating astrocytosis) was elevated in the colon at 24 weeks. Markers of Th1 inflammation (il6) and microgliosis (mrc1) were elevated in the hippocampus. Gut microbiota were compositionally distinct early in life between 3xTg-AD mice and WT mice (permutational multivariate analysis of variance [PERMANOVA], 8 weeks, P = 0.001, 24 weeks, P = 0.039, and 52 weeks, P = 0.058). Mouse genotypes were correctly predicted 90 to 100% of the time using fecal microbiome composition. Finally, we show that the relative abundance of Bacteroides species increased over time in 3xTg-AD mice. Taken together, we demonstrate that changes in bacterial gut microbiota composition at prepathology time points are predictive of the development of AD pathologies. IMPORTANCE Recent studies have demonstrated alterations in the gut microbiota composition in mice modeling Alzheimer's disease (AD) pathologies; however, these studies have only included up to 4 time points. Our study is the first of its kind to characterize the gut microbiota of a transgenic AD mouse model, fortnightly, from 4 weeks of age to 52 weeks of age, to quantify the temporal dynamics in the microbial composition that correlate with the development of disease pathologies and host immune gene expression. In this study, we observed temporal changes in the relative abundances of specific microbial taxa, including the genus Bacteroides, that may play a central role in disease progression and the severity of pathologies. The ability to use features of the microbiota to discriminate between mice modeling AD and wild-type mice at prepathology time points indicates a potential role of the gut microbiota as a risk or protective factor in AD.

Alterations in metabolome and microbiome signatures provide clues to the role of antimicrobial peptide KT2 in ulcerative colitis

Introduction

Ulcerative colitis (UC) is an inflammatory disease of the intestinal tract with unknown etiology. Both genetic and environmental factors are involved in the occurrence and development of UC. Understanding changes in the microbiome and metabolome of the intestinal tract is crucial for the clinical management and treatment of UC.

Methods

Here, we performed metabolomic and metagenomic profiling of fecal samples from healthy control mice (HC group), DSS (Dextran Sulfate Sodium Salt) -induced UC mice (DSS group), and KT2-treated UC mice (KT2 group).

Results and Discussion

In total, 51 metabolites were identified after UC induction, enriched in phenylalanine metabolism, while 27 metabolites were identified after KT2 treatment, enriched in histidine metabolism and bile acid biosynthesis. Fecal microbiome analysis revealed significant differences in nine bacterial species associated with the course of UC, including Bacteroides, Odoribacter, and Burkholderiales, which were correlated with aggravated UC, and Anaerotruncus, Lachnospiraceae, which were correlated with alleviated UC. We also identified a disease-associated network connecting the above bacterial species with UC-associated metabolites, including palmitoyl sphingomyelin, deoxycholic acid, biliverdin, and palmitoleic acid. In conclusion, our results indicated that Anaerotruncus, Lachnospiraceae, and Mucispirillum were protective species against DSS-induced UC in mice. The fecal microbiomes and metabolomes differed significantly among the UC mice and KT2-treated and healthy-control mice, providing potential evidence for the discovery of biomarkers of UC.

Vaginal microbial dynamics and pathogen colonization in a humanized microbiota mouse model

Vaginal microbiota composition is associated with differential risk of urogenital infection. Although vaginal Lactobacillus spp. are thought to confer protection through acidification, bacteriocin production, and immunomodulation, lack of an in vivo model system that closely resembles the human vaginal microbiota remains a prominent barrier to mechanistic discovery. We performed 16S rRNA amplicon sequencing of wildtype C57BL/6J mice, commonly used to study pathogen colonization, and found that the vaginal microbiome composition varies highly both within and between colonies from three distinct vivaria. Because of the strong influence of environmental exposure on vaginal microbiome composition, we assessed whether a humanized microbiota mouse ( HMb mice) would model a more human-like vaginal microbiota. Similar to humans and conventional mice, HMb mice vaginal microbiota clustered into five community state types ( h mCST). Uniquely, HMb mice vaginal communities were frequently dominated by Lactobacilli or Enterobacteriaceae . Compared to genetically-matched conventional mice, HMb mice were less susceptible to uterine ascension by urogenital pathobionts group B Streptococcus (GBS) and Prevotella bivia , but no differences were observed with uropathogenic E. coli . Specifically, vaginal Enterobacteriaceae and Lactobacillus were associated with the absence of uterine GBS. Anti-GBS activity of HMb mice vaginal E. coli and L. murinus isolates, representing Enterobacteriaceae and Lactobacillus respectively, were characterized in vitro and in vivo . Although L. murinus reduced GBS growth in vitro , vaginal pre-inoculation with HMb mouse-derived E. coli , but not L. murinus , conferred protection against vaginal GBS burden. Overall, the HMb mice are an improved model to elucidate the role of endogenous microbes in conferring protection against urogenital pathogens.

IMPORTANCE

An altered vaginal microbiota, typically with little to no levels of Lactobacillus , is associated with increased susceptibility to urogenital infections, although mechanisms driving this vulnerability are not fully understood. Despite known inhibitory properties of Lactobacillus against urogenital pathogens, clinical studies with Lactobacillus probiotics have shown mixed success. In this study, we characterize the impact of the vaginal microbiota on urogenital pathogen colonization using a humanized microbiota mouse model that more closely mimics the human vaginal microbiota. We found several vaginal bacterial taxa that correlated with reduced pathogen levels but showed discordant effects in pathogen inhibition between in vitro and in vivo assays. We propose that this humanized microbiota mouse platform is an improved model to describe the role of the vaginal microbiota in protection against urogenital pathogens. Furthermore, this model will be useful in testing efficacy of new probiotic strategies in the complex vaginal environment.

Actively replicating gut bacteria identified by 5-ethynyl-2'-deoxyuridine (EdU) click chemistry and cell sorting

The composition of the intestinal bacterial community is well described, but recent research suggests that the metabolism of these bacteria plays a larger role in health than which species are present. One fundamental aspect of gut bacterial metabolism that remains understudied is bacterial replication. Indeed, there exist few techniques which can identify actively replicating gut bacteria. In this study, we aimed to address this gap by adapting 5-ethynyl-2'-deoxyuridine (EdU) click chemistry (EdU-click), a metabolic labeling method, coupled with fluorescence-activated cell sorting and sequencing (FACS-Seq) to characterize replicating gut bacteria. We first used EdU-click with human gut bacterial isolates and show that many of them are amenable to this technique. We then optimized EdU-click and FACS-Seq for murine fecal bacteria and reveal that Prevotella UCG-001 and Ileibacterium are enriched in the replicating fraction. Finally, we labeled the actively replicating murine gut bacteria during exposure to cell wall-specific antibiotics in vitro. We show that regardless of the antibiotic used, the actively replicating bacteria largely consist of Ileibacterium, suggesting the resistance of this taxon to perturbations. Overall, we demonstrate how combining EdU-click and FACSeq can identify the actively replicating gut bacteria and their link with the composition of the whole community in both homeostatic and perturbed conditions. This technique will be instrumental in elucidating in situ bacterial replication dynamics in a variety of other ecological states, including colonization and species invasion, as well as for investigating the relationship between the replication and abundance of bacteria in complex communities.

Longitudinal Analysis of the Microbiome and Metabolome in the 5xfAD Mouse Model of Alzheimer's Disease

Recent reports implicate gut microbiome dysbiosis in the onset and progression of Alzheimer's disease (AD), yet studies involving model animals overwhelmingly omit the microbial perspective. Here, we evaluate longitudinal microbiomes and metabolomes from a popular transgenic mouse model for familial AD (5xfAD). Cecal and fecal samples from 5xfAD and wild-type B6J (WT) mice from 4 to 18 months of age were subjected to shotgun Illumina sequencing. Metabolomics was performed on plasma and feces from a subset of the same animals. Significant genotype, sex, age, and cage-specific differences were observed in the microbiome, with the variance explained by genotype at 4 and 18 months of age rising from 0.9 to 9% and 0.3 to 8% for the cecal and fecal samples, respectively. Bacteria at significantly higher abundances in AD mice include multiple Alistipes spp., two Ligilactobacillus spp., and Lactobacillus sp. P38, while multiple species of Turicibacter, Lactobacillus johnsonii, and Romboutsia ilealis were less abundant. Turicibacter is similarly depleted in people with AD, and members of this genus both consume and induce the production of gut-derived serotonin. Contradicting previous findings in humans, serotonin is significantly more concentrated in the blood of older 5xfAD animals compared to their WT littermates. 5xfAD animals exhibited significantly lower plasma concentrations of carnosine and the lysophospholipid lysoPC a C18:1. Correlations between the microbiome and metabolome were also explored. Taken together, these findings strengthen the link between Turicibacter abundance and AD, provide a basis for further microbiome studies of murine models for AD, and suggest that greater control over animal model microbiomes is needed in AD research. IMPORTANCE Microorganisms residing within the gastrointestinal tract are implicated in the onset and progression of Alzheimer's disease (AD) through the mediation of inflammation, exchange of small-molecules across the blood-brain barrier, and stimulation of the vagus nerve. Unfortunately, most animal models for AD are housed under conditions that do not reflect real-world human microbial exposure and do not sufficiently account for (or meaningfully consider) variations in the microbiome. An improved understanding of AD model animal microbiomes will increase model efficacy and the translatability of research findings into humans. Here, we present the characterization of the microbiome and metabolome of the 5xfAD mouse model, which is one of the most common animal models for familial AD. The manuscript highlights the importance of considering the microbiome in study design and aims to lay the groundwork for future studies involving mouse models for AD.