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Quantifying the differential abundance (DA) of specific taxa among experimental groups in microbiome studies is challenging due to data characteristics (e.g., compositionality, sparsity) and specific study designs (e.g., repeated measures, meta-analysis, cross-over). Here we present BIRDMAn (BayesianInferentialRegression forDifferentialMicrobiomeAnalysis), a flexible DA method that can account for microbiome data characteristics and diverse experimental designs. Simulations show that BIRDMAn models are robust to uneven sequencing depth and provide a >20-fold improvement in statistical power over existing methods. We then use BIRDMAn to identify antibiotic-mediated perturbations undetected by other DA methods due to subject-level heterogeneity. Finally, we demonstrate how BIRDMAn can construct state-of-the-art cancer-type classifiers using The Cancer Genome Atlas (TCGA) dataset, with substantial accuracy improvements over random forests and existing DA tools across multiple sequencing centers. Collectively, BIRDMAn extracts more informative biological signals while accounting for study-specific experimental conditions than existing approaches.

Although many aspects of microbiome studies have been standardized to improve experimental replicability, none account for how the daily diurnal fluctuations in the gut lumen cause dynamic changes in 16S amplicon sequencing. Here we show that sample collection time affects the conclusions drawn from microbiome studies and are larger than the effect size of a daily experimental intervention or dietary changes. The timing of divergence of the microbiome composition between experimental and control groups are unique to each experiment. Sample collection times as short as only four hours apart lead to vastly different conclusions. Lack of consistency in the time of sample collection may explain poor cross-study replicability in microbiome research. Without looking at other data, the impact on other fields is unknown but potentially significant.One-Sentence SummaryIf we are not controlling for host circadian rhythm time in microbiome studies when performing experiments, it is like trying to measure sea level rise while not knowing that tides or waves exist.

Obstructive sleep apnea (OSA), characterized by intermittent hypoxia and hypercapnia (IHC), affects the composition of the gut microbiome and metabolome. The gut microbiome has diurnal oscillations that play a crucial role in regulating circadian and overall metabolic homeostasis. Thus, we hypothesized that IHC adversely alters the gut luminal dynamics of key microbial families and metabolites. The objective of this study was to determine the diurnal dynamics of the fecal microbiome and metabolome of Apoe−/− mice after a week of IHC exposure. Individually housed, 10-week-old Apoe−/− mice on an atherogenic diet were split into two groups. One group was exposed to daily IHC conditions for 10 h (Zeitgeber time 2 [ZT2] to ZT12), while the other was maintained in room air. Six days after the initiation of the IHC conditions, fecal samples were collected every 4 h for 24 h (6 time points). We performed 16S rRNA gene amplicon sequencing and untargeted liquid chromatography-mass spectrometry (LC-MS) to assess changes in the microbiome and metabolome. IHC induced global changes in the cyclical dynamics of the gut microbiome and metabolome. Ruminococcaceae, Lachnospiraceae, S24-7, and Verrucomicrobiaceae had the greatest shifts in their diurnal oscillations. In the metabolome, bile acids, glycerolipids (phosphocholines and phosphoethanolamines), and acylcarnitines were greatly affected. Multi-omic analysis of these results demonstrated that Ruminococcaceae and tauro-β-muricholic acid (TβMCA) cooccur and are associated with IHC conditions and that Coriobacteriaceae and chenodeoxycholic acid (CDCA) cooccur and are associated with control conditions. IHC significantly change the diurnal dynamics of the fecal microbiome and metabolome, increasing members and metabolites that are proinflammatory and proatherogenic while decreasing protective ones. IMPORTANCE People with obstructive sleep apnea are at a higher risk of high blood pressure, type 2 diabetes, cardiac arrhythmias, stroke, and sudden cardiac death. We wanted to understand whether the gut microbiome changes induced by obstructive sleep apnea could potentially explain some of these medical problems. By collecting stool from a mouse model of this disease at multiple time points during the day, we studied how obstructive sleep apnea changed the day-night patterns of microbes and metabolites of the gut. Since the oscillations of the gut microbiome play a crucial role in regulating metabolism, changes in these oscillations can explain why these patients can develop so many metabolic problems. We found changes in microbial families and metabolites that regulate many metabolic pathways contributing to the increased risk for heart disease seen in patients with obstructive sleep apnea.

Background Improving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods. Results We combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10–70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice. Conclusions Collectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans.

Improving the probiotic engraftment in humans requires a thorough understanding of in vivo gut-adaptive strategy of probiotics in diverse contexts. Here, we exposed the probiotic Lactobacillus plantarum HNU082 (Lp082) to gut microbiota of healthy humans, mice, and zebrafish for four weeks. Independent of host choice, Lp082 established and adapted the gut by acquiring highly consistent single-nucleotide mutations, which modulated carbohydrate utilization, and acid tolerance, and significantly promoted its in vivo competitive fitness. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g. Bacteroides spp. and Bifidobacterium spp.), actively respond to Lp082 engraftment by accumulating 10-70 folds more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice. Collectively, the highly convergent adaptation strategy of Lp082 across host environments lay the foundation for leveraging the animal model for ex vivo engineering of probiotics for better engraftment outcomes in humans.

Interest in animal microbiomes as therapeutics is rapidly expanding, as techniques to study the microbial world decrease in cost and increase in accessibility and case studies from human medicine receive widespread attention. In this review, we summarize the current state of techniques to modify the microbiome to improve animal health, focusing on applications in domestic pets, farm animals, and in wild settings for conservation. We discuss options for modifying the microbiome, including community-wide changes such as fecal microbiota transplants, prebiotics, probiotics, and antibiotics, and more targeted approaches such as phage therapy and CRISPR-Cas. We conclude that although much remains to be done in untangling the basic biology of microbiome-directed therapies in animals, the rapid progress currently being made in human medicine and the examples to date of application of probiotics and other microbiome-directed therapies in taxa ranging from horses to salamanders to bees suggest excellent prospects for these technologies as they are further developed and as data on both the benefits and risks are carefully and systematically collected. Impact statement Considering the clear effects of microbiota on important aspects of animal biology and development (including in humans), this topic is timely and broadly appealing, as it compels us to consider the possibilities of altering the microbiome (without antibiotics) to positively affect animal health. In this review, we highlight three general approaches to manipulating the microbiome that have demonstrated success and promise for use in animal health. We also point out knowledge gaps where further inquiry would most benefit the field. Our paper not only provides a short and digestible overview of the current state of application, but also calls for further exploration of the microbial diversity at hand to expand our toolkit, while also leveraging the diversity and flexibility of animal systems to better understand mechanisms of efficacy.

Captive wildlife are a unique set of animals, whose diverse host–microbe symbioses are underexplored. Compared to their wild counterparts they are particularly susceptible to a variety of diseases, many of which have explicit or purported links to the microbiome. In this perspective, we will examine how the microbiome influences gastrointestinal disorders, metabolic dysregulation, reproduction, and disease susceptibility in captive wildlife. Investigation of wildlife, and specifically captive wildlife, affords a unique opportunity to gain understanding of the broad diversity of the associated microbiota and learn from nature’s molecular and microbial responses to disease. Studies like these could lead to the discovery of new interventions, ranging from dietary changes to the use of microbes or their natural products as treatment. Intervention strategies can lead to the discovery of medically relevant small molecules and the development of a novel platform for N-of-1 targeted medical investigations.

Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person’s age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site’s microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases., Human gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals (>60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging. IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person’s age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site’s microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.

Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual's microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.

Parvoviruses have a predilection for rapidly dividing cells such as occurs during embryonic development. Potentially, in utero exposure could lead to immune tolerance in progeny mice. To determine if MPV infection in utero results in immune tolerance, pregnant mice were inoculated by oral gavage with 50 ID50 MPV1e or sham inoculated with phosphate buffered saline at day 5 and 12 gestation. Offspring were fostered to MPV-negative recipient dams prior to development of a milk spot. After confirming the offspring were seronegative for MPV by serology and not shedding by fecal PCR, they were challenged with 50 ID50 MPV1e by oral gavage at weaning or sham inoculated. At 4 weeks post inoculation, all weanlings exposed in utero developed antibodies to MPV, and MPV was detected by fecal PCR. Similarly, all weanlings from sham-inoculated dams challenged with MPV developed antibodies and MPV was detected by fecal PCR. None of the sham inoculated weanling mice from MPV infected dams or sham infected dams developed antibodies to MPV nor was MPV detected by fecal PCR. These results demonstrate that in utero exposure to MPV1e via oral gavage was insufficient to induce immune tolerance and provides greater confidence that rederivation techniques may successfully eliminate colonies of MPV. Furthermore, our findings do not provide evidence that MPV tolerance may contribute to hidden infections in mouse colonies.

Author(s): Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Allaband, Celeste; Alupay, Jean; Techanun, Jennifer | Abstract: Part 7 of the Youth Development through Veterinary Science Series, a 4H Youth Development curriculum that introduces youth to many aspects of veterinary science.

Author(s): Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Allaband, Celeste; Alupay, Jean; Techanun, Jennifer | Abstract: Part 2 of the Youth Development through Veterinary Science Series, a 4H Youth Development curriculum that introduces youth to many aspects of veterinary science.

Author(s): Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Lau, Tiffany; Liang, Justin; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Allaband, Celeste; Alupay, Jean; Techanun, Jennifer; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Lau, Tiffany; Liang, Justin; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Pracht-Smith, Eleanor I; Eng, Carlin; Hauert, Rebekka; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Liang, Justin; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Simoes, Kelly Lister; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Allaband, Celeste; Alupay, Jean; Techanun, Jennifer; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Moses, Adele; Wong, Joyce; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Moses, Adele; Wong, Joyce; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Hauert, Rebekka; Smith, Martin H; Meehan, Cheryl L; Ma, Justine; Dasher, H Steve; Camarillo, Joe D; Spitze, Naomi | Abstract: The Youth Development through Veterinary Science Series is a 4H Youth Development curriculum that introduces youth to many aspects of veterinary science. This download includes the entire series, parts 1 through 11.