Comparison of canine colostrum and milk using a multi-omics approach.

BACKGROUND: A mother's milk is considered the gold standard of nutrition in neonates and is a source of cytokines, immunoglobulins, growth factors, and other important components, yet little is known about the components of canine milk, specifically colostrum, and the knowledge related to its microbial and metabolic profiles is particularly underwhelming. In this study, we characterized canine colostrum and milk microbiota and metabolome for several breeds of dogs and examined profile shifts as milk matures in the first 8 days post-whelping. RESULTS: Through untargeted metabolomics, we identified 63 named metabolites that were significantly differentially abundant between days 1 and 8 of lactation. Surprisingly, the microbial compositions of the colostrum and milk, characterized using 16S rRNA gene sequencing, were largely similar, with only two differentiating genera. The shifts observed, mainly increases in several sugars and amino sugars over time and shifts in amino acid metabolites, align with shifts observed in human milk samples and track with puppy development. CONCLUSION: Like human milk, canine milk composition is dynamic, and shifts are well correlated with developing puppies' needs. Such a study of the metabolic profile of canine milk, and its relation to the microbial community, provides insights into the changing needs of the neonate, as well as the ideal nutrition profile for optimal functionality. This information will add to the existing knowledge base of canine milk composition with the prospect of creating a quality, tailored milk substitute or supplement for puppies.

The Cross-talk Between Intestinal Microbiota and MDSCs Fuels Colitis-associated Cancer Development.

Intestinal chronic inflammation is associated with microbial dysbiosis and accumulation of various immune cells including myeloid-derived suppressor cells (MDSC), which profoundly impact the immune microenvironment, perturb homeostasis and increase the risk to develop colitis-associated colorectal cancer (CAC). However, the specific MDSCs-dysbiotic microbiota interactions and their collective impact on CAC development remain poorly understood. In this study, using a murine model of CAC, we demonstrate that CAC-bearing mice exhibit significantly elevated levels of highly immunosuppressive MDSCs, accompanied by microbiota alterations. Both MDSCs and bacteria that infiltrate the colon tissue and developing tumors can be found in close proximity, suggesting intricate MDSC-microbiota cross-talk within the tumor microenvironment. To investigate this phenomenon, we employed antibiotic treatment to disrupt MDSC-microbiota interactions. This intervention yielded a remarkable reduction in intestinal inflammation, decreased MDSC levels, and alleviated immunosuppression, all of which were associated with a significant reduction in tumor burden. Furthermore, we underscore the causative role of dysbiotic microbiota in the predisposition toward tumor development, highlighting their potential as biomarkers for predicting tumor load. We shed light on the intimate MDSCs-microbiota cross-talk, revealing how bacteria enhance MDSC suppressive features and activities, inhibit their differentiation into mature beneficial myeloid cells, and redirect some toward M2 macrophage phenotype. Collectively, this study uncovers the role of MDSC-bacteria cross-talk in impairing immune responses and promoting tumor growth, providing new insights into potential therapeutic strategies for CAC. SIGNIFICANCE: MDSCs-dysbiotic bacteria interactions in the intestine play a crucial role in intensifying immunosuppression within the CAC microenvironment, ultimately facilitating tumor growth, highlighting potential therapeutic targets for improving the treatment outcomes of CAC.

Children with idiopathic short stature have significantly different gut microbiota than their normal height siblings: a case-control study.

Objectives: To investigate the role of gut microbiota (GM) in pathogenesis of idiopathic short stature (ISS) by comparing GM of ISS children to their normal-height siblings. Methods: This case-control study, conducted at the Schneider Children's Medical Center's Institute for Endocrinology and Diabetes between 4/2018-11/2020, involved 30 pairs of healthy pre-pubertal siblings aged 3-10 years, each comprising one sibling with ISS and one with normal height. Outcome measures from fecal analysis of both siblings included GM composition analyzed by 16S rRNA sequencing, fecal metabolomics, and monitoring the growth of germ-free (GF) mice after fecal transplantation. Results: Fecal analysis of ISS children identified higher predicted levels of genes encoding enzymes for pyrimidine, purine, flavin, coenzyme B, and thiamine biosynthesis, lower levels of several amino acids, and a significantly higher prevalence of the phylum Euryarchaeota compared to their normal-height siblings (p<0.001). ISS children with higher levels of Methanobrevibacter, the dominant species in the archaeal gut community, were significantly shorter in stature than those with lower levels (p=0.022). Mice receiving fecal transplants from ISS children did not experience stunted growth, probably due to the eradication of Methanobrevibacter caused by exposure to oxygen during fecal collection. Discussion: Our findings suggest that different characteristics in the GM may explain variations in linear growth. The varying levels of Methanobrevibacter demonstrated within the ISS group reflect the multifactorial nature of ISS and the potential ability of the GM to partially explain growth variations. The targeting of specific microbiota could provide personalized therapies to improve growth in children with ISS.

Signs of aging in midlife: physical function and sex differences in microbiota.

Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater ß-diversity; however, ß-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.

Giardiasis and diarrhea in dogs: Does the microbiome matter?

BACKGROUND: Giardia duodenalis (Gd) causes intestinal parasitosis. The involvement of the intestinal microbiome in determining the infection's clinical phenotype is unknown. OBJECTIVE: Investigate the fecal microbiome features in dogs with giardiasis. ANIMALS AND METHODS: Cross-sectional study, including fecal samples of kenneled dogs with Gd diagnosed by fecal Giardia antigen dot ELISA. The fecal microbial compositional characteristics and dysbiosis index (DI) were compared between diarrheic and nondiarrheic dogs. RESULTS: Fecal samples of 38 Gd-infected dogs (diarrheic, 21; nondiarrheic, 17) were included. No differences were found in Faith's phylogenic diversity and beta diversity (weighted UniFrac distances) and in specific taxa abundances at the phylum, genus, and species levels, as well as in alpha and beta diversities between diarrheic and nondiarrheic dogs, and also when divided by sex or age. Among diarrheic dogs, alpha diversity was higher in males than in females (pairwise Kruskal-Wallis, q = 0.01). Among males, fecal abundances of the genus Clostridium (W = 19) and Clostridium spiroforme species (W = 33) were higher in diarrheic compared to nondiarrheic dogs. In diarrheic dog fecal samples, Proteobacteria were more prevalent (W = 1), whereas Verrucomicrobia were less prevalent in dogs <1 year of age than in older dogs. The fecal sample DI of 19 diarrheic and 19 nondiarrheic dogs was similar (median, -0.2; range, -4.3 to 4.5 and median, -1.0; range, -4.3 to 5.8, respectively). CONCLUSIONS: The fecal microbial composition of symptomatic and asymptomatic dogs with giardiasis is similar. Based on fecal DI, giardiasis is not characterized by prominent dysbiosis. Other host and parasite characteristics might determine the severity of giardiasis in dogs.

Bacteroides is increased in an autism cohort and induces autism-relevant behavioral changes in mice in a sex-dependent manner.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition which is defined by decreased social communication and the presence of repetitive or stereotypic behaviors. Recent evidence has suggested that the gut-brain axis may be important in neurodevelopment in general and may play a role in ASD in particular. Here, we present a study of the gut microbiome in 96 individuals diagnosed with ASD in Israel, compared to 42 neurotypical individuals. We determined differences in alpha and beta diversity in the microbiome of individuals with ASD and demonstrated that the phylum Bacteroidetes and genus Bacteroides were the most significantly over-represented in individuals with ASD. To understand the possible functional significance of these changes, we treated newborn mice with Bacteroides fragilis at birth. B. fragilis-treated male mice displayed social behavior dysfunction, increased repetitive behaviors, and gene expression dysregulation in the prefrontal cortex, while female mice did not display behavioral deficits. These findings suggest that overabundance of Bacteroides, particularly in early life, may have functional consequences for individuals with ASD.

Metabolic inputs in the probiotic bacterium Lacticaseibacillus rhamnosus contribute to cell-wall remodeling and increased fitness.

Lacticaseibacillus rhamnosus GG (LGG) is a Gram-positive beneficial bacterium that resides in the human intestinal tract and belongs to the family of lactic acid bacteria (LAB). This bacterium is a widely used probiotic and was suggested to provide numerous benefits for human health. However, as in most LAB strains, the molecular mechanisms that mediate the competitiveness of probiotics under different diets remain unknown. Fermentation is a fundamental process in LAB, allowing the oxidation of simple carbohydrates (e.g., glucose, mannose) for energy production under oxygen limitation, as in the human gut. Our results indicate that fermentation reshapes the metabolome, volatilome, and proteome architecture of LGG. Furthermore, fermentation alters cell envelope remodeling and peptidoglycan biosynthesis, which leads to altered cell wall thickness, aggregation properties, and cell wall composition. In addition, fermentable sugars induced the secretion of known and novel metabolites and proteins targeting the enteric pathogens Enterococcus faecalis and Salmonella enterica Serovar Typhimurium. Overall, our results link simple carbohydrates with cell wall remodeling, aggregation to host tissues, and biofilm formation in probiotic strains and connect them with the production of broad-spectrum antimicrobial effectors.

Celiac-the lone horse? An autoimmune condition without signals of microbiota dysbiosis.

Accumulating evidence supports the role of microbiota in autoimmune processes, but research regarding the role of the gut microbiota in celiac disease (CD) is still emerging, and a consistent CD-associated dysbiosis pattern has not yet been defined. Here, we characterized the microbiota of children newly diagnosed with CD, with their unaffected family members as a healthy control group to reduce confounding factors including genetic background, hygiene, dietary habits, and environment, and followed children with CD over 1 year of dietary intervention (exclusion of gluten) to understand if the microbiota is associated with CD and its mediation. We did not find differences in the microbiota of siblings with and without CD, despite a wealth of evidence in the literature supporting CD-specific microbiota. CD is common among first-degree relatives, so this could suggest that unaffected family members in this study may be living in a pre-CD state, currently below clinical detection. Interestingly, despite the effectiveness of diet in CD control, we did not observe diet-mediated microbiota changes, except for short-term increase in Akkermansia muciniphila. This lack of effect could suggest a very strong CD microbial signature even when controlled or could be a technical shortcoming. Expanded future studies with both related and unrelated controls and diet interventions in both the CD and control arms can provide further context to our findings. IMPORTANCE The microbiota is the community of microbes that live in and on us. These microbes are essential to our health and everyday function. Disruption of the community is associated with diseases ranging from metabolic syndrome to autoimmune diseases to mental disorders. In the case of celiac disease (CD), research remains inconclusive regarding implications of the microbiota in etiology. Here, we compared microbiota of children with CD to those of their unaffected family members and found very few differences in microbiota profiles. We next examined how gluten elimination in CD patients affects the microbiota. Surprisingly, despite diet adherence, microbiota shifts were minimal, with only a short-term increase in Akkermansia muciniphila. Previous studies suggest that family members of CD patients may be living in a pre-CD state, which could explain their microbial similarity. A larger study with unrelated controls and increased microbiota monitoring during diet intervention should give our findings more perspective.

Recipient-independent, high-accuracy FMT-response prediction and optimization in mice and humans.

BACKGROUND: Some microbiota compositions are associated with negative outcomes, including among others, obesity, allergies, and the failure to respond to treatment. Microbiota manipulation or supplementation can restore a community associated with a healthy condition. Such interventions are typically probiotics or fecal microbiota transplantation (FMT). FMT donor selection is currently based on donor phenotype, rather than the anticipated microbiota composition in the recipient and associated health benefits. However, the donor and post-transplant recipient conditions differ drastically. We here propose an algorithm to identify ideal donors and predict the expected outcome of FMT based on donor microbiome alone. We also demonstrate how to optimize FMT for different required outcomes. RESULTS: We show, using multiple microbiome properties, that donor and post-transplant recipient microbiota differ widely and propose a tool to predict the recipient post-transplant condition (engraftment success and clinical outcome), using only the donors' microbiome and, when available, demographics for transplantations from humans to either mice or other humans (with or without antibiotic pre-treatment). We validated the predictor using a de novo FMT experiment highlighting the possibility of choosing transplants that optimize an array of required goals. We then extend the method to characterize a best-planned transplant (bacterial cocktail) by combining the predictor and a generative genetic algorithm (GA). We further show that a limited number of taxa is enough for an FMT to produce a desired microbiome or phenotype. CONCLUSIONS: Off-the-shelf FMT requires recipient-independent optimized FMT selection. Such a transplant can be from an optimal donor or from a cultured set of microbes. We have here shown the feasibility of both types of manipulations in mouse and human recipients. Video Abstract.

"Residential greenness, gestational diabetes mellitus (GDM) and microbiome diversity during pregnancy".

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with reduced gut microbiota richness that was also reported to differ significantly between those living in rural compared to urban environments. Therefore, our aim was to examine the associations between greenness and maternal blood glucose levels and GDM, with microbiome diversity as a possible mediator in these associations. METHODS: Pregnant women were recruited between January 2016 and October 2017. Residential greenness was evaluated as mean Normalized Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding each maternal residential address. Maternal glucose levels were measured at 24-28 weeks of gestation and GDM was diagnosed. We estimated the associations between greenness and glucose levels and GDM using generalized linear models, adjusting for socioeconomic status and season at last menstrual period. Using causal mediation analysis, the mediation effects of four different indices of microbiome alpha diversity in first trimester stool and saliva samples were assessed. RESULTS: Of 269 pregnant women, 27 participants (10.04%) were diagnosed with GDM. Although not statistically significant, adjusted exposure to medium tertile levels of mean NDVI at 300 m buffer had lower odds of GDM (OR = 0.45, 95% CI: 0.16, 1.26, p = 0.13) and decreased change in mean glucose levels (ß = -6.28, 95% CI: 14.91, 2.24, p = 0.15) compared to the lowest tertile levels of mean NDVI. Mixed results were observed at 100 and 500 m buffers, and when comparing highest tertile levels to lowest. No mediation effect of first trimester microbiome on the association between residential greenness and GDM was observed, and a small, possibly incidental, mediation effect on glucose levels was observed. CONCLUSION: Our study suggests possible associations between residential greenness and glucose intolerance and risk of GDM, though without sufficient evidence. Microbiome in the first trimester, while involved in GDM etiology, is not a mediator in these associations. Future studies in larger populations should further examine these associations.

The intersection of undernutrition, microbiome, and child development in the first years of life.

Undernutrition affects about one out of five children worldwide. It is associated with impaired growth, neurodevelopment deficits, and increased infectious morbidity and mortality. Undernutrition, however, cannot be solely attributed to a lack of food or nutrient deficiency but rather results from a complex mix of biological and environmental factors. Recent research has shown that the gut microbiome is intimately involved in the metabolism of dietary components, in growth, in the training of the immune system, and in healthy development. In this review, we look at these features in the first three years of life, which is a critical window for both microbiome establishment and maturation and child development. We also discuss the potential of the microbiome in undernutrition interventions, which could increase efficacy and improve child health outcomes.

Ordering taxa in image convolution networks improves microbiome-based machine learning accuracy.

The human gut microbiome is associated with a large number of disease etiologies. As such, it is a natural candidate for machine-learning-based biomarker development for multiple diseases and conditions. The microbiome is often analyzed using 16S rRNA gene sequencing or shotgun metagenomics. However, several properties of microbial sequence-based studies hinder machine learning (ML), including non-uniform representation, a small number of samples compared with the dimension of each sample, and sparsity of the data, with the majority of taxa present in a small subset of samples. We show here using a graph representation that the cladogram structure is as informative as the taxa frequency. We then suggest a novel method to combine information from different taxa and improve data representation for ML using microbial taxonomy. iMic (image microbiome) translates the microbiome to images through an iterative ordering scheme, and applies convolutional neural networks to the resulting image. We show that iMic has a higher precision in static microbiome gene sequence-based ML than state-of-the-art methods. iMic also facilitates the interpretation of the classifiers through an explainable artificial intelligence (AI) algorithm to iMic to detect taxa relevant to each condition. iMic is then extended to dynamic microbiome samples by translating them to movies.

Advances in the study of microbiota in reproductive biology: A short review of recent research, following Leclaire et al. (2022).

Research on microbiota dynamics in humans (Gilbert et al., 2018), model organisms (Douglas, 2019), and free-ranging, wild animals (Grond et al., 2018) has taken off in the past decades, and even in nonmodel organisms, research has already shifted from initial characterization studies to those examining associations with behaviour and fitness (Bodawatta et al., 2022; Corl et al., 2020; Risely et al., 2018; Turjeman et al., 2020). The microbiota is known to change through pregnancy and parturition (Koren et al., 2012), and there is also evidence in humans that infertility may be associated with microbiota composition (Silva & Giacobini, 2019), but how the microbiota is related to reproductive fitness in free-ranging species is largely understudied or primarily focused on pathogen transmission (sexually transmitted infection) (Lombardo, 1998; Sheldon, 1993). In a From the Cover article in this issue of Molecular Ecology, Leclaire et al. (2022) begin to tease apart the relationship between the microbiota and reproductive fitness using the black-legged kittiwake (Rissa tridactyla) as their study species. Following characterization of the microbiota in multiple body sites of breeders and nonbreeders, they discovered that breeding and nonbreeding females had distinct microbiota, that higher performing female breeders had lower abundances of potentially pathogenic taxa, and that feathers of these birds were characterized by reduced microbiota diversity compared to low-performance breeders. Leclaire and her colleagues provide some of the first evidence of body-wide differences in microbiota composition in relation to breeding status. Their research further supports the relationship between the microbiota and host fitness, and additional studies focusing on this topic can continue to unravel intricacies in host-microbiota-reproductive strategy evolution (Comizzoli et al., 2021; Rowe et al., 2020). Here, I review the results of Leclaire et al. (2022) and provide a wider context for their research by reviewing other studies in the field, focusing on avian species.

Autophagy controls mucus secretion from intestinal goblet cells by alleviating ER stress.

Colonic goblet cells are specialized epithelial cells that secrete mucus to physically separate the host and its microbiota, thus preventing bacterial invasion and inflammation. How goblet cells control the amount of mucus they secrete is unclear. We found that constitutive activation of autophagy in mice via Beclin 1 enables the production of a thicker and less penetrable mucus layer by reducing endoplasmic reticulum (ER) stress. Accordingly, genetically inhibiting Beclin 1-induced autophagy impairs mucus secretion, while pharmacologically alleviating ER stress results in excessive mucus production. This ER-stress-mediated regulation of mucus secretion is microbiota dependent and requires the Crohn's-disease-risk gene Nod2. Overproduction of mucus alters the gut microbiome, specifically expanding mucus-utilizing bacteria, such as Akkermansia muciniphila, and protects against chemical and microbial-driven intestinal inflammation. Thus, ER stress is a cell-intrinsic switch that limits mucus secretion, whereas autophagy maintains intestinal homeostasis by relieving ER stress.

Gut microbes and host behavior: The forgotten members of the gut-microbiome.

The gut microbiota refers to an entire population of microorganisms that colonize the gut. This community includes viruses, prokaryotes (bacteria and archaea), and eukaryotes (fungi and parasites). Multiple studies in the last decades described the significant involvement of gut bacteria in gut-brain axis communication; however, the involvement of other members of the gut microbiota has been neglected. Recent studies found that these 'forgotten' members of the gut microbiota may also have a role in gut-brain communication, although it is still unclear whether they have a direct effect on the brain or if their effects are mediated by gut bacteria. Here, we provide concrete suggestions for future research to tease out mechanisms of the microbiota-gut-brain axis. This article is part of the Special Issue on "Microbiome & the Brain: Mechanisms & Maladies".

Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis.

OBJECTIVE: Gestational diabetes mellitus (GDM) is a condition in which women without diabetes are diagnosed with glucose intolerance during pregnancy, typically in the second or third trimester. Early diagnosis, along with a better understanding of its pathophysiology during the first trimester of pregnancy, may be effective in reducing incidence and associated short-term and long-term morbidities. DESIGN: We comprehensively profiled the gut microbiome, metabolome, inflammatory cytokines, nutrition and clinical records of 394 women during the first trimester of pregnancy, before GDM diagnosis. We then built a model that can predict GDM onset weeks before it is typically diagnosed. Further, we demonstrated the role of the microbiome in disease using faecal microbiota transplant (FMT) of first trimester samples from pregnant women across three unique cohorts. RESULTS: We found elevated levels of proinflammatory cytokines in women who later developed GDM, decreased faecal short-chain fatty acids and altered microbiome. We next confirmed that differences in GDM-associated microbial composition during the first trimester drove inflammation and insulin resistance more than 10 weeks prior to GDM diagnosis using FMT experiments. Following these observations, we used a machine learning approach to predict GDM based on first trimester clinical, microbial and inflammatory markers with high accuracy. CONCLUSION: GDM onset can be identified in the first trimester of pregnancy, earlier than currently accepted. Furthermore, the gut microbiome appears to play a role in inflammation-induced GDM pathogenesis, with interleukin-6 as a potential contributor to pathogenesis. Potential GDM markers, including microbiota, can serve as targets for early diagnostics and therapeutic intervention leading to prevention.

Comparing invasive and noninvasive faecal sampling in wildlife microbiome studies: A case study on wild common cranes.

In ecological and conservation studies, responsible researchers strive to obtain rich data while minimizing disturbance to wildlife and ecosystems. We assessed if samples collected noninvasively can be used for faecal microbiome research, comparing microbiota of noninvasively collected faecal samples to those collected from trapped common cranes at the same sites over the same periods. We found significant differences in faecal microbial composition (alpha and beta diversity), which likely did not result from noninvasive sample exposure to soil contaminants, as assessed by comparing bacterial oxygen use profiles. Differences might result from trapped birds' exposure to sedatives or stress. We conclude that if all samples are collected in the same manner, comparative analyses are valid, and noninvasive sampling may better represent host faecal microbiota because there are no trapping effects. Experiments with fresh and delayed sample collection can elucidate effects of environmental exposures on microbiota. Further, controlled tests of stressing or sedation may unravel how trapping affects wildlife microbiota.

Linking migration and microbiota at a major stopover site in a long-distance avian migrant.

Migration is one of the most physical and energetically demanding periods in an individual bird's life. The composition of the bird's gut or cloacal microbiota can temporarily change during migration, likely due to differences in diets, habitats and other environmental conditions experienced en route. However, how physiological condition, migratory patterns, and other drivers interact to affect microbiota composition of migratory birds is still unclear. We sampled the cloacal bacterial microbiota of a long-distance migrant, the steppe buzzard (Buteo buteo vulpinus), at an important spring stopover bottleneck in Eilat, Israel, after crossing the ca. 1800 km Sahara Desert. We examined whether diversity and composition of the cloacal microbiota varied with body condition, sex, movement patterns (i.e., arrival time and migration distance), and survival. Early arrival to Eilat was associated with better body condition, longer post-Eilat spring migration distance, higher microbial α-diversity, and differences in microbiota composition. Specifically, early arrivals had higher abundance of the phylum Synergistota and five genera, including Jonquetella and Peptococcus, whereas the phylum Proteobacteria and genus Escherichia-Shigella (as well as three other genera) were more abundant in later arrivals. While the differences in α-diversity and Escherichia-Shigella seem to be mainly driven by body condition, other compositional differences associated with arrival date could be indicators of longer migratory journeys (e.g., pre-fueling at wintering grounds or stopover habitats along the way) or migratory performance. No significant differences were found between the microbiota of surviving and non-surviving individuals. Overall, our results indicate that variation in steppe buzzard microbiota is linked to variation in migratory patterns (i.e., capture/arrival date) and body condition, highlighting the importance of sampling the microbiota of GPS-tracked individuals on multiple occasions along their migration routes to gain a more detailed understanding of the links between migration, microbiota, and health in birds.

Intraamniotic Administration (Gallus gallus) of Genistein Alters Mineral Transport, Intestinal Morphology, and Gut Microbiota.

Genistein is an isoflavone naturally present in numerous staple food crops, such as soybeans and chickpeas. This study utilized the Gallus gallus intraamniotic administration procedure to assess genistein administration effects on trace mineral status, brush border membrane (BBM) functionality, intestinal morphology, and intestinal microbiome in vivo. Eggs were divided into five groups with 1 mL injection of the following treatments: no-injection, DI H2O, 5% inulin, and 1.25% and 2.5% genistein (n = 8 per group). Upon hatch, blood, cecum, small intestine, and liver were collected for assessment of hemoglobin, intestinal microflora alterations, intestinal morphometric assessment, and mRNA gene expression of relevant iron and zinc transporter proteins, respectively. This study demonstrated that intraamniotic administration of 2.5% genistein increased villus surface area, number of acidic goblet cells, and hemoglobin. Additionally, genistein exposure downregulated duodenal cytochrome B (DcytB) and upregulated hepcidin expression. Further, genistein exposure positively altered the composition and function of the intestinal microbiota. Our results suggest a physiological role for genistein administration in improving mineral status, favorably altering BBM functionality and development, positively modulating the intestinal microbiome, as well as improving physiological status.