Project description:The gut microbiota of chickens plays an important role in host physiology. However, the colonization and prevalence of gut microbiota have not been well-characterized. Here, we performed 16S rRNA gene sequencing on the duodenal, cecal and fecal microbiota of broilers at 1, 7, 21, and 35 days of age and characterized the dynamic succession of microbiota across the intestinal tract. Our results showed that Firmicutes was the most abundant phylum detected in each gut site at various ages, while the microbial diversity and composition varied among the duodenum, cecum, and feces at different ages. The microbial diversity and complexity of the cecal microbiota increased with age, gradually achieving stability at 21 days of age. As a specific genus in the cecum, Clostridium_sensu_stricto_1 accounted for 83.50% of the total abundance at 1 day of age, but its relative abundance diminished with age. Regarding the feces, the highest alpha diversity was observed at 1 day of age, significantly separated from the alpha diversity of other ages. In addition, no significant differences were observed in the alpha diversity of duodenal samples among 7, 21, and 35 days of age. The predominant bacterium, Lactobacillus, was relatively low (0.68-6.04%) in the intestinal tract of 1-day-old chicks, whereas its abundance increased substantially at 7 days of age and was higher in the duodenum and feces. Escherichia-Shigella, another predominant bacterium in the chicken intestinal tract, was also found to be highly abundant in fecal samples, and the age-associated dynamic trend coincided with that of Lactobacillus. In addition, several genera, including Blautia, Ruminiclostridium_5, Ruminococcaceae_UCG-014, and [Ruminococcus]_torques_group, which are related to the production of short-chain fatty acids, were identified as biomarker bacteria of the cecum after 21 days of age. These findings shed direct light on the temporal and spatial dynamics of intestinal microbiota and provide new opportunities for the improvement of poultry health and production.
Project description:Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics.
Project description:The microbiome is an integral part of chicken health and can affect immunity, nutrient utilization, and performance. The role of bacterial microbiota members in host health is relatively well established, but less attention has been paid to fungal members of the gastrointestinal tract (GIT) community. However, human studies indicate that fungi play a critical role in health. Here, we described fungal communities, or mycobiomes, in both the lumen and mucosa of the chicken ileum and cecum from hatch through 14 days of age. We also assessed the effects of delayed access to feed immediately post-hatch (PH) on mycobiome composition, as PH feed delay is commonly associated with poor health performance. Chicken mycobiomes in each of the populations were distinct and changed over time. All mycobiomes were dominated by Gibberella, but Aspergillus, Cladosporium, Sarocladium, Meyerozyma, and Penicillium were also abundant. Relative abundances of some taxa differed significantly over time. In the cecal and ileal lumens, Penicillium was present in extremely low quantities or absent during days one and two and then increased over time. Meyerozyma and Wickerhamomyces also increased over time in luminal sites. In contrast, several highly abundant unclassified fungi decreased after days one and two, highlighting the need for improved understanding of fungal gut biology. Mycobiomes from chicks fed during the first 2 days PH versus those not fed during the first 2 days did not significantly differ, except during days one and two. Similarities observed among mycobiomes of fed and unfed chicks at later timepoints suggest that delays in PH feeding do not have long lasting effects on mycobiome composition. Together, these results provide a foundation for future mycobiome studies, and suggest that negative health and production impacts of delayed feeding are not likely related to the development of fungal populations in the GIT.
Project description:BackgroundHigh bacterial burden in the lung microbiota predicts progression of idiopathic pulmonary fibrosis (IPF). Azithromycin (AZT) is a macrolide antibiotic known to alter the lung microbiota in several chronic pulmonary diseases, and observational studies have shown a positive effect of AZT on mortality and hospitalisation rate in IPF. However, the effect of AZT on the lung microbiota in IPF remains unknown.MethodsWe sought to determine the impact of a 3-month course of AZT on the lung microbiota in IPF. We assessed sputum and oropharyngeal swab specimens from 24 adults with IPF included in a randomised controlled crossover trial of oral AZT 500 mg 3 times per week. 16S rRNA gene amplicon sequencing and quantitative PCR (qPCR) were performed to assess bacterial communities. Antibiotic resistance genes (ARGs) were assessed using real-time qPCR.ResultsAZT significantly decreased community diversity with a stronger and more persistent effect in the lower airways (sputum). AZT treatment altered the temporal kinetics of the upper (oropharyngeal swab) and lower airway microbiota, increasing community similarity between the two sites for 1 month after macrolide cessation. Patients with an increase in ARG carriage had lower bacterial density and enrichment of the genus Streptococcus. In contrast, patients with more stable ARG carriage had higher bacterial density and enrichment in Prevotella.ConclusionsAZT caused sustained changes in the diversity and composition of the upper and lower airway microbiota in IPF, with effects on the temporal and spatial dynamics between the two sites.
Project description:Studies analyzing the composition of gut microbiota are quite common at present, mainly due to the rapid development of DNA sequencing technologies within the last decade. This is valid also for chickens and their gut microbiota. However, chickens represent a specific model for host-microbiota interactions since contact between parents and offspring has been completely interrupted in domesticated chickens. Nearly all studies describe microbiota of chicks from hatcheries and these chickens are considered as references and controls. In reality, such chickens represent an extreme experimental group since control chicks should be, by nature, hatched in nests in contact with the parent hen. Not properly realising this fact and utilising only 16S rRNA sequencing results means that many conclusions are of questionable biological relevance. The specifics of chicken-related gut microbiota are therefore stressed in this review together with current knowledge of the biological role of selected microbiota members. These microbiota members are then evaluated for their intended use as a form of next-generation probiotics.
Project description:In this study, we aimed to understand the characteristics of the gut microbial composition in a healthy Chinese population and to evaluate if they differed across different regions. In addition, we aimed to understand the changes in the gut microbial composition over time. We collected 239 fecal samples from healthy Chinese adults living in four regions and performed a 1-year time cohort study in a small population in Beijing. The Chinese gut microbiota share 34 core bacterial genera and 39 core bacterial species, which exist in all collected samples. Several disease-related microorganisms (DRMs), virulence factors, and antibiotic resistance genes were found in one or more healthy Chinese samples. Differences in gut microbiota were observed in samples from different regions, locations, individuals, and time points. Compared to other factors, time was associated with a lower degree of change in the gut microbiota. Our findings revealed spatial and temporal changes in the gut microbiota of healthy Chinese individuals. Compared to fecal microbiomes of 152 samples in the publicly released the Human Microbiome Project (HMP) project from the United States, samples in this study have higher variability in the fecal microbiome, with higher richness, Shannon diversity indices, and Pielou evenness indexes, at both the genus and species levels. The microbiota data obtained in this study will provide a detailed basis for further understanding the composition of the gut microbiota in the healthy Chinese population. IMPORTANCE China accounts for approximately 1/5th of the world's total population. Differences in environment, ethnicity, and living habits could impart unique features to the structure of the gut microbiota of Chinese individuals. In 2016, we started to investigate healthy Chinese people and their gut microbiomes. Phase I results for 16S rRNA amplicons have been released. However, owing to the limitations of 16S rRNA amplicon sequencing, the gut microbiome of a healthy Chinese population could not be examined thoroughly at the species level, and the detailed changes in the gut microbiota over time need to be investigated. To address these knowledge gaps, we started a phase II study and investigated the basis for variations in the gut microbiome composition in a healthy Chinese population at the species level using shotgun metagenomics technology. In the phase II study, we also conducted a time scale analysis of fecal samples from healthy Chinese subjects, as a pioneered study, which quantitatively clarified the changes in the gut microbiota at both the spatial and temporal levels and elucidated the distribution pattern of DRMs in healthy Chinese individuals.
Project description:Abdominal sepsis triggers the transition of microorganisms from the gut to the peritoneum and bloodstream. Unfortunately, there is a limitation of methods and biomarkers to reliably study the emergence of pathobiomes and to monitor their respective dynamics. Three-month-old CD-1 female mice underwent cecal ligation and puncture (CLP) to induce abdominal sepsis. Serial and terminal endpoint specimens were collected for fecal, peritoneal lavage, and blood samples within 72 h. Microbial species compositions were determined by NGS of (cell-free) DNA and confirmed by microbiological cultivation. As a result, CLP induced rapid and early changes of gut microbial communities, with a transition of pathogenic species into the peritoneum and blood detected at 24 h post-CLP. NGS was able to identify pathogenic species in a time course-dependent manner in individual mice using cfDNA from as few as 30 microliters of blood. Absolute levels of cfDNA from pathogens changed rapidly during acute sepsis, demonstrating its short half-life. Pathogenic species and genera in CLP mice significantly overlapped with pathobiomes from septic patients. The study demonstrated that pathobiomes serve as reservoirs following CLP for the transition of pathogens into the bloodstream. Due to its short half-life, cfDNA can serve as a precise biomarker for pathogen identification in blood.
Project description:Knowledge of the spatial and temporal dynamics of the gut microbiome is essential to understanding the state of human health, as over a hundred diseases have been correlated with changes in microbial populations. Unfortunately, due to the complexity of the microbiome and the limitations of in vivo and in vitro experiments, studying spatial and temporal dynamics of gut bacteria in a biological setting is extremely challenging. Thus, in silico experiments present an excellent alternative for studying such systems. In consideration of these issues, we have developed a user-friendly agent-based model, GutLogo, that captures the spatial and temporal development of four representative bacterial genera populations in the ileum. We demonstrate the utility of this model by simulating population responses to perturbations in flow rate, nutrition, and probiotics. While our model predicts distinct changes in population levels due to these perturbations, most of the simulations suggest that the gut populations will return to their original steady states once the disturbance is removed. We hope that, in the future, the GutLogo model is utilized and customized by interested parties, as GutLogo can serve as a basic modeling framework for simulating a variety of physiological scenarios and can be extended to capture additional complexities of interest.