Animal microbiome最新文献

{"title":"Interaction between cecal microbiota and liver genes of laying ducks with different residual feed intake.","authors":"Rongbing Guo, Yuguang Chang, Dandan Wang, Hanxue Sun, Tiantian Gu, Yibo Zong, Shiheng Zhou, Zhizhou Huang, Li Chen, Yong Tian, Wenwu Xu, Lizhi Lu, Tao Zeng","doi":"10.1186/s42523-025-00394-z","DOIUrl":"10.1186/s42523-025-00394-z","url":null,"abstract":"<p><strong>Background: </strong>The gut microbiota exerts a critical influence on energy metabolism homeostasis and productive performance in avian species. Given the diminishing availability of arable land and intensifying competition for finite resources between livestock production and human populations, the agricultural sector faces dual imperatives to enhance productive efficiency while mitigating ecological footprints. Within this paradigm, optimizing nutrient assimilation efficiency in commercial waterfowl operations emerges as a strategic priority. This investigation employs an integrated multi-omics approach framework (metagenomic, metabolomic, and transcriptomic analyses) to elucidate the mechanistic relationships between cecal microbial consortia and feed conversion ratios in Shan Partridge ducks.</p><p><strong>Results: </strong>Based on the analysis of metagenome data, a total of 34 phyla, 1033 genera and 3262 species of bacteria were identified by metagenomic sequencing analysis. At the phylum level, 31 phylums had higher mean abundance in the low residual feed intake ( LRFI) group than in the high residual feed intake (HRFI) group. Among them, the expression of microbiome Elusimicrobiota was significantly higher in the LRFI group than in the HRFI group (P < 0.05). And we also found a significant differences in secondary metabolites biosynthesis, transport, and catabolism pathways between the two groups in microbial function (P < 0.05). Based on metabolomic analysis, 17 different metabolites were found. Among them, Lipids and lipid molecules accounted for the highest proportion. Whereas the liver is very closely related to lipid metabolism, we are close to understanding whether an individual's energy utilization efficiency is related to gene expression in the liver. We selected six ducks from each group of six ducks each for liver transcriptome analysis. A total of 322 differential genes were identified in the transcriptome analysis results, and 319 genes were significantly down-regulated. Among them, we found that prostaglandin endoperoxide synthase 2 (PTGS2) might be a key hub gene regulating RFI by co-occurrence network analysis. Interestingly, the differential gene PTGS2 was enriched in the arachidonic acid pathway at the same time as the differential metabolite 15-deoxy-delta12,14-prostaglandin J2 (15d-PGJ2). In addition, the results of the association analysis of differential metabolites with microorganisms also revealed a significant negative correlation between 15d-PGJ2 and Elusimicrobiota.</p><p><strong>Conclusion: </strong>Based on comprehensive analysis of the research results, we speculate that the Elusimicrobiota may affect the feed utilization efficiency in ducks by regulating the expression of the PTGS2 gene.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"30"},"PeriodicalIF":4.9,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929276/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social organization and physical environment shape the microbiome of harvester ants.","authors":"Denisse Alejandra Gamboa, Peter J Flynn, Eva Sofia Horna-Lowell, Noa Pinter-Wollman","doi":"10.1186/s42523-025-00390-3","DOIUrl":"10.1186/s42523-025-00390-3","url":null,"abstract":"<p><p>All animals harbor microbiomes, which are obtained from the surrounding environment and are impacted by host behavior and life stage. To determine how two non-mutually exclusive drivers - physical environment and social organization - affect an organism's microbiome, we examined the bacterial communities within and around nests of harvester ants (Veromessor andrei). We collected soil and nest content samples from five different ant nests. We used 16S rRNA gene sequencing and calculated alpha and beta diversity to compare bacterial diversity and community composition across samples. To test the hypotheses that physical environment and/or social organization impact ant colonies' community of microbes we compared our samples across (i) sample types (ants, brood, seeds and reproductives (winged alates), and soil), (ii) soil inside and outside the nest, and (iii) soil from different chamber types. Interestingly, we found that both the environment and social organization impact the bacterial communities of the microbiome of V. andrei colonies. Soil from the five nests differed from one another in a way that mapped onto their geographical distance. Furthermore, soil from inside the nests resembled the surrounding soil, supporting the physical environment hypothesis. However, the bacterial communities associated with the contents within the nest chambers, i.e., ants, brood, seeds, and reproductives, differed from one another and from the surrounding soil, supporting the social organization hypotheses. This study highlights the importance of considering environmental and social factors in understanding microbiome dynamics.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"29"},"PeriodicalIF":4.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11921602/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Age matters: exploring differential effects of antimicrobial treatment on gut microbiota of adult and juvenile brown trout (Salmo trutta).","authors":"Lisa-Marie Streb, Paulina Cholewińska, Silvia Gschwendtner, Juergen Geist, Susanne Rath, Michael Schloter","doi":"10.1186/s42523-025-00391-2","DOIUrl":"10.1186/s42523-025-00391-2","url":null,"abstract":"<p><strong>Background: </strong>Antibiotics and antiparasitics are essential tools in controlling infectious disease outbreaks in commercial aquaculture. While the negative effects of antimicrobials on the gut microbiome of various farmed fish species are well documented, the influence of underlying host factors, such as age, on microbiome responses remains poorly understood. This is especially evident for peracetic acid, whose impact on the gut microbiome has not yet been studied. Understanding how microbiome dynamics vary by host age is critical to improving antibiotic stewardship in aquaculture. In this study, juvenile and sexually mature brown trout (Salmo trutta) were used as a model to investigate the age-dependent effects of florfenicol and peracetic acid on the gut microbiome using a 16S rRNA metabarcoding approach.</p><p><strong>Results: </strong>Fish age significantly shaped taxonomic composition and microbial co-occurrence network structure of the gut microbiome, regardless of treatment. Juvenile trout exhibited greater microbiome volatility and a stronger response to both florfenicol and peracetic acid compared to adult fish, with disruptions persisting up to 11 days post-treatment. Temporal dynamics were also evident, with microbial shifts characterized by a decline in beneficial commensals like Cetobacterium and Lactococcus. Although overall abundance recovered by 18 days post-treatment, network positions of key microbial community members remained altered, particularly in juvenile fish. Opportunistic pathogens, including Aeromonas and Streptococcus, were enriched and assumed more central roles within the microbial networks in treated fish.</p><p><strong>Conclusion: </strong>The initial composition of the gut microbiome in brown trout is strongly influenced by fish age, which in turn affects the microbiome's response to antibiotic disruption. Juveniles displayed higher susceptibility to microbiome perturbation, and although recovery was observed at the community level, network properties remained altered. This study also provides the first evidence that external peracetic acid application can disrupt gut microbial communities. Since compositional shifts are often linked to functional alterations, even short-term disruptions may have important consequences for host health in developing fish. These findings emphasize the importance of considering gut microbial community structure in relation to fish age in aquaculture management practices.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"28"},"PeriodicalIF":4.9,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910850/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nasal pathobiont abundance is a moderate feedlot-dependent indicator of bovine respiratory disease in beef cattle.","authors":"Ruth Eunice Centeno-Delphia, Natalie Glidden, Erica Long, Audrey Ellis, Sarah Hoffman, Kara Mosier, Noelmi Ulloa, Johnnie Junior Cheng, Josiah Levi Davidson, Suraj Mohan, Mohamed Kamel, Josh I Szasz, Jon Schoonmaker, Jennifer Koziol, Jacquelyn P Boerman, Aaron Ault, Mohit S Verma, Timothy A Johnson","doi":"10.1186/s42523-025-00387-y","DOIUrl":"10.1186/s42523-025-00387-y","url":null,"abstract":"<p><strong>Background: </strong>Bovine respiratory disease (BRD) poses a persistent challenge in the beef cattle industry, impacting both animal health and economic aspects. Several risk factors make an animal susceptible to BRD, including bacteria such as Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis. Despite efforts to characterize and quantify these bacteria in the nasal cavity for disease diagnosis, more research is needed to understand if there is a pathobiont abundance threshold for clinical signs of respiratory disease, and if the results are similar across feedlots. This study aims to compare the nasal microbiome community diversity and composition, along with the abundance of four bacterial pathogens and associated serotypes, in apparently healthy and BRD-affected beef cattle. Nasal swabs were collected from four beef feedlots across the US, covering the years 2019 to 2022. The study included post-weaned beef cattle with diverse housing conditions.</p><p><strong>Results: </strong>Quantification of BRD-associated pathogens effectively distinguished BRD-affected from apparently healthy beef cattle, surpassing the efficacy of 16S rRNA gene sequencing of the nasal microbiome community. Specifically, H. somni, M. bovis, and M. haemolytica had higher abundance in the BRD-affected group. Utilizing the abundance of these pathobionts and analyzing their combined abundance with machine learning models resulted in an accuracy of approximately 63% for sample classification into disease status. Moreover, there were no significant differences in nasal microbiome diversity (alpha and beta) between BRD-affected and apparently healthy cattle; instead, differences were detected between feedlots.</p><p><strong>Conclusions: </strong>Notably, this study sheds light on the beef cattle nasal microbiome community composition, revealing specific differences between BRD-affected and apparently healthy cattle. Pathobiont abundance was increased in some, but not all farms. Nonetheless, more research is needed to determine if these differences are consistent across other studies. Additionally, future research should consider bacterial-viral interactions in the beef nasal metagenome.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"27"},"PeriodicalIF":4.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11909826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143635003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diurnal oscillations of amino acids dynamically associate with microbiota and resistome in the colon of pigs.","authors":"Hongyu Wang, Yue Li, Jinwei You, Ni Feng, Dongfang Wang, Yong Su, Xiaobo Feng","doi":"10.1186/s42523-025-00393-0","DOIUrl":"10.1186/s42523-025-00393-0","url":null,"abstract":"<p><strong>Background: </strong>Nutrients are one of the key determinants of gut microbiota variation. However, the intricate associations between the amino acid (AA) profile and the dynamic fluctuations in the gut microbiota and resistome remain incompletely elucidated. Herein, we investigated the temporal dynamics of AA profile and gut microbiota in the colon of pigs over a 24-hour period, and further explored the dynamic interrelationships among AA profile, microbiota, and resistome using metagenomics and metabolomics approaches.</p><p><strong>Results: </strong>JTK_circle analysis revealed that both the AA profile and the gut microbiota exhibited rhythmic fluctuations. With respect to the feed intake, all AAs except L-homoserine (P_Adj = 0.553) demonstrated significant fluctuations. Over 50% of Lactobacillaceae, Ruminococcaceae, Clostridiaceae, and Eubacteriaceae species reached their peaks during T15 ∼ T21 when 50% of Lachnospiraceae species experienced a trough. The eLSA results showed that most AAs positively correlated with Prevotellaceae species but negatively correlated with Lactobacillaceae and Lachnospiraceae species. Moreover, most of the AAs negatively correlated with the mobile genetic elements Tn916 and istA group but positively correlated with plasmids. Further partial least squares structural equation model analysis indicated that AAs affected the antibiotic resistance gene dynamics through mobile genetic elements and the gut microbiota.</p><p><strong>Conclusions: </strong>Taken together, the AA profile and the gut microbiota exhibit robust fluctuations over a day. The AA profile can affect the gut microbiota and resistome in a direct or indirect manner. These findings may provide new insights into a potential strategy for manipulating the gut microbiota and resistome.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"26"},"PeriodicalIF":4.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11908058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Lactiplantibacillus plantarum N-1 and isomaltose-oligosaccharide on promoting growth performance and modulating the gastrointestinal microbiota in newborn Hu sheep.","authors":"Xinyi Xu, Zhiwei Zhou, Zhiqiang Zhou, Yudong Ma, Dongmei Luo, Senlin Zhang, Pinggui Yang, Tianwu An, Qun Sun","doi":"10.1186/s42523-025-00392-1","DOIUrl":"10.1186/s42523-025-00392-1","url":null,"abstract":"<p><strong>Background: </strong>Diarrhea is usually observed in newborn Hu lambs, while severe diarrhea may lead to the stunted growth and even death in lambs, necessitating the common practice of antibiotic administration to newborns. In order to explore the application of the effective probiotics and/or prebiotic treatment in animal feed to lessen the recline on antibiotics, 27 newborn of Hu lambs were equally allocated into three groups: control group (Con), probiotics group (Pro) receiving Lactiplantibacillus plantarum N-1 (LPN-1), and synbiotics group (Syn) receiving LPN-1 combined with isomaltose-oligosaccharide (IMO), and raised till 60 days of age.</p><p><strong>Results: </strong>Compared with the Con, the incidence of severe diarrhea was lower in both two treatment groups, accompanied by a significant reduction in terramycin administration frequency (P < 0.05). The daily feed intake in newborns significantly increased after probiotics or synbiotics treatment (P < 0.05), leading to the substantial increment in average daily gain by 48.28% and heart girth (P < 0.05), as well as enhancements in height (P < 0.01) at 60 days of the age in synbiotics treatment group. Applying probiotics and synbiotics exhibited the enhanced rumen weight (P < 0.05), and synbiotics further promoted the spleen development (P < 0.05). The inclusion of probiotics and synbiotics significantly modified the gut microbial composition of Hu lambs (P < 0.01), with an increase in Butyrivibrio proteoclasticus and Pseudoruminococcus massiliensis, which were associated with starch and sucrose metabolism. Additionally, the Syn group exhibited an upsurge in the number of species associated with amino acid metabolism and cellulolysis, as well as the raised short-chain fatty acids levels in the newborn gut (P < 0.05).</p><p><strong>Conclusions: </strong>This study demonstrated that LPN-1 and IMO had an enhanced effect to improve the growth performance and decrease the reliance on antibiotics by promoting the feed intake, balancing the gut microbiota and increasing the short-chain fatty acids content in Hu lambs.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"25"},"PeriodicalIF":4.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143617229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network analyses unraveled the complex interactions in the rumen microbiota associated with methane emission in dairy cattle.","authors":"Xiaoxing Ye, Goutam Sahana, Mogens Sandø Lund, Bingjie Li, Zexi Cai","doi":"10.1186/s42523-025-00386-z","DOIUrl":"10.1186/s42523-025-00386-z","url":null,"abstract":"<p><strong>Background: </strong>Methane emissions from livestock, particularly from dairy cattle, represent a significant source of greenhouse gas, contributing to the global climate crisis. Understanding the complex interactions within the rumen microbiota that influence methane emissions is crucial for developing effective mitigation strategies.</p><p><strong>Results: </strong>This study employed Weighted Gene Co-expression Network Analysis to investigate the complex interactions within the rumen microbiota that influence methane emissions. By integrating extensive rumen microbiota sequencing data with precise methane emission measurements in 750 Holstein dairy cattle, our research identified distinct microbial communities and their associations with methane production. Key findings revealed that the blue module from network analysis was significantly correlated (0.45) with methane emissions. In this module, taxa included the genera Prevotella and Methanobrevibactor, along with species such as Prevotella brevis, Prevotella ruminicola, Prevotella baroniae, Prevotella bryantii, Lachnobacterium bovis, and Methanomassiliicoccus luminyensis are the key components to drive the complex networks. However, the absence of metagenomics sequencing is difficult to reveal the deeper taxa level and functional profiles.</p><p><strong>Conclusions: </strong>The application of Weighted Gene Co-expression Network Analysis provided a comprehensive understanding of the microbiota-methane emission relationship, serving as an innovative approach for microbiota-phenotype association studies in cattle. Our findings underscore the importance of microbiota-trait and microbiota-microbiota associations related to methane emission in dairy cattle, contributing to a systematic understanding of methane production in cattle. This research offers key information on microbial management for mitigating environmental impact on the cattle population.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"24"},"PeriodicalIF":4.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interactions between gilthead seabream intestinal transcriptome and microbiota upon Enteromyxum leei infection: a multi-omic approach.","authors":"Socorro Toxqui-Rodríguez, Itziar Estensoro, Ricardo Domingo-Bretón, Raquel Del Pozo, Jaume Pérez-Sánchez, Detmer Sipkema, Ariadna Sitjà-Bobadilla, M Carla Piazzon","doi":"10.1186/s42523-025-00388-x","DOIUrl":"10.1186/s42523-025-00388-x","url":null,"abstract":"<p><strong>Background: </strong>The enteric myxozoan parasite Enteromyxum leei is an important problem in gilthead seabream aquaculture invading the intestinal epithelium and leading to chronic intestinal inflammation, poor food conversion rates, cachexia, and mortalities, with no treatments available, resulting in significant economic losses. It is known that myxozoan infections are affected by factors such as temperature, duration of exposure, stocking densities, and seasonality. Gut microbiota has key effects on host health, including disease resistance and immune system training and development, tightly interacting with the host, affecting systemic and local physiological functions. This study aimed to gain insights into the host-microbiota-parasite interactions integrating metataxonomics, host transcriptomics, and metatranscriptomics within this disease model.</p><p><strong>Results: </strong>Exposure to E. leei together with temperature and age differences led to alterations in gilthead seabream intestinal microbiota. Samples from 240 g fish kept at 18ºC during a winter trial at 10 weeks post-parasite exposure showed the highest significant changes in their microbial composition with Proteobacteria increasing in abundance from 32.3% in the control group up to 89.8% in the infected group, while Firmicutes and Actinobacteria significantly decreased in relative abundance from 23% and 37.8-2.4% and 1.1%, respectively. After LEfSe analysis, Acinetobacter was identified as the best biomarker for the parasite-exposed group. Parasite exposure also altered the expression of 935 host genes, highlighting genes involved in immune responses such as pathways related to Interleukins, MHCI and Interferons. Microbial transcripts, also showed significant changes upon parasite infection. Integration of the results revealed differential effects on the host induced directly by the parasite or indirectly by parasite-induced microbial shift.</p><p><strong>Conclusions: </strong>Intestinal microbiota and local host gene expression showed significant changes upon en enteromyxosis. The detected activation of the host immune response was not exclusively linked to the parasite infection but also to changes in microbiota, demonstrating the key role of the different components of the mucosal system during disease. These results provided different datasets of bacterial taxa and microbial and host transcripts that will allow a better understanding of host-microbiota-parasite interactions and can serve as starting points for studying and evaluating mucosal health in aquaculture during parasitosis or other diseases.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"22"},"PeriodicalIF":4.9,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Composition of the fecal, vaginal and colostrum microbiotas of dams at parturition and their relationship with neonatal outcomes in dogs.","authors":"Quentin Garrigues, Emmanuelle Apper, Fanny Mercier, Ana Rodiles, Nicoletta Rovere, Sylvie Chastant, Hanna Mila","doi":"10.1186/s42523-025-00384-1","DOIUrl":"10.1186/s42523-025-00384-1","url":null,"abstract":"<p><strong>Background: </strong>Microbial seeding in early life is critical for the host's short- and long-term health, and the mother is the first source of bacteria for the newborn. The objective of this study was to characterize the maternal fecal, vaginal, and colostral microbiotas in the canine species one day after parturition and to evaluate the relationship between the microbial profiles of 36 dams and the neonatal outcomes of 284 newborns.</p><p><strong>Results: </strong>The first part of the study revealed the presence of 2 fecal, 3 vaginal, and 2 colostral microbial clusters on the basis of the core microbiota of the dams. Among these three maternal microbiotas, only the vaginal microbiome was found to be associated with neonatal outcomes. Compared with those in the other clusters, females in Cluster 1, with the lowest stillbirth and neonatal mortality ratios, presented a greater abundance of Moraxellaceae in their vaginal microbiota; Cluster 2, with a greater abundance of Pasteurellaceae, mostly from the Haemophilus genus; and Cluster 3 (with the highest stillbirth and neonatal mortality ratios), a greater abundance of Enterobacteriaceae, mostly E. coli. Moreover, Cluster 3 dams presented significantly lower species richness according to the Shannon index than did dams from the other clusters.</p><p><strong>Conclusions: </strong>This study underscores the strong association between maternal microbiota, particularly the vaginal microbiota, and newborn health. The results of this study call for further research to gain a deeper understanding of the optimal vaginal microbiota composition in canine species and the ways to modulate it to improve neonatal outcomes.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"23"},"PeriodicalIF":4.9,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11887402/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gut microbiome community profiling of Bornean bats with different feeding guilds.","authors":"Muhd Amsyari Morni, Julius William-Dee, Emy Ritta Jinggong, Nor Al-Shuhada Sabaruddin, Nur Afiqah Aqilah Azhar, Muhammad Amin Iman, Peter A Larsen, Jaya Seelan Sathiya Seelan, Lesley Maurice Bilung, Faisal Ali Anwarali Khan","doi":"10.1186/s42523-025-00389-w","DOIUrl":"10.1186/s42523-025-00389-w","url":null,"abstract":"<p><p>Bats are extraordinary mammals. They have evolved to consume various dietary sources, such as insects, fruits, nectar, blood, and meat. This diversity has generated considerable interest in the scientific community, resulting in efforts to leverage bats as model organisms to study the correlation between diet and gut microbiome community. Although such studies now commonly use Next Generation Sequencing (NGS), similar studies are early in their development in Southeast Asia, especially in Malaysia, which harbours an incredibly diverse bat fauna. This study provides pioneering NGS metabarcoding information on Bornean bats. By using a high-throughput Nanopore-based 16S rRNA gene sequencing method, Bacillota, Pseudomonadota, and Campylobacterota were found in insectivorous bats and phytophagous bats. Both insectivorous and phytophagous groups harboured no dominant taxon (D = 0.076; D = 0.085). A comparative analysis of gut bacteria functional groups identified eight major groups in both phytophagous and insectivorous bats, with fermentation being the predominant group. The correlation network analysis revealed a negative correlation between the 'good bacteria' Lactobacillus and various pathogenic bacteria genera, such as Salmonella (-0.4124) and Yersinia (-0.4654), demonstrating its prebiotic characteristics. This study broadens our understanding of the bat gut microbiome from various diets, with emphasis on new data from Borneo.</p>","PeriodicalId":72201,"journal":{"name":"Animal microbiome","volume":"7 1","pages":"21"},"PeriodicalIF":4.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11881492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}