Table_1_Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis.xlsx

BackgroundBovine respiratory disease (BRD) is the most devastating disease affecting beef and dairy cattle producers in North America. An emerging area of interest is the respiratory microbiome’s relationship with BRD. However, results regarding the effect of BRD on respiratory microbiome diversity are conflicting.ResultsTo examine the effect of BRD on the alpha diversity of the respiratory microbiome, a meta-analysis analyzing the relationship between the standardized mean difference (SMD) of three alpha diversity metrics (Shannon’s Diversity Index (Shannon), Chao1, and Observed features (OTUs, ASVs, species, and reads) and BRD was conducted. Our multi-level model found no difference in Chao1 and Observed features SMDs between calves with BRD and controls. The Shannon SMD was significantly greater in controls compared to that in calves with BRD. Furthermore, we re-analyzed 16S amplicon sequencing data from four previously published datasets to investigate BRD’s effect on individual taxa abundances. Additionally, based on Bray Curtis and Jaccard distances, health status, sampling location, and dataset were all significant sources of variation. Using a consensus approach based on RandomForest, DESeq2, and ANCOM-BC2, we identified three differentially abundant amplicon sequence variants (ASVs) within the nasal cavity, ASV5_Mycoplasma, ASV19_Corynebacterium, and ASV37_Ruminococcaceae. However, no ASVs were differentially abundant in the other sampling locations. Moreover, based on SECOM analysis, ASV37_Ruminococcaceae had a negative relationship with ASV1_Mycoplasma_hyorhinis, ASV5_Mycoplasma, and ASV4_Mannheimia. ASV19_Corynebacterium had negative relationships with ASV1_Mycoplasma_hyorhinis, ASV4_Mannheimia, ASV54_Mycoplasma, ASV7_Mycoplasma, and ASV8_Pasteurella.ConclusionsOur results confirm a relationship between bovine respiratory disease and respiratory microbiome diversity and composition, which provide additional insight into microbial community dynamics during BRD development. Furthermore, as sampling location and sample processing (dataset) can also affect results, consideration should be taken when comparing results across studies.</p

Image_3_Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis.tif

BackgroundBovine respiratory disease (BRD) is the most devastating disease affecting beef and dairy cattle producers in North America. An emerging area of interest is the respiratory microbiome’s relationship with BRD. However, results regarding the effect of BRD on respiratory microbiome diversity are conflicting.ResultsTo examine the effect of BRD on the alpha diversity of the respiratory microbiome, a meta-analysis analyzing the relationship between the standardized mean difference (SMD) of three alpha diversity metrics (Shannon’s Diversity Index (Shannon), Chao1, and Observed features (OTUs, ASVs, species, and reads) and BRD was conducted. Our multi-level model found no difference in Chao1 and Observed features SMDs between calves with BRD and controls. The Shannon SMD was significantly greater in controls compared to that in calves with BRD. Furthermore, we re-analyzed 16S amplicon sequencing data from four previously published datasets to investigate BRD’s effect on individual taxa abundances. Additionally, based on Bray Curtis and Jaccard distances, health status, sampling location, and dataset were all significant sources of variation. Using a consensus approach based on RandomForest, DESeq2, and ANCOM-BC2, we identified three differentially abundant amplicon sequence variants (ASVs) within the nasal cavity, ASV5_Mycoplasma, ASV19_Corynebacterium, and ASV37_Ruminococcaceae. However, no ASVs were differentially abundant in the other sampling locations. Moreover, based on SECOM analysis, ASV37_Ruminococcaceae had a negative relationship with ASV1_Mycoplasma_hyorhinis, ASV5_Mycoplasma, and ASV4_Mannheimia. ASV19_Corynebacterium had negative relationships with ASV1_Mycoplasma_hyorhinis, ASV4_Mannheimia, ASV54_Mycoplasma, ASV7_Mycoplasma, and ASV8_Pasteurella.ConclusionsOur results confirm a relationship between bovine respiratory disease and respiratory microbiome diversity and composition, which provide additional insight into microbial community dynamics during BRD development. Furthermore, as sampling location and sample processing (dataset) can also affect results, consideration should be taken when comparing results across studies.</p

Image_1_Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis.tif

BackgroundBovine respiratory disease (BRD) is the most devastating disease affecting beef and dairy cattle producers in North America. An emerging area of interest is the respiratory microbiome’s relationship with BRD. However, results regarding the effect of BRD on respiratory microbiome diversity are conflicting.ResultsTo examine the effect of BRD on the alpha diversity of the respiratory microbiome, a meta-analysis analyzing the relationship between the standardized mean difference (SMD) of three alpha diversity metrics (Shannon’s Diversity Index (Shannon), Chao1, and Observed features (OTUs, ASVs, species, and reads) and BRD was conducted. Our multi-level model found no difference in Chao1 and Observed features SMDs between calves with BRD and controls. The Shannon SMD was significantly greater in controls compared to that in calves with BRD. Furthermore, we re-analyzed 16S amplicon sequencing data from four previously published datasets to investigate BRD’s effect on individual taxa abundances. Additionally, based on Bray Curtis and Jaccard distances, health status, sampling location, and dataset were all significant sources of variation. Using a consensus approach based on RandomForest, DESeq2, and ANCOM-BC2, we identified three differentially abundant amplicon sequence variants (ASVs) within the nasal cavity, ASV5_Mycoplasma, ASV19_Corynebacterium, and ASV37_Ruminococcaceae. However, no ASVs were differentially abundant in the other sampling locations. Moreover, based on SECOM analysis, ASV37_Ruminococcaceae had a negative relationship with ASV1_Mycoplasma_hyorhinis, ASV5_Mycoplasma, and ASV4_Mannheimia. ASV19_Corynebacterium had negative relationships with ASV1_Mycoplasma_hyorhinis, ASV4_Mannheimia, ASV54_Mycoplasma, ASV7_Mycoplasma, and ASV8_Pasteurella.ConclusionsOur results confirm a relationship between bovine respiratory disease and respiratory microbiome diversity and composition, which provide additional insight into microbial community dynamics during BRD development. Furthermore, as sampling location and sample processing (dataset) can also affect results, consideration should be taken when comparing results across studies.</p

Image_2_Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis.tif

BackgroundBovine respiratory disease (BRD) is the most devastating disease affecting beef and dairy cattle producers in North America. An emerging area of interest is the respiratory microbiome’s relationship with BRD. However, results regarding the effect of BRD on respiratory microbiome diversity are conflicting.ResultsTo examine the effect of BRD on the alpha diversity of the respiratory microbiome, a meta-analysis analyzing the relationship between the standardized mean difference (SMD) of three alpha diversity metrics (Shannon’s Diversity Index (Shannon), Chao1, and Observed features (OTUs, ASVs, species, and reads) and BRD was conducted. Our multi-level model found no difference in Chao1 and Observed features SMDs between calves with BRD and controls. The Shannon SMD was significantly greater in controls compared to that in calves with BRD. Furthermore, we re-analyzed 16S amplicon sequencing data from four previously published datasets to investigate BRD’s effect on individual taxa abundances. Additionally, based on Bray Curtis and Jaccard distances, health status, sampling location, and dataset were all significant sources of variation. Using a consensus approach based on RandomForest, DESeq2, and ANCOM-BC2, we identified three differentially abundant amplicon sequence variants (ASVs) within the nasal cavity, ASV5_Mycoplasma, ASV19_Corynebacterium, and ASV37_Ruminococcaceae. However, no ASVs were differentially abundant in the other sampling locations. Moreover, based on SECOM analysis, ASV37_Ruminococcaceae had a negative relationship with ASV1_Mycoplasma_hyorhinis, ASV5_Mycoplasma, and ASV4_Mannheimia. ASV19_Corynebacterium had negative relationships with ASV1_Mycoplasma_hyorhinis, ASV4_Mannheimia, ASV54_Mycoplasma, ASV7_Mycoplasma, and ASV8_Pasteurella.ConclusionsOur results confirm a relationship between bovine respiratory disease and respiratory microbiome diversity and composition, which provide additional insight into microbial community dynamics during BRD development. Furthermore, as sampling location and sample processing (dataset) can also affect results, consideration should be taken when comparing results across studies.</p

DataSheet_1_Geography, niches, and transportation influence bovine respiratory microbiome and health.docx

Bovine respiratory disease (BRD), one of the most common and infectious diseases in the beef industry, is associated with the respiratory microbiome and stressors of transportation. The impacts of the bovine respiratory microbiota on health and disease across different geographic locations and sampling niches are poorly understood, resulting in difficult identification of BRD causes. In this study, we explored the effects of geography and niches on the bovine respiratory microbiome and its function by re-analyzing published metagenomic datasets and estimated the main opportunistic pathogens that changed after transportation. The results showed that diversity, composition, structure, and function of the bovine nasopharyngeal microbiota were different across three worldwide geographic locations. The lung microbiota also showed distinct microbial composition and function compared with nasopharyngeal communities from different locations. Although different signature microbiota for each geographic location were identified, a module with co-occurrence of Mycoplasma species was observed in all bovine respiratory communities regardless of geography. Moreover, transportation, especially long-distance shipping, could increase the relative abundance of BRD-associated pathogens. Lung microbiota from BRD calves shaped clusters dominated with different pathogens. In summary, geography, sampling niches, and transportation are important factors impacting the bovine respiratory microbiome and disease, and clusters of lung microbiota by different bacterial species may explain BRD pathogenesis, suggesting the importance of a deeper understanding of bovine respiratory microbiota in health.</p

Image_3_Hybridization altered the gut microbiota of pigs.jpg

Mammalian gut microbiota plays an important role in the host’s nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs’ gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host “dominance” phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.</p

Image_1_Hybridization altered the gut microbiota of pigs.jpg

Mammalian gut microbiota plays an important role in the host’s nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs’ gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host “dominance” phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.</p

Table_5_Hybridization altered the gut microbiota of pigs.XLSX

Mammalian gut microbiota plays an important role in the host’s nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs’ gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host “dominance” phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.</p

Table_1_Hybridization altered the gut microbiota of pigs.XLSX

Mammalian gut microbiota plays an important role in the host’s nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs’ gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host “dominance” phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.</p

Image_2_Hybridization altered the gut microbiota of pigs.jpg

Mammalian gut microbiota plays an important role in the host’s nutrient metabolism, growth, and immune regulation. Hybridization can enable a progeny to acquire superior traits of the parents, resulting in the hybridization advantage. However, studies on the effects of hybridization on the pigs’ gut microbiota are lacking. Therefore, this study used multi-omics technologies to compare and analyze the gut microbiota of the primary wild boar and its offspring. The 16S rRNA gene sequencing results revealed that the gut microbiota of F4 exhibited a host-like dominance phenomenon with a significant increase in the abundance of Lactobacillus and Bifidobacterium. The beta diversity of Duroc was significantly different from those of F0, F2, and F4; after the host hybridization, the similarity of the beta diversity in the progeny decreased with the decrease in the similarity of the F0 lineage. The metagenomic sequencing results showed that the significantly enriched metabolic pathways in F4, such as environmental, circulatory system, fatty acid degradation adaptation, and fatty acid biosynthesis, were similar to those in F0. Moreover, it also exhibited similar significantly enriched metabolic pathways as those in Duroc, such as carbohydrate metabolism, starch and sucrose metabolism, starch-degrading CAZymes, lactose-degrading CAZymes, and various amino acid metabolism pathways. However, the alpha-amylase-related KOs, lipid metabolism, and galactose metabolism in F4 were significantly higher than those in Duroc and F0. Non-targeted metabolome technology analysis found that several metabolites, such as docosahexaenoic acid, arachidonic acid, and citric acid were significantly enriched in the F4 pigs as compared to those in F0. Based on Spearman correlation analysis, Lactobacillus and Bifidobacterium were significantly positively correlated with these metabolites. Finally, the combined metagenomic and metabolomic analysis suggested that the metabolic pathways, such as valine, leucine, and isoleucine biosynthesis and alanine aspartate and glutamate metabolism were significantly enriched in F4 pigs. In conclusion, the gut microbiota of F4 showed a similar host “dominance” phenomenon, which provided reference data for the genetics and evolution of microbiota and the theory of microbial-assisted breeding.</p