Differences of Growth Performance and Rumen Content Microbial Composition of Homologous Hu Sheep under Different Growing Environmental Conditions
CHEN Fengmei1, CHENG Guangmin1, WANG Ping1, WANG Yunzhou1, ZHANG Wanming2, HU Shilin1, XU Xiangting1, NIU Zhongxiang3
1. Weifang Ruminant Disease Prevention and Control Engineering Center, Shandong Vocational Animal Science and Veterinary College, Weifang 261061, China;
2. Haibei Plateau Modern Ecological Animal Husbandry Science and Technology Experimental Demonstration Park, Haibei 810299, China;
3. College of Animal Science and Technology, Shandong Agricultural University, Tai'an 271018, China
Abstract：The purpose of this experiment was to investigate the effects of different growing environments on the growth performance, rumen content microbial composition and biological information of the homologous Hu sheep. A total of 90 Hu sheep (male:female=1:8) about 1-year-old with similar genetic background and the same birth order were selected and randomly divided into two groups. One group with 45 sheep were transported to a sheep rearing and breeding base in Haiyan, Qinghai province for breeding. Another group with 45 sheep were transported to a sheep rearing and breeding base in Gaomi, Shandong province. They mated in that year and produced lambs in the next year. Lambs produced from both places were weaned at 75 days of age, labeled, and used as candidate test subjects. The experiment was divided into two groups, Shandong group (sdlw group) and Qinghai group (qhlw group). In accordance with the principle of similar weight, 40 healthy 90-day-old Hu sheep were selected for each group, and randomly divided into 4 rearing stalls (mixed breeding between male and female) to start the routine feeding experiment. The pre-test period was 10 days, and the formal period was 150 days. At the end of the experiment, 4 rams were randomly selected from each group to be dissected to collect rumen fluid, and 16s RNA technology was used to analyze the differences in bacterial microflora of two groups and predict the function of Tax4Fun. The results showed as follows:1) when the dietary nutrient bases were similar, the average daily weight gain in sdlw and qhlw groups is significantly different (P<0.05), and the difference in feed/gain is significant (P<0.05). Besides, the observed species index and Shannon indexe were not significantly different between sdlw and qhlw groups (P>0.05). 2) According to the analysis of Unweighted Unifrac distance PCoA, it was found that species in sdlw and qhlw groups were more similar, and species diversity was different between groups. 3)According to the species analysis, the dominant species at the level of phylum mainly included Bacteroidetes, Firmicutes and Chloroflex, and the dominant species at the level of genus were the unidentified_Prevotidae, unidentified Rumenaceae and Bacteroides. The dominant species were Prevotella_sp_DJF_CP65, Rumen_Bacterium_NK4A214 and Prevotella_Ruminicola. The relative abundance of Chloroflex in sdlw group was significantly higher than that in qhlw group (P<0.05). However, the relative abundance of unidentified_Prevotellaceae in the qhlw group was significantly higher than that in the sdlw group (P<0.05), and the relative abundance of unidentified_Rumenaceae in the sdlw group was significantly higher than that in the qhlw group (P<0.05). 4) LEfSe analysis revealed that the f_Ruminococcaceae, g_Flexilinea, c_Anaerolineae, p_Chloroflexi and f_Anaerolineaceae played an important role in sdlw group. Prevotella_sp_DJF_CP65)and f_Prevotellaceae played an important role in the qhlw group. 5) Through the analysis of the first-level functions of biological metabolic pathways, it was found that the gene expression abundance in sdlw group was higher than that in qhlw group in the four biological metabolic pathways of environmental information processing which were metabolism, cellular processes, environmental information_processings and unclassified function, and the gene expression abundance in qhlw group was higher in the aspects of genetic information processing, human disease and organic system. By analyzing the secondary functional layer, it was found that the gene expression abundance in sdlw group was significantly higher than that in qhlw group in transcription, aging, carbohydrate metabolism, biosynthesis of other secondary metabolites, membrane transport, lipid metabolism, cellular community prokaryotes, metabolism of other amino acids, metabolism, cellular processes and signaling, cell motility, cancers, xenobiotics, biodegradation and metabolism, nervous system, amino acid metabolism, signal transduction, genetic information processing. In summary, it was found that in the case of similar dietary nutrient bases, the average daily weight gain of Hu sheep in qhlw and sdlw groups is significantly different, and the feed/gain is significantly different; the regional differences can significantly affect the richness and diversity of Hu sheep. Function prediction shows that the biological metabolism pathway gene expression abundance of Hu sheep fed in Shandong are obviously better than those of Hu sheep fed in Qinghai in transcription, amino acid metabolism, carbohydrate metabolism, membrane transport, lipid metabolism, community prokaryote cells, metabolism, cell signaling, cell activity process and biological degradation et al.
陈凤梅, 程光民, 王萍, 王云洲, 张万明, 胡士林, 徐相亭, 牛钟相. 同源湖羊在不同生长环境条件下生长性能和瘤胃内容物微生物组成的差异[J]. 动物营养学报, 2020, 32(9): 4230-4241.
CHEN Fengmei, CHENG Guangmin, WANG Ping, WANG Yunzhou, ZHANG Wanming, HU Shilin, XU Xiangting, NIU Zhongxiang. Differences of Growth Performance and Rumen Content Microbial Composition of Homologous Hu Sheep under Different Growing Environmental Conditions. Chinese Journal of Animal Nutrition, 2020, 32(9): 4230-4241.
JEWELL K A,MCCORMICK C A,ODT C L,et al.Ruminal bacterial community composition in dairy cows is dynamic over the course of two lactations and correlates with feed efficiency[J].Applied and Environmental Microbiology,2015,81(14):4697-4710.
[3]
BEN SHABAT S K,SASSON G,DORON-FAIGENBOIM A,et al.Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants[J].The ISME Journal,2016,10(12):2958-2972.
HENDERSON G,COX F,GANESH S,et al.Rumen microbial community composition varies with diet and host,but a core microbiome is found across a wide geographical range[J].Scientific Reports,2016,6:19175.
[17]
ASCHENBACH J R,PENNER G B,STUMPFF F,et al.Ruminant nutrition symposium:role of fermentation acid absorption in the regulation of ruminal pH[J].Journal of Animal Science,2011,89(4):1092-1097.
[23]
THOETKIATTIKUL H,MHUANTONG W,LAOTHANACHAREON T,et al.Comparative analysis of microbial profiles in cow rumen fed with different dietary fiber by tagged 16S rRNA gene pyrosequencing[J].Current Microbiology,2013,67(2):130-137.
[26]
FLINT H J,BAYER E A,RINCON M T,et al.Polysaccharide utilization by gut bacteria:potential for new insights from genomic analysis[J].Nature Reviews Microbiology,2008,6(2):121-131.
ZHAO S,ZHAO J,BU D,et al.Metabolomics analysis reveals large effect of roughage types on rumen microbial metabolic profile in dairy cows[J].Letters in Applied Microbiology,2014,59(1):79-85.
PITTA D W,PINCHAK W E,DOWS S,et al.Longitudinal shifts in bacterial diversity and fermentation pattern in the rumen of steers grazing wheat pasture[J].Anaerobe,2014,30:11-17.
[28]
高凤.奶牛肠道微生物群落结构与多样性研究[D].硕士学位论文.邯郸:河北工程大学,2017
[19]
WU S G,WANG G T,ANGERT E R,et al.Composition,diversity,and origin of the bacterial community in grass carp intestine[J].PLoS One,2012,7(2):e30440.
[20]
WONGWILAIWALIN S,LAOTHANACHAREON T,MHUANTONG W,et al.Comparative metagenomic analysis of microcosm structures and lignocellulolytic enzyme systems of symbiotic biomass-degrading consortia[J].Applied Microbiology and Biotechnology,2013,97(20):8941-8954.
