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孙会增,博士,浙江大学“百人计划”研究员,博导。本人一直从事反刍动物应用基础研究,利用多组学技术如转录组学、代谢组学、宏基因组学系统解析了秸秆粗饲料利用、奶牛乳蛋白合成的代谢机制、饲料效率的调节机制等问题。近5年来,在国际权威期刊发表论文20余篇,其中第一作者身份在TrAC-Trend Anal Chem,Bioinformatics,Sci Data,BMC Genomics,J Proteome Res,Proteomics,J Dairy Sci,J Anim Sci Biotechno等杂志发表。 欢迎报考硕、博研究生或开展博士后合作研究! 教学与课程 博士生选修课:动物营养基因组学 研究与成果 一、系统解析了不同质量粗饲料影响奶牛泌乳性能的生理和代谢机制 我国奶牛养殖业目前高度依赖进口苜蓿草,使得养殖成本大幅增加,同时大量农作物秸秆资源在收获季被废弃焚烧,不仅资源浪费而且严重污染环境。奶牛因为庞大的瘤胃和丰富的厌氧微生物使其能够消化秸秆饲料产生挥发性脂肪酸供给机体产奶,因此提高秸秆饲料在奶牛养殖中的应用具有重要的经济和环境效益。大量实践集中在应用物理、化学和生物学等外部处理方法解决秸秆饲料营养价值较低的问题,但仍然没有解决饲喂秸秆奶牛奶产量和质量下降的问题。揭示秸秆饲料下奶牛奶产量和乳蛋白合成机理成为克服这一问题的最后一环和关键所在。 本人依托博士导师的奶业973课题和国家自然科学基金等项目,在阐明优质苜蓿草和低质玉米秸秆对奶牛泌乳性能,瘤胃发酵参数和血液生化指标不同影响的基础上,分析了奶牛瘤胃液、血清、奶液和尿液的代谢组图谱,发现了代谢图谱具有体液特异性,且在不同质量粗饲料处理下明显不同,这种差异可以通过尿液中的Hippuric acid来指征(J Anim Sci Biotechno)。同时利用四体液中29种共有代谢物及不同体液的共同差异,鉴定到影响乳蛋白合成的关键代谢通路-Gly,Ser and Thr通路(J Proteome Res);进一步利用宏基因组分析了瘤胃微生物丰度和功能差异,发现饲料秸秆中非纤维碳水化合物尤其是果胶含量较低造成了产琥珀酸丝状杆菌、Treponema属及3个种水平微生物以及产生丙酸的琥珀酸通路下调,直接导致瘤胃中丙酸合成减少(Bioinformatics)。这也导致了肝脏中葡萄糖合成前体物供应不足,利用肝脏组织代谢组学结合转录组学发现糖异生通路下调,Gly,Ser and Thr通路在肝脏中改变的结果使得秸秆组N利用效率下降,朝着马尿酸而不是胍基乙酸的通路转变,同时发现饲喂稻草秸秆饲料存在潜在的代谢风险(Proteomics)。最后由于血液氨基酸模式改变以及肝脏合成葡萄糖减少,乳腺中氨基酸摄取和代谢功能都出现下调,奶产量和乳蛋白含量都下降(BMC genomics)。该结果为提高秸秆类饲料利用率和奶牛泌乳性能提供了理论指导和潜在营养调控措施。 二、提出了饲料组学概念并深入分析了牛饲料效率相关的调控机制 规模化牛场中饲料成本占到总成本的60%~70%,牛是大型反刍动物,因其瘤胃的存在,每天可产生约500L的甲烷(占到所需能量的10%以上),是所有畜种中最大的温室气体贡献者,提高饲料效率不仅能直接提高经济利润,同时还能减少由于浪费能量产生的环境污染物。因此提高牛的饲料效率成为畜牧业可持续发展中的关键词,目前牛饲料效率相关的分子机制很大程度上还是未知的。 组学可以在短时间内获得大量分子表型同时应用生物信息学解析其中的规律,这为应对当前挑战提供了可能,同时饲料效率等是非常复杂的表型,受到多种生物过程影响同时反映在不同的分子水平,因此多组学技术的系统思维能够突破现有研究局限。申请者在多组学应用的理论构建上开展了一些突破性工作。食品组学(Foodomics)是2009年首先提出来的,指的是通过应用和整合先进的组学技术来研究食品和营养以改善人类的福祉,健康和知识的学科,目前已经发展成为一个非常系统完善的学科方向。类比食品组学,我们首次在动物上提出饲料组学的概念,Feedomics,定义为利用多组学技术通过研究饲料,环境,动物生理及其共生微生物之间的相互作用,了解和揭示决定动物生产力、产品质量、福利和健康的生物机制(TrAC-Trend Anal Chem)。同时我们也提出了Feedomics在奶牛中的应用方向及存在的局限(J Dairy Sci),为多组学技术在奶牛上的应用提供了理论指导。 有了理论上的指导,我们进一步通过试验加以佐证。比较分析了牛瘤胃上皮、肝脏、肌肉和脂肪组织的全转录组图谱,构建了基因共表达网络,发现不同组织功能对饲料效率的贡献各不相同,如肝脏更适合通过采食量来研究饲料效率。同时结合饲喂效率相关表型分析了饲喂效率高度相关的基因模块及功能,鉴定到了19个调控肉牛饲料效率的基因marker(Bioinformatics)。进一步通过全基因组水平的可变剪接事件深入研究了关键基因的具体调控机制,发现了7个特异的可变剪接事件在其中发挥重要作用。 三、牛分子表型特征研究 动物营养与饲料科学经过几十年的发展积累了大量的表型数据,比如饲料营养成分、血液生化指标、动物生长性能和产品品质数据等,我们通过一系列的组学研究发现内在的分子表型如基因、蛋白、代谢物包括微生物都有很强的规律和特征,这些分子表型是不是能解释很多传统方法解释不了的问题,更重要的是这些分析表型是不是应该进一步研究和记录,进入真正的动物营养与饲料科学2.0时代,申请者据此开展了系列创新性工作。基于大量样本研究牛的分子表型特征,包括在334头泌乳中期奶牛中通过16S rRNA测序解析了乳蛋白产量相关的瘤胃细菌多样性,报道了4,460个OTU和6,082个扩增子序列变异体(Sci Data)。系统研究了牛11种组织及外周miRNA表达图谱,发现bta-miR-143和bta-miR-27b是高度保守的(Sci Data),为将来miRNA定量提供参考。对196头泌乳奶牛的血液DNA甲基化频率分析后发现泌乳中期奶牛血液DNA甲基化频率的平均值为12.4%,高于人和小鼠的水平,甲基化频率和产奶量呈负相关趋势(J Dairy Sci)。同时针对以上分子表型初步构建了牛组学数据库平台Cattleomics,用于积累、共享和重挖掘分子表型数据。

研究领域

奶牛系统生物学,胃肠道功能与微生物组,营养基因组学,奶牛营养与代谢等。

近期论文

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Data.6,180301.DOI:10.1038/sdata.2018.301. 17.Sun,H.Z.,Zhao,K.,Zhou,M.,Chen,Y.,&Guan,L.L.(2018).Landscape of multi-tissue global gene expression reveals the regulatory signatures of feed efficiency in beef cattle.Bioinformatics.35(10):1712-19. 16.Sun,H.Z.,&Guan,L.L.(2018).Feedomics:promises for food security with sustainable food animal production.TrAC-Trend Anal Chem.107,130-141.DOI:10.1016/j.trac.2018.07.025. 15.Xue,M.Y.,Sun,H.Z.,Wu,X.H.,Guan,L.L.,&Liu,J.X.(2018).Assessment of rumen microbiota from a large cattle cohort reveals the pan and core bacteriome contributing to varied phenotypes.Appl Environ Microb.84(19),e00970-183.602.DOI=10.1128/AEM.00970-18. 14.Wu,X.H.,Sun,H.Z.,Xue,M.Y.,Wang,D.M.,Guan,L.L.,&Liu,J.X.(2018).Serum metabolome profiling revealed potential biomarkers for milk protein yield in dairy cows.J Proteomics.184,54-61.DOI:10.1016/j.jprot.2018.06.005. 13.Wang,B.,Sun,H.Z.,Wu,X.H.,Jiang,L.,Guan,L.L.,&Liu,J.X.(2018).Arteriovenous blood metabolomics:An efficient method to 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nutrient and metabolic defects of feeding low-quality forage to dairy cows.Feed Industry,38(11),1-8. 7.Sun,H.Z.,Wang,B.,Wang,J.,Liu,H.,&Liu,J.X.(2016).Biomarker and pathway analyses of urine metabolomics in dairy cows when corn stover replaces alfalfa hay.J Anim Sci Biotechno,7(1),49.DOI:10.1186/s40104-016-0107-7. 6.Wang,B.,Sun,H.Z.,Xu,N.N.,Zhu,K.J.,&Liu,J.X.(2016).Amino acid utilization of lactating dairy cows when diets are changed from an alfalfa-based diet to cereal straw-based diets.Anim Feed Sci Tech.217,56-66.DOI:10.1016/j.anifeedsci.2016.04.014. 5.Wang,D.M.,Liang,G.X.,Wang,B.,Sun,H.Z.,Liu,J.X.,&Guan,L.L.(2016).Systematic micrornaome profiling reveals the roles of micrornas in milk protein metabolism and quality:insights on low-quality forage utilization.Sci Rep,6(7),630-631.DOI:10.1038/srep21194. 4.Zhang,B.,Wang,C.,Wei,Z.H.,Sun,H.Z.,Xu,G.Z.,Liu,J.X.,&Liu,H.Y.(2016).The effects of dietary phosphorus on the growth performance and phosphorus excretion of dairy heifers.Asian-Australasian J Anim Scis,29(7),960.DOI:10.5713/ajas.15.0548. 3.Sun,H.Z.,Wang,D.,Wang,B.,Wang,J.K.,Liu,H.,Guan,L.L.,&Liu,J.X.(2015).Metabolomics of four biofluids from dairy cows:potential biomarkers for milk production and quality.J Proteome Res.14,1287-1298.DOI:10.1021/pr501305g. 2.Shen,J.S.,Song,L.J.,Sun,H.Z.,Wang,B.,Chai,Z.,Chacher,B.,&Liu,J.X.(2015).Effects of corn and soybean meal types on rumen fermentation,nitrogen metabolism and productivity in dairy cows.Asian-Australasian J Anim Scis.28(3),351.DOI:10.5713/ajas.14.0504. 1.Sun,H.Z.,&Liu,J.X.(2014).Nutritional metabolomics and its application in dairy cow nutrition research.Chinese J Anim Sci,50(11),81-85 Conference proceedings and abstracts 16.Sun,H.Z.Zhao,K.,Zhou,M.,Chen,Y.&Guan,L.L.(2019).Transcriptomics analysis of key metabolic tissues to identify regulatory patterns of feed efficiency.The 70th Annual Meeting of the European Federation of Animal Science,Ghent,Belgium,August 26-30. 15.Sun,H.Z.&Guan,L.L.(2019).Non-coding RNA based epigenetic mechanisms impacting cattle productivity and health.Alberta Epigenetics Network Veterinary Medicine Symposium,Calgary,Alberta,Canada,March 8. 14.Sun,H.Z.Chen,Y.,&Guan,L.L.(2018).Milk production related DNA methylation rates analysis in the dairy cow.The Alberta Epigenetics Annual Summit,Edmonton,Alberta,Canada,March 25-27. 13.Sun,H.Z.,Shi,K.,Wu,X.H.,Xue,M.Y.,Wei,Z.H.,&Liu,H.Y.(2017).Lactation-related metabolic mechanism investigated based on the relationships between 4 biofluids and mammary gland metabolomics in dairy cows.J Dairy Sci.100(E-Suppl.2):69. 12.Sun,H.Z.,Liu,H.Y.,Wang,D.M.,Guan,L.L.&Liu,J.X.(2017).Identification of metabolic differences in dairy cows consuming corn stover and rice straw through liver metabolomics and transcriptomics.J Dairy Sci.100(E-Suppl.2):69. 11.Xue,M.Y.,Sun,H.Z.,Wang,D.M.,Guan,L.L.,Wang,J.K.,&Liu,J.X.Potential role of rumen bacterial communities in shaping milk production and composition of 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Sci.94(E-Suppl.5):520-521. 6.Sun,H.Z.,Guan,L.L.,&Liu,J.X.(2015).Metabolome based relationships of four biofluids from dairy cows.J Dairy Sci.98(E-Suppl.2):303-304 5.Sun,H.Z.,Wei,Z.H.,Zhu,W.,Xie,X.,Wang,J.K.,Guan,L.L.,&Liu,J.X.(2015).The effect of pelletized corn stover replacing alfalfa hay on lactation performance,blood parameters and rumen fermentation in dairy cows.J Dairy Sci.98(E-Suppl.2):464. 4.Sun,H.Z.,Wang,B.,Wang,D.M.,Wang,J.K.,Guan,L.L.,&Liu,J.X.(2014).Metabolomics profiling of four biofluids from dairy cow fed different forage using GC-TOF/MS.J Dairy Sci.98(E-Suppl.2):254. 3.Sun H.Z.,Wei Z.H.,Zhu W.,Xie X.,Wang J.K.,&Liu J.X.(2015).Effect of replacement of alfalfa with corn stover on production performance and rumen fermentation of lactating dairy cows.The 8th National Congress of China Animal Husbandry Society.Beijing,China,April 25~27. 2.Wang B.,Sun H.Z.,Xu N.N.,Zhu K.J.,&Liu J.X.(2014).A comparative study on the nitrogen metabolism and amino acid utilization of straw and alfalfa as a forage feed source for dairy cows.The 7th China Feed and Nutrition Symposium.Zhengzhou,China,October 16-18. 1.Sun H.Z.,Wang B.,Wang J.K.,&Liu J.X.(2014).Metabolomics analysis the rumen metabolism of lactating dairy cows fed corn stover-and alfalfa-based diets.The 7th China Feed and Nutrition Symposium.Zhengzhou,China,October 16-18.

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