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[学术文献 ] Machine learning-aided design and screening of an emergent protein function in synthetic cells 进入全文

Nature Communications

Recently, utilization of Machine Learning (ML) has led to astonishing progress in computational protein design, bringing into reach the targeted engineering of proteins for industrial and biomedical applications. However, the design of proteins for emergent functions of core relevance to cells, such as the ability to spatiotemporally self-organize and thereby structure the cellular space, is still extremely challenging. While on the generative side conditional generative models and multi-state design are on the rise, for emergent functions there is a lack of tailored screening methods as typically needed in a protein design project, both computational and experimental. Here we describe a proof-of-principle of how such screening, in silico and in vitro, can be achieved for ML-generated variants of a protein that forms intracellular spatiotemporal patterns. For computational screening we use a structure-based divide-and-conquer approach to find the most promising candidates, while for the subsequent in vitro screening we use synthetic cell-mimics as established by Bottom-Up Synthetic Biology. We then show that the best screened candidate can indeed completely substitute the wildtype gene in Escherichia coli. These results raise great hopes for the next level of synthetic biology, where ML-designed synthetic proteins will be used to engineer cellular functions.

[前沿资讯 ] An e-nose could be a powerful tool in the feed chain for quality and safety control and mycotoxin monitoring 进入全文

FEED NAVIGATOR

Dr Matteo Ottoboni, from the Department of Veterinary Medicine and Animal Sciences, at the University of Milan, presented on the application of electronic noses for feed safety and animal nutrition at the World Mycotoxin Forum in Antwerp in Belgium last month.

[前沿资讯 ] 南京农业大学消化道微生物团队发现生命早期瘤胃微生物衍生物对反刍动物瘤胃发育影响 进入全文

南京农业大学

日粮在塑造胃肠道微生物群落方面扮演不可或缺的角色,微生物的代谢产物可作为信号或底物,影响宿主器官的发育和代谢健康。日粮、微生物和宿主之间的相互作用构建了一个复杂的共生体系,其如何共同促进人类和动物的健康已经引起了广泛关注,但它们之间的直接关联在很大程度上仍然是一个未解之谜。在瘤胃中,微生物发挥着多重作用,它们不仅能有效地将膳食纤维转化为重要的代谢前体,例如挥发性脂肪酸(VFA)、微生物蛋白质和维生素,还能显著影响瘤胃复层上皮和肌层的发育。瘤胃微生物的初始定植及其在出生后逐渐稳定的过程会受到不同日粮(如液态奶、谷物固体饲料、干草或这些日粮的组合)的显著影响。然而,目前仍然难以明确在出生后不同日粮营养条件下,瘤胃微生物群究竟如何影响瘤胃壁的发育以及动物的生长过程。 研究以哺乳羔羊为研究对象,利用极端化早期营养干预策略构建了瘤胃上皮/肌层的差异化发育表型;基于天然植物成分的微生物产物标准物质质谱库和极性/非极性物质的色谱选择策略,首次鉴定出与瘤胃上皮和肌层发育密切相关的代谢物吲哚-3-甲醛(IAld)和前列腺素D2(PGD2);利用宏基因组技术厘清了IAld和PGD2在瘤胃内的微生物合成路径并筛选出候选代谢微生物菌株,进一步通过单菌体外纯培养试验,发现假长双歧杆菌可代谢色氨酸生成IAld,白色念珠球菌具有生成PGD2的能力;利用转录组技术锚定瘤胃差异化发育的信号调控通路,体内外试验揭示了IAld通过激活Wnt/β-catenin信号通路促进瘤胃上皮发育,PGD2依赖Ca2+信号通路调控瘤胃肌层发育。研究结果加深了对生命早期日粮-微生物-宿主互作的理解,首次明确了瘤胃特定菌株及其下游代谢物与瘤胃生理的直接联系,为幼龄反刍动物开食料添加剂的开发应用提供新思路。

[前沿资讯 ] 华中农业大学猪肠道微生物参考基因集及核心优势细菌功能解析研究取得进展 进入全文

华中农业大学

 近日,The ISME Journal杂志在线发表了华中农业大学农业微生物资源发掘与利用全国重点实验室、教育部动物育种与健康养殖前沿科学中心、湖北洪山实验室晏向华教授课题组的研究成果,论文题为“Characterizing core microbiota and regulatory functions of the pig gut microbiome”。该研究构建了猪肠道微生物参考基因集,筛选到猪肠道核心优势细菌,并解析其对宿主代谢的调控作用机制,对实施肠道菌群干预改善猪生长与肠道健康具有重要意义。 研究人员综合运用宏基因组学和细菌16S rDNA扩增子测序技术系统解析了7个品种猪(即杜×(长×大)猪、藏猪、莱芜猪、沙子岭猪、从江香猪、环江香猪和宁乡猪)共计56头断奶仔猪和56头育肥末期猪的肠道微生物区系组成。鉴定了11418273个非冗余肠道微生物基因,通过与已发表文献的非冗余肠道微生物基因进行整合,本研究构建了包含17020160个非冗余基因的猪肠道微生物基因集,通过对宏基因组组装数据进行分箱,共重构获得了4910个非冗余原核微生物基因组。研究表明我国地方猪肠道微生物的营养物质(包括脂类、氨基酸、碳水化合物和核苷酸)代谢能力和能量代谢能力比杜×(长×大)商品猪更强。杜×(长×大)商品猪肠道微生物的抗生素抗性基因丰度比中国地方猪更高,研究发现品种和日龄是影响猪肠道微生物区系组成和功能的关键因素。综合评估微生物的出现率、微生物相对丰度和猪生长阶段,利用宏基因组学和细菌16S rDNA扩增子测序共鉴定出3种猪肠道核心优势细菌(Phascolarctobacterium succinatutens、Prevotella copri和Oscillibacter valericigenes),结果表明灌服上述3种核心优势细菌可显著增加无菌小鼠的器官指数(包括心脏、脾脏和胸腺),降低胃肠道的长度,增强肠道上皮屏障功能,增加肠道的隐窝深度,同时上述3种核心优势细菌可显著改变无菌小鼠的营养物质代谢过程(包括初级胆汁酸的生物合成、苯丙氨酸、酪氨酸和色氨酸的生物合成、苯丙氨酸的代谢等)。综上,本研究系统性解析了7个品种猪的肠道微生物的组成与功能,筛选出猪肠道微生物核心优势细菌并证明了其对无菌小鼠器官指数、肠道屏障功能、肠道黏膜形态和营养物质代谢的关键调控作用,为实施肠道菌群干预改善猪生长与肠道健康提供理论依据和新资料。

[前沿资讯 ] 华中农业大学在江汉鸡肠道微生物组解析和益生菌筛选中取得新进展 进入全文

华中农业大学

华中农业大学生命科学技术学院益生菌智造创新团队赵述淼副教授课题组在国际学术期刊Microbiome上发表题为“Metagenome-assembled genome reveals species and functional composition of Jianghan chicken gut microbiota and isolation of Pediococcus acidilactic with probiotic properties”的研究论文,研究采用宏基因组测序技术揭示江汉鸡肠道微生物群物种和功能组成以及分离了具有益生菌特性的乳酸片球菌。 研究团队利用宏基因组测序技术分析了长江流域附近四个城市江汉鸡肠道微生物的物种和功能组成。结果表明,江汉鸡肠道菌群的细菌种类组成与其他鸡品种相似,其中Phocaeicola和Bacteroides是最丰富的细菌属。LEfSe 分析显示荆州样品与其他三组样品之间的物种组成和功能特征存在显著差异。功能注释表明,江汉鸡肠道菌群以代谢基因为主,其中与碳水化合物代谢相关的基因数量最多。发现了多个抗生素抗性基因(ARG),并且ARG的组成与集约化笼养鸡相似,表明抗生素广泛存在于江汉鸡的肠道微生物群中。结合宏基因组的研究结果,从鸡肠道中分离、鉴定出了829株微生物,并进行了大规模的益生性评价,其中3 株乳酸片球菌(P. acidilatic)表现出较强的益生潜力。这些发现提供了对江汉鸡独特肠道微生物群的深入了解,并强调了益生菌株在养殖业的潜在应用前景。

[学术文献 ] Discovery of Toxin-Degrading Enzymes with Positive Unlabeled Deep Learning 进入全文

ACS Catalysis

Identifying functional enzymes for the catalysis of specific biochemical reactions is a major bottleneck in the de novo design of biosynthesis and biodegradation pathways. Conventional methods based on microbial screening and functional metagenomics require long verification periods and incur high experimental costs; recent data-driven methods apply only to a few common substrates. To enable rapid and high-throughput identification of enzymes for complex and less-studied substrates, we propose a robust enzyme’s substrate promiscuity prediction model based on positive unlabeled learning. Using this model, we identified 15 new degrading enzymes specific for the mycotoxins ochratoxin A and zearalenone, of which six could degrade >90% mycotoxin content within 3 h. We anticipate that this model will serve as a useful tool for identifying new functional enzymes and understanding the nature of biocatalysis, thereby advancing the fields of synthetic biology, metabolic engineering, and pollutant biodegradation.

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