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[前沿资讯 ] 科学家发展AI赋能的蛋白质理性设计新方法 进入全文
科学网
华东理工大学生物反应器工程国家重点实验室教授郁惠蕾、许建和团队，利用人工智能（AI）赋能的蛋白质理性设计技术重塑了羧酸还原酶的活性中心，大幅提升羧酸还原酶的活性和底物专一性，并成功应用于尼龙6和尼龙66的单体（1,6-己二胺和6-氨基己酸）的生物合成中。相关研究发表于《科学进展》。 研究团队发展了AI赋能的蛋白质理性设计新方法，构建了基于近攻击构象概率和酶-底物结合能的物理模型，并利用Rosetta Design对活性中心多个位点的庞大组合突变体库进行了高效精准的设计和评价，实现了酶活性中心大范围协同突变的“功能重塑”。实验结果显示，人工设计的突变体酶对底物6-氨基己酸的催化效率提升101倍，对底物1,6-己二酸的催化效率提升14倍且底物专一性提高86倍。最终，由1,6-己二酸出发合成的尼龙前体6-氨基己酸和1,6-己二胺，生产强度分别达到文献报道最高值的13.3倍和12倍。
[前沿资讯 ] 学者构建安全高效微生物控制策略 进入全文
科学网
华南理工大学生物科学与工程学院教授熊伟团队与美国国家可再生能源实验室合作，开发出一种基于集群建模与CRISPR干扰（CRISPRi）的新型微生物控制策略。相关成果近日发表于《细胞系统》（Cell Systems）。 研究提出了一种全新的代谢稳健性调控方法。利用计算建模工具，预测并锁定了微生物核心代谢网络中的关键靶点，这些靶点对代谢网络的稳健性具有显著影响。通过CRISPR干扰技术，研究团队能够在实验中精准调控这些基因的表达，定量控制微生物适应度，抑制微生物的生长。 实验过程中，研究团队首先开发了一个基于“稳健性预测”的计算框架，通过模拟酶活性波动对代谢网络的影响，筛选出对稳健性最敏感的基因靶点，如大肠杆菌核心代谢网络中的磷酸果糖激酶、丙酮酸激酶等。得益于CRISPRi技术对调控效率的提升，实验中使用了精简版的Cas12m蛋白和经过优化的遗传绝缘体RiboJ，这种组合不仅大幅减少了基因回路的泄漏，还显著增强了多重基因调控的效率与稳定性。 为了确保安全性，研究还关注了多靶点调控，设计了单基因、多基因联合调控策略，证明通过同时靶向多个代谢稳健性关键节点，可以显著降低微生物逃逸的概率。例如，四重基因靶点（ppc、metE、ptsH和cysH）的CRISPRi设计在实验中表现出极强的生长抑制效果，其逃逸频率远低于当前公认的设定标准。 在多种实验室和自然环境模拟条件下，该系统均能保持较高的稳定性和安全性，在葡萄糖、甘油、乙酸等多种碳源条件的验证中始终有效。在经过长达数周的遗传稳定性测试后，仅观察到少量引导RNA突变，没有出现目标基因功能丧失的情况。研究团队还通过LuxR-AHL诱导系统开发了一种“关闭式”CRISPRi回路，在无诱导剂条件下，能够有效终止微生物的增殖，进一步提升了逃逸控制能力。
[学术文献 ] S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure 进入全文
Advanced Science
Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein functions and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences. However, the lack of crucial 3D structure information in most PLMs restricts the prediction capacity of PLMs in various applications, especially those heavily dependent on 3D structures. To address this issue, S-PLM is introduced as a 3D structure-aware PLM that utilizes multi-view contrastive learning to align the sequence and 3D structure of a protein in a coordinated latent space. S-PLM applies Swin-Transformer on AlphaFold-predicted protein structures to embed the structural information and fuses it into sequence-based embedding from ESM2. Additionally, a library of lightweight tuning tools is provided to adapt S-PLM for diverse downstream protein prediction tasks. The results demonstrate S-PLM's superior performance over sequence-only PLMs on all protein clustering and classification tasks, achieving competitiveness comparable to state-of-the-art methods requiring both sequence and structure inputs. S-PLM and its lightweight tuning tools are available at https://github.com/duolinwang/S-PLM/.
[学术文献 ] Mechanistic Insight into the Reproductive Toxicity of Trifloxystrobin in Male Sprague-Dawley Rats 进入全文
Environmental Science & Technology
Previous studies have demonstrated the reproductive toxicity of trifluorostrobin (TRI) in male organisms. However, the underlying mechanisms of TRI responsible for testicular damage and hormonal disruption remain elusive. This study elucidated the male reproductive toxicity of TRI at the molecular level under environmentally relevant concentrations and its associations with gut microbiota dysbiosis. The rats were administered TRI (1.5, 15, and 75 mg/kg of body weight/day) continuously via gavage for 90 days. Exposure to 15 mg/kg (below the no-observed adverse effect level (NOAEL) of 30 mg/kg) and 75 mg/kg TRI damaged testicular tissue, reduced sperm count, and lowered serum hormone and total cholesterol levels. Transcriptomics analysis combined with molecular docking simulations and cell proliferation assays showed that exposure to TRI led to testicular damage by inhibiting the expression of cholesterol receptor genes, which, in turn, disrupted steroid hormone biosynthesis. Furthermore, exposure to TRI resulted in a marked decline in the relative abundance of the probiotic bacteria. Consistently, significant reductions in the relative abundance of short-chain fatty acids (SCFAs), retinoic acids, and steroid hormones in the gut were observed. Additionally, a significant correlation was observed between the relative abundance of Parabacteroides and serum testosterone levels, a vital biomarker for reproductive toxicity monitoring. These findings shed light on the mode of action of TRI-induced male reproductive toxicity and highlight the link between testicular injury and gut microbiota.
[前沿资讯 ] 天津工业生物技术研究所在通过阻断几丁质合成酶表达提高菌丝蛋白转化率方面取得新进展 进入全文
中科院天津工业生物技术研究所
威尼斯镰刀菌在发酵生产真菌蛋白方面具有诸多显著优势，如营养丰富、安全性良好、能够可持续大规模生产等，因此被广泛应用于真菌肉类替代品及其他相关产品中。然而，利用天然菌株生产菌丝体蛋白时，存在转化率低、蛋白含量低等问题，这也导致了较高的生产成本。经研究团队前期研究发现，威尼斯镰刀菌菌丝中高膳食纤维含量是导致大量碳损失的关键因素之一，基于此，降低真菌细胞壁中膳食纤维的含量成为提高菌株转化效率的关键要点。 中国科学院天津工业生物技术研究所李德茂研究员带领的工业生物系统工程研究团队，以降低威尼斯镰刀菌菌丝体蛋白发酵生产中其细胞壁膳食纤维合成为突破口，通过生信分析与评估，对威尼斯镰刀菌中全部共12个几丁质合成酶基因进行了深入研究，精准地锁定了最有希望降低几丁质含量的基因并将其敲除，成功获得几丁质含量下降26%，菌体和蛋白转化率分别提高16%、36%的转化子。然后通过转录组分析，靶定以阻断副产物乙醇合成为主的丙酮酸代谢途径来进一步减少碳代谢流流失。最终使菌体和蛋白的转化率得到了进一步提升，菌体转化率提高了29%，蛋白转化率提高了40%。
[学术文献 ] Model-assisted CRISPRi/a library screening reveals central carbon metabolic targets for enhanced recombinant protein production in yeast 进入全文
Metabolic Engineering
Production of recombinant proteins is regarded as an important breakthrough in the field of biomedicine and industrial biotechnology. Due to the complexity of the protein secretory pathway and its tight interaction with cellular metabolism, the application of traditional metabolic engineering tools to improve recombinant protein production faces major challenges. A systematic approach is required to generate novel design principles for superior protein secretion cell factories. Here, we applied a proteome-constrained genome-scale protein secretory model of the yeast Saccharomyces cerevisiae (pcSecYeast) to simulate α-amylase production under limited secretory capacity and predict gene targets for downregulation and upregulation to improve α-amylase production. The predicted targets were evaluated using high-throughput screening of specifically designed CRISPR interference/activation (CRISPRi/a) libraries and droplet microfluidics screening. From each library, 200 and 190 sorted clones, respectively, were manually verified. Out of them, 50% of predicted downregulation targets and 34.6% predicted upregulation targets were confirmed to improve α-amylase production. By simultaneously fine-tuning the expression of three genes in central carbon metabolism, i.e. LPD1, MDH1, and ACS1, we were able to increase the carbon flux in the fermentative pathway and α-amylase production. This study exemplifies how model-based predictions can be rapidly validated via a high-throughput screening approach. Our findings highlight novel engineering targets for cell factories and furthermore shed light on the connectivity between recombinant protein production and central carbon metabolism.
