Probiotic Lactobacillus johnsonii BS15 Promotes Growth Performance,Intestinal Immunity,and Gut Microbiota in Piglets

Probiotics and Antimicrobial Proteins - Numerous studies have investigated the beneficial effects of Lactobacillus johnsonii strain BS15 on mice and broilers. This study aimed to understand the...     

2种调查方法对四川黑竹沟国家级自然保护区3种雉类种群密度调查的比较

种群数量是物种的重要生态学基础资料,合适的密度调查方法是数量估算的基础。2016年4-5月,采用广泛应用于鸡形目Galliformes鸟类种群密度调查的样线法和样点法,调查了四川黑竹沟国家级自然保护区3种鸡形目鸟类(白腹锦鸡Chrysolophus amherstiae、红腹角雉Tragopan temminckii和血雉Ithaginis cruentus)的种群密度。样线法和样点法估算的雄体密度分别是:白腹锦鸡1.20只/km^2和(6.31±0.98)只/km^2,红腹角雉5.41只/km^2和(0.39±0.17)只/km^2,血雉3.01只/km^2和(5.97±2.70)只/km^2。除红腹角雉外,样点法估算的白腹锦鸡、血雉种群密度均大于样线法。建议针对不同鸡形目鸟类采用不同的调查方法,并尽量扩大样本数量,从而提高调查结果的准确性。     

Integrated analysis of ceRNA network and tumor-infiltrating immune cells in esophageal cancer

Background: Esophageal cancer (ESCA) is one of the most commonly diagnosed cancers in the world. Tumor immune microenvironment is closely related to tumor prognosis. The present study aimed at analyzing the competing endogenous RNA (ceRNA) network and tumor-infiltrating immune cells in ESCA.Methods: The expression profiles of mRNAs, lncRNAs, and miRNAs were downloaded from the Cancer Genome Atlas database. A ceRNA network was established based on the differentially expressed RNAs by Cytoscape. CIBERSORT was applied to estimate the proportion of immune cells in ESCA. Prognosis-associated genes and immune cells were applied to establish prognostic models basing on Lasso and multivariate Cox analyses. The survival curves were constructed with Kaplan–Meier method. The predictive efficacy of the prognostic models was evaluated by the receiver operating characteristic (ROC) curves.Results: The differentially expressed mRNAs, lncRNAs, and miRNAs were identified. We constructed the ceRNA network including 23 lncRNAs, 19 miRNAs, and 147 mRNAs. Five key molecules (HMGB3, HOXC8, HSPA1B, KLHL15, and RUNX3) were identified from the ceRNA network and five significant immune cells (plasma cells, T cells follicular helper, monocytes, dendritic cells activated, and neutrophils) were selected via CIBERSORT. The ROC curves based on key genes and significant immune cells all showed good sensitivity (AUC of 3-year survival: 0.739, AUC of 5-year survival: 0.899, AUC of 3-year survival: 0.824, AUC of 5-year survival: 0.876). There was certain correlation between five immune cells and five key molecules.Conclusion: The present study provides an effective bioinformatics basis for exploring the potential biomarkers of ESCA and predicting its prognosis.     

Post-translational modification of RNA m6A demethylase ALKBH5 regulates ROS-induced DNA damage response

Faithful genome integrity maintenance plays an essential role in cell survival. Here, we identify the RNA demethylase ALKBH5 as a key regulator that protects cells from DNA damage and apoptosis during reactive oxygen species (ROS)-induced stress. We find that ROS significantly induces global mRNA N⁶-methyladenosine (m⁶A) levels by modulating ALKBH5 post-translational modifications (PTMs), leading to the rapid and efficient induction of thousands of genes involved in a variety of biological processes including DNA damage repair. Mechanistically, ROS promotes ALKBH5 SUMOylation through activating ERK/JNK signaling, leading to inhibition of ALKBH5 m⁶A demethylase activity by blocking substrate accessibility. Moreover, ERK/JNK/ALKBH5-PTMs/m⁶A axis is activated by ROS in hematopoietic stem/progenitor cells (HSPCs) in vivo in mice, suggesting a physiological role of this molecular pathway in the maintenance of genome stability in HSPCs. Together, our study uncovers a molecular mechanism involving ALKBH5 PTMs and increased mRNA m⁶A levels that protect genomic integrity of cells in response to ROS.     

Independent component analysis based gene co-expression network inference (ICAnet) to decipher functional modules for better single-cell clustering and batch integration

With the tremendous increase of publicly available single-cell RNA-sequencing (scRNA-seq) datasets, bioinformatics methods based on gene co-expression network are becoming efficient tools for analyzing scRNA-seq data, improving cell type prediction accuracy and in turn facilitating biological discovery. However, the current methods are mainly based on overall co-expression correlation and overlook co-expression that exists in only a subset of cells, thus fail to discover certain rare cell types and sensitive to batch effect. Here, we developed independent component analysis-based gene co-expression network inference (ICAnet) that decomposed scRNA-seq data into a series of independent gene expression components and inferred co-expression modules, which improved cell clustering and rare cell-type discovery. ICAnet showed efficient performance for cell clustering and batch integration using scRNA-seq datasets spanning multiple cells/tissues/donors/library types. It works stably on datasets produced by different library construction strategies and with different sequencing depths and cell numbers. We demonstrated the capability of ICAnet to discover rare cell types in multiple independent scRNA-seq datasets from different sources. Importantly, the identified modules activated in acute myeloid leukemia scRNA-seq datasets have the potential to serve as new diagnostic markers. Thus, ICAnet is a competitive tool for cell clustering and biological interpretations of single-cell RNA-seq data analysis.     

Plant Growth-Promoting Effect of the Chitosanolytic Phosphate-Solubilizing Bacterium Burkholderia gladioli MEL01 After Fermentation with Chitosan and Fertilization with Rock Phosphate

Phosphate-solubilizing bacteria (PSB) are important plant growth-promoting rhizobacteria that can increase soil fertility through the solubilization of insoluble inorganic phosphate and organophosphorus. In this study, a PSB, Burkholderia gladioli MEL01, was isolated and identified from rice–wheat rotation rhizosphere soil. MEL01 had an excellent phosphate-solubilizing capacity (reaching 107.69 mg/L) toward insoluble inorganic phosphate rock phosphate. HPLC analysis revealed that the mechanism of phosphate solubilization of MEL01 was probably due to secreted oxalic acid and gluconic acid transformation of phosphate from insoluble to soluble. MEL01 also exhibited 4030 U/L specific chitosanase activity when cultured with chitosan fermentation medium. Interestingly, the chitosan hydrolysis product chitooligosaccharide could significantly enhance the MEL01 phosphate-solubilizing capacity. Pot experiments showed that MEL01 chitosan medium fermentation liquor (MCMFL) could promote improvement of soil available phosphorus and pakchoi growth when supplemented with phosphate rock phosphate as the phosphate fertilizer. In addition, pot experiments demonstrated that MCMFL could also promote the growth of wheat, which could decrease the amount of compound fertilizer used. Microbial diversity analysis showed that the genera Pseudomonas, Burkholderia, Mycoplana, and Cellvibrio were enriched, which might participate in synergetic phosphate solubilization. Therefore, after fermentation with chitosan and fertilization with rock phosphates, MEL01 has potential as a phosphate biofertilizer in ecological agricultural production.

     

新工科背景下生物反应工程课程的多元化教学模式 改革与探索

生物反应工程作为一门理论性与应用性都很强的专业课程,在生物工程等相关专业的课程设置中处于桥梁和纽带地位,对新型应用型工科人才的培养发挥着重要的作用。但由于该课程中公式等抽象理论知识过多,导致学生学习效率十分低下。因此,为了适应新工科教育背景下对创新型人才培养的需求,提高学生的学习兴趣和积极性,并培养学生的自主学习等创新能力,教学团队在课程教学中通过引入虚拟仿真技术、开展微课教学、采用案例式教学模式、利用科研平台等多元化方式,对该课程的教学模式、方法和手段尝试改革和探索,取得了一定的教学效果,并就此进行了一些探讨,以期能为相关课程的教学改革提供一些思路和启示。     

毛竹APX基因系统进化与表达分析

抗坏血酸过氧化物酶(aseorbate peroxidase, APX)是植物活性氧代谢中重要的抗氧化酶之一,尤其是叶绿体中清除H₂O₂的关键酶,也是维生素C代谢的主要酶类。该文基于生物信息学方法,利用毛竹的基因组及转录组数据鉴定毛竹中的APX基因家族成员,并对其编码的蛋白基本理化性质、基因结构、启动子元件、系统进化及共线性关系、重复串联基因、GO注释及表达模式进行综合分析,共鉴定出21种编码APX的基因。结果表明:(1)PeAPX基因家族成员多为不稳定疏水蛋白,基因结构、基序及结构域相对较为保守,大多数APX基因具有高度保守的内含子模式。(2)系统进化关系显示毛竹APX基因与水稻APX基因有着较高的同源性关系,PeAPX具有较高的进化保守性。(3)Ka/Ks分析表明PeAPX基因都经历了纯化选择压力,此外在每个APX基因的启动子序列中发现有许多与应激反应和植物激素相关的顺式作用元件,结合表达量分析,表明毛竹APX基因在毛竹生长发育中起着正向促进作用。该研究为进一步了解毛竹APX基因家族基本功能及其抗氧化机制提供了一定的参考,为毛竹APX基因功能的深层次鉴定提供了重要依据。