Sequence analysis and rule development of predicting protein stability change upon mutation using decision tree model

Understanding the mechanism of the protein stability change is one of the most challenging tasks. Recently, the prediction of protein stability change affected by single point mutations has become an interesting topic in molecular biology. However, it is desirable to further acquire knowledge from large databases to provide new insights into the nature of them. This paper presents an interpretable prediction tree method (named iPTREE-2) that can accurately predict changes of protein stability upon mutations from sequence based information and analyze sequence characteristics from the viewpoint of composition and order. Therefore, iPTREE-2 based on a regression tree algorithm exhibits the ability of finding important factors and developing rules for the purpose of data mining. On a dataset of 1859 different single point mutations from thermodynamic database, ProTherm, iPTREE-2 yields a correlation coefficient of 0.70 between predicted and experimental values. In the task of data mining, detailed analysis of sequences reveals the possibility of the compositional specificity of residues in different ranges of stability change and implies the existence of certain patterns. As building rules, we found that the mutation residues in wild type and in mutant protein play an important role. The present study demonstrates that iPTREE-2 can serve the purpose of predicting protein stability change, especially when one requires more understandable knowledge.     

Synthetic biology and metabolic engineering of actinomycetes for natural product discovery

Actinomycetes are one of the most valuable sources of natural products with industrial and medicinal importance. After more than half a century of exploitation, it has become increasingly challenging to find novel natural products with useful properties as the same known compounds are often repeatedly re-discovered when using traditional approaches. Modern genome mining approaches have led to the discovery of new biosynthetic gene clusters, thus indicating that actinomycetes still harbor a huge unexploited potential to produce novel natural products. In recent years, innovative synthetic biology and metabolic engineering tools have greatly accelerated the discovery of new natural products and the engineering of actinomycetes. In the first part of this review, we outline the successful application of metabolic engineering to optimize natural product production, focusing on the use of multi-omics data, genome-scale metabolic models, rational approaches to balance precursor pools, and the engineering of regulatory genes and regulatory elements. In the second part, we summarize the recent advances of synthetic biology for actinomycetal metabolic engineering including cluster assembly, cloning and expression, CRISPR/Cas9 technologies, and chassis strain development for natural product overproduction and discovery. Finally, we describe new advances in reprogramming biosynthetic pathways through polyketide synthase and non-ribosomal peptide synthetase engineering. These new developments are expected to revitalize discovery and development of new natural products with medicinal and other industrial applications.     

Prediction of GPCR-G protein coupling specificity using features of sequences and biological functions

Understanding the coupling specificity between G protein-coupled receptors （GPCRs） and specific classes of G proteins is important for further elucidation of receptor functions within a cell. Increasing information on GPCR sequences and the G protein family would facilitate prediction of the coupling properties of GPCRs. In this study, we describe a novel approach for predicting the coupling specificity between GPCRs and G proteins. This method uses not only GPCR sequences but also the functional knowledge generated by natural language processing, and can achieve 92.2% prediction accuracy by using the C4.5 algorithm. Furthermore, rules related to GPCR-G protein coupling are generated. The combination of sequence analysis and text mining improves the prediction accuracy for GPCR-G protein coupling specificity, and also provides clues for understanding GPCR signaling.     

放线菌来源的羊毛硫肽研究进展

羊毛硫肽(lanthipeptide)是一类由核糖体合成并经翻译后修饰的含羊毛硫氨酸或β-甲基羊毛硫氨酸的多肽。近年来,放线菌来源的羊毛硫肽因其突出的抗菌活性和罕见的生物活性而备受关注。本文重点对放线菌来源的不同类型的羊毛硫肽的结构特征及其特性进行了综述,讨论了生物或化学方法修饰天然羊毛硫肽和基因组挖掘发现结构新颖的羊毛硫肽在开发符合实际应用需求的放线菌来源的羊毛硫肽中的应用,并对放线菌来源的羊毛硫肽的应用潜力进行了总结和展望。     

北方粳稻品种识别数据库系统的设计

为借助Internet技术进行数据的共享以及开发一套基于DNA指纹信息来识别粳稻品种的计算机功能平台,设计一套北方粳稻品种识别数据库系统。根据该数据库的设计所包含的信息含量,确定本数据库包含的四个表,并根据功能需求分析,设计了用户管理,北方粳稻DNA指纹数据管理,粳稻DNA指纹查询与粳稻品种识别分析四个功能模块,同时设计了该系统的界面设计图,为北方粳稻品种识别数据库系统的构建奠定基础。     

农林院校生物信息学专业数据库技术课程教学改革刍议

生物信息学是一门交叉学科,对于现代生物学研究具有重要的意义。数据库技术是生物信息学的基础之一。本文对农林院校的生物信息学专业的数据库技术课程的教学现状做了一些介绍,对目前生物信息专业数据库教学存在的问题进行了分析。结合教学的实践,有针对性的提出了一些教学改革的具体措施。     

Microbial cycling of iron and sulfur in sediments of acidic and pH-neutral mining lakes in Lusatia (Brandenburg, Germany)

A vast number of lakes developed in the abandoned opencast lignite mines of Lusatia (East Germany) contain acidic waters (mmolSm^–2a^–). Potential Fe(III) reduction measured by the accumulation of Fe(II) during anoxic incubation yielded similar rates in both types of sediments, however, the responses towards the supplementation of Fe(III) and organic carbon were different. Sulfate reduction rates estimated with ³⁵S-radiotracer were much lower in the slightly acidic sediment than in the pH-neutral sediment (156 v.s. 738mmolSO₄ ^2–m^–2a^–1). However, sulfate reduction rates were increased by the addition of organic carbon. Severe limitation of sulfate-reducing bacteria under acidic conditions was also reflected by low most probable numbers (MPN). High MPN of acidophilic iron- and sulfur-oxidizing bacteria in acidic sediments indicated a high reoxidation potential. The results show that potentials for reductive processes are present in acidic sediments and that these are determined mainly by the availability of oxidants and organic matter.     

Two-dimensional gel electrophoresis database of murine R1 embryonic stem cells

Embryonic stem (ES) cell lines represent a population of undifferentiated pluripotent cells capable of multilineage differentiation in vitro. Although very useful for studying developmental processes, human ES cell lines have also been suggested as a potential and unlimited source for cellular transplantation and the treatment of human disease. The proteomic basis of embryonic stemness (pluripotentiality and multilineage differentiation) and the transitions that lead to specific cell lineages however, remain to be defined. As an important first step in defining these processes, we have performed a proteomic analysis of undifferentiated mouse R1 ES cell lines using pH 3-10, 4-7 and 6-11 two-dimensional electrophoresis gels, matrix-assisted laser desorption/ionization and tandem mass spectrometry. Of the 700 gel spots analyzed, 241 distinct protein species were identified corresponding to 218 unique proteins, with a significant proportion functionally related to protein expression.     

Bioinformatic Mining of Type I Microsatellites from Expressed Sequence Tags of Channel Catfish (<Emphasis Type="Italic">Ictalurus punctatus</Emphasis>)

Gene-derived markers are pivotal to the analysis of genome structure, organization, and evolution and necessary for comparative genomics. However, gene-derived markers are relatively difficult to develop. This project utilized the genomic resources of channel catfish expressed sequence tags (ESTs) to identify simple sequence repeats (SSRs), or microsatellites. It took the advantage of ESTs for the establishment of gene identities, and of microsatellites for the acquisition of high polymorphism. When microsatellites are tagged to genes, the microsatellites can then be used as gene markers. A bioinformatic analysis of 43,033 ESTs identified 4855 ESTs containing microsatellites. Cluster analysis indicated that 1312 of these ESTs fell into 569 contigs, and the remaining 3534 ESTs were singletons. A total of 4103 unique microsatellite-containing genes were identified. The dinucleotide CA/TG and GA/TC pairs were the most abundant microsatellites. AT-rich microsatellite types were predominant among trinucleotide and tetranucleotide microsatellites, consistent with our earlier estimation that the catfish genome is highly AT-rich. Our preliminary results indicated that the majority of the identified microsatellites were polymorphic and, therefore, useful for genetic linkage mapping of catfish. Mapping of these gene-derived markers is under way, which will set the foundation for comparative genome analysis in catfish.     

The evidential value in the DNA database search controversy and the two-stain problem

Summary . Does the evidential strength of a DNA match depend on whether the suspect was identified through database search or through other evidence (“probable cause”)? In Balding and Donnelly (1995, Journal of the Royal Statistical Society, Series A 158, 21–53) and elsewhere, it has been argued that the evidential strength is slightly larger in a database search case than in a probable cause case, while Stockmarr (1999 , Biometrics 55, 671–677) reached the opposite conclusion. Both these approaches use likelihood ratios. By making an excursion to a similar problem, the two‐stain problem, we argue in this article that there are certain fundamental difficulties with the use of a likelihood ratio, which can be avoided by concentrating on the posterior odds. This approach helps resolving the above‐mentioned conflict.