Utilizing the power of microbial genetics to bridge the gap between the promise and the application of marine natural products

Marine organisms are a rich source of secondary metabolites. They have yielded thousands of compounds with a broad range of biomedical applications. Thus far, samples required for preclinical and clinical studies have been obtained by collection from the wild, by mariculture, and by total chemical synthesis. However, for a number of complex marine metabolites, none of these options is feasible for either economic or environmental reasons. In order to proceed with the development of many of these promising therapeutic compounds, a reliable and renewable source must be found. Over the last twenty years, the study of microbial secondary metabolites has greatly advanced our understanding of how nature utilizes simple starting materials to yield complex small molecules. Much of this work has focused on polyketides and nonribosomal peptides, two classes of molecules that are prevalent in marine micro- and macroorganisms. The lessons learned from the study of terrestrial metabolite biosynthesis are now being applied to the marine world. As techniques for cloning and heterologous expression of biosynthetic pathways continue to improve, they may provide our greatest hope for bridging the gap between the promise and application of many marine natural products.     

PATTERN MINING AND DISCOVERY ORIENTED TO ARTIFICIAL LIFE

１ＩＮＴＲＯＤＵＣＴＩＯＮＰａｔｅｒｎｍｉｎｉｎｇａｎｄｄｉｓｃｏｖｅｒｙｉｓｏｎｅｏｆｔｈｅｅｍｅｒｇｉｎｇｂｒａｎｃｈｅｓｏｆＫＤＤ（ＫｎｏｗｌｅｄｇｅＤｉｓｃｏｖｅｒｙｉｎＤａｔａｂａｓｅ）ｗｈｉｃｈｉｓａｐｒｏｍｉｓｉｎｇｆｉｅｌｄｏｆｔｈ...     

计算机科学在生物信息学中的应用

生物信息学是一门新兴的交叉学科,计算机科学如何更快更好地发挥其在生物信息学中的作用是我国的广大计算机研究和开发人员面临的一个重要的新课题。本文通过对计算机在生物信息学中的若干应用的现状分析与前景展望,为计算研究人员如何寻找计算机科学在生物信息学中的切入点提供了某些启示。     

生命科学的春天

由于中、美、英、法、日、德等六国科学家的共同努力,启动于1990年的人类基因组计划(HGP)在2000年6月完成了遗传图、物理图、序列图(工作框架)．并于2001年2月12日公布了对人类的基因组(由31．674亿个碱基对组成,含有3万到4万个结构基因)的分析．这表明了人类结构基因组计划已初步完成,并启动了后基因组(也即功能基因组)计划．以揭示人类的出生、年龄、疾病和死亡的秘密．首先．HGP促进了医学领域的进步．基因识别、基因治疗、基因药品以及药物基因组学渗透到了医学的每个角落．通过分子生物学诊断和治疗人类疾病将成为普通的临床实践．人类主宰自己命运的梦想将成为现实,人们将健康而长寿的生活．比较基因组学是另一个得益于HGP的平稳运行和成功的领域．迄今为止已对200多种生物物种绘制了精度不同的遗传图和物理图,其中一些已经完成了整个基因序列和遗传密码翻译．特别是与人类生活联系紧密的经济类动植物．动植物基因项目的完成将为高质高产地培养繁殖物种提供分子基础和方法．同时,随着比较基因组学的进步．一些关系到生物分类和进化的疑点将得以解决．生命科学所迈出的科技发展的第一步已庄严地展现在人们面前．通过生物工业使我们的国家繁荣昌盛是人们的共同目标．21世纪是生命科学的世纪,生命科学的春天将鼓舞每一个从事生命科学研究的科学工作者奋勇向前,充分施展自己的才华．迎接未来的挑战．     

Polar Mapper: a computational tool for integrated visualization of protein interaction networks and mRNA expression data

Polar Mapper is a computational application for exposing the architecture of protein interaction networks. It facilitates the system-level analysis of mRNA expression data in the context of the underlying protein interaction network. Preliminary analysis of a human protein interaction network and comparison of the yeast oxidative stress and heat shock gene expression responses are addressed as case studies.     

Prostate Cancer Radiogenomics—From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.     

Four-Dimensional Chromosome Structure Prediction

Chromatin conformation plays an important role in a variety of genomic processes, including genome replication, gene expression, and gene methylation. Hi-C data is frequently used to analyze structural features of chromatin, such as AB compartments, topologically associated domains, and 3D structural models. Recently, the genomics community has displayed growing interest in chromatin dynamics. Here, we present 4DMax, a novel method, which uses time-series Hi-C data to predict dynamic chromosome conformation. Using both synthetic data and real time-series Hi-C data from processes, such as induced pluripotent stem cell reprogramming and cardiomyocyte differentiation, we construct smooth four-dimensional models of individual chromosomes. These predicted 4D models effectively interpolate chromatin position across time, permitting prediction of unknown Hi-C contact maps at intermittent time points. Furthermore, 4DMax correctly recovers higher order features of chromatin, such as AB compartments and topologically associated domains, even at time points where Hi-C data is not made available to the algorithm. Contact map predictions made using 4DMax outperform naïve numerical interpolation in 87.7% of predictions on the induced pluripotent stem cell dataset. A/B compartment profiles derived from 4DMax interpolation showed higher similarity to ground truth than at least one profile generated from a neighboring time point in 100% of induced pluripotent stem cell experiments. Use of 4DMax may alleviate the cost of expensive Hi-C experiments by interpolating intermediary time points while also providing valuable visualization of dynamic chromatin changes.     

乳杆菌噬菌体基因组学研究进展

随着乳杆菌在乳品工业中的广泛应用,噬菌体污染对终产品造成的严重威胁日益增加。目前,噬菌体相关研究已从最初的形态学进入到了分子水平。许多噬菌体的全基因组测序工作已经完成。基因组研究有助于揭示噬菌体侵染宿主的机制,能挖掘其关键功能基因。本文基于乳杆菌噬菌体的基因组信息对主要乳杆菌噬菌体基因组的特征、功能基因组及比较基因组进行了分析和概述,为进一步研究噬菌体提供理论依据。