Chemogenomics approaches to novel target discovery

Chemogenomics involves the combination of a compound's effect on biological targets together with modern genomics technologies. The merger of these two methodologies is creating a new way to screen for compound-target interactions, as well as map chemical and biological space in a parallel fashion. The challenge associated with mining complex databases has initiated the development of many novel in silico tools to profile and analyze data in a systematic way. The ability to analyze the combinatorial effects of chemical libraries on biological systems will aid the discovery of new therapeutic entities. Chemogenomics provides a tool for the rapid validation of novel targeted therapeutics, where a specific molecular target is modulated by a small molecule. Along with targeted therapies comes the ability to discovery pathway nodes where a single molecular target might be an essential component of more than one disease. Several disease areas will benefit directly from the chemogenomics approach, the most advanced being cancer. A genetic loss-of-function screen can be modulated in the presence of a compound to search for genes or pathways involved in the compound's activity. Several recent papers highlight how chemogenomics is changing with RNA interference-based screening and shaping the discovery of new targeted therapies. Together, chemical and RNA interference-based screens open the door for a new way to discovery disease-associated genes and novel targeted therapies.     

Technique review: how to use RNA interference.

RNA interference (RNAi) has been rapidly adopted as a general method for inhibiting gene expression in most laboratory organisms. This paper discusses how libraries of RNAi reagents are being used to perform genome-wide reverse genetic screens in both model organisms and mammalian cells. Guidelines for designing effective small interfering RNAs and appropriate controls for mammalian RNAi experiments will also be discussed.     

Cellular phenotyping by RNAi.

A systematic characterization of genes with unknown function is a key challenge after the sequencing of the human genome and the genomes of many model organisms. High-throughput RNA-interference (RNAi) screenings have become a widely used approach in invertebrate model organisms and also promise to revolutionize cell biology in mammals. Genome-wide RNAi screens in Caenorhabditis elegans and Drosophila, and in a smaller scale in mammalian cells have proven to be a valuable and successful method for the dissection of diverse biological processes. A number of RNAi libraries have become available that rely on different technologies, such as long double-stranded (ds) RNAs, in vitro diced short-interfering (si) RNAs, synthetic siRNAs and short-hairpin (sh) RNAs, which all have specific advantages and disadvantages. In addition, progress in screening technologies and data analysis allows the adaptation of screening methods to analyse more complex cellular processes. This review will summarize strategies in combining genome-scale RNAi libraries, high-throughput screening technologies, integrated high-content data analysis and will discuss future challenges.     

Screening of siRNA target sequences by using fragmentized DNA

BACKGROUND: RNA interference (RNAi) has become a powerful tool in silencing target genes in various organisms. In mammals, RNAi can be induced by using short interfering RNA (siRNA). The efficacy of inducing RNAi in mammalian cells by using siRNA depends very much on the selection of the target sequences. METHODS: We developed an siRNA target sequence selection system by first constructing parallel-type siRNA expression vector libraries carrying siRNA expression fragments originating from fragmentized target genes, and then using a group selection system. For a model system, we constructed parallel-type siRNA expression vector libraries against DsRed and GFP reporter genes. RESULTS: We carried out the first screening of groups containing more than 100 random siRNA expression plasmids in total for each target gene, and successfully obtained target sequences with very strong efficacy. Furthermore, we also obtained some clones that express dsRNAs of various lengths that might induce cytotoxicity. CONCLUSIONS: This system should allow us to perform screening for powerful target sequences, by including all possible target sequences for any gene, even without knowing the whole sequence of the target gene in advance. At the same time, target sequences that should be avoided due to cytotoxicity can be identified.     

Functional genomics and target validation approaches using antisense oligonucleotide technology

The recent increase in the amount and rate of accumulation of genomic information has created new challenges for the pharmaceutical industry. These include how best to rapidly and efficiently identify key genes responsible for complex disease phenotypes and how to use this information to develop new and specific classes of drugs. Antisense technology offers a powerful approach to identify novel cellular networks and signaling "cassettes" and provides a method to validate genes in vivo as attractive drug targets.     

高通量分析技术在资源微生物及功能基因发掘中的应用

随着新的微生物资源不断被发现以及微生物基因组测序数据的积累和完善,目前研究重点和难点是如何从大量数据中快速发现和鉴定与微生物重要表型相关的功能基因,这就需要高通量的分析研究手段,主要涉及建库和筛选两个主要技术单元。其中,建库是指构建能够覆盖微生物全基因组的突变或干扰文库,所涉及的技术包括宏基因组、转座子插入突变、RNA干扰(RNA interference,RNAi)、反转录子文库重组工程(retron library recombineering,RLR)、CRISPR抑制(CRISPRi)和CRISPR激活(CRISPRa)等。筛选则是通过某种胁迫压力来促使文库菌群的差异化生长,并结合高通量测序全面发掘与特定表型相关的功能基因,从而为后续研究提供有效信息。本文对功能基因组学研究中现有的高通量分析技术进行了梳理、总结和展望,以期为这类技术方法的拓展、优化以及应用提供参考。     

Recent novel approaches for population genomics data analysis

Next‐generation sequencing (NGS) technology is revolutionizing the fields of population genetics, molecular ecology and conservation biology. But it can be challenging for researchers to learn the new and rapidly evolving techniques required to use NGS data. A recent workshop entitled ‘Population Genomic Data Analysis’ was held to provide training in conceptual and practical aspects of data production and analysis for population genomics, with an emphasis on NGS data analysis. This workshop brought together 16 instructors who were experts in the field of population genomics and 31 student participants. Instructors provided helpful and often entertaining advice regarding how to choose and use a NGS method for a given research question, and regarding critical aspects of NGS data production and analysis such as library preparation, filtering to remove sequencing errors and outlier loci, and genotype calling. In addition, instructors provided general advice about how to approach population genomics data analysis and how to build a career in science. The overarching messages of the workshop were that NGS data analysis should be approached with a keen understanding of the theoretical models underlying the analyses, and with analyses tailored to each research question and project. When analysed carefully, NGS data provide extremely powerful tools for answering crucial questions in disciplines ranging from evolution and ecology to conservation and agriculture, including questions that could not be answered prior to the development of NGS technology.     

Innovative approaches to novel antibacterial drug discovery

Increasing antibiotic resistance in microorganisms and new emerging pathogens have become a major problem in our society. Rising to satisfy this urgent medical need is a recent confluence of powerful new drug discovery technologies: combinatorial chemistry; sequence and functional genomic analysis; and novel methods of high-throughput screening. The combination of these technologies will bring to bear untapped power in the search for new antimicrobials.     

A novel system for rapid screening of effective siRNA target sites by one step transfection with a single vector

siRNA technique has been widely used to study the gene functions and to develop disease therapeutics. One of the challenges of RNAi application is to obtain the most effective target specific siRNA sequences. Currently the process to select and validate optimal siRNA sites for a given gene, which is usually based on screening by using Western blot, Northern blot or Q-PCR, remains empirical and time consuming. Although few fluorescence-based siRNA sequence selection systems have proven useful, the rapid and efficient screening of siRNA target sites is still challenging. In the paper, we developed a quick and efficient method to screen siRNA target sites with a novel single vector system, which contains the following cassettes: (1) an eGFP reporter gene expression cassette followed by a multiple cloning site and SV40 pA for insertion of a target sequence; (2) siRNA expression cassette containing a dual PoI III promoter driving in opposite directions; and (3) an internal loading control, mCherry reporter gene. Based on this one-step transfection with single vector system, we could rapidly screen effective, target specific siRNA fragments in an unbiased manner by judging the fluorescence intensity ratio of eGFP to mCherry. The generation of this novel vector system will promote the application of siRNA in basic research and disease therapy.     

多肽配体技术在植物功能基因组学中的应用前景

人工智能配体或适配体(Aptamer)技术是近年来兴起的一项特异性极强的基因干扰技术。通过人工合成特异的智能配体结合靶基因的蛋白产物, 达到特异干扰靶基因的生物学功能, 这是人工智能配体技术的基本设想。文章综述了多肽配体(Peptide aptamer)技术在基因功能验证中的主要进展, 着重阐明它在植物基因功能验证和作物抗病毒育种中的应用前景, 并提出克服该技术主要风险对策。     

基因组信息的整合与植物功能基因组学研究的策略

近年来,随着许多植物基因组测序和可利用序列的增加,相继建立了一些基于靶基因诱变的“反向”遗传学研究策略,如T—DNA诱变、基因敲除、基因沉默和超表达分析等。同时,DNA微阵列和基因芯片技术的发展使得快速、定量检测植物发育不同时期和不同组织器官的基因转录时空变化成为现实。作图技术的改进和来自不同物种基因组信息的整合也正在加速图谱克隆程序的简化和发展。因此,随着生物基因组测序工作日益增多,整合不同类群植物基因组的信息和资源,在植物功能基因组学研究中的重要性日趋显著。     

Functional consequences of RNA interference targeting COMMD1 in a canine hepatic cell line in relation to copper toxicosis

A deletion in the copper metabolism (Murr1) domain containing 1 (COMMD1) gene is associated with hepatic copper toxicosis in dogs, yet evidence of copper retention in COMMD1-depleted hepatic cells has not been shown. In a dog hepatic cell line, we analysed the copper metabolic functions after an 80% (mRNA and protein) COMMD1 reduction with COMMD1-targeting siRNAs. Exposure to 64Cu resulted in a significant increase in copper retention in COMMD1-depleted cells. COMMD1-depleted cells were almost three times more sensitive to high extracellular copper concentrations. Copper-mediated regulation of metallothionein gene expression was enhanced in COMMD1-depleted cells. Based on the increased copper accumulation and enhanced cellular copper responses upon COMMD1 reduction, we conclude that COMMD1 has a major regulatory function for intracellular copper levels in hepatic cells.     

Analysis of multiple compound–protein interactions reveals novel bioactive molecules

The discovery of novel bioactive molecules advances our systems‐level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound–protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Herein, we demonstrate that machine learning of multiple CPIs can not only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold‐hopping compounds. Through a machine‐learning technique that uses multiple CPIs, we have successfully identified novel lead compounds for two pharmaceutically important protein families, G‐protein‐coupled receptors and protein kinases. These novel compounds were not identified by existing computational ligand‐screening methods in comparative studies. The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.     

RNA干扰文库及其在功能基因组学研究中的应用

随着人类基因组大规模测序的完成,下一步的挑战是了解每一个基因的功能 . RNA 干扰文库为大规模基因功能筛选提供了可能 . 虽然用于线虫等模式生物的 RNAi 文库,已经证明是大规模基因功能筛选的有效方法,但这些文库不能用于高等动物的细胞 . 自 2003 年以来,用于人的细胞和哺乳动物细胞的 RNAi 文库取得了突破,相继出现构建已知基因 RNAi 文库和构建随机 RNAi 文库的报道,并成功地应用于大规模基因功能的筛选 . RNAi 文库作为一种简单、高效、大规模、高通量的功能基因组学研究的工具,将在基因功能研究、发现新的药物靶基因、发现疾病相关基因等方面有广阔的应用前景 .     

High-throughput RNAi in Caenorhabditis elegans: genome-wide screens and functional genomics

The phenomenon of RNA-mediated interference (RNAi) was first discovered in the nematode Caenorhabditis elegans, in which introduction of double-stranded RNA causes specific inactivation of genes with corresponding sequences. Technical advances in RNAi methodology and the availability of the complete genome sequence have enabled the high-throughput, genome-wide RNAi analysis of this organism. Several groups have used large-scale RNAi to systematically examine every C. elegans gene for knock-down phenotypes, providing basal information to be mined in more detailed studies. Now, in addition to functional genomic RNAi analyses, high-throughput RNAi is also routinely used for rapid, genome-wide screens for genes involved in specific biological processes. The integration of high-throughput RNAi experiments with other large-scale data, such as DNA microarrays and protein-protein interaction maps, enhances the speed and reliability of such screens. The accumulation of RNAi phenotype data dramatically accelerates our understanding of this organism at the genetic level.     

Progress in functional genomics approaches to antifungal drug target discovery

Antifungal drug discovery is starting to benefit from the enormous advances in the genomics field, which have occurred in the past decade. As traditional drug screening on existing targets is not delivering the long-awaited potent antifungals, efforts to use novel genetics and genomics-based strategies to aid in the discovery of novel drug targets are gaining increased importance. The current paradigm in antifungal drug target discovery focuses on basically two main classes of targets to evaluate: genes essential for viability and virulence or pathogenicity factors. Here we report on recent advances in genetics and genomics-based technologies that will allow us not only to identify and validate novel fungal drug targets, but hopefully in the longer run also to discover potent novel therapeutic agents. Fungal pathogens have typically presented significant obstacles when subjected to genetics, but the creativity of scientists in the anti-infectives field and the cross-talk with scientists in other areas is now yielding exciting new tools and technologies to tackle the problem of finding potent, specific and non-toxic antifungal therapeutics.     

The Application of Reverse Genetics to Polyploid Plant Species

Polyploidy events (polyploidization) followed by progressive loss of redundant genome components are a major feature of plant evolution, with new evidence suggesting that all flowering plants possess ancestral genome duplications. Furthermore, many of our most important crop plants have undergone additional, relatively recent, genome duplication events. Recent advances in DNA sequencing have made vast amounts of new genomic data available for many plants, including a range of important crop species with highly duplicated genomes. Along with assisting traditional forward genetics approaches to study gene function, this wealth of new sequence data facilitates extensive reverse genetics-based functional analyses. However, plants featuring high levels of genome duplication as a result of recent polyploidization pose additional challenges for reverse genetic analysis. Here we review reverse genetic analysis in such polyploid plants and highlight key challenges.