Genome-wide RNAi as a route to gene function in Drosophila.

With the sequencing of the human genome and the genomes of most major model organisms completed, the systematic characterisation of gene functions remains a key challenge. During the past few years, RNA interference (RNAi) has become a powerful tool to silence the expression of genes and analyse their loss-of-function phenotype when mutant alleles are not available. Genome-wide RNAi screens against all predicted genes have been successfully used to dissect a variety of biological processes in Caenorhabditis elegans. Recently, a genome-wide library of double-stranded RNAs, that target every gene in the Drosophila genome and that is suitable for high throughput cell-based assays, was published. In this paper, recent advances will be summarised. Screening strategies and applications as a route to comprehensively characterising gene function will be discussed.     

A novel quantitative proteomics strategy to study phosphorylation-dependent peptide-protein interactions

Phosphorylation-dependent protein-protein interactions provide the mechanism for a large number of intracellular signal transduction pathways. One of the goals of signal transduction research is to understand more precisely the nature of these phosphorylation-dependent interactions. Here, we report a novel strategy based on quantitative proteomics that allows for the rapid analysis of peptide-protein interactions with more than one phosphorylation site involved. The phosphorylation of two tyrosine residues, Y342 and Y346, within the linker B region of the protein-tyrosine kinase Syk is important for optimal signaling from the B cell receptor for antigen. We employed four amino-specific, isobaric reagents to differentially label proteins interacting in vitro with four Syk peptides containing none, one, or two phosphates on tyrosine residues Y342 and Y346, respectively. In total, 76 proteins were identified and quantified, 11 of which were dependent on the phosphorylation of individual tyrosine residues. One of the proteins, peroxiredoxin 1, preferably bound to phosphorylated Y346, which was further verified by Western blotting results. Thus, we demonstrate that the use of 4-fold multiplexing allows for relative protein measurements simultaneously for the identification of interacting proteins dependent on the phosphorylation of specific residues.     

Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics

BACKGROUND: Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. RESULTS: Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. CONCLUSION: The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings.     

Advances in quantitative proteomics

Large-scale protein quantification has become a major proteomics application in many areas of biological and medical research. During the past years, different techniques have been developed, including gel-based such as differential in-gel electrophoresis (DIGE) and liquid chromatography-based such as isotope labeling and label-free quantification. These quantitative proteomics tools hold significant promise for biomarker discovery, diagnostic and therapeutic applications. They are also important for research in functional genomics and systems biology towards basic understanding of molecular networks and pathway interactions. In this review, we summarize current technologies in quantitative proteomics and discuss recent applications of the technologies.     

Screening for gene function in chicken embryo using RNAi and electroporation

In the postgenomic era the elucidation of the physiological function of genes has become the rate-limiting step in the quest to understand the development and function of living organisms. Gene functions cannot be determined by high-throughput methods but require analysis in the context of the entire organism. This is particularly true in the developing vertebrate nervous system. Because of its easy accessibility in the egg, the chicken embryo has been the model of choice for developmental in vivo studies. However, its usefulness has been hampered by a lack of methods for genetic manipulation. Here we describe an approach that could compensate for this disadvantage. By combining gene silencing by dsRNA (through RNA interference, RNAi) with in ovo electroporation, we developed an efficient method to induce loss of gene function in vivo during the development of the chicken CNS. This method opens new possibilities for studying gene function not only by gain-of-function but also by loss-of-function approaches and therefore represents a new tool for functional genomics.     

Genome-wide screening for gene function using RNAi in mammalian cells

Mammalian genome sequencing has identified numerous genes requiring functional annotation. The discovery that dsRNA can direct gene-specific silencing in both model organisms and mammalian cells through RNA interference (RNAi) has provided a platform for dissecting the function of independent genes. The generation of large-scale RNAi libraries targeting all predicted genes within mouse, rat and human cells, combined with the large number of cell-based assays, provides a unique opportunity to perform high-throughput genetics in these complex cell systems. Many different formats exist for the generation of genome-wide RNAi libraries for use in mammalian cells. Furthermore, the use of these libraries in either genetic screens or genetic selections allows for the identification of known and novel genes involved in complex cellular phenotypes and biological processes, some of which underpin human disease. In this review, we examine genome-wide RNAi libraries used in model organisms and mammalian cells and provide examples of how these information rich reagents can be used for determining gene function, discovering novel therapeutic targets and dissecting signalling pathways, cellular processes and complex phenotypes.     

Large-scale analysis of gene function in Caenorhabditis elegans by high-throughput RNAi

Genome-wide analysis of gene function is essential for the post-genome era, and development of efficient and economical technology suitable for it has been in demand. Here we report a large-scale inactivation of the expressed genes in the nematode Caenorhabditis elegans. For this purpose, we have established a high-throughput "RNAi-by-soaking" methodology by modifying the conventional RNAi method [1, 2]. A set of tag-sequenced, nonredundant cDNAs corresponding to approximately 10,000 genes [3] (representing half of the predicted genes [4]) was used for the systematic RNAi analysis. We have processed approximately 2500 genes to date. In development, 27% of them showed detectable phenotypes, such as embryonic lethality, post-embryonic lethality, sterility, and morphological abnormality. Of these, we analyzed the phenotypes of F1 sterility in detail, and we have identified 24 genes that might play important roles in germline development. Combined with the ongoing analysis of expression patterns of these cDNAs [3, 5], the functional information obtained in this work will provide a starting point for the further analysis of each gene. Another finding from this screening is that the incidence of essential genes is significantly lower in the X chromosome than in the autosomes.     

A proteome catalog of Drosophila melanogaster: an essential resource for targeted quantitative proteomics

Proteomic analyses are critically important for systems biology because important aspects related to the structure, function and control of biological systems are only amenable by direct protein measurements. It has become apparent that the current proteomics technologies are unlikely to allow routine, quantitative measurements of whole proteomes. We have therefore suggested and largely implemented a two-step strategy for quantitative proteome analysis. In a first step, the discovery phase, the proteome observable by mass spectrometry is extensively analyzed. The resulting proteome catalog can then be used to select peptides specific to only one protein, so-called proteotypic peptides (PTPs). It represents the basis to realize sensitive, robust and reproducible measurements based on targeted mass spectrometry of these PTPs in a subsequent scoring phase. In this Extra View we describe the need for such proteome catalogs and their multiple benefits for catalyzing the shift towards targeted quantitative proteomic analysis and beyond. We use the Insulin signaling cascade as a representative example to illustrate the limitations of currently used proteomics approaches for the specific analysis of individual pathway components, and describe how the recently published Drosophila proteome catalog already helped to overcome many of these limitations.     

The methods of quantitative proteomics

In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and funciotnal homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.     

The use of centrifugation to study early Drosophila embryogenesis

By the end of 10th nuclear cycle, the somatic nuclei of the Drosophila embryo have migrated to the periphery of the egg. Centrifugation of embryos did not result in the displacement of these nuclei, since cytoskeletal elements anchor them to the cortex. But, mild centrifugal forces displace the centrally located, nascent yolk nuclei. If this increased sensitivity to hypergravity occurs before the beginning of nuclear differentiation during cycle 8, when the nascent yolk and somatic nuclei physically separate, then it would mark the earliest functional difference between these two lineages.     

The use of comparative quantitative proteomics analysis in rice grain-filling in determining response to moderate soil drying stress

Moderate soil drying (MSD) stress at the grain filling stage can improve grain filling efficiently and thus increase grain yield. To elucidate the molecular response of grain filling to MSD stress, a labeling LC-based quantitative proteomics approach using tandem mass tags was applied to determine the changes in leaf and grain protein abundance level at 15 days after flowering. A total of 2109 leaf proteins and 3220 grain proteins were detected, and 251 leaf proteins and 220 grain proteins were differentially expressed under MSD stress. Based on MapMan ontology, differentially expressed proteins in leaf and grain were categorized within 22 and 18 functional categories, respectively. The patterns observed were interesting in that in some categories such as photosynthesis-related protein in leaf and cell division related proteins in grain showed higher expression abundant under MSD stress, which facilities increasing the source supply and sink size. In other categories, such as carbohydrate metabolism and mitochondrial electron transport, surprisingly showed a completely different expression pattern between leaf and grain under MSD stress, which led to faster and better remobilization of carbon from leaf to grain. Additionally, the complicated functional network including the small GTP-binding proteins, calmodulin, and 14-3-3 proteins play an important role in regulation carbon remobilization mediated by the stressful signals from soil after rice plants were treated with MSD at grain-filling stage. The findings provide theoretical evidence for better quality control and scientific improvement of rice in practice.     

Simple RNAi vectors for stable and transient suppression of gene function in rice

Since the recent sequencing of the rice genome, the functional identification of rice genes has become increasingly important. Various tagged lines have been generated; however, the number of tagged genes available is not sufficient for extensive study of gene function. To help identify the functions of genes in rice, we developed a Gateway vector, pANDA, for RNA interference of rice genes. This vector can be used for Agrobacterium transformation of rice and allows easy and fast construction of efficient RNAi vectors. In the construct, hairpin RNA derived from a given gene is transcribed from a strong maize ubiquitin promoter, and an intron is placed 5' upstream of inverted repeats to enhance RNA expression. Analysis of rice genes using this vector showed that suppression of mRNA expression was observed in more than 90% of transgenic plants examined, and short interfering RNA indicative of RNA silencing was detected in each silenced plant. A similar vector, pANDA-mini, was also developed for direct transfer into leaf cells or protoplasts. This vector can be used for transient suppression of gene function in rice. These vectors should help identify the functions of rice genes whose tagged mutants are not available at present and complement existing methods for functional genomics of rice.     

Mass spectrometric-based approaches in quantitative proteomics

Classically, experiments aimed at studying changes in protein expression have always followed a small set of proteins. This focused approach was necessary since tools to efficiently analyze large numbers of proteins were simply not available. Large-scale quantitative proteomics promises to produce reams of data that previously would have taken decades to measure with classical methods. Mass spectrometry is already a well-established protein identification tool and recent methodological developments indicate that it can also be successfully applied to extract quantitative data of protein abundance. From the first reports 4 years ago, numerous schemes to take advantage of stable isotope nuclei incorporation in proteins and peptides have been developed. Here we review the benefits and pitfalls of some of the most commonly used protocols, focusing on a procedure now being used extensively in our laboratory, stable isotope labeling with amino acids in cell culture (SILAC). The basic theory, application, and data analysis of a SILAC experiment are discussed. The emerging nature of these techniques and the rapid pace of technological development make forecasting the directions of the field difficult but we speculate that SILAC will soon be a key tool of quantitative proteomics.     

Drosophila RNAi screening in a postgenomic world

Drosophila melanogaster has a long history as a model organism with several unique features that make it an ideal research tool for the study of the relationship between genotype and phenotype. Importantly fundamental genetic principles as well as key human disease genes have been uncovered through the use of Drosophila. The contribution of the fruit fly to science and medicine continues in the postgenomic era as cell-based Drosophila RNAi screens are a cost-effective and scalable enabling technology that can be used to quantify the contribution of different genes to diverse cellular processes. Drosophila high-throughput screens can also be used as integral part of systems-level approaches to describe the architecture and dynamics of cellular networks.     

Functional and quantitative proteomics using SILAC

Researchers in many biological areas now routinely characterize proteins by mass spectrometry. Among the many formats for quantitative proteomics, stable-isotope labelling by amino acids in cell culture (SILAC) has emerged as a simple and powerful one. SILAC removes false positives in protein-interaction studies, reveals large-scale kinetics of proteomes and - as a quantitative phosphoproteomics technology - directly uncovers important points in the signalling pathways that control cellular decisions.