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PubMed2006

Drosophila melanogaster as a model for studying protein-encoding genes that are resident in constitutive heterochromatin.

The organization of chromosomes into euchromatin and heterochromatin is one of the most enigmatic aspects of genome evolution. For a long time, heterochromatin was considered to be a genomic wasteland, incompatible with gene expression. However, recent studies--primarily conducted in Drosophila melanogaster--have shown that this peculiar genomic component performs important cellular functions and carries essential genes. New research on the molecular organization, function and evolution of heterochromatin has been facilitated by the sequencing and annotation of heterochromatic DNA. About 450 predicted genes have been identified in the heterochromatin of D. melanogaster, indicating that the number of active genes is higher than had been suggested by genetic analysis. Most of the essential genes are still unknown at the molecular level, and a detailed functional analysis of the predicted genes is difficult owing to the lack of mutant alleles. Far from being a peculiarity of Drosophila, heterochromatic genes have also been found in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Oryza sativa and Arabidopsis thaliana, as well as in humans. The presence of expressed genes in heterochromatin seems paradoxical because they appear to function in an environment that has been considered incompatible with gene expression. In the future, genetic, functional genomic and proteomic analyses will offer powerful approaches with which to explore the functions of heterochromatic genes and to elucidate the mechanisms driving their expression.

Animals↗

PubMed2002

Proteomics gives insight into the regulatory function of chloroplast thioredoxins.

Thioredoxins are small multifunctional redox active proteins widely if not universally distributed among living organisms. In chloroplasts, two types of thioredoxins (f and m) coexist and play central roles in regulating enzyme activity. Reduction of thioredoxins in chloroplasts is catalyzed by an iron-sulfur disulfide enzyme, ferredoxin-thioredoxin reductase, that receives photosynthetic electrons from ferredoxin, thereby providing a link between light and enzyme activity. Chloroplast thioredoxins function in the regulation of the Calvin cycle and associated processes. However, the relatively small number of known thioredoxin-linked proteins (about 16) raised the possibility that others remain to be identified. To pursue this opportunity, we have mutated thioredoxins f and m, such that the buried cysteine of the active disulfide has been replaced by serine or alanine, and bound them to affinity columns to trap target proteins of chloroplast stroma. The covalently linked proteins were eluted with DTT, separated on gels, and identified by mass spectrometry. This approach led to the identification of 15 potential targets that function in 10 chloroplast processes not known to be thioredoxin linked. Included are proteins that seem to function in plastid-to-nucleus signaling and in a previously unrecognized type of oxidative regulation. Approximately two-thirds of these targets contained conserved cysteines. We also identified 11 previously unknown and 9 confirmed target proteins that are members of pathways known to be regulated by thioredoxin. In contrast to results with individual enzyme assays, specificity for thioredoxin f or m was not observed on affinity chromatography.

Chloroplasts↗

PubMed2003

Detection of regulatory circuits by integrating the cellular networks of protein-protein interactions and transcription regulation.

The post-genomic era is marked by huge amounts of data generated by large-scale functional genomic and proteomic experiments. A major challenge is to integrate the various types of genome-scale information in order to reveal the intra- and inter- relationships between genes and proteins that constitute a living cell. Here we present a novel application of classical graph algorithms to integrate the cellular networks of protein-protein interactions and transcription regulation. We demonstrate how integration of these two networks enables the discovery of simple as well as complex regulatory circuits that involve both protein-protein and protein-DNA interactions. These circuits may serve for positive or negative feedback mechanisms. By applying our approach to data from the yeast Saccharomyces cerevisiae, we were able to identify known simple and complex regulatory circuits and to discover many putative circuits, whose biological relevance has been assessed using various types of experimental data. The newly identified relations provide new insight into the processes that take place in the cell, insight that could not be gained by analyzing each type of data independently. The computational scheme that we propose may be used to integrate additional functional genomic and proteomic data and to reveal other types of relations, in yeast as well as in higher organisms.

DNA, Fungal↗

PubMed2003

Evolution of the cellular stress proteome: from monophyletic origin to ubiquitous function.

Cells respond to acute environmental change by activating a stress response that is widely studied. However, knowledge of this stress response is fragmentary, and a unifying concept explaining its universality for many different species and types of stress is lacking. The need for a holistic view emphasizing the key aspects of the stress response is addressed by the following hypothesis. The cellular stress response is a reaction to any form of macromolecular damage that exceeds a set threshold, independent of the underlying cause. It is aimed at temporarily increasing tolerance limits towards macromolecular damage by utilizing a phylogenetically conserved set of genes and pathways that mediate global macromolecular stabilization and repair to promote cellular and organismal integrity under suboptimal conditions. This mechanism affords time for a separate set of stressor-specific adaptations, designed to re-establish cellular homeostasis, to take action. Supporting evidence, emerging conclusions, and ways to test this hypothesis are presented.

Amino Acid Sequence↗

PubMed2004

Using RNAi to catch Drosophila genes in a web of interactions: insights into cancer research.

The completion of whole-genome sequencing of various model organisms and the recent explosion of new technologies in the field of Functional Genomics and Proteomics is poised to revolutionize the way scientists identify and characterize gene function. One of the most significant advances in recent years has been the application of RNA interference (RNAi) as a means of assaying gene function. In the post-genomic era, advances in the field of cancer biology will rely upon the rapid identification and characterization of genes that regulate cell growth, proliferation, and apoptosis. Significant efforts are being directed towards cancer therapy and devising efficient means of selectively delivering drugs to cancerous cells. In this review, we discuss the promise of integrating genome-wide RNAi screens with proteomic approaches and small-molecule chemical genetic screens, towards improving our ability to understand and treat cancer.

Animals↗

PubMed2026

An integrated proteomics and transcriptomics analysis highlights concordance between protein turnover and carbohydrate transport and metabolism as key functional categories during the growth of Trichophyton rubrum.

Dermatophytes are a class of keratinophilic skin fungi that invade host skin, hair, and nails to acquire nutrients. An integrated multi-omics approach utilizing liquid chromatography-tandem mass spectrometry and RNA-seq after growth in a protein-rich soy medium was employed to capture the major subset of secreted protein families of Trichophyton rubrum. The secretome consisted mainly of proteases and cell wall-degrading enzymes, with subtilisins (Sub6 and Sub7), metallopeptidase (LAP2), and chitinase having the most abundant peptides. Transcriptional profiling indicated fungal adaptation in protein-rich media to process the protein nutrients through modulation of metabolism and general cellular function pathways. Correlation analysis between proteomics and transcriptomics data using functional KOG categories shows high concordance of KOG categories O (posttranslational modification, protein turnover, and chaperones), P (inorganic ion transport and metabolism), and G (carbohydrate transport and metabolism), as per cosine similarity analysis.IMPORTANCEDermatophytes are keratinophilic skin fungal pathogens that invade host skin, hair, and nails to acquire nutrients. There is an epidemic-like increase in infections, as well as an increase in antimicrobial resistance among dermatophytes, as witnessed over the last decade. There is hence a need to understand the key pathways and virulence factors required during growth and infection. We present an integrated multi-omics analysis (proteomics and transcriptomics data) using a vector-based similarity approach to show high concordance of KOG functional categories belonging to posttranslational modification, protein turnover, carbohydrate transport, and metabolism.

Proteomics↗

PubMed2026

Proteome-wide Mendelian randomisation of lung function to identify potential therapeutic targets for respiratory disease.

BACKGROUND: Despite multiple clinical trials, disease-modifying treatments for COPD are currently limited. Since many drugs target proteins, identifying causality between proteins and lung function informs understanding of COPD pathophysiology and may suggest novel targets. We used Mendelian randomisation (MR) to prioritise proteins as potentially causal for imparied lung function. For prioritised proteins, we explored their potential suitability as drug targets by predicting their effects on a range of clinical outcomes. METHODS: We used genome-wide association study (GWAS) data on 2923 proteins (n=48 195, UK Biobank) to identify single genetic variants (protein quantitative trait loci (cis-pQTLs)) associated with protein levels (p≤5×10-9, variant ≤100 kb of a transcription start site). We performed cis-pQTL-MR analyses of four spirometric traits (n=149 166, 36 independent cohorts). Sensitivity analyses included colocalisation and reverse direction MR. We report associations between cis-pQTLs for prioritised proteins and multiple clinical respiratory outcomes, and use phenome-wide analysis to explore potential adverse effects or drug repurposing opportunities. FINDINGS: 1841 proteins had a suitable cis-pQTL. We implicated 16 proteins as potentially causal for lung function (p<1.71×10-5): seven proteins have not been implicated by previous lung function GWAS or MR (CCND2, DTD1, PILRA, PTPRK, TDRKH, GRHPR, NUDT5), and we provide corroborative evidence for 10 proteins. We add to the literature identifying surfactant protein D (SFTPD) as a candidate, yet predict that integrin subunit alpha V (ITGAV) inhibition could impair some lung function measures, mimicking adverse results from a recent trial. INTERPRETATION: Our approach identifies proteins (some novel) that are potentially therapeutic targets for respiratory disease, and which warrant follow-up for utility and safety.

Journal Article↗

PubMed2004

The Arabidopsis thaliana chloroplast proteome reveals pathway abundance and novel protein functions.

BACKGROUND: Chloroplasts are plant cell organelles of cyanobacterial origin. They perform essential metabolic and biosynthetic functions of global significance, including photosynthesis and amino acid biosynthesis. Most of the proteins that constitute the functional chloroplast are encoded in the nuclear genome and imported into the chloroplast after translation in the cytosol. Since protein targeting is difficult to predict, many nuclear-encoded plastid proteins are still to be discovered. RESULTS: By tandem mass spectrometry, we identified 690 different proteins from purified Arabidopsis chloroplasts. Most proteins could be assigned to known protein complexes and metabolic pathways, but more than 30% of the proteins have unknown functions, and many are not predicted to localize to the chloroplast. Novel structure and function prediction methods provided more informative annotations for proteins of unknown functions. While near-complete protein coverage was accomplished for key chloroplast pathways such as carbon fixation and photosynthesis, fewer proteins were identified from pathways that are downregulated in the light. Parallel RNA profiling revealed a pathway-dependent correlation between transcript and relative protein abundance, suggesting gene regulation at different levels. CONCLUSIONS: The chloroplast proteome contains many proteins that are of unknown function and not predicted to localize to the chloroplast. Expression of nuclear-encoded chloroplast genes is regulated at multiple levels in a pathway-dependent context. The combined shotgun proteomics and RNA profiling approach is of high potential value to predict metabolic pathway prevalence and to define regulatory levels of gene expression on a pathway scale.

Arabidopsis↗

PubMed2004

Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective.

Proteomics is the study of the protein complement of a genome and employs a number of newly emerging tools. One such tool is chemical proteomics, which is a branch of proteomics devoted to the exploration of protein function using both in vitro and in vivo chemical probes. Chemical proteomics aims to define protein function and mechanism at the level of directly observed protein-ligand interactions, whereas chemical genomics aims to define the biological role of a protein using chemical knockouts and observing phenotypic changes. Chemical proteomics is therefore traditional mechanistic biochemistry performed in a systems-based manner, using either activity- or affinity-based probes that target proteins related by chemical reactivities or by binding site shape/properties, respectively. Systems are groups of proteins related by metabolic pathway, regulatory pathway or binding to the same ligand. Studies can be based on two main types of proteome samples: pooled proteins (1 mixture of N proteins) or isolated proteins in a given system and studied in parallel (N single protein samples). Although the field of chemical proteomics originated with the use of covalent labeling strategies such as isotope-coded affinity tagging, it is expanding to include chemical probes that bind proteins noncovalently, and to include more methods for observing protein-ligand interactions. This review presents an emerging role for nuclear magnetic resonance spectroscopy in chemical proteomics, both in vitro and in vivo. Applications include: functional proteomics using cofactor fingerprinting to assign proteins to gene families; gene family-based structural characterizations of protein-ligand complexes; gene family-focused design of drug leads; and chemical proteomic probes using nuclear magnetic resonance SOLVE and studies of protein-ligand interactions in vivo.

Magnetic Resonance Spectroscopy↗

PubMed2006

C. elegans: an invaluable model organism for the proteomics studies of the cholesterol-mediated signaling pathway.

With the availability of its complete genome sequence and unique biological features relevant to human disease, Caenorhabditis elegans has become an invaluable model organism for the studies of proteomics, leading to the elucidation of nematode gene function. A journey from the genome to proteome of C. elegans may begin with preparation of expressed proteins, which enables a large-scale analysis of all possible proteins expressed under specific physiological conditions. Although various techniques have been used for proteomic analysis of C. elegans, systematic high-throughput analysis is still to come in order to accommodate studies of post-translational modification and quantitative analysis. Given that no integrated C. elegans protein expression database is available, it is about time that a global C. elegans proteome project is launched through which datasets of transcriptomes, protein-protein interaction and functional annotation can be integrated. As an initial target of a pilot project of the C. elegans proteome project, the cholesterol-mediated signaling pathway will be an excellent example since, like in other organisms, it is one of the key controlling pathways in cell growth and development in C. elegans. As this field tends to broaden to functional proteomics, there is a high demand to develop the versatile proteome informatics tools that can mange many different data in an integrative manner.

Animals↗

PubMed2005

System, trends and perspectives of proteomics in dicot plants. Part III: Unraveling the proteomes influenced by the environment, and at the levels of function and genetic relationships.

This review is devoted to the proteomics studies in dicotyledoneous (dicot) plants, such as Arabidopsis, Medicago, potato, soybean, and tomato, under the influence of the environment and at the functional and genetic relationship levels, where the two core technologies, two-dimensional gel electrophoresis (2-DGE) and mass spectrometry (MS) have been instrumental in unraveling the proteomes affected therein. Abiotic and biotic stress responses, including the affect of allergens, the symbiotic interaction between the members of the Leguminoseae family and genera of nitrogen fixing bacteria, phosphoproteomics, and proteomics in revealing the genetic relationships between species and genera have been the subject of many proteomics studies, and these are discussed in this review. In all, these studies have complemented and extended the studies of developmental proteomics [G.K. Agrawal, M. Yonekura, Y. Iwahashi, H. Iwahashi, R. Rakwal, J. Chromatogr. B (2004)].

Cold Temperature↗

PubMed2005

Proteomics meets microbiology: technical advances in the global mapping of protein expression and function.

The availability of complete genome sequences for a large number of pathogenic organisms has opened the door for large-scale proteomic studies to dissect both protein expression/regulation and function. This review highlights key proteomic methods including two-dimensional gel electrophoresis, reference mapping, protein expression profiling and recent advances in gel-free separation techniques that have made a significant impact on the resolution of complex proteomes. In addition, we highlight recent developments in the field of chemical proteomics, a branch of proteomics aimed at functionally profiling a proteome. These techniques include the development of activity-based probes and activity-based protein profiling methods as well as the use of synthetic small molecule libraries to screen for pharmacological tools to perturb basic biological processes. This review will focus on the applications of these technologies to the field of microbiology.

Bacterial Proteins↗

PubMed2005

Experimental and bioinformatic approaches for interrogating protein-protein interactions to determine protein function.

An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. One strategy to determine protein function is to identify the protein-protein interactions. The increasing use of high-throughput and large-scale bioinformatics-based studies has generated a massive amount of data stored in a number of different databases. A challenge for bioinformatics is to explore this disparate data and to uncover biologically relevant interactions and pathways. In parallel, there is clearly a need for the development of approaches that can predict novel protein-protein interaction networks in silico. Here, we present an overview of different experimental and bioinformatic methods to elucidate protein-protein interactions.

Animals↗

PubMedDate not supplied

A review of proteomics in cancer research.

The most functional compartment encoded by the genome is proteome. Therefore study of proteome i.e. proteomics is the promising approach in identification, separation and quantitation of functional changes. It aims to gain a comprehensive understanding of the expressions, modifications, interactions, and regulation of proteins in cells. The power of two-dimensional electrophoresis and advances in mass spectrometric techniques, combined with sequence data base correlation, has enabled speed and accuracy in identification of proteins in complex mixtures. Therefore, proteomics may provide a better understanding of the molecular basis of cancer growth, with identification of potential pathological markers and therapeutic targets. Tobacco related cancers are the major health hazard in Asian countries; the proteomics approach should be employed for understanding the underlying disease processes and hopefully reveal important clues for identifying high risk individuals and early changes during malignant transformation.

Biomarkers, Tumor↗

PubMed2006

Transcriptomics, proteomics and interactomics: unique approaches to track the insights of bioremediation.

Microbial mediated bioremediation has a great potential to effectively restore contaminated environment, but the lack of information about factors regulating the growth and metabolism of various microbial communities in polluted environment often limits its implementation. Newly seeded techniques such as transcriptomics, proteomics and interactomics offer remarkable promise as tools to address longstanding questions regarding the molecular mechanisms involved in the control of mineralization pathways. During mineralization, transcript structures and their expression have been studied using high-throughput transcriptomic techniques with microarrays. Generally however, transcripts have no ability to operate any physiological response; rather, they must be translated into proteins with significant functional impact. These proteins can be identified by proteomic techniques using powerful two-dimensional polyacrylamide gel electrophoresis (2-DE). Towards the establishment of functional proteomics, the current advances in mass spectrometry (MS) and protein microarrays play a central role in the proteomics approach. Exploring the differential expression of a wide variety of proteins and screening of the entire genome for proteins that interact with particular mineralization regulatory factors would help us to gain insights into bioremediation.

Biodegradation, Environmental↗

PubMed2003

Construction of linear functional expression elements with DNA and RNA hybrid primers: a flexible and fast method for proteomics.

Two methods of constructing linear functional expression elements (LFEE) using hybrid DNA and RNA primers in DNA amplification for rapid gene expression are described. In both methods, it is not necessary to have additional transformation or bacterial propagation. The promoter, open reading frame (ORF) and terminator are amplified using Pfu or Taq DNA polymerase. Three elements containing DNA or RNA overhang are covalently ligated by T4 DNA ligase. The recombinant molecule is amplified with element-specific primers. The LFEE can be generated by both methods in a few hours and can be expressed in mammalian cells.

Animals↗

PubMed2006

Antibodies for proteomic research: comparison of traditional immunization with recombinant antibody technology.

Antibodies play a pivotal role in studying the expression and function of proteins. Proteomics studies require the generation of specific and high-affinity antibodies against large numbers of proteins. While traditional animal-based antibody generation is laborious, difficult to automate, and therefore less suited to keep up with the requirements of proteomics research, the use of recombinant in vitro antibody technology might offer a solution to this problem. However, it has not been demonstrated yet that such antibodies are at least as useful as conventional antibodies for typical proteomics applications. Here we generated novel recombinant Fab antibody fragments from the naïve HuCAL GOLD library against a number of targets derived from a mouse cDNA library. We compared these antibodies with polyclonal antisera produced against the same targets and show that these recombinant antibodies are useful reagents for typical applications like Western blotting or immunohistochemistry.

Animals↗

PubMedDate not supplied

Proteomics and regulomics: the yin and yang of functional genomics.

Protein analysis is a field of research with a long history. Recently, the development of a series of proteomics approaches, i.e., simultaneous analyses on all or a majority of proteins in a cell at a given state, has reinvigorated protein analyses. Mass Spectrometry also developed into one of the most versatile technical tools supporting or even enabling many proteomics-oriented approaches, providing a convenient link between experimental protein analysis and the corresponding amino acid sequences. Thus direct links to the genomic sequence can be established, which opens the door for a synergistic combination with genomic sequence analysis. This review focuses especially on aspects of genome-wide transcription control, regulomics in analogy to all the other -omics, and how a combination of MS-based proteomics with in silico regulomics analyses can produce synergistic effects in the quest to understand how cells function. This is illustrated on a real life example showing how the MS-analysis and in silico promoter analysis can extend the list of candidates for signaling pathways, here the MAP kinase pathway.

Energy Metabolism↗