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PubMed2006

Genome-wide functional analysis of human cell-cycle regulators.

Human cells have evolved complex signaling networks to coordinate the cell cycle. A detailed understanding of the global regulation of this fundamental process requires comprehensive identification of the genes and pathways involved in the various stages of cell-cycle progression. To this end, we report a genome-wide analysis of the human cell cycle, cell size, and proliferation by targeting >95% of the protein-coding genes in the human genome using small interfering RNAs (siRNAs). Analysis of >2 million images, acquired by quantitative fluorescence microscopy, showed that depletion of 1,152 genes strongly affected cell-cycle progression. These genes clustered into eight distinct phenotypic categories based on phase of arrest, nuclear area, and nuclear morphology. Phase-specific networks were built by interrogating knowledge-based and physical interaction databases with identified genes. Genome-wide analysis of cell-cycle regulators revealed a number of kinase, phosphatase, and proteolytic proteins and also suggests that processes thought to regulate G(1)-S phase progression like receptor-mediated signaling, nutrient status, and translation also play important roles in the regulation of G(2)/M phase transition. Moreover, 15 genes that are integral to TNF/NF-kappaB signaling were found to regulate G(2)/M, a previously unanticipated role for this pathway. These analyses provide systems-level insight into both known and novel genes as well as pathways that regulate cell-cycle progression, a number of which may provide new therapeutic approaches for the treatment of cancer.

Cell Cycle Proteins↗

PubMed2006

Proteomics, part II: the emerging role of proteomics over genomics in spontaneous preterm labor/birth.

UNLABELLED: Conventional wisdom holds that complications of immature organ systems such as respiratory distress syndrome, intraventricular hemorrhage, necrotizing enterocolitis, and bronchopulmonary dysplasia are the primary causes of the high neonatal morbidity and mortality attendant preterm delivery. However, recent evidence suggests that a major cause of prematurity-associated neonatal pathology is the fetal and neonatal response to inflammation/infection. Although functional genomics offered the promise of providing answers to many of these questions, the identification of the genes intrinsic to human parturition proved to be a difficult task. Proteomic profiling of the amniotic fluid (AF) provides a precise means for detection of inflammation by revealing the presence of 4 biomarkers (defensins-2 and -1, calgranulin-C, and calgranulin-A) that are highly predictive of intrauterine inflammation (MR score). The MR score is especially useful as it presents a gradient of disease activity progressing from "absent" to "mild" to "severe" inflammation. Thus, it provides the ability to identify patients who may benefit from interventions in utero in a modern diagnostic-therapeutic framework. TARGET AUDIENCE: Obstetricians & Gynecologists, Family Physicians. LEARNING OBJECTIVES: After completion of this article, the reader should be able to explain that the cause or causes of preterm delivery are still unknown, recall that functional genomics has not given the answer to these causes, and state that proteomic profiling of amniotic fluid, through mass-restricted (MR) scoring, may be predictive of intrauterine inflammation and allow for potential diagnosis and potential therapy.

Animals↗

PubMed2002

Identification of gene function and functional pathways by systemic plasmid-based ribozyme targeting in adult mice.

To date, functional genomic studies have been confined to either cell-based assays or germline mutations, using transgenic or knockout animals. However, these approaches are often unable either to recapitulate complex biologic phenotypes, such as tumor metastasis, or to identify the specific genes and functional pathways that produce serious diseases in adult animals. Although the transcription factor NF-kappaB transactivates many metastasis-related genes in cells, the precise genes and functional-pathways through which NF-kappaB regulates metastasis in tumor-bearing hosts are poorly understood. Here, we show that the systemic delivery of plasmid-based ribozymes targeting NF-kappaB in adult, tumor-bearing mice suppressed NF-kappaB expression in metastatic melanoma cells, as well as in normal cell types, and significantly reduced metastatic spread. Plasmid-based ribozymes suppressed target-gene expression with sequence specificity not achievable by using synthetic oligonucleotide-based approaches. NF-kappaB seemed to regulate tumor metastasis through invasion-related, rather than angiogenesis-, cell-cycle- or apoptosis-related pathways in tumor-bearing mice. Furthermore, ribozymes targeting either of the NF-kappaB-regulated genes, integrin beta(3) or PECAM-1 (a ligand-receptor pair linked to cell adhesion), reduced tumor metastasis at a level comparable to NF-kappaB. These studies demonstrate the utility of gene targeting by means of systemic, plasmid-based ribozymes to dissect out the functional genomics of complex biologic phenotypes, including tumor metastasis.

Aging↗

PubMedDate not supplied

Genomics and phenotypic profiles in dementia: implications for pharmacological treatment.

Constitutive genomics are probably determinant for the onset of dementia in conjunction with cerebrovascular and environmental factors. Furthermore, pharmacogenomic studies predict that the therapeutic response in Alzheimer's disease (AD) is genotype-specific, and that the expression of genes involved in the regulation of drug metabolism can influence efficacy and safety issues in pharmacotherapy. AD and dementia with a vascular component (DVC = VD + MXD) are the most prevalent forms of dementia. These clinical entities share many similarities, but they differ in major phenotypic and genotypic profiles, as revealed by structural and functional genomics studies. Comparative phenotypic studies have identified significant differences in 25% of more than 100 parametric variables, including anthropometry, cardiovascular function, aortic atherosclerosis, brain atrophy, blood pressure, blood biochemistry, hematology, thyroid function, folic acid and vitamin B(12) levels, brain hemodynamics and lymphocyte markers. The phenotypic profile of patients with DVC differs from that of AD patients in the following: (a) anthropometric values, (b) cardiovascular function, (c) blood pressure, (d) lipid metabolism, (e) uric acid levels, (f) peripheral calcium levels, (g) liver function (GOT, GPT, GGT), (h) alkaline phosphatase, (i) lactate dehydrogenase, (j) red and white blood cells, (k) regional brain atrophy (left temporal region, inter-hippocampal distance) and (l) brain blood flow velocity. Functional genomics studies incorporating APOE-related changes in biological markers extended the difference between AD and DVC up to 57%. Structural genomics studies with AD-related genes, including APP, MAPT, APOE, PS1, PS2, A2M, ACE, AGT, cFOS and PRNP genes, demonstrate different genetic profiles in AD and DVC, with an absolute genetic variation rate ranging from 30 to 80%, depending upon genes and genetic clusters. Single gene analysis identifies relative genetic variations ranging from 0 to 5%. The relative polymorphic variation in genetic clusters integrated by 2, 3 or 4 genes associated with AD ranges from 1 to 3%. The main phenotypic differences between AD and DVC are genotype-dependent, especially in AD, probably indicating that different genomic factors are essential for the expression of dementia symptoms that might be accelerated or induced by environmental and/or cerebrovascular factors.

Age Distribution↗

PubMed2005

Bioinformatics in microbial biotechnology--a mini review.

The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics--sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics--identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.

Journal Article↗

PubMed2004

Alcohol and gene expression in the central nervous system.

AIMS: To describe recent research focusing on the analysis of gene and protein expression relevant to understanding ethanol consumption, dependence and effects, in order to identify common themes. METHODS: A selective literature search was used to collate the relevant data. RESULTS: Over 160 genes have been individually assessed before or after ethanol administration, as well as in genetically selected lines. Techniques for studying gene expression include northern blots, differential display, real time reverse transcriptase-polymerase chain reaction (RT-PCR) and in situ hybridization. More recently, high throughput functional genomic technology, such as DNA microarrays, has been used to examine gene expression. Recent gene expression analyses have dramatically increased the number of candidate genes (nine array papers have illuminated 600 novel gene transcripts that may contribute to alcohol abuse and alcoholism). CONCLUSIONS: Although functional genomic experiments (transcriptome analysis) have failed to identify a single alcoholism gene, they have illuminated important pathways and gene products that may contribute to the risk of alcohol abuse and alcoholism.

Alcoholism↗

PubMed2000

Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation.

The unfolded protein response (UPR) regulates gene expression in response to stress in the endoplasmic reticulum (ER). We determined the transcriptional scope of the UPR using DNA microarrays. Rather than regulating only ER-resident chaperones and phospholipid biosynthesis, as anticipated from earlier work, the UPR affects multiple ER and secretory pathway functions. Studies of UPR targets engaged in ER-associated protein degradation (ERAD) reveal an intimate coordination between these responses: efficient ERAD requires an intact UPR, and UPR induction increases ERAD capacity. Conversely, loss of ERAD leads to constitutive UPR induction. Finally, simultaneous loss of ERAD and the UPR greatly decreases cell viability. Thus, the UPR and ERAD are dynamic responses required for the coordinated disposal of misfolded proteins even in the absence of acute stress.

Endoplasmic Reticulum, Rough↗

PubMed2002

Dermatological applications of DNA array technology.

The Human Genome Project and other large scale sequencing consortia continue to generate huge amounts of DNA sequence data. Despite the identification of specific disease-related genes and genetic markers, we still appear to know little about how diverse gene products actually interact with each other or respond to other chemical or biological stimuli. Such information is of course fundamental to understanding complex disease pathways and biochemical processes and, as such, has spawned new fields of investigative genetics, that of functional genomics and proteomics. DNA array technology is emerging as a powerful, high-throughput and versatile tool that can be applied to the study of functional genomics. This article reviews the methodology involved in array analysis and provides insight into how, as an investigative tool, DNA arrays are becoming increasingly useful in understanding fundamental abnormalities in dermatological disease and also in refining the management of patients with certain skin disorders.

Gene Expression Profiling↗

PubMed2005

Genetic, genomic, and functional analysis of the granule lattice proteins in Tetrahymena secretory granules.

In some cells, the polypeptides stored in dense core secretory granules condense as ordered arrays. In ciliates such as Tetrahymena thermophila, the resulting crystals function as projectiles, expanding upon exocytosis. Isolation of granule contents previously defined five Granule lattice (Grl) proteins as abundant core constituents, whereas a functional screen identified a sixth family member. We have now expanded this screen to identify the nonredundant components required for projectile assembly. The results, further supported by gene disruption experiments, indicate that six Grl proteins define the core structure. Both in vivo and in vitro data indicate that core assembly begins in the endoplasmic reticulum with formation of specific hetero-oligomeric Grl proprotein complexes. Four additional GRL-like genes were found in the T. thermophila genome. Grl2p and Grl6p are targeted to granules, but the transcripts are present at low levels and neither is essential for core assembly. The DeltaGRL6 cells nonetheless showed a subtle change in granule morphology and a marked reduction in granule accumulation. Epistasis analysis suggests this results from accelerated loss of DeltaGRL6 granules, rather than from decreased synthesis. Our results not only provide insight into the organization of Grl-based granule cores but also imply that the functions of Grl proteins extend beyond core assembly.

Amino Acid Sequence↗

PubMed2005

Putting microarrays in a context: integrated analysis of diverse biological data.

In recent years, multiple types of high-throughput functional genomic data that facilitate rapid functional annotation of sequenced genomes have become available. Gene expression microarrays are the most commonly available source of such data. However, genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower-quality data than traditional experimental methods. Thus sophisticated analysis methods are necessary to make accurate functional interpretation of these large-scale data sets. This review presents an overview of recently developed methods that integrate the analysis of microarray data with sequence, interaction, localisation and literature data, and further outlines current challenges in the field. The focus of this review is on the use of such methods for gene function prediction, understanding of protein regulation and modelling of biological networks.

Algorithms↗

PubMed2004

In silico identification of transcriptional regulators associated with c-Myc.

The development of powerful experimental strategies for functional genomics and accompanying computational tools has brought major advances in the delineation of transcriptional networks in organisms ranging from yeast to human. Regulation of transcription of eukaryotic genes is to a large extent combinatorial. Here, we used an in silico approach to identify transcription factors (TFs) that form recurring regulatory modules with c-Myc, a protein encoded by an oncogene that is frequently disregulated in human malignancies. A recent study identified, on a genomic scale, human genes whose promoters are bound by c-Myc and its heterodimer partner Max in Burkitt's lymphoma cells. Using computational methods, we identified nine TFs whose binding-site signatures are highly overrepresented in this promoter set of c-Myc targets, pointing to possible functional links between these TFs and c-Myc. Binding sites of most of these TFs are also enriched on the set of mouse homolog promoters, suggesting functional conservation. Among the enriched TFs, there are several regulators known to control cell cycle progression. Another TF in this set, EGR-1, is rapidly activated by numerous stress challenges and plays a central role in angiogenesis. Experimental investigation confirmed that c-Myc and EGR-1 bind together on several target promoters. The approach applied here is general and demonstrates how computational analysis of functional genomics experiments can identify novel modules in complex networks of transcriptional regulation.

Animals↗

PubMed2004

siRNAs: mechanism of RNA interference, in vivo and potential clinical applications.

Small interfering RNAs are currently the most widely used nucleic acid-based sequence-specific gene silencing molecules. These molecules mediate RNA interference--a natural post-transcriptional gene-silencing pathway. Given the high reliability and higher efficiency of small interfering RNA-mediated RNA interference, compared to earlier reverse genetic technologies, this is now the preferred technique in functional genomics. Furthermore, the exquisite specificity and exceptional gene-silencing potency of small interfering RNAs has resulted in intense research related to potential target-specific therapeutic applications of these molecules. This review will discuss the mechanism of RNA interference and applications of the pathway in molecular biology including functional genomics will be overviewed. The article will outline in vivo and potential clinical applications of small interfering RNA molecules.

Gene Targeting↗

PubMed2004

Genomic characterization of Alzheimer's disease and genotype-related phenotypic analysis of biological markers in dementia.

More than 180 genes distributed across the human genome are potentially involved in the pathogenesis of Alzheimer's disease (AD). The AD population shows a higher genetic variation rate than the control population. Significant differences in allelic distribution and frequency exist when AD-related polygenic clusters are compared with other forms of dementia, indicating that the genetic component in neurodegenerative dementia differs from that of other CNS disorders. The characterization of AD genotype-related phenotypic profiles reveals substantial differences in biological markers among AD clusters associated with different genes and/or allelic combinations. AD and dementia with vascular component (DVC) are the most prevalent forms of dementia. Both clinical entities share many similarities, but they differ in their major phenotypic and genotypic profiles, as revealed by structural and functional genomics studies. Comparative phenotypic studies have identified significant differences in 25% of more than 100 parametric variables, including anthropometric values, cardiovascular function, blood pressure, lipid metabolism, uric acid metabolism, peripheral calcium homeostasis, liver function, alkaline phosphatase, lactate dehydrogenase, red and white blood cells, regional brain atrophy, and brain blood flow velocity. Functional genomic studies incorporating apolipoprotein E (APOE)-related changes in biological markers extended the difference between AD and DVC by up to 57%. Structural genomic studies with AD-related genes, including APP, MAPT, APOE, PS1, PS2, A2M, ACE, AGT, cFOS, and PRNP, demonstrate different genetic profiles in AD and DVC, with an absolute genetic variation rate in the range of 30-80%, depending upon genes and genetic clusters. The relative polymorphic variation in genetic clusters integrated by two, three or four genes associated with AD ranges from 1 to 3%. The main phenotypic differences in AD are genotype dependent, indicating a powerful influence of polygenic factors on the AD phenotypic profile. All these genotypic and phenotypic variations bring about important consequences for the pharmacogenomics of AD.

Adolescent↗

PubMed2003

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development.

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Animals↗

PubMed2004

A primer on molecular biology for imagers: III. Proteins: structure and function.

This article along with the first 2 in this series (4,12) completes the discussion on the key molecules and process inside the cell namely, DNA, RNA, and proteins. These 3 articles provide a very basic foundation for understanding molecular biology concepts and summarize some of the work of numerous scientists over the past century. We understand these processes far better now than we did in the past, but clearly this knowledge is by no means complete and a number of basic scientists are working hard to elucidate and understand the fundamental mechanisms that operate within a cell. Genes and gene products work with each other in complex, interconnected pathways, and in perfect harmony to make a functional cell, tissue, and an organism as a whole. There is a lot of cross-talk that happens between different proteins that interact with various other proteins, DNA, and RNA to establish pathways, networks, and molecular systems as a team working to perfection. The past 15 years have seen the rapid development of systems biology approaches. We live in an era that emphasizes multi-disciplinary, cross-functional teams to perform science rather than individual researchers working on the bench on a very specific problem. Global approaches have become more common and the amount of data generated must be managed by trained bioinformatics personnel and large computers. In our subsequent articles, we will discuss these global approaches and the areas of genomics, functional genomics, and proteomics that have revolutionized the way we perform science.

Molecular Biology↗

PubMed2005

Genomic technologies and the interrogation of the transcriptome.

Functional genomics refers to the study of whole genomes and the function of its constituent parts to explain biological processes. Though these investigations may involve whole proteome analysis, the primary focus is on the transcriptome and how it is regulated. Recent advances in technologies that can interrogate cellular transcripts on a genome-wide scale seek the complete disclosure of the transcriptome over time-intervals and across many different cellular states. This massively complex data when viewed as a whole can provide surprisingly precise assessment of cellular conditions. Moreover, these data can define hierarchies of importance and have shown us new transcriptional elements. Herein, we describe the technologies and the experimental strategies to study the transcriptome that would be pertinent to cancer and ageing research.

Animals↗

PubMed2001

Evolution in health and disease: work in progress.

This article surveys progress in Darwinian medicine since 1991. Evolutionary thinking has been providing an increasing flow of fresh ideas into medical science, ideas that would not be suggested by other perspectives. Recent contributions have shed new light on the evolution of virulence, of antibiotic resistance, of oocytic atresia, of menopause, of the timing of the expression of genetic disease, of links between mate choice and disease resistance, and of genomic conflict between mother and fetus over resource provisioning. An important consequence of changes from the environment of evolutionary adaptedness concerns reproductive cancers; the incidence of reproductive cancers may be linked to changes in the frequency of menstruation in postindustrial societies. Other intriguing developments include some unanticipated and undesirable consequences of good hygiene, hope from an unexpected quarter for progress on nerve and muscle regeneration, evolutionary interpretations of mental disease, and insights from functional genomics into the nature of tradeoffs. The application of evolutionary thinking to problems in medical research and practice has thus yielded an abundant and growing harvest of insights. Some are well founded, others remain speculative. The field is moving from an initial phase dominated by speculation and hypothesis formation into a more rigorous phase of experimental testing of explicit alternatives. Currently the most promising areas, those in which experimental rigor can be applied efficiently, include experimental evolution and functional genomics. The pioneers can be proud of what they have set in motion.

Adaptation, Physiological↗

PubMed1998

Genomic and functional map of the chromosome 14 t(12;14) breakpoint cluster region in uterine leiomyoma.

A translocation involving chromosomes 12 and 14 [t(12;14)(q15;24.1)] is commonly seen in benign smooth muscle tumor as uterine leiomyoma (UL). A contig of P1-derived artificial chromosome and bacterial artificial chromosome clones on chromosome 14, encompassing a t(12;14) breakpoint cluster region (BCR) in UL, was generated principally using the recently developed HAPPY map of chromosome 14 as a framework (P. H. Dear et al., 1998, Genomics 48: 232-241). Three UL t(12;14) breakpoints have been localized within this contig, showing that a BCR of at least 400 kb exists on chromosome 14. Other studies of tumors with t(12;14) rearrangements similarly show breakpoints within a 475-kb multiple aberration region on chromosome 12. Thus t(12;14) is an example of a translocation in which the breakpoints are located within a BCR on both chromosome 12 and chromosome 14, justifying the identification of expressed sequences that are altered in these BCR regions. A total of four expressed sequences were identified in the BCR on chromosome 14. Two of these were novel cDNAs (D14S1460E and D14S1461E). The chromosome 14 cDNAs were expressed in multiple adult tissues. The identification of a large breakpoint cluster region on chromosome 14 suggests that translocations in this region mediate their effects at a distance and also that elements that predispose this region to recurrent chromosomal translocation may be widely distributed.

Amino Acid Sequence↗