Current Pharmaceutical Biotechnology - Volume 9, Issue 5, 2008

A technique termed Serial Analysis of Gene Expression (SAGE) has emerged in 1995 and promised becoming a sort of a ‘golden bullet’ in the list of gene expression profiling methods available at the moment. Most importantly, it appeared being truly high-throughput technique, allowing gene expression profiling reaching nearly genomic scale: a success then achieved only by multi-site EST sequencing projects. More convenient than any alternative technique (including EST sequencing), SAGE was greeted with much enthusiasm and a number of tag libraries constructed and analyzed have started growing rapidly. Though challenging technically, initial SAGE protocol has been applied with success in many studies of different nature, yielding accurate large-scale gene expression profiles of numerous samples derived from various cells and tissues. Furthermore, SAGE has soon become a platform of many adaptations aiming decreasing the required amount of starting material, improving tag yield and cloning efficiency, overcoming certain sources of potential bias and finally increasing the length of the yielded tags. The latter feature has been essential to allow effective identification of tagged genes, as well as rapid cloning of gene targets. To the success of SAGE, a progress of the ongoing genome sequencing projects has contributed. Advances in sequencing technology allowed both a higher number of tags sequenced within each project's budget, and increasingly higher number of tags matching known (sequenced) genes. Additionally, a number of bioinformatics-based approaches aimed improving the reliability of SAGE data. A convenience of SAGE applications was further supplemented with the appearance of public databases serving as SAGE library depositaries (Gene Expression Omnibus (GEO; NCBI), to name the most important) and gene annotation tools (including both SAGE software and SAGEmap resource (NCBI)). It should be noted that SAGE technique has emerged in the very beginning of DNA microarray era and only by year 2002-2003 did DNA microarray technology match SAGE in terms of the throughput. Importantly, notwithstanding an astonishing progress of microarray technology, it is generally believed that SAGE still possesses certain advantages over the former - thus allowing a researcher to choose a suitable platform for each experiment. This Special Issue aims to review the evolution of SAGE and related techniques, covering such features as adapting SAGE to the requirements of mini- and micro- samples, generation of longer tags and finally bioinformatics means of SAGE data analysis. It also covers SAGE application in hematological, diabetes and cancer research, providing a fine cross-section of the abilities of this important technique. There is no doubt that in its modified form SAGE will remain in the arsenal of highthroughput gene expression profiling methods for many decades to come.

A number of molecular methods of gene expression analysis can approach genomic level. Among those, Serial Analysis of Gene Expression (SAGE) stands out. Unlike many other techniques, SAGE allows both qualitative and quantitative analysis of previously unknown transcripts. Over the course of the last 13 years, SAGE has became a recognized tool of large-scale gene expression profiling, being used extensively in human, animal, yeast and plant studies of various nature. A number of important adaptations was introduced both to the protocol of SAGE library construction and to the analytical algorithm employed. Moreover, some variations of the original protocol (MAGE, SADE, microSAGE, miniSAGE, longSAGE, superSAGE, deepSAGE, etc.) were derived to improve the utility of SAGE in certain conditions. Current review aims comparing the benefits and drawbacks of the techniques for high-throughput gene expression analysis (including SAGE) in a realistic, balanced manner. Issues related to modifications to the original protocol and further development of the SAGE are discussed.

Since Serial Analysis of Gene Expression (SAGE) was introduced more than a decade ago, it has been widely applied to characterise gene expression profiles in various tissues, cell types and cell lines of diverse origin including human, mouse, rat, yeast, plant and parasites. Throughout the past years many modifications to the original SAGE protocol have been developed, which address several aspects of SAGE, including an increase in sequencing efficiency (deep- SAGE), improved tag-to-transcript mapping of SAGE tags (LongSAGE) and a reduction of the amount of required input RNA (microSAGE). Furthermore, the applications of SAGE have expanded from exclusively transcriptome analysis to now also include genome analysis, identifying genome signature tags that pinpoint transcription factor binding sites throughout the genome (Serial Analysis of Chromatin Occupancy or SACO). The review gives an overview of the main modifications to the SAGE technology that have been developed in the last decade, with a particular focus on the large reduction in the amount of required input RNA that has been achieved in the many SAGE modifications for downscaling or miniaturisation of SAGE (including microSAGE, PCR-SAGE and small amplified RNA-SAGE). The available methods for downscaling or miniaturisation of SAGE and their specific features will be discussed, illustrated by some examples of their application. This reduction in required quantity of input RNA has greatly expanded the possible applications of SAGE, allowing characterisation of global gene expression in material obtained from needle biopsies, small anatomical structures and specific cell types isolated by fluorescence activated cell sorting or laser microdissection.

The multiple levels of post-transcriptional processing and million-fold differences in expression levels make fully decoding the transcriptome in any given species extremely challenging. This review addresses the influence of sequenced length on transcriptome decoding under current DNA sequencing capabilities. Comparison of full-length cDNA, EST, 14-base SAGE, 21-LongSAGE, 26-SuperSAGE, and other variations shows that the sequenced length has been a key factor in determining the sensitivity and specificity for mRNA detection.

SuperSAGE is a variant of SAGE (Serial Analysis of Gene Expression) technology, which allows making transcript profiling by 26-bp tags extracted from cDNA employing the typeIII restriction enzyme EcoP15I. Its tag length is the longest among all the versions of SAGE, and is advantageous in tag-to-gene annotation, thereby allowing the technique to applicable to any eukaryotic life organisms. For model organisms with genome or cDNA sequences available, genes corresponding to 26-bp tags are uniquely defined by simple BLAST search. For non-model organisms without these sequence information, the 26-bp tag sequence is directly applicable to design PCR primer for amplifying cDNA of corresponding genes by 3'- or 5'-RACE. Furthermore, SuperSAGE allows various applications including “interaction transcriptome” and “SuperSAGE array”. Emerging “Next Generation Sequencing” technologies perfectly complement Super- SAGE, and their combination has generated a novel transcriptome platform, that is superior to all the different microarray variants in terms of throughput, data quality and cost of analysis.

Blood cells perform many important functions within the body, including homeostasis and host defense against various invading stimuli such as viral infection, cancer and autoimmune diseases. The subsets of leukocytes interact with each other through various surface molecules such as cytokine receptors, co-stimulation molecules and adhesion molecules. Over the last several years, accumulation of cDNA and genome databases has led to the accelerated identification of the molecules responsible for cell-cell interaction, cell activation and cell differentiation. In addition, technologies used in functional genomics, such as DNA microarray and serial analysis of gene expression (SAGE), have allowed us to analyze the expression of thousands of genes. The comprehensive analysis of gene expression is very useful to elucidate the function of cells, because characteristics of each cell type depend on the genes selectively expressed at various stages. The SAGE method, which is very quantitative, can cover the number of expressed genes that are unequaled by any other mammalian DNA microarray systems yet available. In order to molecularly define the subset and function of blood cells, we and other groups have performed SAGE in various types of hematipoietic cells. Here, we review the SAGE data obtained from the gene expression libraries made from various differentiation and activation stages of a broad range of blood cells, including phagocytes, T cells, B cells, platelets, reticulocytes and NK cells.

Type 2 diabetes is a multifactorial disease that is caused by the disruption of inter-organ networks. These disruptions lead to absolute and/or relative deficiencies in the actions of insulin due to either a genetic disposition or environmental factors. Specifically, the liver plays a central role in energy homeostasis and is a major source of bioactive secretory proteins that contribute to the pathophysiology of diabetes and subsequent complications. Therefore, comprehensive gene expression analyses of critical tissues, including the liver, are important steps for understanding the molecular signature of type 2 diabetes. Serial analysis of gene expression (SAGE) techniques have made it possible to compare tag levels among independent libraries and to identify previously unrecognized genes with novel functions that may be important in the development of diseases. Here, we review possible applications of SAGE to the study of diabetes from the following perspectives: (1) to understand and quantify normal gene expression profiles in the liver with respect to both a single gene and gene ontology of cellular components; (2) to identify biological pathways or co-regulated gene sets associated with the pathophysiology of diabetes to gain a more comprehensive understanding of genetic and environmental alterations; and (3) to identify novel functional hepatic genes that may regulate the pathophysiology of diabetes by comparing independent SAGE libraries in combination with DNA chip analyses. Such SAGE-based approaches may lead to the identification of novel therapeutic targets for the treatment of type 2 diabetes and its complications.

Spirulina is a photosynthetic, filamentous, spiral-shaped and multicellular edible microbe. It is the nature's richest and most complete source of nutrition. Spirulina has a unique blend of nutrients that no single source can offer. The alga contains a wide spectrum of prophylactic and therapeutic nutrients that include B-complex vitamins, minerals, proteins, γ-linolenic acid and the super anti-oxidants such as β-carotene, vitamin E, trace elements and a number of unexplored bioactive compounds. Because of its apparent ability to stimulate whole human physiology, Spirulina exhibits therapeutic functions such as antioxidant, anti-bacterial, antiviral, anticancer, anti-inflammatory, anti-allergic and antidiabetic and plethora of beneficial functions. Spirulina consumption appears to promote the growth of intestinal micro flora as well. The review discusses the potential of Spirulina in health care management.

Advances in molecular biology and biochemistry have dramatically increased our understanding of disease. The molecular mechanisms are the pathogenic basis of disease is changing modern medicine. New drugs often inhibit specific key pathways. In nuclear medicine, molecular imaging agents have been used for years, but most contrast agents for MRI or CT today are unspecific. The diagnosis is based on alterations in morphology and basic physiology, all of which are late manifestations of the original molecular changes. There are only few more specific contrast agents available. Microbubbles are the one, of size of blood cells are used as contrast agents for ultrasound imaging and are particularly valuable for targeting selected tissues and for providing useful information about the efficacy of chemotherapy. The exploitation of microbubble agents can be achieved when there is a full understanding of the bubble/ultrasound interaction for microbubbles freely suspended in blood or attached to blood vessel walls. Microbubbles are promising tool for targeting chemotherapeutics, polypeptides and genetic material to its target in body.

Advancements in single molecule detection (SMD) continue to unfold powerful ways to study the behavior of individual and complex molecular systems in real time. SMD enables the characterization of complex molecular interactions and reveals basic physical phenomena underlying chemical and biological processes. We present here a systematic study of the quenching efficiency of Forster-type energy-transfer (FRET) for multiple fluorophores immobilized on a single antibody. We simultaneously monitor the fluorescence intensity, fluorescence lifetime, and the number of available photons before photobleaching as a function of the number of identical emitters bound to a single IgG antibody. The detailed studies of FRET between individual fluorophores reveal complex through-space interactions. In general, even for two or three fluorophores immobilized on a single protein, homo-FRET interactions lead to an overall non-linear intensity increase and shortening of fluorescence lifetime. Over-labeling of protein in solution (ensemble) results in the loss of fluorescence signal due to the self-quenching of fluorophores making it useless for assays applications. However, in the single molecule regime, over-labeling may bring significant benefits in regards to the number of available photons and the overall survival time. Our investigation reveals possibilities to significantly increase the observation time for a single macromolecule allowing studies of macromolecular interactions that are not obscured by ensemble averaging. Extending the observation time will be crucial for developing immunoassays based on single-antibody.