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Current
Pharmaceutical Biotechnology
ISSN: 1389-2010
Current Pharmaceutical Biotechnology
Volume 9, Number 5, October 2008
Contents
Serial Analysis of Gene Expression (SAGE)
Guest Editor: Sergey V. Anisimov
Editorial Pp. 337
Serial Analysis of Gene Expression (SAGE): 13 Years
of Application in Research Pp. 338-350
S.V. Anisimov
[Abstract]
Scaling Down SAGE: From miniSAGE to microSAGE
Pp. 351-361
N.A. Datson
[Abstract]
Long-Short-Long Games in mRNA Identification:
The Length Matters Pp. 362-367
S.M. Wang
[Abstract]
SuperSAGE: A Modern Platform for Genome-Wide
Quantitative Transcript Profiling Pp. 368-374
H. Matsumura, D.H. Krüger, G. Kahl
and R. Terauchi
[Abstract]
Application of Serial Analysis of Gene
Expression in Cancer Research Pp. 375-382
T. Yamashita, M. Honda, and S.
Kaneko
[Abstract]
SAGE Application in Hematological Research
Pp. 383-391
S.-I. Hashimoto and K. Matsushima
[Abstract]
SAGE Application in the Study of Diabetes
Pp. 392-399
T. Takamura, H. Misu, T. Yamashita
and S. Kaneko
[Abstract]
General Articles
Spirulina in Health Care Management Pp.
400-405
Archana Kulshreshtha, Anish Zacharia J,
Urmila Jarouliya, Pratiksha Bhadauriya, G.B.K.S. Prasad and
P.S. Bisen
[Abstract]
Microbubble: A Potential Ultrasound Tool
in Molecular Imaging Pp. 406-410
Rajesh M. Patel
[Abstract]
Research Article
Single Molecule Studies of Multiple-Fluorophore Labeled Antibodies.
Effect of Homo-FRET on the Number of Photons Available Before
Photobleaching Pp. 411-420
R. Luchowski, E.G. Matveeva, I. Gryczynski, E.A. Terpetschnig,
L. Patsenker, G. Laczko, J. Borejdo, and Z. Gryczynski
[Abstract]
Abstracts
[Back to top]
Editorial:
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 high-throughput gene expression profiling methods for many
decades to come.
Sergey V. Anisimov
Guest Editor
Head, Research Department,
V.A.Almazov Federal Center for Heart, Blood & Endocrinology,
Akkuratova Str.,2,
197341, Saint-Petersburg,
Russia;
Tel: +7 (812) 702 3733;
Fax: +7 (812) 702 3701;
E-mail: grants@hbe-centre.ru
[Back to top]
Serial Analysis of Gene Expression (SAGE): 13 Years
of Application in Research
S.V. Anisimov
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.
[Back to top]
Scaling Down SAGE: From miniSAGE to microSAGE
N.A. Datson
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 (deepSAGE), 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.
[Back to top]
Long-Short-Long Games in mRNA Identification: The Length Matters
S.M. Wang
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.
[Back to top]
SuperSAGE: A Modern Platform for Genome-Wide Quantitative
Transcript Profiling
H. Matsumura, D.H. Krüger, G. Kahl
and R. Terauchi
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.
[Back to top]
Application of Serial Analysis of Gene Expression in Cancer
Research
T. Yamashita, M. Honda, and S.
Kaneko
It is now widely believed that tumors originate from
normal cells as a result of accumulated genetic/epigenetic
changes. These alterations affect the signaling pathways at
transcriptional and post-transcriptional level that drive
cells into uncontrolled cell division, growth, and migration.
Recent advancement of molecular technologies have yielded
comprehensive gene expression profiling techniques that have
successfully provided candidate diagnostic and prognostic
markers in human cancers. Serial Analysis of Gene Expression
(SAGE) is a technology to facilitate the measurement of mRNA
transcripts of normal and malignant tissues in a non-biased
and highly accurate and quantitative manner. SAGE produces
a comprehensive gene expression portrait without α
priori gene sequence information, leading to the identification
of novel transcripts potentially involved in the pathogenesis
of human cancer. In this review, we provide a brief outline
of SAGE to underscore the advantages of the method relative
to the other gene expression profiling approaches in cancer
research. We also summarize the progression of recent gene
expression profiling studies and discuss the current topics
of SAGE analysis in cancer research for the development of
novel therapeutic interventions.
[Back to top]
SAGE Application in Hematological Research
S.-I. Hashimoto and K. Matsushima
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.
[Back to top]
SAGE Application in the Study of Diabetes
T. Takamura, H. Misu, T. Yamashita
and S. Kaneko
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.
[Back to top]
Spirulina in Health Care Management
Archana Kulshreshtha, Anish Zacharia J,
Urmila Jarouliya, Pratiksha Bhadauriya, G.B.K.S. Prasad and
P.S. Bisen
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, Υ-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 anti-diabetic
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.
[Back to top]
Microbubble: A Potential Ultrasound Tool in Molecular Imaging
Rajesh M. Patel
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.
[Back to top]
Single Molecule Studies of Multiple-Fluorophore Labeled Antibodies.
Effect of Homo-FRET on the Number of Photons Available Before
Photobleaching
R. Luchowski, E.G. Matveeva, I. Gryczynski, E.A. Terpetschnig,
L. Patsenker, G. Laczko, J. Borejdo, and Z. Gryczynski
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 Förster-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 over-all 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.
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