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Current
Genomics
ISSN: 1389-2029

Current Genomics
Volume 9, Number 5, August 2008
Contents

Recent Advances in the Characterization of Genetic
Factors Involved in Human Susceptibility to Infection by Schistosomiasis
Pp. 290-300
A. Isnard and C. Chevillard
[Abstract]
Post-Translational Control of Sp-Family Transcription
Factors Pp. 301-311
J.S. Waby, C.D. Bingle and B.M.
Corfe
[Abstract]
How Drosophila melanogaster Forms its Mechanoreceptors
Pp. 312-323
D.P. Furman and T.A. Bukharina
[Abstract]
Genetic and Molecular Basis of QTL of Diabetes in
Mouse: Genes and Polymorphisms Pp. 324-337
P. Gao, Y. Jiao, Q. Xiong, C.-Y. Wang, I.
Gerling and W. Gu
[Abstract]
Multiple Hsp70 Isoforms in the Eukaryotic Cytosol:
Mere Redundancy or Functional Specificity? Pp.
338-348
M. Kabani and C.N. Martineau
[Abstract]
Can Systems Biology Understand Pathway Activation?
Gene Expression Signatures as Surrogate Markers for Understanding
the Complexity of Pathway Activation Pp. 349-360
H. Itadani, S. Mizuarai and H.
Kotani
[Abstract]
Abstracts

[Back to top]
Recent Advances in the Characterization of
Genetic Factors Involved in Human Susceptibility to Infection
by Schistosomiasis
A. Isnard and C. Chevillard
Human resistance to infection by schistosomes is associated
to a strong Th2 immune. However a persistent Th2 response
can cause severe kidney and liver disease in human. In this
review, we mainly focused on the control of infection levels
caused by schistosomes. Several experimental models allowed
us to better understand the immunological mechanisms of the
host against schistosome infection. High IgE and eosinophil
levels are associated with resistance to infection by schistosomes
and this effect is counterbalanced by IgG4. IgE and eosinophils
are highly dependent on IL-4, IL-13, and Il-5, which are three
main Th2 cytokines. We also examined the genetic factors involved
in human susceptibility to infection by schistosomiasis. Infection
levels are mainly regulated by a major locus SM1, in 5q31-q33
region, which contains the genes encoding for the IL-4, IL-13,
and Il-5 cytokines. An association between an IL13
polymorphism, rs1800925, and infection levels has been shown.
This polymorphism synergistically acts with another polymorphism
(rs324013) in the STAT6 gene, encoding for the signal
transducer of the IL13 pathway. This pathway has also been
involved in atopic disorders. As helminthiasis, atopy is the
result of aberrant Th2 cytokine response to allergens, with
an increased production of IL-4, IL-13, Il-9 and Il-5, with
high amounts of allergen-specific and total IgE and eosinophilia.
However, the Th2 immune response is protective in helminthiasis
but aggravating in atopic disorders. Several studies reported
interplay between helminthic infections and allergic reactions.
The different results are discussed here.
[Back to top]
Post-Translational Control of Sp-Family Transcription
Factors
J.S. Waby, C.D. Bingle and B.M.
Corfe
Sp-family transcription factors are widely expressed
in human tissues and involved in the regulation of many cellular
processes and response to cellular microenvironment. These
responses appear to be mediated by alterations in transcription
factor affinity for DNA rather than altered protein level.
How might such changes be effected? This review will identify
the range of known post-translational modifications (PTMs)
of Sp-factors and the sometimes conflicting literature about
the roles of PTMs in regulating activity. We will speculate
on the interaction between cell environment, chromatin microenvironment
and the role of PTM in governing functionality of the proteins
and the complexes to which they belong.
[Back to top]
How Drosophila melanogaster Forms its Mechanoreceptors
D.P. Furman and T.A. Bukharina
A strictly determined number of external sensory organs,
macrochaetes, acting as mechanoreceptors, are orderly located
on drosophila head and body. Totally, they form the bristle
pattern, which is a species-specific characteristic of drosophila.
Each mechanoreceptor comprises four specialized cells derived
from the single sensory organ precursor
(SOP) cell. The conserved bristle pattern combined with a
comparatively simple structure of each mechanosensory organ
makes macro-chaetes a convenient model for studying the formation
spatial structures with a fixed number of elements at certain
posi-tions and the mechanism underlying cell differentiation.
The macrochaete morphogenesis consists of three stages. At
the first stage, the proneural clusters segregate from the
massive of ectodermal cells of the wing imaginal disc. At
the second stage, the SOP cell is determined and its position
in the cluster is specified. At the third stage, the SOP cell
undergoes two asymmetric divisions, and the daughter cells
differentiate into the components of mechanoreceptor: shaft,
socket, bipolar neuron, and sheath.
The critical factor determining the neural pathway of cell
development is the content of proneural proteins, products
of the achaete-scute (AS-C) gene complex,
reaching its maximum in the SOP cell.
The experimental data on the main genes and their products
involved in the control of bristle pattern formation are systematized.
The roles of achaete-scute complex, EGFR and Notch
signaling pathways, and selector genes in these processes
are considered. An integral scheme describing the functioning
of the system controlling macrochaete development in D.
melanogaster is proposed based on analysis of literature
data.
[Back to top]
Genetic and Molecular Basis of QTL of Diabetes in
Mouse: Genes and Polymorphisms
P. Gao, Y. Jiao, Q. Xiong, C.-Y. Wang, I.
Gerling and W. Gu
A systematic study has been conducted of all available
reports in PubMed and OMIM (Online Mendelian Inheritance in
Man) to examine the genetic and molecular basis of quantitative
genetic loci (QTL) of diabetes with the main focus on genes
and polymorphisms. The major question is, What can the QTL
tell us? Specifically, we want to know whether those genome
regions differ from other regions in terms of genes relevant
to diabetes. Which genes are within those QTL regions, and,
among them, which genes have already been linked to diabetes?
whether more polymorphisms have been associated with diabetes
in the QTL regions than in the non-QTL regions.
Our search revealed a total of 9038 genes from 26 type 1 diabetes
QTL, which cover 667,096,006 bp of the mouse genomic sequence.
On one hand, a large number of candidate genes are in each
of these QTL; on the other hand, we found that some obvious
candidate genes of QTL have not yet been investigated. Thus,
the comprehensive search of candidate genes for known QTL
may provide unexpected benefit for identifying QTL genes for
diabetes.
[Back to top]
Multiple Hsp70 Isoforms in the Eukaryotic Cytosol:
Mere Redundancy or Functional Specificity?
M. Kabani and C.N. Martineau
Hsp70 molecular chaperones play a variety of functions
in every organiism, cell type and organelle, and their activities
have been implcated in a number of human pathologies, ranging
from cancer to neurodegenerative diseases. The functions,
regulations and structure of Hsp70s were intensively studied
for about three decades, yet much still remains to be learned
about these essential folding enzymes. Genome sequencing efforts
revealed that most genomes contain multiple members of the
Hsp70 family, some of which co-exist in the same cellular
compartment. For example, the human cytosol and nucleus contain
six highly homologous Hsp70 proteins while the yeast Saccharomyces
cerevisiae contains four canonical Hsp70s and three fungal-specific
ribosome-associated and specialized Hsp70s. The reasons and
significance of the requirement for multiple Hsp70s is still
a subject of debate. It has been postulated for a long time
that these Hsp70 isoforms are functionally redundant and differ
only by their spatio-temporal expression patterns. However,
several studies in yeast and higher eukaryotic organisms challenged
this widely accepted idea by demonstrating functional specificity
among Hsp70 isoforms. Another element of complexity is brought
about by specific cofactors, such as Hsp40s or nucleotide
exchange factors that modulate the activity of Hsp70s and
their binding to client proteins. Hence, a dynamic network
of chaperone/co-chaperone interactions has evolved in each
organism to efficiently take advantage of the multiple cellular
roles Hsp70s can play. We summarize here our current knowledge
of the functions and regulations of these molecular chaperones,
and shed light on the known functional specificities among
isoforms.
[Back to top]
Can Systems Biology Understand Pathway Activation?
Gene Expression Signatures as Surrogate Markers for Understanding
the Complexity of Pathway Activation
H. Itadani, S. Mizuarai and H.
Kotani
Cancer is thought to be caused by a sequence of multiple
genetic and epigenetic alterations which occur in one or more
of the genes controlling cell cycle progression and signaling
transduction. The complexity of carcinogenic mechanisms leads
to heterogeneity in molecular phenotype, pathology, and prognosis
of cancers.
Genome-wide mutational analysis of cancer genes in individual
tumors is the most direct way to elucidate the complex process
of disease progression, although such high-throughput sequencing
technologies are not yet fully developed. As a surrogate marker
for pathway activation analysis, expression profiling using
microarrays has been successfully applied for the classification
of tumor types, stages of tumor progression, or in some cases,
prediction of clinical outcomes. However, the biological implication
of those gene expression signatures is often unclear.
Systems biological approaches leverage the signature genes
as a representation of changes in signaling pathways, instead
of interpreting the relevance between each gene and phenotype.
This approach, which can be achieved by comparing the gene
set or the expression profile with those of reference experiments
in which a defined pathway is modulated, will improve our
understanding of cancer classification, clinical outcome,
and carcinogenesis. In this review, we will discuss recent
studies on the development of expression signatures to monitor
signaling pathway activities and how these signatures can
be used to improve the identification of responders to anticancer
drugs.
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