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Apr 1, 2012 (Vol. 32, No. 7)

Exploiting Gene-Expression Data

  • The field of gene expression continues to grow and evolve. Commonly used technologies such as microarrays are packing higher densities in a smaller footprint, and qPCR is becoming more accurate and reproducible with new guidelines in place.

    Additionally, the introduction of next-generation sequencing has revolutionized the study of transcriptomics by promoting RNA analysis via cDNA sequencing on a massive scale (RNA-seq). The latter eliminates the limited dynamic range of detection in microarrays but adds its own challenges of reproducibility and interpretation.

    GEN spoke with several researchers who shared their insights on how they are utilizing gene-expression technologies, the challenges faced, and what they expect of the field for the future.

  • Transcriptome Analysis

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    Researchers at UPenn are studying Vibrio cholerae in order to better understand how the bacteria cause disease by manipulation of gene expression and also to develop a therapeutic against its targets.

    Pathogens subvert the immune system by sensing and then responding to avert host protective responses. This is accomplished by activating and expressing the pathogen’s virulence genes. Jay Zhu, Ph.D., assistant professor of microbiology, University of Pennsylvania Perelman School of Medicine, suggests that pathogens may also specifically repress other sets of their genes to “outsmart” the innate immune response.

    “We are studying Vibrio cholerae, the causative agent of cholera. These bacteria employ both positive and negative transcriptional regulation in order to colonize the host intestine and establish infection. Our goal is not only to better understand how the bacteria cause disease by manipulation of gene expression, but also to develop a therapeutic against its targets.”

    Dr. Zhu says the organism’s entire genome has been sequenced, allowing for easier reading of gene-expression changes. To assess how V. cholerae targets and works in the target intestinal tract, they first infect mice with the organism and then monitor intestinal responses.

    “Although we could isolate RNA from the intestine, it is difficult to utilize a typical microarray to analyze gene-expression changes because one cannot get high-quality bacterial RNA from such a complex tissue. Therefore, we use other genetic tools such as transposon mutagenesis, RNA-seq that allows sequencing of the entire transcriptome. We next confirm our findings using RT-PCR to confirm with a few targets for screening.

    According to Dr. Zhu, these approaches established that components of flagellar biosynthesis also controlled so-called quorum sensing by regulating hapR expression.

    “Quorum sensing refers to the ability of bacteria communicating with each other to determine certain cellular process in the whole population. Our studies identified components of flagellar biosynthesis that also participated in the control of quorum sensing so that V. cholerae can sense the “right environment” (i.e., intestines) to activate virulence genes. Overall this data provided a link between regulation of motility and regulation of quorum sensing by V. cholerae during infection of hosts.”

    Dr. Zhu says these studies provide a clearer picture of how the bacteria can access colonization sites and at the same time allow the natural expression of virulence genes.

  • In Search of Biomarkers

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    Researchers at the Mayo Clinic are attempting to predict which subsets of patients will respond most effectively to a given treatment using a combination of technologies, including laser capture microdissection and DNA amplification.

    “We are now moving into an era of individualized medicine,” reports George Vasmatzis, Ph.D., assistant professor, department of laboratory medicine and pathology, Mayo Clinic. “The clinical dilemma is to predict which subsets of patients will respond most effectively to a given treatment and to develop specific tests for that. The goals of such molecularly targeted medicine depend on the identification of specific biomarkers that could stratify patient populations.”

    Dr. Vasmatzis utilizes a combination of technologies. He first captures the specific cell populations of interest using laser capture microdissection (LCM) and then amplifies the genomic DNA. The amplified DNA from these samples is analyzed using next-generation sequencing to evaluate DNA changes. Finally, he validates his findings using microarrays in which RNA levels can be correlated with genetic expression.

    “We find that the use of these technologies together provides a powerful means to profile as well as stratify patient populations. We are able to separate different grades and different types of tumors and then look for genetic changes. Next-gen sequencing is capable of sequencing both sides of DNA fragments and can do so for hundreds of millions of sequences. For a couple thousand dollars, one can virtually cover an individual’s entire genome.”

    Looking next at RNA expression data from microarrays can provide a global look at what is upregulated or downregulated. For example, using this methodological approach, Dr. Vasmatzis and colleagues discovered recurrent translocations in the DUSP22 phosphatase gene on 6p25.3. “DUSP22 is an important prognostic biomarker in T-cell lymphomas. We hope to utilize this same approach to also work on other cancers such as lung, endometrial, and prostate cancers.”

  • Juvenile Idiopathic Arthritis Subtypes

    Another example of the use of gene-expression profiling is for identifying patient subtypes in juvenile idiopathic arthritis (JIA). “We are studying gene-expression analysis in peripheral blood mononuclear cells (PBMC) in order to identify sets of genes that may help us better understand differences within the patient population,” says Michael G. Barnes, Ph.D., research associate, division of rheumatology, Cincinnati Children’s Hospital Medical Center, speaking on behalf of a large team of researchers involved in the project, which was supported by the NIH.

    Juvenile idiopathic arthritis (JIA) encompasses the majority of childhood arthritis. Although seven subtypes have been described, there is increasing evidence for heterogeneity even within these types. “Use of genome-level technologies can provide a comprehensive determination of genetic and genomic biological signatures, giving an unprecedented opportunity to define JIA on the basis of molecular phenotypes and can help us understand disease mechanisms. This may ultimately help improve therapeutic approaches,” Dr. Barnes explains.

    To begin the analysis, PBMC are first isolated using Ficoll gradient centrifugation. RNA is immediately stabilized and later isolated and purified. “We assess RNA quality with standard protocols and then label it using NuGEN Ovation (NuGEN Technologies). Next we hybridize the labeled samples to Affymetrix GeneChips (Affymetrix). This array has nearly 55,000 probe sets and can measure up to 47,000 transcripts.”

    Processing the monumental amount of data generated into meaningful results requires the use of bioinformatic approaches. “To begin analysis, we import the data we generate into a program called GeneSpring GX (Agilent Technologies). We then adjust batch to batch variation by a process called distance-weighted discrimination. Next we identify genes with different levels between groups. Finally, we perform a functional analysis of the data.”

    Employing these approaches, Dr. Barnes and colleagues found substantial PBMC gene-expression differences in patients with early-onset JIA as compared to those with late-onset disease.

    “Age of onset may be an important characteristic for classifying certain JIA patient subtypes. Today, differential diagnosis between the oligoarticular and polyarticular JIA subtypes is based, to a large extent, on how many joints are affected in patients. Utilizing molecular approaches in addition to other biologic markers like antinuclear antibodies (ANA) provides great potential to grasp pathologic mechanisms that may help explain the differences between patients with early and late disease onset. Understanding these processes ultimately may lead to better treatments for JIA.”


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