Microarray

Research essay by Kedar Ghimire/ Jacobs University Bremen

"Microarrays” Application and potential

Submitted by Kedar Ghimire, Earth

Jacobs University Bremen

9/5/2007

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen

Introduction The central dogma of biology suggests us that the genetic information flows from DNA to RNA and finally to the translation of proteins. This theory was first proposed by Francis Crick in 1957. The DNA gets coded to mRNA (messenger RNA) by the process called transcription. This process is facilitated by RNA polymerase and transcription factors. RNA structure resembles with that of DNA in many aspects except that RNA is single stranded and the DNA is double stranded and also has uracil instead of thymine in DNA. This mature mRNA will be transported into ribosome where it will be translated into amino acids. A series of 3 nucleotides determines the coding one amino acid. Eukaryotes genes contain coding regions (exons) and non-coding regions (introns). RNA goes through a series of modifications where exons are joined. The introns are removed by post-transcriptional modifications. This RNA formed after removing the non coding region is now termed as the mRNA. The process from transcription to translation can be referred to as gene expression. Epigenetics, environmental factors, cellular developmental stages are critical parameters guiding the gene expression pattern. One of the consequences of central dogma is that the genes codes for proteins. In order to study the expression pattern of thousands of genes we need a technology which is relatively convenient and can give a faster and reliable highthroughput. Older technologies to study gene expression pattern were often tedious and time consuming. Hence Microarrays has proven to be a revolution to molecular biologist in studying the gene expression. Research in molecular biology increased its scope in recent decades from the need of monitoring expression level of few genes to thousands of genes. By the help of this technique a gene can be monitored at its transcription level. Expression data of a mRNA from a large pool of genes can be easily collected by the help of DNA microarrays. DNA Microarray technology can be simply defined as a recent development that helps to know how much mRNA corresponding to a particular cell is present. This technique is a result of the technological advancement in the field of micro-fluidics, robotics and computer technology. Human Genome Project (HGP), Polymerase Chain reaction (PCR) and the base pairing rule found by Watson and Crick are some of the important groundwork which led to the development of this gene technology. Today, we can get thousand-fold high sensitivity in just a few minutes using modern microarray slides, fluorescent dye probes and laser detectors. What once used to take two days to visualize on X-ray film using radioactive test DNA now takes only few minutes, and also is automatically saved as a computer file. Microarray has revolutionized the field of life science today. Various types of microarrays are in development like protein microarray, antibody microarray, tissue microarray but this article would focus on DNA microarray. Complementary DNA Microarray (cDNA Microarrays) and oligonucleotide microarrays are two common types of microarrays used for gene expression. The main difference between these two is in their experimental design. C-DNA which can be obtained from

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen mRNA can be used as targets and upon fluorescent labeling they will be hybridized onto the Microarray. In order to understand the basic principle, a very simple application is provided. Suppose we are interested in studying whether a particular cell expresses the protein myoglobin. In order to achieve this we should isolate mRNA from the cell under observation. This single stranded RNA can be made to bind with the DNA probes that are in the chip surface. Finally a fluorescent dye can be used to study whether a particular DNA in the DNA chip has hybridized with the RNA or not. Suppose if we have following mRNA sequence available: 5' GAGCAAGCAU CCCGGGACU UUGGUGCUGA UGCCAGGGG 3'

Then the correct DNA target would be: 3’CTCGTTCGTA

GGGCCCCTGA

AACCACGAC

ACGGGTCCCC5’

From the above mentioned sequences RNA-DNA hybrid, the following of the double stranded hybrid is made: 5' GAGCAAGCAU CCCGGGACU UUGGUGCUGA UGCCAGGGG 3' 3’ CTCGTTCGTA GGGCCCCTGA AACCACGAC ACGGGTCCCC 5’ In this particular example, we do not see a great advantage of this DNA chip because we are looking at only a single gene. But if we were to use older techniques for 100000 genes then we had to carry the experiment 100000 times. But if we use a DNA chip then we can have 100000 different probes where the single stranded RNA can hybridize with DNA probes. One good advantage of DNA chip is that we can reuse it.

Design of DNA chips The design of DNA chips is usually divided into three different phases: Step 1: Designing Gene Probes A known sequence of DNA strands can be made by using Polymerase chain reaction (PCR). This known sequence acts as a probe to be hybridized with the single stranded RNA from the sample under investigation. Probes can be generated by two different methods. One of the methods uses PCR to generate cDNA probes. The other method utilizes synthetic oligonucleotide generated by chemical methods and spotted onto the chip by using photolithography. This latter approach is widely used by companies such as Affymetrix and Agilent Chips. While other companies like Nanogen Inc. use their own particular techniques to prepare probes and arrays and a lot of varieties are thus available according to the need to research and experiment.

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen

Fig 1: Photolithography used in designing Microarray

Figure adapted from: http://www.devicelink.com/ivdt/archive/98/09/009.html

Step 2: Design of Water Surface Techniques such as photolithography can turn the rough glass surface desirable for being able to act as a receptacle for DNA probes. Step 3.Genetic sequence deposition By the use of Robotic techniques we can deposit the genetic materials to the substrate.

Various Applications of Micro arrays DNA microarray is a useful tool in identifying the changes at the cellular level. Now, various applications of microarrays from molecular biological perspectives are described. DNA microarray finds its wide use in medicine, biotechnology, pharmaceuticals, bioinformatics etc. The application of DNA microarray has already been witnessed in identification of a diseased gene or novel drugs. Gene Expression and profiling Wen et. al. (1998) in PNAS has explained the use of microarray with Reverse transcriptase PCR (RT-PCR) to observe a high-resolution temporal map of fluctuations in mRNA expression of 112 genes during the development of the central nervous system of a rat. A functional relationship was found among the genes fluctuating in parallel. Genes categorized to distinct functional classes showed a particular expression profiles. Khan et. al (1999) in PNAS has shown the use of cDNA microarray for studying gene expression profile of 1238 cDNAs to investigate the gene expression profile of a group of a seven alveolar rhabdomyosarcoma (ARMS) cell lines which were characterized by the presence of PAX3-FKHR fusion gene. They reported that the clustering of the cells were due to the consistent pattern of gene expression by ARMS cells. Their research was of importance in using cDNA microarray technology in showing tumor-specific gene expression profile in human cancers. Each microarray experiment requires relatively large amount of material that has posed restrictions on the use of this high throughput technique. Development of sample amplification procedures has tried to solve this obstacle. Linear and exponential sample amplifications are two used methods to obtain gene expression data from small samples using microarray. The conservation of transcript abundance throughout the procedures,

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen has generally found to be at an acceptable limit in both strategies. Exponential amplification was found to be accurate than the linear strategy. Amplification efficiencies technically allow profiling of extremely small samples, from tens of nanograms to single cells. Various options were found by Nygaard and Eivind in 2005 for profiling small samples with the combination of amplification technology and microarray technology. cDNA microarrays are capable of profiling gene expression patterns of tens of thousands of genes in a single experiment (Duggan et. al., 1999). DNA microarray in detecting cancerous cells Microarray potential is virtually unlimited. Recently, Cowell and Hawthorn (2007) in the journal of Current Molecular Medicine reported about the application of microarray technology to the analysis of the cancer genome. The genetic events occurring in the development of a cancerous tissue can be traced by the use of DNA microarrays. The gene expression arrays give an estimation of the gain and loss of function of a tumorous cell. Traditionally, rodent bioassays were used to identify carcinogenic and toxicological substances. However these assays often take a long time and the dose required for these essays are relatively larger. Eric Lander from Massachusetts institute of Technology (MIT) first reported that it is possible to distinguish different types of cancers depending on their gene expression profile. One of the important finding made by Lander was that he was able to distinguish between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). This distinction between AML and ALL was not possible by pathological examination. In order to achieve this distinction mRNAs were obtained from bone marrow of 38 patients with either AML or ALL. These samples were labeled with Biotin and applied in a microarray containing probes for nearly 6800 genes. Chang et. al. (2005) in Stanford reported that a unique pattern of gene expression can be found in the cells recruited by breast cancers. Similarly it is also possible for researchers now to see how cancer promoting oncogenes disturb the expression of other genes. Microarrays are also used to see how these cancerous cells show response to some chemotherapeutic agents. Genes involved in transcription factor binding sites is made possible by using chromatin immunoprecipitation coupled with promoter microarrays (ChIP-chip). This helps to identify the genes involved in various cell cycles and in identifying cancer signatures. Rhodes et.al. compared 265 gene expression signatures with 361 sequence derived transcription factor binding site profile. Roughly 300 cases in which transcription factor was associated with cancer signature were identified. One possible conclusion that might be found from this experiment is that the transcription factors might be responsible for the expression of the gene. Usually when we see cells affected by different types of tumors by microscope, it is not distinct what type of tumor it is. But when we use Microarray technology this confusion can be avoided as the expression pattern for different type of tumor cells will be different.

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen

DNA micro arrays in anesthesia Not much has been understood regarding the effects of long term side effects of anesthetic agents. DNA microarray can screen mammalian genome to see which genes are expressed or suppressed due to its exposure to anesthetic agents. There might be side effects associated with anesthetic agents. These side effects can be as such as preconditioning, post-operative depression, hepatotoxicity etc. If these side effects result in change in the gene expression then this change can be figured out by using DNA microarrays. Primate behavioral neuroscience research A unique problem for primate research is the limited availability of speciesspecific arrays. Arrays designed for humans are often used, but expression level differences are inevitably limited by gene sequence differences in all cross-species array applications. Karssen et. al., 2005 showed that the application of human microarrays in nonhuman primate neuroscience research recovers useful information from thousands of genes, and provides an important strategy for explaining the molecular complexity of behavior and mental health. Non human primate research is important because they play a vital role in research on the neural basis of emotional, cognitive, and social aspects of behavior. The application of microarrays still presents various limitations and challenges for primate neuroscience research which is hoped to be overcome in coming days. For now, it is critical that the outcomes of microarray studies of nonhuman primates are validated and extended by the classic techniques (e.g., quantitative PCR, in situ hybridization, and immunohistochemistry) applied to new, independent sets of brain tissue samples. DNA micro arrays in C. elegans Microarray studies are used in C. elegans to study the gene expression patterns that are linked with a specific cell. The C. elegans gene chip designed by Affymetrix contains nearly 22,500 transcripts probes. DNA Microarray studies of C. elegans are useful in studying aging and age related diseases. Enzyme specificities and protein interactions Recently a lot of Biotech industries are using Microarray technology to identify enzyme specificities. By using techniques such as chemoselective coupling it is possible to generate microarray data from covalently attached peptides. This technology can help to understand about signal transduction pathways. Similarly, any contamination in the enzyme activities can also be detected. Optimal substrate for a particular enzyme can be identified. Just by performing one peptide synthesis it is possible to get hundreds of identical microarray copies. It is estimated that there are nearly 500 genes which encodes for protein kinase. But so far only few kinase encoding genes have been characterized. Because Kinase can serve as a potential drug targets, these days many research groups have attempted to identify the peptidic kinase substrates by using microarray-based approaches. Schutkowski et. al. (2004) were the first to perform the high density peptide microarray.

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen They were able to array 6912 peptides in one microscopic slide. Edwin southern (1999) discussed in nature genetics how arrays of oligonucleotides provide powerful tools to study the molecular basis of these interactions on a scale which is impossible using conventional analysis, which also should highlight the importance of understanding molecular interactions using microarrays. Two general approaches are followed for peptide Microarray technology. Peptide scans covering common kinase substrate proteins such as myelin basic proteins were printed onto chips (Reimer et.al, 2002). In the second approach, peptide libraries derived from phosphorylation sites in human proteins were used. Autoradiography and fluorescent labeling was carried out for detection approaches. Forensics Genetic fingerprints often serve as an important issue in identifying a criminals or personnel involved in the crime site. Since the expression pattern of genes from different people will be different, this indirect microarray technology can be used in identifying criminals in rape cases, paternity claims etc. A recent famous example of this can be seen on the issue of resolving who was the father of former playmate girl Anna Nicole smith and it was found that Larry Birkhead was the father at relative percent of 99.99% through genetic fingerprinting, which dissolved the court case. Using DNA microarrays to study Natural Variations (Gilad et al., 2006) The genetic and phenotypic variations occurring within and between different species are useful to understand the natural variations. Along with different technologies such as Solexa, DNA microarray has become a useful tool in detection and genotyping of single nucleotide polymorphism (SNPs). But the hybridization in the microarray is detected by various factors and hence it is exactly difficult to know the particular source of variation. Biomedical Applications and drug screening One of the future potential of Microarrays can be in the field of Biomarker discovery. Single gene biomarkers such as CD20 have been detected for the treatment of Acute Rejection (Sarwal et. al., 2003). The so called autoantibody microarrays have also been used for biomarker discovery (Caiazzo Jr et. al., 2007). Such high-density arrays have the ability to detect multiple autoantigens and improve sensitivity and specificity of detection for autoantibody profiling as the main challenge till now had been to working with autoantibodies which are usually very sensitive. Identification of potential prognostic markers for vulvar cancer has been done using simple immunohistochemical staining of tissue microarrays (Fons et. al., 2007). The procedure for this was rather simple and this might even change the medical expense for designing such markers and the cost of diagnostics might go down. Fossey et. al, (2007) claimed the identification of biomarkers for multiple sclerosis. Multiple sclerosis affects neurons, the cells of the brain and spinal cord that carry information, create thought and perception, and allow the brain to control the body. Their approach may have diagnostic utility not only for multiple sclerosis but also for other

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen clinically complex autoimmune diseases. They used quantitative real-time polymerase chain reaction analysis to identify a minimum number of genes of which transcript levels discriminated multiple sclerosis patients from patients with other chronic diseases and from controls. Gene expression can be used to see which particular genes will be stimulated by the effect of a particular drug. Similarly DNA chips can be used to decide which drug would be the most effective by their expression ways. Microarray Application in Microbial Ecology Research The activity of different microbial population can be measured in relation to the environment in which the microorganisms grow (Gentry et. al., 2006). Rhee et.al. (2004) reported the use of 50-Mer Oligonucleotide Microarrays in detecting the genes that are responsible for the biodegradation in the microbial communities. It was also possible to infer about the pathways involved in the biodegradation and metal resistance by using the microarrays. Usually the microarrays used in the environmental studies are classified into 3 major groups based on the types of probes arrayed. These three major classes are: Functional gene arrays (FGAs), community genome arrays (CGAs) and phylogenetic oligonucleotide array. The major enzymes responsible for environmental processes are probed by FGAs. CGAs are designed by using the DNA obtained from pre-culture microorganisms. Short synthetic oligonucleotide obtained from Ribosomal RNA (rRNA) was used in constructing phylogenetic oligonucleotide arrays. Tissue Microarrays: applications in urological cancer research Tissue Microarray (TMAs) is a useful tool in screening a large number of tissue banks for biomarker expression. Li et al. in 2003 showed that neutral amino acid transporter ASCT2 plays is role in intratumoral metabolism. 640 different tissues obtained by the surgical removal of prostate gland were microarrayed. "ASCT2 expression was inversely correlated (P = 0.046) to the duration of recurrence-free survival following surgical treatment (Li et al. 2003)" Microarray applications in infectious disease A gene expression data from can be obtained from an infectious host. This would help in predicting the virulence mechanism. Monitoring whole-genome host and pathogen gene expression can aid in providing a complete understanding of the progress of the infectious disease. This array can also show the response of host to its pathogens and vice versa. Before the microarray technology came into existence scientists used to sequence and monitor the events of a small-subset of genes which they suspect to be involved in virulence. But now a genome wide expression pattern gives a clear picture in understanding a wide range of genes.

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen One of the experiments in understanding pathogens response to its host environment was recently done. by Wolfgang et. al., 2004. They used GeneChip Pseudomonas aeruginosa genome arrays in order to understand the interaction occurring between the airway liquids infected from cystic fibrosis (CF) patients and P. aeruginosa. By understanding the genomic expression and the toxins expressed by P. aeruginosa, scientists have been able to recognize the mechanism for disease pathway. This has potential therapeutic applications. Similarly in understanding pathogens impact for host expression; Izmailova reported that Tat protein (a major HIV virulence factor) is the first to be infected by retroviruses. This gave an understanding of complete interferon pathway. According to Izamailova et.al. (2003), the expression of viral infection is carried on by the chemokines molecules as the ultimate virus target. A potential therapeutic outcome of this study may be in designing therapies against Tat proteins and therapeutic pathways. Yu et, al,. (2007) have implicated the use of genotyping microarray as the Rapid and sensitive detection of fluoroquinolone-resistant Escherichia coli from urine samples. This method can be used to diagnose various types of urinary tract infections (UTI) as UTI is among the most common bacterial in human beings with E coli being the major cause of infection. The DNA microarray test displayed an assay time of 3.5h, a sensitivity of 100CFU/ml, and the ability to detect fluoroquinolone-resistant E. coli in the presence of a 10-fold excess of fluoroquinolone-susceptible E. coli cells which is very rapid compared to other assays. Some of the other breakthroughs are that the microarray has been used to resequence the complete genome of SARS virus. These microarray technologies are also used in identifying an infecting pathogen. Each pathogen will have a unique combination of genetic make-up and hence the array sequencing can easily identify the distinct genetic composition of the pathogens. Multi-Pathogen Identification (MPID) microarray performed by Wilson et. al, (2002). This technology was successful in identifying eighteen different prokaryotes, eukaryotes and viruses. A major advantage of this technique was that it could detect pathogenic DNA as little as 10 femtograms. This amount of DNA was not detected by other detection methods. Microarray applications in other diseases Till now, scientists have not been able to use microarray for diseases like atherosclerosis but they might be able to add microparticles to the array of understanding of this disease process to have the chance to decrease its harmful effect on the individual and society in near future. Microarray allows the detection of labeled RNA hybridizing to DNA molecules attached to a solid surface, using this simple idea, it has already identified a thousand of genes potentially involved in cardiovascular medicine.(Joerg Herrmann, 2003).

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen

Fig 1: Microarray used in Multi-Pathogen Identification (MPID)

Figure adapted from Affymetrix application notes Microarray application in ion channels Ion channels are a group of membrane proteins and these proteins are very important target for drug discovery. Whole-genome microarrays have proved to be very important in case of cardiac ion channels. A large number of data sets obtained from whole-genome microarrays will be useful in various pathophysiological applications. Demolombe et.al.(2005) reported that they have developed a specialized DNA microarray compromising PCR amplified probes for most of the voltage gated Na+, Ca2+ , Cl-, and K+ channels alpha and beta subunits. A 3' untranslated region sequence specific for each channel genes was used as probes in their case. Anderle et.al (2003) studied the mRNA expression profiles of various genes that encodes for transporters and ion channels, in differentiating Caco-2 cells and human small intestine. In order to find the expression of the mRNA; microarray chip with 750 deoxyoligonucleotide probes was used. The expression profile of Caco-2 cells were compared with that of total RNA of human intestines by taking the ratio between fluorescence dye labeled cDNA derived from poly(A)+ RNA samples Caco-2 cells with the total RNA of human intestines. The finding of their report was that the Caco-2 cells are a suitable model in career-mediated transport in human intestines. But the expression of number of transporters and ion channel genes varied significantly and did not reflect mRNA levels in human intestine. Microarray screening in food safety Microarrays are excellent potential tools for monitoring and tracking foodborne pathogens. For this, cDNA microarray and tools of bioinformatics have been fused. The DNA microarray technology has been used to compare the gene expression profiles in liver among three groups of mice fed a diet containing 5% royal jelly, a diet containing 5% royal jelly stored at 40 °C for 7 d (40 – 7 d royal jelly) or a control diet which Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen provides the same total energy as royal jelly. The results suggest that the efficacy of royal jelly decreased and the toxicity of royal jelly increased during storage at high temperature. Rapid and sensitive detection of microbial pathogens is needed to ensure food safety. Recently, a fiber-optic DNA microarray using microsphere-immobilized oligonucleotide probes specific for the Salmonella invA and spvB genes was developed for the detection of Salmonella spp. A disposable microarray (ArrayTubes) has been developed for the detection of up to 90 antibiotic resistance genes in gram-positive bacteria by hybridization. A novel DNA-microarray based detection method has been recently reported (Roy and Sen, 2005). The technique has been used to analyse Campylobacter and non-Campylobacter reference strains and to detect Campylobacter directly from the faecal swabs. In order to utilize microarray technology to mainstream food safety it is important to develop various user-friendly tools that may be applied in a field setting. In addition, a standardized process for regulatory agencies is immediately needed to be developed which should act upon microarray-based data.

Future potential The future potential of Microarray is unbound and limitless. Affymetrix manufactured arrays can detect the expression patterns in the genes in yeast, mice, rats, humans etc. But the technology in itself is still in its infancy. Of course the major reason why it has superseded other technologies might be due to its small size which makes it portable. Recently, imaging-guided microarray had been established (Pereira et. Al, 2007). Its use has been implicated in Neuronal and aging diseases. Both of these diseases contribute to hippocampal dysfunction but molecular mechanisms underlying these diseases could be very different. Gene expression profiling can provide hints to these mechanisms. The analytical challenges in this process can be overcome with imageguided microarray and the separate mechanisms could be elucidated. While Baldwin and Salama (2007) have used genomic microarrays to study insertional/transposon mutant libraries, which is a novel method in enzymology. Such a combination of these methods facilitates pointing out large numbers of mutants for phenotypic studies, consequently improving both in the efficiency of genome-saturating library screens and in the functional annotation of unknown genes. Cobo and Concha (2007) hinted to the application of microarray technology for microbial diagnosis in stem cell cultures. Stem cell cultures are contaminated by different pathogens which renders them useless to use in regenerative medicine and transplantation in humans. Thus, microbial diagnosis for stem cell cultures can be done in a cheap and effective manner. These were just few future potentials which have turned into reality now. One thing to notice is that biological variability can arise from independently-prepared RNA samples. Hence multiple arrays might be needed to overcome this variability. Similarly

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen some other questions for the experimental design can be as the amount of RNA needed for hybridization. Usually 2–5μg of total RNA is sufficient for single array hybridization. One of the biggest problems in Microarray analysis is that the gene expression level might not exactly correlate with protein levels. Techniques such as immunolocalization can be used to determine the protein level. It is also a debated topic that biologists need to know more mathematics than they currently   know.   In   order   to   analyze   various   potential   biological   data   that   might   be  obtained from Microarray, biologists should be more motivated and keen to understand  that mathematical languages. However transdisciplinary courses such as bioinformatics,  biostatistics, and biomechanics are some of the backgrounds that are trying to cover both  the   aspects  of  mathematics  and  biology.  There  are  various  web  based  tools  for  gene  analysis such as gene expression pattern analysis suite (GEPAS), Expression Profiler: next  generation (EP: NG), and Microarray data analysis web tool (MIDAW). These web based  tools   have   greatly   aided   in   understanding   the   enormous   data   potential.   Similarly   the  analysis technique called clustering includes a number of statistical and computational  tools.  Agglomerative hierarchical clustering, k­means, k­medians, self­organizing maps,  and   self­organizing   tree   algorithm   are   some   of   the   statistical   tools   in   analyzing   the  Microarray data.  Gene expression microarrays are being used widely to address a myriad of complex biological questions. Microarrays offer the promise of discoveries far greater than those happened when recombinant DNA methods were developed. Molecular biology and genetics have advanced much in the recent years. But still much not have been understood in terms of analyzing the data obtained from Microarray. Lot can be done to make all these analyzing methods more robust and efficient. Some of the areas that must be looked into in the future are the efficient data analysis techniques, image recognition techniques. Though DNA chip has been one of the breakthroughs, there lies a lot of challenges like increasing the number of arrays in a single chip. Similarly the current price of a single Microarray is rather expensive for most of the labs that are not well equipped financially. Thus scientists working in this field should also look at minimizing the cost factor involved in the production of DNA chip. Today, lasers can detect very low levels of fluorescent dyes, and this is a plus point for microarray technology. A hybridized microarray slide is inserted into the microarray reader or scanner. Filters distinguish the red and green wavelengths of the fluorescent dyes. A detector measures the intensity of each spot. New approaches in statistics are being developed to help us interpret the gene expression patterns and verify results. DNA chips promise to carry the way of understanding genomes to a whole new level, and to bring tools for getting DNA-sequence information out of research labs into hospitals in near future.

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen Thus for future, microarray should be combined with other powerful technology to make it more efficient, useful and multipurpose then only can its true potential can be exploited.

References Ana Carolina Pereira, William Wu and Scott a small (2007) Imaging-Guided Microarray: Isolating Molecular Profiles That Dissociate Alzheimer's Disease from Normal Aging; Ann. N.Y. Acad. Sci. 1097: 225-238 Alter O, Brown P, Botstein D (2000) Singular value decomposition for genome-wide expression data processing and modeling. Proc Nat Acad Sci USA. Adriaan M. Karssen, Jun Z. Li, Song Her, Paresh D. Patel, Fan Meng, Simon J. Evans, Marquis P. Vawter, Hiroaki Tomita, Prabhakara V. Choudary, William E. Bunney, Jr., Edward G. Jones, Stanley J. Watson, Huda Akil, Richard M. Myers, Alan F. Schatzberg and David M. Lyons (2005) Application of microarray technology in primate behavioral neuroscience research. Methods, vol 38. issue 3, 227-234, models for primate behaviour. David J Duggan, Michael Bittner, Yidong Chen, Paul Meltzer & Jeffrey M. Trent (1999), Expression profiling using cDNA microarrays, Nature Genetics 21, 10 - 14 David N. Baldwin and Nina R. Salama (2007), Using Genomic Microarrays to Study Insertional/Transposon Mutant Libraries, methods in enzymology, volume 421, 2007, 90110 Edwin Southern, Kalim Mir & Mikhail Shchepinov (1999), Molecular interactions on microarrays, Nature Genetics 21, 5 - 9 F. Cobo and Á Concha (2007) Application of microarray technology for microbial diagnosis in stem cell cultures: a review, Cytotherapy, volume 9, I1, 53-59 Fons G, Burger MP, Ten Kate FJ, van der Velden J (2007) Identification of potential prognostic markers for vulvar cancer using immunohistochemical staining of tissue microarrays. International Journal of Gynecological Pathology. 26(2):188-193. Cowell and Hawthorn (2007) The application of microarray technology to the analysis of the cancer genome. Curr Molec Med 7:1:103-120 Wen et al. (1998) Large-scale temporal gene expression mapping of central nervous system development. PNAS, 334-339

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen Khan et al, (1998) Gene Expression Profiling of Alveolar Rhabdomyosarcoma with cDNA Microarrays, Cancer Research 58, 5009-5013

Demolombe et.al.(2005) Functional genomics of cardiac ion channel genes, Cardiovasc Res., 67(3):438-47 Christine Debouck & Peter N. Goodfellow (1999), DNA microarrays in drug discovery and development, Nature Genetics 21, 48 - 50 doi:10.1038/4475 Brady, G. (2000) Expression profiling of single mammalian cells — small is beautiful. Yeast 17:211-217. Joerg Herrmann (2003), New kits on the blot—can we microarray the future of atherosclerosis? Cardiovascular research, vol 60, issue 2, 220-222 Li F, and Stormo GD (2001) Selection of optimal DNA oligos for gene expression arrays. Bioinformatics 17(11): 1067-1076. Robert J Caiazzo Jr, Oliver W Tassinari, Joshua R Ehrlich, Brian CS Liu (2007), Autoantibody microarrays for biomarker discovery, Expert Review of Proteomics, April 2007, Vol. 4, No. 2, Pages 261-272 Sashwati Roy and Chandan K. Sen (2005) cDNA microarray screening in food safety, Toxicology, Volume 221, Issue 1, 128-133 Vigdis Nygaard and Eivind Hovig (2005), Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling, Nucleic Acids Res. 2006; 34(3): 996–1014. W. J. Wilson, C. L. Strout, T. Z. DeSantis, J. L. Stilwell, A. V. Carrano and G. L. Andersen (2002) Sequence-specific identification of 18 pathogenic microorganisms using microarray technology. Molecular and Cellular Probes (2002) 16, 119–127 doi:10.1006/mcpr.2001.0397 Wolfgang M.C., Jyot J., Goodman A.L., Ramphal R., & Lory S. (2004) Pseudomonas aeruginosa regulates fl agellin expression as part of a global response to airway fl uid from cystic fi brosis patients. Proc.Natl.Acad.Sci.U.S.A 101, 6664-6668. Yue H et al, (2001) An evaluation of the performance of cDNA microarrays for detecting changes in global mRNA expression. Nuc. Acids. Res. 29(8): e41.

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart

Research essay by Kedar Ghimire/ Jacobs University Bremen Yu X, Susa M, Weile J, Knabbe C, Schmid RD and Bachmann TT (2007) Rapid and sensitive detection of fluoroquinolone-resistant Escherichia coli from urine samples using a genotyping DNA microarray. Int J Med Microbiol. 2007 May 4

Websites consulted http://genome-www5.stanford.edu/microarray/SMD/index.shtml http://en.wikipedia.org/wiki/DNA_microarray http://science-education.nih.gov/newsnapshots/TOC_Chips/Chips_RITN/chips_ritn.html http://www.ncbi.nlm.nih.gov/About/primer/microarrays.html http://www.bio.davidson.edu/Courses/genomics/chip/chip.html http://learn.genetics.utah.edu/units/biotech/microarray/ http://www.microarray.org/sfgf/

© Kedar Ghimire

Course High-throughput Screening Technology II / Instructor of record: Dr. Helge Weingart