Group 8 Project - Microarray

From CellBiology
DNA microarray : A two-colour fluorescent image

Microarrays are a type of multiple technology that measure the mRNA levels of tens of thousands of genes in tissue samples simultaneously in a high-throughput and cost-effective manner.[1] They involve the use of different nucleic acid probes that are fluorescently labeled and hybridized (chemically attached) to a substrate (which can be a microchip, a glass slide or a microsphere-sized bead).[2] The obtained image conveys the various gene expression of the genes being analysed where the intensity of fluorescence is proportional to the amount of gene expression.[3]

Microarray technology is used for whole-genome and large-scale profiling of gene expression under various conditions.[4] They have been intensively applied to screen for genes involved in specific biological processes of interest such as diseases (cancer) or responses to environmental stimuli (radiation). [5] Additionally, microarrays are used to survey the expression of thousands of genes in a single experiment. Applied creatively, they can be used to test or even generate new hypotheses. As the technology becomes more accessible, microarray analysis is an important application in diverse areas of biology. [6]

In this website, the focus will be on the history of the development of microarrays, an overview of common types of microarrays, and a discussion on the benefits and drawbacks of the use of microarrays. There are various types of microarrays, and to name a few, they can include: DNA Microarrays, Protein Microarrays, Tissue Microarrays, Cellular Microarrays and Antibody Microarrays. The focus in the following sections will be of DNA, protein and tissue microarrays.

History

1980 - Protein microarray-based ligand binding assays were initially developed by Ekins et al(protein microarray) [7]

1986 - Multi-tissue blocks were introduced by H. Battifora (tissue microarray)

1987 - Distinct DNAs in arrays for expression profiling were collected (DNA microarray) [8]

1990 - The checkerboard tissue block was used (tissue microarray)

1991 - Photolithographic printing (Affymetrix)[9]

1994 - The first cDNA collections were developed at Stranford[10]

1995 - Miniaturized microarrays for gene expression profiling was used (DNA microarray).[11] Gene expressions were also quantitatively monitored using a cDNA microarray.[12]

1997 - A complete eukaryotic genome (Saccharomyces cerevisiae) on a microarray was published (DNA microarray) [13]

1998 - Tissues of regular size and shape that can be more densely and precisely arrayed was developed by J. Kononen (tissue microarray)

2002 - A DNA microarray which is used to follow changes in gene expression as Deinococcus radiodurans recovers from a sub-lethal dose (3000Gy) of ionizing radiation was constructed [14]

2004 - The entire human genome is successfully printed on one microarray.[15]


Current Researches

Types of Microarrays

There are various types of microarrays. These include DNA microarrays, protein microarrays, tissue microarrays, cellular microarrays (transfection microarrays), chemical compound microarrays, antibody microarrays and carbohydrate arrays (glycoarrays). Among the various types, DNA microarrays, protein microarrays and tissue microarrays are most widely used.

DNA Microarray



DNA Microarrays (also known as oligonucleotide arrays, GeneChip arrays, or simply ‘chips’) are a type of nucleic acid-based multiplex technique involving high-density arrays of nucleic acids on glass that allows to evaluate mRNA abundance of up to tens of thousands of genes simultaneusly. [16]

Comparison between one-colour expression analysis and two-colour expression analysis

Procedure

Small dots of oligonucleotides or cDNA are placed on a microscope slide. The cDNA is then flourescently labeled and hybridized to the chip to reveal the expression level of each gene. The intensity of the flourescence is proportional to the level of gene transcription.[17]

To get a quantitative result of gene expression (also known as expression profiling), one- and two-colour fluorescent probe hybridization can be used. One-colour fluorescent probe involves the production of the expression profile of each sample on a single microarray using a single fluorescent label. The separate images can therefore be compared. Two-colour fluorescent probe hybridization involves the labeling of two samples separately with different fluorescent tags on a single microarray. The microarray is scanned to produce images from the two channels. Both images can be superimposed in order to determine which genes are activated, repressed, and expressed equally between the two samples. [18] Either of the two fluorescent schemes enable the comparison of different tissue types.


DNA Microarray robot

Applications

One of the most important applications of DNA Microarrays is the monitoring of gene expression where the abundance of the mRNA produced is determined for each gene. Such differences in gene expression are accountable for morphological and phenotypic differences as well as indicative of cellular responses to environmental stimuli and perturbations. Changes in the multi-gene patterns of expression can provide clues about regulatory mechanisms and broader cellular functions and biochemical pathways. In the context of medicine and treatment, such changes in patterns of expression can help to determine the causes and consequences of disease, how drugs and drug candidates work in cells and organisms, and what gene products might have therapeutic uses themselves or may be appropriate targets for therapeutic intervention. [19]

Advantages

In earlier experiments, only a small set of genes which were subjectively thought to be important to a process were included on the arrays. With the invention and use of DNA microarrays, their ability to analyse the gene expression of up to tens of thousands of genes at once makes it unnecessary to guess what the important genes or mechanisms are in advance. This therefore allows less bias and consequently, a broader and more thorough analysis of the cellular response. [20]

Challenges

Accurate analysis and interpretation of data have always been a challenge with microarrays. [21] Specifically, the detection and determination of the relative abundance of diverse individual sequences in complex DNA samples is a recurring experimental challenge in DNA Microarrays. [22]

To overcome such challenges, DNA Microarrays can be used with other techniques such as fluorescent labeling. This not only allows the determination of specific sequences represented in DNA samples, but it also enables an accurate and reliable comparison of the relative abundance of specific sequences between complex samples. [23]


Links:

Protein Microarray


In the past few years, protein microarray technology has shown its great potential in basic research, diagnostics and drug discovery. It has been applied to analyse antibody–antigen, protein–protein, protein–nucleic-acid, protein–lipid and protein–small-molecule interactions, as well as enzyme–substrate interactions. Recent progress in the field of protein chips includes surface chemistry, capture molecule attachment, protein labeling and detection methods, high-throughput protein/antibody production, and applications to analyse entire proteomes. [24]

Types of Protein Microarrays

There are mainly three types of protein microarrays which are currently used to study the biochemical activities of proteins: analytical microarrays, functional microarrays and reverse phase microarrays.

Student-drawn Diagram Showing Different Types of Protein Microarrays. Adapted from Protein Microarray Technology
Schematics of the ci-ELISA and protein microarray procedures
The Major Types of Protein Microarrays
Description Analytical Microarrays Functional Protein Microarrays Reverse Phase Protein Microarray
Definition Analytical microarrays are typically used to profile a complex mixture of proteins in order to measure binding affinities, specificities, and protein expression levels of the proteins in the mixture.[25] Functional protein microarrays differ from analytical arrays in that functional protein arrays are composed of arrays containing full-length functional proteins or protein domains. [26] Reverse Phase Protein Microarray (RPA) related to analytical microarrays is a micro-cell lysate dot-blot that allows measurement of protein expression levels in a large number of biological samples simultaneously in a quantitative manner when high-quality antibodies are available.
Description In this technique, a library of antibodies, aptamers, or affibodies is arrayed on a glass microscope slide. The array is then probed with a protein solution. A full-length functional proteins or protein domains is arrayed on a glass microscope slide. The array is then probed with a protein solution. In RPA, cells are isolated from various tissues of interest and are lysed. The lysate is arrayed onto a nitrocellulose slide using a contact pin microarrayer. The slides are then probed with antibodies against the target protein of interest, and the antibodies are typically detected with chemiluminescent, fluorescent, or colorimetric assays. Reference peptides are printed on the slides to allow for protein quantification of the sample lysates.
Use These types of microarrays can be used to monitor differential expression profiles and for clinical diagnostics. Examples include profiling responses to environmental stress and healthy versus disease tissues. [27] These protein chips are used to study the biochemical activities of an entire proteome in a single experiment. [28] RPAs allow for the determination of the presence of altered proteins that may be the result of disease.
Special Features Antibody microarrays are the most common analytical microarray. [29] They are being increasingly employed for biological discovery purposes which include the characterization of autoantibody responses, antibody specificity profiling, protein-protein domain interaction profiling and a comprehensive characterization of coiled-coil interactions. [30] Specifically, post-translational modifications, which are typically altered as a result of disease, can be detected using RPAs. [31] Once it is determined which protein pathway may be dysfunctional in the cell, a specific therapy can be determined to target the dysfunctional protein pathway and treat the disease of interest.

Protein Microarray vs ELISA

Zhong et al.' s study has shown that protein microarray technology is a more sensitive, reliable and efficient method for small molecule detection than traditional ELISA. In the study, the protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique.[32]

Tissue Microarray


Tissue microarrays (TMA) consist of paraffin blocks in which up to 1000 separate tissue cores are assembled in array fashion to allow multiplex histological analysis. This technique is commonly performed by the Beecher Instruments MTA-1 tissue arrayer.

Links: Instruction Manual Manual Tissue Arrayer MTA-1

Procedure

To produce a tissue microarray, a hollow needle is used to remove tissues (0.6 mm in diameter) from desired clinical biopsies or tumor samples, usually during surgery. These tissue cores are fixed in formalin and embedded in a recipient paraffin block in a precisely spaced array pattern. Sections from this block are cut using a microtome, mounted on a microscope slide and then analyzed by standard histological analysis. Each microarray block can be cut into 100 – 500 sections, which can be subjected to independent tests. Tests commonly employed in tissue microarray include immunohistochemistry, fluorescent in situ hybridization and analysis of cancer samples. [33]

Immunohistochemistry in normal bronchial epithelium (A–B) and in cancer epithelium(C–H) on tissue microarray

Immunohistochemical analysis

Tissue microarrays from paraffin-embedded blocks were always used for the immunohistochemistry (IHC) experiments. One common use of IHC is to obtain antigens from the tissues. Sections from the blocks were deparaffinized by xylene and rehydrated by degraded ethanol. Antigen retrieval was performed by heating the sample in a microwave oven with occasional interruption to avoid tissue degradation by excessive heat. Immunostaining was performed with the Lab Vision Autostainer and the samples were then counterstained with hematoxylin, rinsed with ethanol, dried and visualized by light microscopy. IHC allows the differentiation of cancer tissues from normal tissues and can also be used to evaluate the status of a gene.[34][35]

Fluorescent in situ hybridization

Fluorescent in situ hybridization (FISH) is used to detect and localize the presence or absence of specific DNA sequences on chromosomes by using fluorescent probes that bind to only those parts of the chromosome with which they show a high degree of sequence similarity. The wavelength and concentration of DNA can then be measured. Isolated DNA (using isolation kit such as QiAmp DNA ) is quantified by a fluorometric assay (e.g. Quant-iT Pico Green dsDNA Kit) and its fluorescence is measured by a microplate fluorescence reader (e.g. TECAN SpectrafluorPLUS). Both the excitation wavelength and the emission wavelength are measured and the DNA concentrations can be calculated from a standard curve. [36]

Both Immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) are widely used in evaluating the status of a gene and assisting research especially cancer. For example, breast cancer is caused by an overexpression of HER2(human epidermal growth factor receptor-2) proto-oncogene that initiates intracellular signaling pathways involved in cell proliferation, differentiation, migration and apoptosis. Trastuzumab is a humanized monoclonal antibody that targets the HER2 extracellular domain and inhibits HER2-positive tumor cell proliferation to treat breast cancer. The accurate evaluation of HER2 status is essential for optimal patient selection for trastuzumab, which is done by IHC and FISH. In contrast, FISH has been shown to more accurately select patients than IHC, but is more costly and not routinely available. Most researches use IHC alone but combine FISH if ambiguous samples are present.[37]

Fluorescence in situ hybridization of breast cells on tissue microarray.

Significance in cancer analysis

Analysis of hundreds of specimens from patients in different stages of disease, especially breast and lung cancer, is required to establish the diagnostic, prognostic and therapeutic importance of each of the emerging cancer gene candidates. Tissue microarray facilitates gene expression and copy number surveys of very large numbers of tumors. Up to 1000 biopsies from individual tumors can be distributed in a single tumor tissue microarray. Sections of the microarray provide targets for parallel in situ detection of DNA, RNA and protein targets in each specimen on the array, and consecutive sections allow the rapid analysis of hundreds of molecular markers in the same set of specimens. This is[38]

The validation of all potential role in cancer or other diseases genes requires in situ analysis of high numbers of clinical tissues samples. The tissue microarray technology greatly facilitates such analysis. All in situ methods suitable for histological studies can be applied to tissue microarrays without major changes of protocols, including immunohistochemistry, fluorescence in situ hybridization, or RNA in situ hybridization. Since all tissues are analyzed simultaneously by the same reagents, tissue microarray provides a remarkable degree of standardization, speed, and cost efficiency. [39]

Challenges

A microarray image showing spot irregularity

Accuracy

Just like any quantification of experimental data, microarrays cannot produce 100% accuracy. The obtained image in itself poses deviations from the ideal image - an array of perfect spots spaced evenly. Furthemore, many of the systems used to analyse the obtained image ignore these deviations and also require human interaction which introduces bias.

There are always deviations in the positions of subarray grids and individual spots in produced images. Looking at shape of individual spots in detail, there are deviations from the ideal uniform circle and some spots would be missing. Background signals can also be introduced due to non-specific binding of the labeled nucleic acids to the array substrate and its fluorescence. These backgrounds signals may also vary in location.

Many software systems, in the attempt to simplify analysis, make assumptions such as spot shapes being circular or ignoring the background. Misidentification of the background as the foreground leads to a "dilution effect" in which the estimate of the absolute signal due to specific hybridisation (mean foreground pixel intensity - mean background pixel intensity) is lower than its true value. Many systems also encourage or require extensive human interaction. Any bias or fatigue introduced can lead to the unnecessary variation of derived parameters.

The solution to inaccuracies are better software systems. A highly automated system for microarray image quantification which requires minimal, if not any human interaction is desirable. Jain et. al. (2002) discusses a recent software called "Spot" in which the software automatically locates and segments each spot and estimates ratios. The system does not make assumptions such as perfect spot circularity - but instead, it identifies precise pixels for each spot. A more accurate estimate of the absolute signal can therefore be obtained. Because it does not require any human interaction, the quantification process is very fast (an average image of 6000 spots takes less than 20s).[40]

Reproducibility

Although microarrays have become major research tools in biology and medicine, the large datasets and complex analyses cause several challenges. Authors find difficulties in analyzing large amount of data and how much data needs to be presented within the paper. Reviewers and editors are uncertain in deciding on the suitability of papers for publication. Readers are challenged to decide how to assess the data presented. The results from several high-profile papers have already proved difficult to reproduce, even by those with sufficient time and computing expertise.

The Microarray Gene Expression Data Society has proposed a set of guidelines (MIAME) for the reporting of microarray data, and that all such data should be deposited in public databases. Some researchers advocate the use of standard statistical packages, which allows the reader to repeat an entire analysis quickly and obtain solid results. Some authors have produced a transcript of their statistical analyses as a supplement to their articles (e.g., Nucleic Acids Res 32: e50). Authors are also recommended to have a protocol with a prespecified plan for patient selection and statistical analysis—accepted practice for clinical trials. [41]

Reliability

Microarray-based studies may report findings that are not only difficult to reproduce, but also not reliable. Common causes include improper analysis or validation, insufficient control of false positives, and inadequate reporting of methods. This is susceptible in small sample sizes relative to large numbers of potential predictors because typically tens of thousands of probes are investigated in only tens or hundreds of biological samples.

Combining information from multiple existing studies can increase the reliability and generalizability of results. The use of statistical techniques to combine results from independent but related studies, namely “meta-analysis” is a relatively inexpensive option that has the potential to increase both the statistical power and generalizability of single-study analysis. A stepwise approach with seven key issues is suggested in conducting meta-analysis of microarray datasets:

  1. Identify suitable microarray studies
  2. Extract the data from studies
  3. Prepare the individual datasets
  4. Annotate the individual datasets
  5. Resolve the many-to-many relationship between probes and genes
  6. Combine the study-specific estimates
  7. Analyze, present, and interpret results [42]

Microarray data are more relevant when a large number of samples and tissue classes are used. One research has proved that using few classes of thyroid lesions have offered limited predictive accuracy on the genetic markers for thyroid cancers. To improve diagnostic relevance, six public datasets covering a total of 347 thyroid tissue samples representing 12 histological classes of follicular lesions and normal thyroid tissue were simultaneously analyzed instead of just one dataset. [43]

Summary

In recent decades, high-throughput scientific methods have been developed to optimize the study of large numbers of molecules, including DNA, proteins and metabolites. Microarray technology has become a crucial tool for large-scale and high-throughput biology. It allows fast, easy and parallel detection of thousands of addressable elements in a single experiment. DNA microarrays in particular have proved valuable in genomic research. [44] They have been used to study gene expression patterns, to locate transcription factor binding sites, and to detect sequence mutations and deletions on a grand scale. However, DNA microarrays tell us only about the genes themselves and provide little information regarding the functions of the proteins they encode. Thus, protein microarrays were developed and were seen as high throughput approaches for the study of protein. [45] On the other hand, tissue microarray is seen to provide a remarkable degree of standardization, speed, and cost efficiency for cancer analysis. [46]

Related Links

Glossary

Array: An orderly geometric arrangement of features on a solid surface.

Complementary DNA (cDNA): A DNA synthesized from a mature mRNA template in a reaction catalyzed by the enzyme reverse transcriptase and the enzyme DNA polymerase.

DNA Microarray: A type of nucleic acid-based multiplex technique involving high-density arrays of nucleic acids on glass that allows to evaluate mRNA abundance of up to tens of thousands of genes simultaneously.

Fluorescent in situ hybridization (FISH): A cytogenetic technique used to detect and localize the presence or absence of specific DNA sequences on chromosomes by using fluorescent probes that bind to only those parts of the chromosome with which they show a high degree of sequence similarity.

Immunohistochemistry (IHC): A process of localizing antigens in cells of a tissue section exploiting the principle of antibodies binding specifically to antigens in biological tissues.

Microarray: A 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening methods.

Microtome: A sectioning instrument that allows for the cutting of extremely thin slices of material, known as sections.

Multiplex Technology: A type of laboratory procedure that simultaneously measures multiple analytes (dozens or more) in a single assay. It is distinguished from procedures that measure one or a few analytes at a time.

Perturbation: An alteration of function of a biological system induced by external or internal mechanisms.

Photolithography: A technique used to create oligo-nucleotides by using repetitive serial photochemical reactions.

Protein Microarray: A microarray that provides a multiplex approach to identify protein–protein interactions, the substrates of protein kinases, transcription factor protein-activation or the targets of biologically active small molecules.

Proto-oncogene: A normal gene that can become an oncogene, a gene when mutated or expressed at high levels, helps turn a normal cell into a tumor cell.

Tissue microarray (TMA): A microarray that consists of paraffin blocks in which separate tissue cores are assembled in array fashion to allow multiplex histological analysis.

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2010 Projects

Fluorescent-PCR | RNA Interference | Immunohistochemistry | Cell Culture | Electron Microsopy | Confocal Microscopy | Monoclonal Antibodies | Microarray | Fluorescent Proteins | Somatic Cell Nuclear Transfer