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Microarray chips allow us to conduct many expression experiments in parallel to each other but they can be used only once as far as i know. Are there reusable microarray chips? Have people ever tried it? If there are, are they becoming more common? If people do not choose to use them even though they are in the market, what can be the reasons?
As far as I am aware, there are no commercially available re-usable microarrays. The reason for this is most likely that the arrays are really sensitive and you run into the trouble with false positive signals. I have once seen a microarray which has been stripped and still delivered quite some signals in areas which had a strong signal before.
You have to make sure to strip all the hybridized samples from the chip without damaging the probes which are bound on the surface. I think the trade-off between "everything is off" and "some sample is still bound" is not good enough. Who wants to risk false positive signals and possibly retract publications on this basis? You may also loose weak signals which are hidden under false-positive signals.
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Reusable microarray chips - Biology
Principle of a DNA microarray chip : use as Variant Detector Arrays (VDAs)
(after SM Carr et al. 2008. Comp Biochem Physiol D, 3:11)
A DNA chip is a small piece of silicon glass (
1 cm 2 ) to which a large number of synthetic, single-stranded DNA oligonucleotides (" oligos ") have been chemically bonded [left]. Oligos function as DNA probes : they " stick " (anneal) selectively only to those DNA molecules whose nucleotide sequences are exactly complementary: T pairs with A , and G with C . They can therefore be used to identify the presence of specific DNA sequences in a heterogeneous mixture of genes, for example the presence of a particular allele against the background of a complete genome. In effect, oligos act like molecular " velcro ." A computer " reads " the pattern of annealing and " reports " which alleles are present.
DNA chips can be used s Variant Detector Arrays (VDAs) to look for DNA sequences that differ by single nucleotide polymorphisms (" SNPs "). In this example, the DNA sequences of the four oligos highlighted in the first bloc differ only at the last position. To determine which alleles are present, genomic DNA from an individual is isolated, fragmented, tagged with a fluorescent dye, and applied to the chip. The genomic DNA fragments anneal only to those oligos to which they are perfectly complementary: in this case, the allele with the
A oligo , and the allele with the
G oligo . A computer reads the position of the two fluorescent tags and identifies the individual as a C / T heterozygote . [The single spots in the other three columns indicate that the individual is homozygous at the three corresponding SNP positions].
The 4 x 4 arrays fits in one corner of a 256-oligo chip (lower right). The current generation of microarrays can accommodate hundreds of thousands of oligos.
What is DNA Microarray ? | Genetics
In this article we will discuss about the meaning of DNA microarray.
DNA microarray is a new technology to monitor the whole genome on a single chip so that researchers can have a better image of the interactions among thousands of genes simultaneously. The new genome chip is preferred to monitor the whole genome on a single chip. DNA Microarray will allow scientist to assess the genetic status of an entire organ. Until recently, analysis of RNA in cells was painstaking and time-consuming.
In 1991, researchers from Stanford University developed a new technology adapted from the microchip used by the computer industry. This microchip is a potent tool in monitoring changes in level of gene expression of thousands of genes from any biological origin. The theory behind gene chip is simple, where RNA molecule combined with its DNA template contained within a particular cell.
Once cDNA is produced, in the laboratory, which is then exposed to the DNA chip because cDNA binds with its complementary. The message molecules recognise and attach to the spots on the chip corresponding to the DNA template. These message molecules have been targeted with fluorescent dyes so that scientist can see pattern of genes being expressed at any particular time.
It is possible to compare spot with region of the gene not being expressed. The chip is made up of glass microscopic slide, 7.62 centimeters by 2.54 cm and about 1.7 millimeter thick. Sample of DNA microarray in the form of spots are printed on the slide using a procedure similar to the one used to print computer chips.
The DNA spots easily adhere to the slide. Each spot represents a gene. The DNA spot is either fully sequenced genes of known function or collection of partially sequenced unknown genes. The chip manufacturing by printing or spotting is carried out by a machine called an arrazer.
Most arrays are featuring high speed robotic arm fitted with a number of pins. The arm is controlled by software that allows placement of genes in select areas and configurations on the glass slide to generate cDNA microarray chip. Computer can keep track of the location of each gene on the gene chip.
Illumina microarray technology (also known as BeadArray technology) uses silica microbeads. On the surface of each array, or BeadChip, hundreds of thousands to millions of genotypes for a single individual can be assayed at once. These tiny silica beads are housed in carefully etched microwells and coated with multiple copies of an oligonucleotide probe targeting a specific locus in the genome.
Silica beads that self-assemble in microwells on either of two substrates: fiber optic bundles or planar silica slides.
How Do Illumina Microarrays Work?
As DNA fragments pass over the BeadChip, each probe binds to a complementary sequence in the sample DNA, stopping one base before the locus of interest. Allele specificity is conferred by a single base extension that incorporates one of four labeled nucleotides. When excited by a laser, the nucleotide label emits a signal. The intensity of that signal conveys information about the allelic ratio at that locus.
How Microarrays Work
Each assay genotypes a locus using two color readouts: one color for each allele. The relative intensity of the two colors indicate whether a genotype is heterozygous or homozygous at that locus.
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Wojcik, G.L., Graff, M., Nishimura, K.K. et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature. 2019570(7762),514–518.
Capper, D., Jones, D., Sill, M. et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018555(7697),469–474.
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DNA Strand Designations
Learn about the different strand designations found in Illumina array manifests and GenomeStudio projects.
Guidelines for Identifying TOP/BOT Strand and A/B Allele
A step-by-step method to help you understand this nomenclature for single nucleotide polymorphisms.
How to Interpret DNA Strand and Allele Information for Array Data
When comparing genotyping data, it is important to use the same DNA strand designation.
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Methylation arrays enable high-throughput, quantitative interrogation of methylation sites across the genome at single-nucleotide resolution.
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Software tools for array experimental design, sample tracking, and analysis of microarray data.
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Reviewer’s report 1: Dr. Janet Siefert
Jaksik et al. have written a review article on the use of microarrays and the cautions and complications of using the results of them to evaluate research data. The Kimmel lab has considerable experience, over several years, with microarray data so the expertise of his team to evaluate and write such an article is well placed. I find their review to be comprehensive and thorough. It will be of considerable use to anyone considering employing microarray experiments as well as those who need to troubleshoot previous use of microarrays and accompanying statistical evaluations. Although the published literature offers a number of articles reviewing microarray use, it is the expertise of this team, as statisticians actively working with numerous microarray data sets, that makes this article valuable to the researching community.
Reviewer’s report 2: Dr. Leonid Hanin
This is an interesting article that lists and analyzes in detail various sources of errors and inconsistencies associated with microarray technology. It represents an important step towards answering the following fundamental question: Is microarray technology a reliable tool for furthering our understanding of biological systems at the genomic level or is it bound to produce a lot of biological/technological artefacts and largely generate false knowledge? I believe the main deficiency of the article is that it is entirely qualitative in that no quantitative estimates of the impact of various factors identified in this work or of their relative importance were given. The basic question that a researcher utilizing microarrays would ask is whether impact of these factors is minor or major. The article does not provide any information or opinion in this regard. Given that the processes collectively forming microarray technology are either biochemical or physical in nature, estimating the effects of various factors on gene expression signals quantitatively seems to be in principle possible. For example, here are two relevant publications, just from the top of my head, about the physics of DNA/RNA hybridization, see also references therein:
1. E. Carlon, T. Heim (2006), Thermodynamics of RNA/DNA hybridization in high-density oligonucleotide microarrays, Physica A 362: 433.
2. A. Ferrantini, E. Carlon (2008), On the relationship between perfect matches and mismatches in Affymetrix Genechips, Gene 422: 1𠄶.
On a more technical level, I have the following questions and comments.
1. One of the sources of uncertainty in determination of gene expression levels that was not mentioned in the article is errors in gene finding. While for well-annotated genomes of model organisms they are probably insignificant, for many other organisms type I and II errors in gene finding may be as high as 10 %.
Authors’ response: Description of probe design flaws resulting from inaccurate transcriptome data were added to the description of the data pre-processing step.
“Summarization step is highly dependent on the quality of the probe and probeset definitions which are in many cases low due to inaccurate transcriptome data at the time of microarray design. This can result in probesets targeting transcripts of multiple genes due to low probe specificity, probes that do not map any of the known transcripts [41, 42] or multiple probesets that map the same gene [39, 40], requiring the development of methods used for the validation of existing probes and for probeset redefinition [41, 42, 96]. “
2. Another factor that was mentioned only very briefly in the text but probably deserves more discussion is heterogeneity of biological material from which mRNA is extracted. It may include different types of cells, cells in various phases of their life cycle, quiescent and proliferating cells, etc.
Authors’ response: Cellular heterogeneity is a major problem in many biological studies and can indeed significantly affect the results of a microarray study. However because this problem is unrelated to the technical aspects of the microarray protocol, we find it to be outside of the scope of this article.
3. It was mentioned, again very briefly, in the Conclusions section that utilizing several replications may improve design of microarray experiments. I think this is a very important point. I find it pretty appalling that a lot of microarray experiments with so many sources of variation and error were based on a single run of the process! What minimum replication number would the authors of the article recommend?
Authors’ response: Based on our experience we suggest using at least 3 replicates for studies based on cell lines. From a statistical point of view a minimum of 3 samples are required for the estimate of standard deviation to be valid. Higher number of replicates might be highly beneficial for experiments dealing with poor quality material or studies aiming to detect small differences in gene expression. For experiments based on samples extracted from multiple patients, replicates are usually not necessary since the confidence level increases with the number of patients studied.
4. It was stated in the Microarray Structure section that the 𠇊mount of material hybridized to a given probe… is related to the amount of DNA or RNA of a given gene in the sample. ”What is this functional relationship? Is the magnitude of the optical signal produced by microarray chip proportional to the copy number of a gene’s RNA transcript in the sample? What happens to this relationship when microarray output data are pre-processed?
Authors’ response: The fluorescence intensity of probe is proportional to the RNA level of corresponding gene although, as shown by Held et al. in 2006 the relationship is not linear whether or not the data are pre-processed.
Finally, here are few minor comments.
Authors’ response: Minor comments of the reviewer have been taken into account. Corresponding changes in the manuscript are highlighted in grey.
1. Introduction, line 2. “physical or chemical conditions”. Perhaps biological conditions too?
2. Introduction, line 4. It seems like “their” should be inserted between 𠇎valuate” and “variability”.
3. Introduction, paragraph 2, sentence 2. Aren’t “specific methods used” and “inaccuracies of the measurements” themselves 𠇎xperimental factors”?
4. Introduction, last paragraph. What is the difference between uracy” and “precision”? Also, how is specificity defined in the case of microarrays?
Author’s response: Definitions of accuracy and precision can be found in ref. 45.
In the case of microarrays specificity refers to the ability of a probe to bind a unique target sequence. A specific probe provides signal proportional only to the amount of the target sequence, while non-specific probe signal will be a result of interaction with more than one target sequence. The specificity of a probe can be diminished by cross-hybridization, also called non-specific hybridization, a phenomenon in which sequences that are not strictly complementary according to the Watson𠄼rick rules bind to each other.
5. Introduction, last sentence. Delete “have”.
6. Microarray Structure, paragraph 2. “ nt sequence fragments located near the 3′ end of a specific transcript (Fig. 1 ). “This is not clear from Fig. 1 .
7. Microarray Structure, last paragraph. Platform differences contribute to low accuracy of microarrays, so spite” seems to be out of place.
8. Step I: RNA isolation, paragraph 1. “…ribosomal RNA… is rarely studied”. I think rRNA is studied quite extensively in phylogeny and pharmacology.
9. Step I: cDNA synthesis, paragraph 1. Shouldn’t the figure referred to here be 4 rather than 3?
10. Conclusions, paragraph 1. What is the significance of “morphological features” in this context?
11. Caption to Fig. 1 . What is the purpose of probe sets A and B? Also, does 𠇌orresponds to” mean “proportional to”, see technical comments 4?
12. Figure 2 . I think it would be better if the steps of microarray experiment shown in the figure correspond to the steps described under Biological background of microarray experiments.
13. Table 2 . What about the other two combinations of control probe-set outcomes involving an error?
14. The authors are encouraged to proofread their submission. There are a few places with missing or extra commas, instances where article “the” can (or perhaps should) be removed, etc.
Reviewer’s report 3: Dr. I King Jordan
This reviewer provided no comments for publication.
Applications of DNA microarray:
Obviously the first and foremost application of DNA microarray is the study of transcriptomics.
The transcriptome is a complete set of total mRNA of a genome going to translate into protein.
The gene has the sequences to form the protein which intermediately transcribed into mRNA and then translated into the protein.
By estimating the mRNA formed during transcription, we can estimate in which amount the protein forms.
Therefore, we can even study proteomes using microarray.
In modern days, one of the fascinating application of microarray is in the diagnosis of many inherited as well as non-inherited disease.
Multigenic disorders can not be studies during the PCR method, the microarray can analyse so many genes at a time, therefore, mutations in a gene or mutations of many genes can be studied and analysed using the microarray.
Even the microarray is the first choice for the diagnosis of rare genetic conditions and predisposition of cancer.
Gene expression between two tissues (tissue-specific transcriptome study), is possible using DNA microarray.
mRNA from two different tissues are extracted, reverse transcribed into cDNA and labelled with two different fluorescent dye.
Both tissue-specific cDNA complete with each other for hybridize with probe settled on a glass slide.
The intensity of the signal emitted is directly proportional to the amount of hybridization and hence the expressions of different genes in different tissues can be determined.
It is used in the genomic gain and loss studies.
As we discussed above, in the SNP microarray, all the copy number variation from different chromosomes can be determined, thus we can measure the amount of sequence deleted or loss and add into the genome.
In another type of DNA microarray, different microorganism present in different environmental DNA can be identified in a single microarray experiment.
New mutations associated with the disease can be characterised.
The microarray technique is based on the information of mutation available with us, unlike the DNA sequence, it can not determine new mutations or variations.
But it can be used for studying the association of mutations with the disease we wish to study, thus genome-wide association study.
- GMO plant studies
- Population study
- Gene and genotyping studies
- Forensic studies
- Pharmacogenomic studies
- Cancer research
Individuals or groups of students could present information about one or several genes, along with evidence based on published information to support their ideas.
Students can do a presentation or written assignment to demonstrate mastery of bioinformatics tools using the information from this DNA chip or from published microarray data.
This DNA chip lends itself to a rich discussion of experimental design concepts such as validity and reliability. These concepts could be assessed by the students' interpretation of control spots on their chips.
Students could demonstrate their understanding of the chemical interactions involved in microarray printing and hybridization. Using the wealth of emerging information available on the web, students could write a review of current and potential applications of microarray technology.
Hand-printed DNA chip hybridized with simulated cDNA target. Grid 1 was hybridized with simulated cDNA representing Arabidopsis seedlings grown in the light, and Grid 2 was hybridized with simulated cDNA representing dark-grown seedlings. The identity of the DNA spots on the chip is indicated by the Probe Layout diagram. The corresponding gene names can be found in Table I. Probe 10 is the positive control, and Probe 11 is the negative control (see under “Results”).
Every day, newspapers publish stories about discoveries made using genomic methods. One popular method is the DNA microarray, which allows investigators to measure the level of gene activity for an entire genome. Recent research has revealed that DNA microarrays can be used to better diagnose diseases such as cancer. Soon, microarrays will be a part of clinical diagnosis (Kakiuchi et al., 2004). It is increasingly important for more people to understand genomic methods. Fortunately, undergraduates are gaining access to DNA microarrays through a number of initiatives (Brewster et al., 2004 Campbell et al., 2006 Campbell and Heyer, 2006a, 2006b Genome Consortium for Active Teaching [GCAT], 2006a). However, high school students often miss out on learning the newest methods such as microarrays because of constraints on time and funding (National Research Council [NRC], 2002).
We have developed a wet lab simulation that is part of a 2- to 3-d DNA microarray module that teaches high school students about DNA microarrays. Our goals included 1) providing an interactive way to experience how microarrays are used to study gene expression 2) teaching students that DNA microarrays can measure the activity of many genes simultaneously and 3) enabling students to discover that genes are differentially regulated (expressed differently under different conditions). This module uses a wet lab simulation (in combination with a paper lab exercise Zanta, 2004, 2006) to teach students how DNA microarray experiments are performed. Furthermore, through the simulation, students learn that genes are differentially regulated. In preliminary testing, the microarray simulation facilitated active, hands-on learning the students enjoyed the lab and they significantly improved their scores on surveys conducted before and after the simulation. The simulation is very reliable and fits within a 45-min class period. The reagents are inexpensive and can be prepared once for multiple classes. In today's educational testing climate, for a new biology module to be incorporated into the curriculum, it must address some of the National Science Education Standards (NRC, 1996) that appear on standardized tests. The microarray simulation uses a case study in cancer biology to help students address several education standards covered in end-of-year tests (see Supplemental Material 1).
A recent study by the NRC (2005) found that U.S. high school classrooms frequently lack challenging and meaningful laboratory experiences for students. The NRC report outlined what constitutes a good lab. Students should have hands-on and minds-on opportunities to learn. Furthermore, college faculty often complain that entering students are poorly prepared for modern biology. Therefore, there is a need for curricular materials that will help high school teachers provide high-quality, interesting lab experiences for their students and help prepare them for college biology courses. This article describes a simulation that can be used for large numbers of students. The simulation has been used with >100 high school teachers in national workshops, with two teachers and 338 students in Hinsdale, IL, and with four high school teachers and ∼150 students in the Montgomery County School District in Maryland. The appendices in the Supplemental Material online provide the wet lab handouts and all assessment tools the paper lab exercise is also available online (Zanta, 2004). The simulation has been commercialized by Genisphere (Hatfield, PA) with the agreement that we would be able to publish a “how to create your own” version.
DNA Microarray Methodology
DNA microarrays are a high-throughput method used to survey the relative amount of transcription (gene expression) for every gene in a genome. DNA microarrays (sometimes referred to as gene chips) do not allow absolute levels of quantification of gene expression (e.g., 250 mRNA molecules per cell). However, DNA chips do allow investigators to determine how much mRNA was produced in a sample relative to the amount of mRNA produced by a control population. An example study might compare lung cancer tissue to healthy lung tissue in order to determine whether there is an increase (induction) or decrease (repression) of gene expression and, if so, by how much. The relative amounts of mRNA produced by a particular gene in two samples can be used to produce a ratio that indicates the differences in transcription. For example, if Gene A produced 250 mRNA molecules in healthy lung cells and 1000 mRNAs in lung cancer cells, then Gene A is induced fourfold in lung cancer (i.e., 1000 ÷ 250 = 4). Conversely, perhaps healthy cells produce 4000 mRNA molecules from Gene B but lung cancer cells only produce 500, then Gene B is repressed eightfold in cancer cells (i.e., 4000 ÷ 500 = 8). However, some genes will not show differences in the level of transcription between the lung cancer cells and healthy lung cells, and thus their ratio of gene regulation will be approximately one. If we wanted to understand the causes of lung cancer, we might want to focus on Gene A and Gene B rather than the hundreds that were equivalent in the two tissues.
Scientists and clinicians are collaborating to improve the diagnosis of diseases such as lung cancer. Currently, diagnoses are made in broad categories based on clinical observations, and all patients are treated the same within a category. Using DNA chips, many investigators believe medicine can become personalized such that each patient will be prescribed medical treatment that will best match his or her illness. Within their lifetimes, today's high school students will probably benefit clinically from DNA chip–based diagnosis. Approximately 1 of 3 women and 1 of 2 men in the United States will develop cancer (American Cancer Society, 2006), and many of them may be diagnosed with DNA microarrays.
With this great potential for social impact, it is important that high school students understand gene chips, regardless of their post–high school career plans. The wet lab simulation and accompanying case study provide a realistic scenario that is easy for students to follow and makes the cancer scenario relevant to their lives. The student-friendly microarray module that we have developed can easily be integrated into high school, community college, and introductory college biology curricula. As an introduction to the gene chip methodology, students read the handouts we have produced (see Supplemental Material 3) and view a free animation (Campbell, 2000 Figure 1). DNA microarrays that measure gene activity require many steps, all of which are too small to observe by eye. Therefore, a paper microarray lab (Zanta, 2004) combined with the animation provide a good foundation that prepares students for the wet lab simulation.
Figure 1. Screen shots of DNA microarray animation. Students are directed to view this animation along with reading some brief introductory materials (see Supplemental Material 3) before the first class session. (A–D) Different stages of the animation after cDNA synthesis.
(i) T4 RNA ligase surface ligation chemistry for RNA microarray fabrication
The RNA microarray fabrication methodology described here has a number of significant advantages when compared with existing RNA microarray fabrication methods. The first advantage is that the surface ligation strategy uses unmodified ssRNA. This means that both synthetic and in vitro transcribed RNA molecules can be readily used for the fabrication process. Conventional RNA microarray fabrication methods often employ biotin or thiol-modified RNA molecules and a chemical surface attachment chemistry similar to that used in the fabrication of DNA microarrays ( 12, 13, 16). These chemical modifications to the ssRNA can reduce the stability of the ssRNA, leading to cross reaction of RNA molecules during the fabrication process, and potentially interfere with the RNA aptamer folding and subsequent bioaffinity interactions. Moreover, RNA modification is a non-trivial process that is not only time-consuming and expensive, but cannot be easily incorporated into RNA in vitro transcription methods.
The second advantage of this RNA–DNA surface ligation strategy is that it can be used to create high-surface density RNA array elements with a very small amount of ssRNA and standard array spotting technology. The use of a universal ssDNA sequence means that ssDNA can be first attached to all of the array elements in a microarray in one solution reaction, and then the ssRNA probes can be spotted and ligated directly. The T4 RNA ligase reaction has a surface ligation efficiency of 85% or higher, and can create RNA microarray elements with surface densities up to 4 × 10 12 molecules/cm 2 . The 500 μm array elements used in this paper required 300 fmol of ssRNA per spot for the ligation reaction fabrication of 50 μm array elements would require only 3 fmol of ssRNA.
A third advantage of this array fabrication strategy is that the RNA microarrays created with the surface ligation chemistry do not contain any background proteins such as streptavidin, making them clean, robust and reusable. Attachment strategies that utilize streptavidin or other proteins have documented problems with non-specific adsorption of target proteins ( 40, 41), and cannot endure harsh washing conditions. The surface ligation reaction allows for facile separation of excess enzyme and reactants by simply rinsing the array. Because the microarray elements only contain covalently linked nucleic acids, target proteins bound to the array can also be easily removed from the surface by rinsing with 8 M urea and then the array can be reused. Moreover, the RNase H hydrolysis reaction can be used to regenerate the phosphorylated ssDNA array and a new RNA microarray can be created on the same substrate ( 19).
(ii) RNase H surface hydrolysis reaction for measuring relative surface densities
For the accurate measurement of multiple aptamer–protein affinity interactions, it is essential for each array element of the RNA microarray to have comparable and reproducible amounts of aptamers regardless of the different RNA hairpin structures. If this were not the case, signals from target protein binding at different aptamer array elements could not be compared quantitatively. This issue has not been addressed previously with other RNA attachment strategies, but is addressed in this paper with the novel RNase H surface hydrolysis methodology.
The RNase H hydrolysis reaction is a unique and convenient approach for measuring relative surface densities. The key factor in this approach is the (A)8 spacer arm in each RNA aptamer that allows the facile hybridization of (T)24 DNA and subsequent hydrolysis by RNase H. The hairpin formation in RNA aptamers makes it difficult to test the amount of RNA present on the surface by directly hybridizing the aptamers with their complementary DNA however, by using the (A)8 spacer arm and RNase H, the amount of RNA removed from the surface is readily detected by SPRI and therefore provides a good measurement of the relative surface coverages of different RNA aptamers.
For the T4 RNA ligase attachment chemistry, measurements of the relative surface density of different RNA aptamer array elements by RNase H hydrolysis confirmed that the same amount of RNA was ligated to each DNA array element regardless of aptamer hairpin structures. We attribute this consistency in RNA surface density to the long spacer arms placed between the RNA aptamers and the surface that reduce potential steric hindrance. The 20mer DNA anchor probe used in the ligation reaction serves as a spacer in the attachment of RNA aptamers. In addition, eight adenosine bases were added to the 3′ end of each RNA aptamer to elongate the single-stranded region at the 3′-hydroxyl group, which also facilitates the ligation catalyzed by T4 RNA ligase by eliminating the shielding effect caused by hairpin formation. Owing to these two spacer arms, any effect of hairpin structures on the ligation reaction is minimized.
The RNA–DNA surface ligation methodology and RNase H hydrolysis reaction described here were used for gold-modified surfaces and SPRI measurements. However, both are compatible in principle with any ssDNA microarray on a variety of surfaces such as glass, silicon and polymer matrices. We expect that this RNA attachment methodology will find additional application on these substrates in order to take advantage of the various well-characterized DNA microarray attachment and fabrication methodologies that are currently available ( 42– 46).
(iii) SPRI measurements of protein binding to an RNA aptamer microarray
The application of RNA microarrays in conjunction with SPRI for the rapid screening and selection of potential RNA aptamers was demonstrated with the protein fIXa involved in the blood coagulation process. The use of RNA aptamer microarrays allows for the simultaneous SPRI analysis of multiple RNA aptamers on the surface, as compared with single channel angle shift SPR measurements. A single SPRI measurement identified the best aptamer for fIXa from a set of five potential candidates. The SPRI measurement also showed that changing a single base in the RNA sequence could completely destroy the aptamer activity. This suggests that as well as screening aptamers with high affinities, SPRI measurements can be used to identify the active binding site in an RNA aptamer.
In addition to the selection of aptamers, SPRI measurements of RNA microarrays can also be used for the direct detection of multiple proteins from biological samples. A particular protein would be identified by its unique pattern of simultaneous adsorption onto multiple RNA aptamer array elements. The sensitivity of detection of proteins by SPRI with these RNA microarrays is primarily limited by the Langmuir adsorption coefficient for adsorption of the protein to the surface. The creation of RNA aptamers with higher binding affinities will increase the sensitivity of the multiplexed SPRI measurements. Additional sensitivity for the detection of both proteins at very low concentrations and smaller molecules (<10 kDa) can also be achieved by using a sandwich assay format similar to those required for fluorescence measurements. These sandwich assays include the use of nanoparticle-amplified methodologies ( 47, 48) that we recently employed in SPRI measurements for single nucleotide polymorphism identification and detection ( 49). A future challenge will be the development of microarrays with a sufficiently large number of RNA aptamer array elements to identify and detect multiple related proteins.