Mechanistic concept behind microarray technology

Microarray technology is formulated on the basis of three major design criteria: firstly the probe type employed on the array, secondly the assembly of the arrays and thirdly the number of samples (single or double-channel) which can be concurrently determined on the same array (Tarca et al., 2006). Conventional microarray offered by Affymetrix is made up of probe attachment via surface engineering to a solid surface (e.g. glass or silicon chip) by a covalent bond to a chemical matrix such as epoxy-silane, amino-silane, lysine, polyacrylamide Later developed microarray platforms by Illumina employed microscopic beads, as opposed to the large solid support. Nevertheless, microarrays from different companies are typically made up of an arrayed series of thousands of microscopic spots of DNA oligonucleotides, called features, each containing picomoles (10−12 _{moles) of a specific DNA sequence, known as probes (or reporters). Each of these} probes was repeated tens of times on the same array. These can be a short section of a gene or other DNA element that are used to hybridize a cDNA or cRNA sample (called target) under high-stringency conditions. Probe-target hybridization is usually detected and quantified by detection of fluorophore- (Cy3 or Cy5) labeled targets to determine relative abundance of nucleic acid sequences in the target.

The basic principle behind microarray technology is the high specificity hybridization between first DNA strand (target sequence) and the second DNA strand (probe on

62 microarray) (Southern et al., 1999). This is dependent on the property of complementary nucleic acid sequences to exclusively pair with each other via hydrogen bonds between corresponding nucleotide base pairs. The higher the degree of base pair complementation in a nucleotide sequence, the stronger and tighter the non-covalent bonding between the two strands. After removal of non-specific bonding sequences by repeated washings, only DNA strands specific to the probes will remain hybridized. As such, fluorescently labeled (Cy3 or Cy5) target sequences that bind to a probe sequence emit a signal that is subjected to the strength of the hybridization (determined by the number of paired bases), the hybridization conditions (temperature and duration), and washing after hybridization. Total strength of the signal, from a spot (feature), is quantitated by the amount of target sample binding to the probes present on that spot. Microarrays use relative quantitation in which the intensity of a feature is compared to the intensity of the same feature under a different condition (e.g. treatment and diseased state), and the identity of the feature is known by its position. A simplified workflow of a microarray experiment is shown in Figure 1.4.

Fluorescently labeled target sequences could be DNAs, RNAs or cDNAs. Microarray analysis of mRNA samples required the mRNAs to be reversed transcribed using a oligo- d(T) primers to form cDNAs. The cDNA templates are then amplified using RNA polymerase to form cRNAs using fluorescently labeled nucleotides. These target sequences can be hybridized onto the arrays in a single (one sample) or dual (two samples) -channel array formats. Single-channel arrays, employing only one flurophore for detection, commonly used oligonucleotides as probes, although in some cases cDNA

63 or PCR fragments are adopted. Employing this array layout implies that only one sample can be hybrized per array, and differential gene expression data is obtainable through comparative normalization with other arrays upon completion of whole microarray experiment. The single-channel array format is depicted in Figure 1.5.

Similarly, dual-channel arrays also adopt oligonucleotides, cDNA or PCR fragments as probes. The distinct differenece is that this array format highly relies upon the competitive hybridization between two samples (target and control reference), each differentiated by different fluorophore labeling, on a single array. Advantage of this technique is that relative gene expression differences between the two samples are observedly simultaneously. Its difference in layout from single-channel format is shown in Figure 1.6.

Three key points need to be taken into consideration when designing a microarray experiment: Firstly, the number of biological samples to ensure the reliability of the conclusions drawn from the experimenty; secondly, technical replicates (two RNA samples obtained from each experimental unit) to ensure precision by the handler and allow for testing differences within treatment groups. The technical replicates may be two independent RNA extractions or two aliquots of the same extraction; and lastly, the number of replicates of each cDNA clone or oligonucleotide presented as replicates (at least duplicates) on the microarray slide, to provide a measure of technical precision in each hybridisation. It is important to formulate a good and meticulous microarray experimental design so that high quality results can be yielded in conjunction with valid

64 and sound conclusions. As such, guidelines on microarray designs have been published in MIAME (minimum information about a microarray experiment) standards (http://www.mged.org/Workgroups/MIAME/miame.html).

65 Figure 1.5 A schematic diagram depicting a single-channel (one sample) microarray experiment layout.

66 Figure 1.6 A schematic diagram depicting a dual-channel (two samples: Target and Reference) microarray experiment layout.

67 1.8.3 Assignment of functional-biological pathway definition to significantly- modulated genes using online database tool

Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.7 is a high- throughput and integrative data-mining bioinformatics environment, which is able to identify and assign biological pathway significance associated with large gene lists through classification of co-functioning genes to biological annotations and statistically highlight those enriched (over-represented) annotations (Dennis et al., 2003; Huang et al., 2009). This exploratory, computational-cum-statistical instrument of clustering and enrichment is crucial in the identification of biological processes most pertinent to the biological phenomena of interest.

Differentially modulated, statistically significant gene probes identified from biostatistical software (e.g. GeneSpring® and Partek®) were input onto the functional classification interface on DAVID for functional genomic analysis. The results emergent from this stepwise DAVID analysis suggested gene functional classification based on their biological-function annotations (setting the background to the respective microarray platform and array type use i.e. companies and species) and clustering annotation was carried out to rank the importance of the overall annotation term groups through enrichment and statistically validation by gene-term enrichment score through modified Fisher‘s exact test and Benjamini correction.

68 1.8.4 Relevance of global gene profiling to elucidation of pathogenesis of neuropathological disorders

The study of gene expression on a global scale using microarrays has significantly accelerated the analysis of diseases and the unraveling of cellular signaling pathways. One area in which microarray analysis has received significant attention is in neurobiology (Geschwind, 2000; Lockhart and Barlow, 2001). Differential gene expression mapping in multiple brain regions has been used to determine the genetic etiologies and molecular mechanisms accountable for the neurobehavioral differences in mice (Sandberg et al., 2000). Studies using microarrays to determine gene expression changes occurring in the neocortex and cerebellum of aging mice have shown that brain aging in the mice might be comparable to changes in human neurodegenerative disorders at the transcriptional level (Lee et al., 2000). Similarly, microarrays have been extensively used to measure transcript expression profiles or search for molecular markers and pathways involved in the pathogenesis of AD, multiple sclerosis and stroke (Colangelo et al., 2002; Emilsson et al., 2006; Ginsberg et al., 2000; Rink et al., 2010; Tseveleki et al., 2010). Studies for the development of new therapies for diseases without suitable animal models, such as schizophrenia, also involved microarray analysis of gross brain samples to reveal alterations in specific metabolic pathways (Hakak et al., 2001; Middleton et al., 2002; Mirnics et al., 2000).

69 1.9 Aims of my Ph.D. project

The objective of my Ph.D. project is to lay the foundation for development of screening platforms for stroke using comparative global transcriptional profiling anlyses of in vitro

and in vivo models to define novel biological target, and via pharmacological manipulation to determine its effectiveness in neuronal injury abrogation. My aims are as follow:

1. To identify common signaling pathways in vitro stroke models of excitotoxicity

2. To verify and correlate the occurrence of common signaling pathways also in different

in vivo stroke subtypes animal models

3. Using transgenic knockout animals to further illustrate the importance of primary mechanistic events during stroke

4. To ascertain if manipulation of the expression level of an identified novel biological target would attenuate ischemic-induced infarct damage

5. To determine if the identified signaling pathways in stroke are universal to other neurodegenerative disorders

70 Global gene profiling of stroke has been reported in several recent literatures (Rink et al., 2010; Tseveleki et al., 2010) to identify genes which influence the pathological and clinical changes during focal cerebral ischemia. In my current project, a more in-depth and extensive microarray approach was adopted to facilitate a comprehensive elucidation of the pathogenesis of cerebral ischemia, which subsequently facilitated the identification of a novel family of biological targets (Auora kinase A (AURKA) and B (AURKB)). Functional genomics study of cerebral ischemia is made more detailed in two ways: firstly, temporal global transcriptomic profiling over a 24h-period is conducted and secondly, both in vitro and in vivo cerebral ischemia models are adopted for microarray analyses. Furthermore, a concurrent comparative microarray analysis of various in vitro

neurodegenerative models offers unprecedented novel mechanistic insights common to numerous neurodegenerative disorders. In this Ph.D. study, great emphasis is placed on over-represented biological processes related to neuronal injury. For the purpose of clear distinction during reference to proteins and genes, gene symbols in the text are denoted in sentence case, while that with reference to proteins are in uppercase.

Temporal microarray analysis of in vitro ischemia models using specific iGluRs agonists on cultured murine primary cortical neurons elucidates the significance of excitotoxicity, an upstream process during cerebral ischemia. This provides invaluable insights into significantly modulated biological processes triggered by excitotoxicity (discussed in Chapter 3), and thereby facilitates the identification of novel biological targets which would theoretically show promising efficacy in the abrogation of infarct damage due to their implications in the pathogenesis of cerebral ischemia (Discussed in Chapter 6).

71 As focal cerebral ischemia can be subdivided into more specific disorder categories depending on the etiology, the age of the affected and the duration of ischemia, my present study has for the first time looked into the temporal global transcriptomic profiling of three subtypes: neonatal hypoxic ischemia, transient and permanent cerebral ischemia (Discussed in Chapter 4 -6). Oxidative stress is one of the two main physio- pathological mechanisms in cerebral ischemia in addition to inflammation. The importance of intact functional anti-oxidant mechanisms to combat oxidative stress during cerebral ischemia is accentuated by the employment of glutathione peroxidase 1 – knockout (Gpx-1-/-_{) transgenic mice, and its temporal microarray analysis is conducted in} parallel with and compared against that of the wild-type mice (Discussed in Chapter 5).

A novel biological target, AURKs family, has been identified to be involved in cell cycle re-activation during excitotoxicity in in vitro cerebral ischemia models. Functional translational study involving administration of AURKs inhibitor in in vivo permanent cerebral ischemia model demonstrated substantial attenuation of infarct volume and this neuroprotective effect has been attributed to the suppression of the neuro-inflammatory cascades as shown by comparative temporal microarray analysis (Discussed in Chapter 6).

To ascertain the common pathways of neurodegeneration in the pathogeneses of different neurodegenerative diseases, unprecedented comparative microarray analysis of in vitro

models of cerebral ischemia against that of other neurpathological conditions mainly AD, PD and ALS induced by pharmacological agents rotenone, lactacystin, hypochlorous acid

72 (HOCl) and NO is conducted (Discussed in Chapter 7). Invaluable mechanistic modulatory insights from as general as biological processes down to specific gene regulation aids the identification of more novel biological targets whose manipulations would provide even more effective therapeutic intervention across the neurodegenerative disease spectrum.

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Chapter 2: