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Endocrinology Vol. 143, No. 6 2002-2006
Copyright © 2002 by The Endocrine Society

NEUROENDOCRINOLOGY

Perspective: Micoarrays and Differential Display PCR—Tools for Studying Transcript Levels of Genes in Neuroendocrine Systems

Jessica A. Mong, Christopher Krebs and Donald W. Pfaff

Laboratory of Neurobiology and Behavior (J.A.M., C.K., D.W.P.) Rockefeller University, New York, New York 10021, and Department of Human Genetics (C.K.), University of Michigan Medical School, Ann Arbor, Michigan 48109

Address all correspondence and requests for reprints to: Jessica A. Mong, Ph.D., Box 275, Laboratory of Neurobiology and Behavior, Rockefeller University, 1230 York Avenue, New York, New York 10021. E-mail: . mongj{at}mail.rockefeller.edu


   Abstract
Top
 Abstract
Introduction
 Differential display PCR (DD...
 Microarrrays
 Methodological criteria
 References
 


   Introduction
Top
 Abstract
 Introduction
Differential display PCR (DD...
 Microarrrays
 Methodological criteria
 References
 
A central goal of neuroendocrinology is the understanding of how hormones modulate a variety of neurobiological functions including releasing factors for anterior pituitary secretions and behavior. We know that mechanisms of hormone actions clearly include the activation and repression of genes either directly through nuclear hormone receptors or indirectly, through a series of transduced signals originating from membrane receptors. Until recently, identification of the differentially expressed genes has been a "gene-at-a-time" proposition. With the advent of the completion of sequencing of several genomes including those of the human and mouse, new methods for the simultaneous assessment of many genes’ expression are proving especially timely. Two such methods, differential display PCR and gene microarrays, are based on the well-established principles of DNA amplification and nucleic acid hybridization, respectively. With properly designed and well-executed experiments, these methods are powerful tools in the assessment of differentially expressed genes yielding results both expected and unanticipated.


   Differential display PCR (DD-PCR)
Top
 Abstract
 Introduction
 Differential display PCR (DD...
Microarrrays
 Methodological criteria
 References
 
The DD-PCR technique, through the use of RT and a nonspecific PCR strategy, generates a set of radiolabeled cDNA fragments from two different sources, such as the ventromedial hypothalamus of hormone-treated and vehicle-treated rats. The fragments are fractionated side-by-side on a polyacrylamide gel to facilitate comparison. Bands that exhibit different intensities on the autoradiogram correspond to genes whose transcript abundance is altered, either elevated or reduced due to treatment. Isolation of the bands and reamplification by PCR permits their molecular cloning into plasmid vectors and sequencing to determine their identity (1, 2). Since the technique first appeared in the literature, it has been slightly improved and tailored to address focused areas of investigation. For instance, Wrang et al. (3) employed restriction enzymes and the ligation of linker molecules at the ends of the cDNAs to produce amplifiable fragments closer to the 5'-ends, a modification helpful in the subsequent identification of the differentially expressed gene product. Others (4) have developed a set of primers that will restrict the differential PCR to amplify only transcripts that possess signal peptide sequences. This reduces the number of genes in the pool and amounts to fishing in a smaller pond for target genes of interest. These are just two examples of alterations to the original DD-PCR protocol, but they exemplify how the technique can be narrowed or broadened to suit the needs of the investigation and precisely address the biological system in question.

Several laboratories have successfully used DD-PCR to address neuroendocrinological questions. In a study addressing the regulation of ingestive behavior (5), DD-PCR comparing hypothalamic mRNA from ob/ob mice with their wild-type controls found elevated expression of melanin-concentrating hormone mRNA, which was subsequently localized to the periventricular area of the hypothalamus. Further experiments demonstrated a role in the regulation of feeding, suggesting that melanin-concentrating hormone participates in the hypothalamic regulation of body weight. We have identified several progesterone- and estrogen- responsive genes in the female rat ventromedial hypothalamus encoding proteins ranging from molecular chaperones and secretory proteins to membrane-associated receptors (6, 7, 8). Park et al. (9) also recently reported the discovery of many estrogen- and progesterone-responsive genes in the rat preoptic area. However, the neuroendocrine consequences of these genes remain to be explored.

The success of these and many other studies which have employed the DD-PCR approach is due in large part to the power of the technique, which resides in the PCR step that permits the amplification of cDNA from as little as 200 ng of total RNA (1). PCR can also be designed as a high-throughput method, which translates into the ability to replicate reactions on groups of individuals and therefore distinguish individual or stochastic variation from significant changes in gene expression that truly correlate with treatment. DD-PCR entails a relatively small number of steps and laboratories that are able to isolate and manipulate RNA and DNA are well suited for the two required primary techniques of PCR and gel electrophoresis. From a financial perspective, DD-PCR is relatively inexpensive and several biotech supply companies [e.g. GeneHunter (Nashville, TN), QIAGEN (Valencia, CA), Ambion, Inc. (Austin, TX)] have kits available to help apply the DD-PCR technique. Scientifically, DD-PCR has the advantage to uncover new genes or transcripts, an aspect that the microarray technology still lacks (see below), but as genome sequences of model organisms are completed, this advantage will diminish. However, DD-PCR is not without its shortcomings and conundra. For example, primer specificity, restricting the population of amplified messages, must be balanced against primer degeneracy, which then can lead to a lack of reproducibility, especially for rare messages. To address this latter problem, the technique of suppressive subtractive hybridization, now available as a CLONTECH kit (Palo Alto, CA), amplifies differentially expressed rare mRNAs at the expense of the abundant ones, thus allowing the experimenter a measurement of messages likely to be of regulatory importance.


   Microarrrays
Top
 Abstract
 Introduction
 Differential display PCR (DD...
 Microarrrays
Methodological criteria
 References
 
Although there are a variety of approaches one may use to explore differential gene expression, microarray technology is, presently, one of the more dynamic. DNA and oligonucleotide microarrays are collections of hundreds to thousands of cDNA molecules or oligonucleotides affixed on a solid substrate. Using nucleic acid hybridization, these microarrays are capable of monitoring and comparing the differential expression of the represented genes simultaneously. Currently, there are two types of microarrays widely used for expression profiling and comparison of thousands of genes: high density oligonucleotide (10, 11, 12) and cDNA arrays (13, 14, 15). Both have advantages and disadvantages. For example, Affymetrix, Inc. (Santa Clara, CA) is a major manufacturer of the high-density oligonucleotide arrays. They use a unique photolithography system (16) to synthesize short oligonucleotide sequences (usually 25 oligomers) directly on a glass surfaces with a total area smaller than one half square inch (for in-depth reviews see Refs. 11 and 17). The oligonucleotide sequences on the Affymetrix GeneChip typically represent 12,000–13,000 genes and expressed sequence tags for a given species. At present, AffyGeneChips are available for a number of organisms including human, mouse, and rat. Multiple oligonucleotide sequences (approximately 16–20 probe sets per gene or expressed sequence tags) represent different 3' regions of the same gene. Each probe set consists of perfect match and mismatch sequences. The mismatch sequences contain a single mismatched base pair and provide an estimate of nonspecific hybridization, thus increasing the confidence and reliability of the data.

High-density oligonucleotide arrays have several advantages (18). The direct synthesis of sequences onto the chips precludes their reliance on physical intermediates such as PCR products. Also, the shorter probes can be targeted to unique regions of the gene, thereby reducing cross-hybridization and increasing specificity, especially between closely related members of gene families. Because the AffyGeneChips only allow for hybridization of one biotin-labeled sample per chip, individual samples can be compared, with appropriate normalization (see Methodological criteria), across multiple treatment groups, allowing for post hoc data comparisons simultaneously regardless of whether they were hybridized at the same time. Finally, their standards for quality control in manufacturing currently reduce variability among experiments. Although the costs of Affymetrix GeneChips are slowly decreasing, the expense of the materials and processing equipment (hybridization chambers, washing stations, and scanners) can be prohibitive for many laboratories and institutions. Cost aside, the major disadvantage of the Affymetrix system is the predefined choice of genes; however, key genes involved in endocrine systems are represented.

In the case of cDNA microarrays or "spotted arrays," the main advantages are versatility and specificity of hybridization. Here, both the experimental and reference samples are mixed and hybridized simultaneously to the array, reducing variability due to separate hybridizations. cDNA fragments such as clones, PCR products, or large oligonucleotides from 100–1,000 bp are immobilize onto glass slides (13, 19, 20). These arrays are readily customized by employing a spotting robot that will array the particular cDNAs (19) using either microspotting or ink-jetting technology (21). Typically, approximately 10,000 spots can be arrayed onto a glass microscope slide. cDNA arrays are best used for comparative gene expression studies. Fluorescently labeled (Cy3 or Cy5) nucleotides are incorporated in the cDNA from the two samples (one fluorochrome per sample) during RT. The labeled samples are then combined and hybridized to the same microarray. Each arrayed spot or probe will bind its fluorescently labeled cDNA complement. The amount of fluorescent signal from each sample is measured, according to wavelength, from a digitized image of the array and independently quantified and compared. Some of the main advantages of cDNA arrays would include 1) the relative ease in customizing the genes on the array and 2) the application of the technique to a variety of species popular for neuroendocrine studies. The major disadvantages are: 1) the inherent variability due to differences in spotting efficiencies, although this is corrected for in some respects by hybridizing the experimental and reference sample to the same chip and by spotting the same cDNA in multiple locations; and 2) the dependence on high-quality physical intermediates (PCR products, clones, and cDNA), which makes these homemade arrays less well controlled.

Microarrays and hormonal regulation of target genes.
High-density oligonucleotide arrays and cDNA arrays have been used extensively to study differential gene expression in cell differentiation (22, 23), oncogenesis (13, 24, 25), cell cycles (26, 27, 28, 29), and drug targeting (30, 31), as well as broad profiling of gene expression in certain cancers (32, 33) and brain regions (34, 35, 36, 37, 38, 39, 40). However, thus far there is a paucity of studies using microarrays to assess hormonal regulation of target genes and their expression patterns. A PubMed search for "MICROARRAYS or GENE CHIPS" revealed approximately 2,500 relevant references. Only 50 of those references were endocrine related, and only 7 of these pertained to neuroendocrine effects. Because microarray technology is such a powerful tool for assessing the expression of thousands of genes simultaneously, it is only a matter of time before the field of endocrinology embraces this technique with greater enthusiasm. Thus, at this critical juncture it is important to understand their advantages and limitations (see Methodological criteria).

For one neuroendocrine example, estrogens have wide ranging effects in the central nervous system (CNS) that include but are not limited to 1) regulation of endocrine secretions from the anterior pituitary (41, 42, 43, 44); 2) behavior (45, 46); 3) learning and memory (47, 48, 49); and 4) neuroprotection (50, 51, 52). These varying effects depend on estrogens’ actions in specific estrogen-concentrating cell nuclei. We have been using microarrays (both oligonucleotide and cDNA arrays) to elucidate estrogen’s short and long-term actions on the transcriptomes of several of these regions. Arrays hybridized with RNA from the medial basal hypothalamus of hormone-treated and vehicle-treated adult female mice have revealed several unanticipated gene regulations. One of the more interesting ones is prostaglandin D synthetase (PGDS), a nonneuronal enzyme that catalyzes the conversion of PGH2 to PGD2, which is involved in a variety of functions including sedation and sleep (Mong, J. A., and D. W. Pfaff, manuscript submitted). In the parenchyma of the adult rodent, PGDS has been localized to oligodendrocytes (53, 54). Our in situ hybridization analysis has demonstrated a similar localization. Moreover, E2 increases expression in the arcuate and ventromedial nucleus of the hypothalamus, but there is dramatic suppression in the preoptic area. One exciting implication of the PDGS regulation, as well as the regulation of several other E2-responsive glial-specific genes, is that microarray screens may be uncovering hormone-dependent neuronal-glial interactions in vivo. These are emerging as important players in the hormonal modulation of neural function. To date, whereas ERs are expressed in cultured astrocytes from the hypothalamus (55), there is a lack of evidence for in vivo expression (for reviews, see Refs. 56 and 57). Previous studies have demonstrated that in the adult and neonatal rodent arcuate nucleus of the hypothalamus, astrocytes are responsive to E2 (56, 58, 59, 60, 61, 62, 63, 64), and recent work in vivo has demonstrated that the estrogenic signal is mediated by neuronal factors (57). The cellular mechanisms are still unknown.


   Methodological criteria
Top
 Abstract
 Introduction
 Differential display PCR (DD...
 Microarrrays
 Methodological criteria
References
 
It has been our experience that a well-designed and successful microarray experiment must meet the following criteria: 1) narrowly defined stimuli; 2) sample reliability and reproducibility; 3) quantitative confirmation of differential expression with biochemical or histochemical techniques; 4) adequate data analysis; and 5) functional evaluation.

Differential stimuli.
The nature of the inducing stimulus, hormonal or sensory, must be selective enough such that the resulting spectrum of differentially expressed genes can be interpreted in a sensible manner. Poorly conceived experiments would use very broad conditions such as "sleep vs. wakefulness" (65) or "aged vs. young" (66). In these examples, so many physiological processes are involved that the results are hard to interpret. In contrast, a narrowly defined inducer such as a functionally characterized hormonal treatment can be extremely informative. This has been demonstrated by Feng et al. (67), who were the first to use cDNA microarray technology to examine hormonal regulation of target genes in vivo. Using hypothyroid and T3-treated mice, they identified target genes from the liver, many of which were, surprisingly, negatively regulated by T3.

Sample RNA.
Microarray experiments are in greatest peril at the very beginning, when mRNA sample reliability and reproducibility are most vulnerable. In tissues with high levels of ribonuclease such as CNS and pancreas, it is difficult to get RNA of high quality, and great care must be taken in dissection and tissue handling. As Geschwind (68) eloquently outlined in a recent commentary, even small changes in experimental conditions (i.e. RNA degradation or nonuniform dissection techniques) can give the appearance of altering gene expression significantly, especially when thousands of genes are surveyed in parallel. A clever dissection of brain cell groups, rapid yet accurate, is a must. Samples containing multiple brain nuclei will pose problems for data interpretation. When possible, comparisons of duplicate chips from the same brain region, but using different animals, comprise the best way to assess variability. Alternatively, when this is not possible due to limited tissue availability or high cost, pooling a large number of animals for each experimental condition and brain region constitutes one strategy for reducing individual sample variability and thus reducing the number of arrays.

Confirming with biochemical and histochemical assays.
Another characteristic of a well-executed chip study is the quantitative confirmation of apparent positive results. Northern blots and quantitative RT-PCR are possible methods of verification. However, for the CNS, in situ hybridization is much more informative as it gives cellular resolution with respect to the differentially expressed genes (34, 40, 69). Zirlinger et al. (40) have beautifully demonstrated the informative nature of in situ hybridization in the CNS as it relates to data sets from multiple chip comparisons. Amygdala-specific candidate genes were identified with high- density oligonucleotide arrays. Interestingly, in situ hybridization for those identified genes revealed that the majority of them exhibited intraamygdaloid expression boundaries corresponding to cytoarchitectonically defined subnuclei.

How large a change is required to be statistically or biologically significant? There is no fixed rule. In fact, there may be a marked discrepancy between what is experimentally verifiable with any given technique (with microarrays, customarily, more than 2.0- or 2.5-fold change) and what is neurobiologically important. That is, in highly regulated systems such as in the CNS, alterations that appear numerically small may be functionally important. Moreover, the follow up experiments with histochemistry in the CNS are particularly important. A given percent alteration in the entire dissected tissue sample may actually reflect a huge change in a subpopulation of neurons or glial cells.

Data analysis.
There are many sources of systematic variation in microarray experiments for both oligonucleotide and cDNA arrays. Sources of variation are introduced during 1) manufacturing (probe concentration and substrate surface characteristics); 2) hybridization (target-probe hybridization is influenced by the nature of buffers, temperature, and duration of the hybridization reaction; and 3) optical measurement (irregularities in laser and scanner lens, spot misalignment and imaging algorithms). Normalization is the term used to describe the process of removing the consequences of these inherent variations and is a prerequisite for any thorough statistical analysis. Several normalization methods exist and have been successfully applied to data sets obtained from cDNA and oligonucleotide array experiments (70, 71, 72, 73, 74).

Using microarrays to identify individually changed genes in response to varying hormonal conditions without taking into consideration the pattern of changes across the entire transcriptome of a particular tissue would be an under-utilization of this technology. Even the simplest array study will generate an enormous amount of data, which must be managed with some form of multifactorial analyses and bioinformatic support. These are constantly improving (10, 75, 76, 77, 78, 79). In particular, k-means cluster analysis (80) and singular variate decomposition (81, 82) have been successfully used for discerning patterns of change. In addition, a variety of clustering algorithms such as hierarchical clustering, self organizing maps, mixture-based clustering (83) and dimension reduction techniques that include multidimensional scaling and sliced inverse regression (84) have been successfully used for discerning patterns of change.

Functional evaluation.
Differentially expressed genes, revealed by either microarray or DD-PCR experiments, should be considered a starting point for addressing their specific functions in neuroendocrine processes. Behavioral and pituitary endpoints are easily assayed. Pharmacological manipulation, antisense oligonucleotide technology, and/or the utilization of knockout mice can aid in addressing the physiological relevance of the identified genes. In recent years, for example, improvements in antisense design and manufacturing (for reviews, see Refs. 85 and 86) have made this technology a successful tool for modulating gene expression in the brain, thus to elucidate neural functions of specific mRNAs.

In sum, DD-PCR and "Gene Chip" technologies are two valuable approaches allowing neuroendocrinologists to move from examining how steroid hormone receptors regulate single genes, to a much broader understanding of the complete orchestration of genomic changes taking place in the nuclei of neurons and glia in response to hormones.


   Acknowledgments
 
The authors are grateful to professors Randy Nelson, Francesca Chiaromonte, and Nina Fedoroff for their helpful comments on the manuscript and to Carol Oliver for editorial assistance.


   Footnotes
 
Abbreviations: CNS, Central nervous system; DD-PCR, differential display PCR; PGDS, prostaglandin D synthetase.

Received February 27, 2002.

Accepted for publication March 4, 2002.


   References
Top
 Abstract
 Introduction
 Differential display PCR (DD...
 Microarrrays
 Methodological criteria
 References
 

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