Serial Analysis Of Gene Expression Libraries Research Articles

Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression

Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available on-line SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human genome and better biocomputational techniques have substantially improved the assignment of differentially expressed SAGE “tags” to human genes. These improvements have provided us with an opportunity to re-evaluate global gene expression in pancreatic cancer using existing SAGE libraries. SAGE libraries generated from 6 pancreatic cancers were compared to SAGE libraries generated from 11 non-neoplastic tissues. Compared to normal tissue libraries, we identified 453 SAGE tags as differentially expressed in pancreatic cancer, including 395 that mapped to known genes and 58 “uncharacterized” tags. Of the 395 SAGE tags assigned to known genes, 223 were overexpressed in pancreatic cancer, and 172 were underexpressed. In order to map the 58 uncharacterized differentially expressed SAGE tags to genes, we used a newly developed resource called TAGmapper (http://tagmapper.ibioinformatics.org), to identify 16 additional differentially expressed genes. The differential expression of 7 genes, involved in multiple cellular processes such as signal transduction (MIC-1), differentiation (DMBT1 and Neugrin), immune response (CD74), inflammation (CXCL2), cell cycle (CEB1) and enzymatic activity (Kallikrein 6), was confirmed by either immunohistochemical labeling of tissue microarrays (Kallikrein 6, CD74 and DMBT1) or by RT-PCR (CEB1, Neugrin, MIC1, and CXCL2). Of note, Neugrin was one of the genes whose previously uncharacterized SAGE tag was correctly assigned using TAGmapper, validating the utility of this program. Novel differentially expressed genes in a cancer type can be identified by revisiting updated and expanded SAGE databases. TAGmapper should prove to be a powerful tool for the discovery of novel tumor markers through assignment of uncharacterized SAGE tags.

Gene expression profiling of the rat superior olivary complex using serial analysis of gene expression

The superior olivary complex (SOC) is an auditory brainstem region that represents a favourable system to study rapid neurotransmission and the maturation of neuronal circuits. Here we performed serial analysis of gene expression (SAGE) on the SOC in 60-day-old Sprague-Dawley rats to identify genes specifically important for its function and to create a transcriptome reference for the subsequent identification of age-related or disease-related changes. Sequencing of 31 035 tags identified 10 473 different transcripts. Fifty-seven per cent of the unique tags with a count greater than four were statistically more highly represented in the SOC than in the hippocampus. Among them were genes encoding proteins involved in energy supply, the glutamate/glutamine shuttle, and myelination. Approximately 80 plasma membrane transporters, receptors, channels, and vesicular transporters were identified, and 25% of them displayed a significantly higher expression level in the SOC than in the hippocampus. Some of the plasma membrane proteins were not previously characterized in the SOC, e.g. the purinergic receptor subunit P2X(6) and the metabotropic GABA receptor Gpr51. Differential gene expression between SOC and hippocampus was confirmed using RNA in situ hybridization or immunohistochemistry. The extensive gene inventory presented here will alleviate the dissection of the molecular mechanisms underlying specific SOC functions and the comparison with other SAGE libraries from brain will ease the identification of promoters to generate region-specific transgenic animals. The analysis will be part of the publicly available database ID-GRAB.

Mining SAGE data allows large-scale, sensitive screening of antisense transcript expression

As a growing number of complementary transcripts, susceptible to exert various regulatory functions, are being found in eukaryotes, high throughput analytical methods are needed to investigate their expression in multiple biological samples. Serial Analysis of Gene Expression (SAGE), based on the enumeration of directionally reliable short cDNA sequences (tags), is capable of revealing antisense transcripts. We initially detected them by observing tags that mapped on to the reverse complement of known mRNAs. The presence of such tags in individual SAGE libraries suggested that SAGE datasets contain latent information on antisense transcripts. We raised a collection of virtual tags for mining these data. Tag pairs were assembled by searching for complementarities between 24-nt long sequences centered on the potential SAGE-anchoring sites of well-annotated human expressed sequences. An analysis of their presence in a large collection of published SAGE libraries revealed transcripts expressed at high levels from both strands of two adjacent, oppositely oriented, transcription units. In other cases, the respective transcripts of such cis-oriented genes displayed a mutually exclusive expression pattern or were co-expressed in a small number of libraries. Other tag pairs revealed overlapping transcripts of trans-encoded unique genes. Finally, we isolated a group of tags shared by multiple transcripts. Most of them mapped on to retroelements, essentially represented in humans by Alu sequences inserted in opposite orientations in the 3'UTR of otherwise different mRNAs. Registering these tags in separate files makes possible computational searches focused on unique sense-antisense pairs. The method developed in the present work shows that SAGE datasets constitute a major resource of rapidly investigating with high sensitivity the expression of antisense transcripts, so that a single tag may be detected in one library when screening a large number of biological samples.

Comparison of Cord Blood and Bone Marrow Mononuclear Cells by Serial Analysis of Gene Expression (SAGE).

Hematopoietic stem/progenitor cells with their dual ability for self-renewal, expansion and multilineage differentiation constitute an essential component of hematopoietic transplantation. These qualities, together with their transfection capacity make them useful for gene therapy also. Umbilical cord blood and bone marrow represent efficient sources of these cells. Cord blood stem cells are more primitive than bone marrow cells. They have a greater capacity to self-renewal, proliferation, expansion, multilineage differentiation and are better transfected. They can also be transplanted without complete HLA compatibility.Some recent studies are demonstrating that they could have a better trafficking and homing than the others, which could promote an efficient development and proliferation in the marrow microenvironment and better recovering when transplanted. However, these mechanisms of migration/cell adhesion and cell cycle are not fully understood. The aim of this study is to compare cord blood mononuclear cells with the existing bone marrow mononuclear cells library (esage database) by means of serial analysis of gene expression in order to investigate if there are any differences that could explain those findings. We obtained, by sequencing the SAGE library of cord blood cells, a total of 44.924 tags representing 15.519 unique tags. These unique tags were distribute as: known genes= 7772; sequence predicted or annotated=3935; no matches= 3812. The bone marrow library showed total tags=36577 being unique tags=13075: known genes= 6711; sequence predicted or annotated = 3371; no matches= 2993. These genes were annotated using Gene Ontology Consortium and the distribution of the categories in both libraries was similar. The different expression genes, selected using the fold difference (fold≥5 and ≤ 5), were 238. In order to validate the library, we tested 12 different expressed genes by real time PCR. The first six of them (SMARCC2, CDC25B, S100-8, alpha-globin, beta-globin, gamma-globin) confirmed the SAGE results. The more expressed cord blood genes were SMARCC2, CDC25B and gamma-globin. Beta-globin, and S100-8 were more expressed in bone marrow. The alpha- globin result demonstrated almost the same result between cord blood and bone marrow. CDC25B is a member of the CDC25, family of phosphatases, it activates cyclin dependent kinase CDC2 which is required for entry into mitoses. SMARCC2 is a member of SWI/SNF family proteins which display helicase and ATPase activities. It is responsible for regulation of transcription of certain genes by altering the chromatin structure around those genes. S100-8 is a calcium binding protein with a prominent role in leukocyte trafficking. It stimulates shedding of L-selectin, which is also involved in cell adhesion. It makes a role in inflammatory process towards neutrophil migration to inflammatory sites. The alpha, beta and gamma globin results were those expected based on the ontogeny. The differential gene expression here obtained could be an important tool to guide new functional studies regarding the molecular mechanisms of homing, cell cycle and cell adhesion of cord blood cells.

From Mice to Humans

Genetically engineered mouse mammary cancer models have been used over the years as systems to study human breast cancer. However, much controversy exists on the utility of such models as valid equivalents to the human cancer condition. To perform an interspecies gene expression comparative study in breast cancer we used a mouse model that most closely resembles human breast carcinogenesis. This system relies on the transplant of p53 null mouse mammary epithelial cells into the cleared mammary fat pads of syngeneic hosts. Serial analysis of gene expression (SAGE) was used to obtain gene expression profiles of normal and tumor samples from this mouse mammary cancer model (>300,000 mouse mammary-specific tags). The resulting mouse data were compared with 25 of our human breast cancer SAGE libraries (>2.5 million human breast-specific tags). We observed significant similarities in the deregulation of specific genes and gene families when comparing mouse with human breast cancer SAGE data. A total of 72 transcripts were identified as commonly deregulated in both species. We observed a systematic and significant down-regulation in all of the tumors from both species of various cytokines, including CXCL1 (GRO1), LIF, interleukin 6, and CCL2. All of the mouse and most human mammary tumors also displayed decreased expression of genes known to inhibit cell proliferation, including NFKBIA (IKBalpha), GADD45B, and CDKN1A (p21); transcription-related genes such as CEBP, JUN, JUNB, and ELF1; and apoptosis-related transcripts such as IER3 and GADD34/PPP1R15A. Examples of overexpressed transcripts in tumors from both species include proliferation-related genes such as CCND1, CKS1B, and STMN1 (oncoprotein 18); and genes related to other functions such as SEPW1, SDFR1, DNCI2, and SP110. Importantly, abnormal expression of several of these genes has not been associated previously with breast cancer. The consistency of these observations was validated in independent mouse and human mammary cancer sets. This is the first interspecies comparison of mammary cancer gene expression profiles. The comparative analysis of mouse and human SAGE mammary cancer data validates this p53 null mouse tumor model as a useful system closely resembling human breast cancer development and progression. More importantly, these studies are allowing us to identify relevant biomarkers of potential use in human studies while leading to a better understanding of specific mechanisms of human breast carcinogenesis.

Changes in mouse granulosa cell gene expression during early luteinization.

Changes in gene expression during granulosa cell luteinization have been measured using serial analysis of gene expression (SAGE). Immature normal mice were treated with pregnant mare serum gonadotropin (PMSG) or PMSG followed, 48 h later, by human chorionic gonadotropin (hCG). Granulosa cells were collected from preovulatory follicles after PMSG injection or PMSG/hCG injection and SAGE libraries generated from the isolated mRNA. The combined libraries contained 105,224 tags representing 40,248 unique transcripts. Overall, 715 transcripts showed a significant difference in abundance between the two libraries of which 216 were significantly down-regulated by hCG and 499 were significantly up-regulated. Among transcripts differentially regulated, there were clear and expected changes in genes involved in steroidogenesis as well as clusters of genes involved in modeling of the extracellular matrix, regulation of the cytoskeleton and intra and intercellular signaling. The SAGE libraries described here provide a base for functional investigation of the regulation of granulosa cell luteinization.

Serial analysis of gene expression in sinusoidal endothelial cells from normal and injured mouse liver

Here we describe gene expression profiles of mouse liver sinusoidal endothelial cells (LSECs) revealed by serial analysis of gene expression (SAGE). We prepared SAGE libraries of LSECs from normal and injured liver by CCl 4 administration, and we obtained 32,867 tags from normal and 37,493 tags from injured liver, representing 6011 unique transcripts. CCl 4 administration upregulated several genes related to cell growth and differentiation (Cdkn1a, Irf1, Il4ra, etc.), whereas it downregulated genes related to cell growth or protein transport (Kdr, Igfbp4, Ap1b1, etc.). To identify genes preferentially expressed in LSEC, we compared our SAGE libraries with 77 publicly available libraries generated from various mouse tissues and cell lines. We identified 23 genes, including Stab2 and uncharacterized genes, as possible markers for LSEC, which will be useful to analyze the specific role for LSECs in normal as well as regenerating liver.

Analysis of mouse germ-cell transcriptome at different stages of spermatogenesis by SAGE: Biological significance

The transcriptomes of mouse type A spermatogonia (Spga), pachytene spermatocytes (Spcy), and round spermatids (Sptd) were determined by sequencing the respective SAGE (Serial Analysis of Gene Expression) libraries. A total of 444,015 tags derived from one Spga, two Spcy, and one Sptd library were analyzed, and 34,619 different species of transcripts were identified, 5279 of which were novel. Results indicated the germ-cell transcriptome comprises of more than 30,000 transcripts. Virtual subtraction showed that cell-specific transcripts constitute 12–19.5% of the transcriptome. Components of the protein biosynthetic machinery are highly expressed in Spga. In Spcy transcription factors are abundantly expressed while transcripts encoding proteins involved in chromosome remodeling and testis-specific transcripts are prominent in Sptd. The databases generated by this work provide very useful resources for cellular localization of genes in silico. They are also extremely useful as sources for identification of splice variants of genes in germ cells.

Global transcription analysis of immature avian erythrocytic progenitors: from self-renewal to differentiation.

The molecular mechanisms regulating the cell fate decision between self-renewal and differentiation/apoptosis in stem and progenitor cells are poorly understood. Here, we report the first comprehensive identification of genes potentially involved in the switch from self-renewal toward differentiation of primary, non-immortalized erythroid avian progenitor cells (T2EC cells). We used the Serial Analysis of Gene Expression (SAGE) technique in order to identify and quantify the genome fraction functionally active in a self-renewing versus a differentiating cell population. We generated two SAGE libraries and sequenced a total of 37,589 tags, thereby obtaining the first transcriptional profile characterization of a chicken cell. Tag identification was performed using a new relational database (Identitag) developed in the laboratory, which allowed a highly satisfactory level of identification. Among 123 differentially expressed genes, 11 were investigated further and for nine of them the differential expression was subsequently confirmed by real-time PCR. The comparison of tag abundance between the two libraries revealed that only a small fraction of transcripts was differentially expressed. The analysis of their functions argue against a prominent role for a master switch in T2EC cells decision-making, but are in favor of a critical role for coordinated small variations in a relatively small number of genes that can lead to essential cellular identity changes.

ARNA-longSAGE: a new approach to generate SAGE libraries from microdissected cells.

Large-scale gene expression analyses of microdissected primary tissue are still difficult because generally only a limited amount of mRNA can be obtained from microdissected cells. The introduction of the T7-based RNA amplification technique was an important step to reduce the amount of RNA needed for such analyses. This amplification technique produces amplified antisense RNA (aRNA), which so far has precluded its direct use for serial analysis of gene expression (SAGE) library production. We describe a method, termed 'aRNA-longSAGE', which is the first to allow the direct use of aRNA for standard longSAGE library production. The aRNA-longSAGE protocol was validated by comparing two aRNA-longSAGE libraries with two Micro-longSAGE libraries that were generated from the same RNA preparations of two different cell lines. Using a conservative validation approach, we were able to verify 68% of the differentially expressed genes identified by aRNA-longSAGE. Furthermore, the identification rate of differentially expressed genes was roughly twice as high in our aRNA-longSAGE libraries as in the standard Micro-longSAGE libraries. Using our validated aRNA-longSAGE protocol, we were able to successfully generate longSAGE libraries from as little as 40 ng of total RNA isolated from 2000-3000 microdissected pancreatic ductal epithelial cells or cells from pancreatic intraepithelial neoplasias.

Reduction of the transcription level of the mitochondrial genome in human glioblastoma

Screening of human fetal brain cDNA library by glioblastoma (GB) and normal human brain total cDNA probes revealed 80 differentially hybridized clones. Hybridization of the DNA from selected clones and the same cDNA probes confirmed this difference for 38 clones, of which eight clones contained Alu-repeat inserts with increased levels in GB. Thirty clones contained cDNAs corresponding to mitochondrial genes for ATP synthase subunit 6 (ATP6), cytochrome c oxidase subunit II (COXII), cytochrome c oxidase subunit III (COXIII), NADH dehydrogenase subunit 1 (ND1), NADH dehydrogenase subunit 4 (ND4), and mitochondrial 12S rRNA. The levels of all these mitochondrial transcripts were decreased in glioblastomas as compared to tumor-adjacent histologically normal brain. Earlier we found the same for cytochrome c oxidase subunit I (COXI) Serial Analysis of Gene Expression (SAGE) showed lower content of the tags for all mitochondrial genes in GB SAGE libraries and together with our experimental data could serve as evidence of general inactivation of the mitochondrial genome in glioblastoma—the most malignant and abundant form of human brain tumor.

Search for new biomarkers of gastric cancer through serial analysis of gene expression and its clinical implications.

Gastric cancer is one of the most common human cancers and is the second most frequent cause of cancer-related death in the world. Serial analysis of gene expression (SAGE) is a powerful technique to allow genome-wide analysis of gene expression in a quantitative manner without prior knowledge of the gene sequences. SAGE on 5 samples of gastric cancer with different histology and clinical stages have created large SAGE libraries of gastric cancer that enable us to identify new cancer biomarkers. Commonly up-regulated genes in gastric cancer in comparison with normal gastric epithelia included CEACAM6, APOC1 and YF13H12. By comparing gene expression profiles of gastric cancers at early and advanced stages, several genes differentially expressed by tumor stage were also identified, including FUS, CDH17, COL1A1 and COL1A2, which should be novel genetic markers for high-grade malignancy. Regenerating gene type IV (REGIV) is one of the most up-regulated genes in a SAGE library of a scirrhous-type gastric cancer. In vitro studies using RegIV-transfected cells revealed that RegIV is secreted by cancer cells and inhibits apoptosis, suggesting that RegIV may serve as a novel biomarker and therapeutic target for gastric cancer. Production of RNA aptamers could be a useful approach to establish a detection system in blood. A custom-made array, named Ex-STOMACHIP, consisting of 395 genes, including highly differentially expressed genes identified by our SAGE and other known genes related to carcinogenesis and chemosensitivity, is useful to study the molecular pathogenesis of gastric cancer and to obtain information about biological behavior and sensitivity to therapy in the clinical setting. Combined analyses of gene expression profile, genetic polymorphism and genetic instability will aid not only cancer detection, but also characterization of individual cancers and patients, leading to personalized medicine and cancer prevention.

A Serial Analysis of Gene Expression (SAGE) database analysis of chemosensitivity: comparing solid tumors with cell lines and comparing solid tumors from different tissue origins.

Drug sensitivity and resistance has been most extensively studied in cell lines carried in tissue culture. Furthermore, cell lines have been widely used in testing new anticancer agents, despite the widely recognized observation that cell lines are more sensitive to cytotoxic drugs than are their corresponding solid tumors. We used the Serial Analysis of Gene Expression (SAGE) database to identify differences between solid tumors and cell lines, hoping to detect genes that could potentially explain differences in drug sensitivity. SAGE libraries were available for both solid tumors and cell lines from breast, colon, ovarian, pancreatic, and prostate carcinomas and from gliomas and medulloblastomas. Sixty-two genes were identified as overexpressed in tumors. The immune response and complement pathways were the significant common themes, with extracellular matrix (ECM) proteins third. For the 61 genes overexpressed in cell lines, protein synthesis was the dominant theme. We next used the SAGE database to identify genetic differences between tumor types that convey a broad range of survival to the patients that bear them as distant metastases. SAGE gene expression data were correlated with 5-year survivals documented in the SEER (Surveillance, Epidemiology and End-Results) database for patients diagnosed with "distant" or metastatic cancers. These are unlikely to be amenable to surgical resection; therefore, survival here reflects, to some extent, sensitivity to systemic therapy, i.e., chemotherapy. Using survival data as a surrogate of chemotherapy sensitivity, a spectrum can be generated, with testicular cancer at one end and pancreatic cancer at the other. Favorable 5-year survival, despite a distant presentation, correlates with expression of protein synthesis genes. Poor 5-year survival correlates with expression of cell adhesion, cytoskeletal, and ECM genes, a pattern similar to that found to distinguish solid tumors from the more cytotoxin-sensitive cancer cell lines. One interpretation is that resistance to chemotherapy may arise, in part, from the adherent, relatively inert condition (i.e., low in protein synthesis potential) of refractory cancers. Thus, attachment or ECM genes could be targets for anticancer therapy.

Clustering of Molecular Alterations in Gastroesophageal Carcinomas

Gene expression levels are regulated at many levels. Integration of genome-wide analyses for the study of DNA and RNA provides a unique tool to detect genetic alterations in the cancer genome. In this study, we generated and integrated DNA amplification data from comparative genomic hybridization (CGH) and serial analyses of gene expression (SAGE) in order to obtain a molecular profile of gastroesophageal junction (GEJ) carcinomas. DNA amplifications mapped to specific chromosomal regions and were frequently seen at 1 q, 4q, 5q, 6p, 7p, 8q, 17q, and 20q. Using SAGE, we obtained over 156,432 tags from GEJ adenocarcinomas and normal gastric mucosa. These tags were assigned to UniGene clusters. Chromosomal positions for overexpressed genes were obtained to produce a GEJ carcinoma transcriptome map. A total of 123 genes was significantly overexpressed (more than fivefold; P<.011) in one or more SAGE libraries. This gene overexpression map was integrated and compared to the chromosomal CGH ideogram. Several chromosomal arms that had frequent DNA amplifications showed frequent gene expression alterations such as chromosomes 1 (15 genes), 2 (9 genes), 6 (6 genes), 11 (6 genes), 12 (8 genes), and 17 (13 genes). Despite the relatively large DNA amplification regions, overexpressed genes frequently mapped and clustered to small chromosomal regions at early-replicating (Giemsa light) bands such as 1q21.3 (nine genes), 6p21.3 (five genes), and 17q21 (eight genes). These results provide a comprehensive tool to search for DNA amplifications and overexpressed genes in GEJ carcinoma. The observed phenomenon of the presence of large amplification areas, yet clustering of overexpressed genes to relatively small loci, may suggest a high organization of chromatin and cancer-related genes in the nucleus.

Incidence of "quasi-ditags" in catalogs generated by Serial Analysis of Gene Expression (SAGE)

BackgroundSerial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files; however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags ("quasi-ditags").ResultsWe provide examples of quasi-ditags that originate from cloning and sequencing artifacts (i.e. genomic contamination or random combinations of nucleotides) that are included in SAGE libraries. We have employed a mathematical model to predict the frequency of quasi-ditags in random nucleotide sequences, and our data show that clones containing less than or equal to 2 ditags (which include chromosomal cloning artifacts) should be excluded from the analysis of SAGE catalogs.ConclusionsCloning and sequencing artifacts contaminating SAGE libraries could be eliminated using simple pre-screening procedure to increase the reliability of the data.

The Mouse SAGE Site: database of public mouse SAGE libraries.

The Mouse SAGE Site is a web-based database of all available public libraries generated by the Serial Analysis of Gene Expression (SAGE) from various mouse tissues and cell lines. The database contains mouse SAGE libraries organized in a uniform way and provides web-based tools for browsing, comparing and searching SAGE data with reliable tag-to-gene identification. A modified approach based on the SAGEmap database is used for reliable tag identification. The Mouse SAGE Site is maintained on an ongoing basis at the Institute of Molecular Genetics, Academy of Sciences of the Czech Republic and is accessible at the internet address http://mouse.biomed.cas.cz/sage/.

Kallikrein gene downregulation in breast cancer.

Recent evidence suggests that many members of the human kallikrein gene family are differentially regulated in breast cancer and other endocrine-related malignancies. In this study, we utilised the serial analysis of gene expression (SAGE) and expressed sequence tag (EST) databases of the Cancer Genome Anatomy Project (CGAP) to perform in silico analyses of the expression pattern of the 15 human kallikrein genes in normal and cancerous breast tissues and cell lines using different analytical tools such as Virtual Northern blotting, Digital Differential Display and X-profiler. Our results indicate that at least four kallikrein genes (KLK5, 6, 8, 10) are downregulated in breast cancer. Probing eight normal and 24 breast cancer SAGE libraries with gene-specific tags for each of the above kallikreins indicated moderate-to-high expression densities in normal breast (27–319 tags per million; tpm, in two to five out of eight libraries), compared to no or low expression (0 – 34 tpm in zero to two libraries out of 24) in breast cancer. These data were verified by screening the EST databases, where all mRNA clones isolated for these genes, except for one in each, were from normal breast libraries, with no clones detected from breast cancer tissues or cell lines (with the exception of KLK8). X-profiler comparison of two pools of normal and breast cancer libraries further verified the presence of significant downregulation of expression levels of 4 of the kallikreins genes (KLK5, 6, 10, 12). We experimentally verified the downregulation of these four kallikreins (KLK5, 6, 8, 10 and 12) by RT – PCR analysis.

Serial analysis of gene expression in mouse kidney following angiotensin II administration.

As a new line of inquiry into the molecular mechanisms underlying pathophysiological processes associated with angiotensin (ANG II)-dependent hypertension, we applied the method of serial analysis of gene expression (SAGE) to examine genome-wide transcription changes in the kidneys of mice that developed hypertension in response to chronic ANG II administration. Mice were infused subcutaneously via osmotic minipumps with ANG II for 7 days, and systolic blood pressure was measured by tail-cuff plethysmography. Subsequently, mice were euthanized, and the total RNA isolated from the kidneys was used to construct SAGE libraries. Comparison of 11,447 SAGE tags from the hypertensive kidneys, representing 5,740 unique transcripts, and 11,273 tags from the control kidneys, corresponding to 5,619 different transcripts, identified genes that are significantly (P < 0.05) down- or upregulated in the hypertensive kidney. Our assessment of the genome-wide influence of ANG II resulted in the detection of several novel genes and in a recognition of potential new roles for the previously characterized genes, thus providing new probes with which to further explore the ANG II effects in normal and disease states.

Expression of complement components in the peripheral nervous system.

We have generated a SAGE (serial analysis of gene expression) library of normal sciatic nerve and found tags encoding for mRNAs of the complement system highly represented. RNA (RT-PCR and northern blot hybridization) and protein (western blot analysis and immunohistochemistry) studies confirmed these findings. High expression of classical pathway components, alternative pathway components and inhibitory components was observed in specific regions of the sciatic nerve. The first components of complement were found in axons, whereas the inhibitory components were detected in the perineurium, thereby protecting the nerve from a complement attack. Immunoreactivity towards activated complement factors was noted in post traumatic neuromas and after acute crush injury, which exemplify nerve regeneration and degeneration. We propose that local production of complement in the peripheral nervous system participates in the protection of healthy nerve and is needed for efficient clearance of myelin after injury: a prerequisite for normal regeneration and remyelination of the peripheral nerve.

Cryptococcus neoformans gene expression during experimental cryptococcal meningitis.

Cryptococcus neoformans, an encapsulated basidiomycete fungus of medical importance, is capable of crossing the blood-brain barrier and causing meningitis in both immunocompetent and immunocompromised individuals. To gain insight into the adaptation of the fungus to the host central nervous system (CNS), serial analysis of gene expression (SAGE) was used to characterize the gene expression profile of C. neoformans cells recovered from the CNS of infected rabbits. A SAGE library was constructed, and 49,048 tags were sequenced; 16,207 of these tags were found to represent unique sequences or tag families. Of the 304 most-abundant tags, 164 were assigned to a putative gene for subsequent functional grouping. The results (as determined according to the number of tags that identified genes encoding proteins required for these functions) indicated that the C. neoformans cells were actively engaged in protein synthesis, protein degradation, stress response, small-molecule transport, and signaling. In addition, a high level of energy requirement of the fungal cells was suggested by a large number of tags that matched putative genes for energy production. Taken together, these findings provide the first insight into the transcriptional adaptation of C. neoformans to the host environment and identify the set of fungal genes most highly expressed during cerebrospinal fluid infection.