Sanggyu Lee

Quercetin inhibits expression of inflammatory cytokines through attenuation of NF-κB and p38 MAPK in HMC-1 human mast cell line

Abstract.Objective and design:Mast cell-mediated allergic inflammation is involved in many diseases such as asthma, sinusitis, and rheumatoid arthritis. Mast cells induce production of pro-inflammatory cytokines with immune regulatory properties. We investigated the effect of quercetin on the expression of pro-inflammatory cytokines in human mast cell line, HMC-1.Methods:HMC-1 cells were stimulated with phorbol 12-myristate 13-acetate (PMA) and calcium ionophore A23187 (PMACI).Results:Quercetin decreased the gene expression and production of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and IL-8 in PMACI-stimulated HMC-1 cells. Quercetin attenuated PMACI-induced activation of NF-κB and p38 mitogen-activated protein kinase.Conclusion:Our study provides evidence that quercetin may suitable for the treatment of mast cell-derived allergic inflammatory diseases.

Identifying novel transcripts and novel genes in the human genome by using novel SAGE tags

The number of genes in the human genome is still a controversial issue. Whereas most of the genes in the human genome are said to have been physically or computationally identified, many short cDNA sequences identified as tags by use of serial analysis of gene expression (SAGE) do not match these genes. By performing experimental verification of more than 1,000 SAGE tags and analyzing 4,285,923 SAGE tags of human origin in the current SAGE database, we examined the nature of the unmatched SAGE tags. Our study shows that most of the unmatched SAGE tags are truly novel SAGE tags that originated from novel transcripts not yet identified in the human genome, including alternatively spliced transcripts from known genes and potential novel genes. Our study indicates that by using novel SAGE tags as probes, we should be able to identify efficiently many novel transcripts/novel genes in the human genome that are difficult to identify by conventional methods.

SAGE is far more sensitive than EST for detecting low-abundance transcripts

BackgroundIsolation of low-abundance transcripts expressed in a genome remains a serious challenge in transcriptome studies. The sensitivity of the methods used for analysis has a direct impact on the efficiency of the detection. We compared the EST method and the SAGE method to determine which one is more sensitive and to what extent the sensitivity is great for the detection of low-abundance transcripts.ResultsUsing the same low-abundance transcripts detected by both methods as the targeted sequences, we observed that the SAGE method is 26 times more sensitive than the EST method for the detection of low-abundance transcripts.ConclusionsThe SAGE method is more efficient than the EST method in detecting the low-abundance transcripts.

Oligo(dT) primer generates a high frequency of truncated cDNAs through internal poly(A) priming during reverse transcription

We have analyzed a systematic flaw in the current system of gene identification: the oligo(dT) primer widely used for cDNA synthesis generates a high frequency of truncated cDNAs through internal poly(A) priming. Such truncated cDNAs may contribute to 12% of the expressed sequence tags in the current dbEST database. By using a synthetic transcript and real mRNA templates as models, we characterized the patterns of internal poly(A) priming by oligo(dT) primer. We further demonstrated that the internal poly(A) priming can be effectively diminished by replacing the oligo(dT) primer with a set of anchored oligo(dT) primers for reverse transcription. Our study indicates that cDNAs designed for genomewide gene identification should be synthesized by use of the anchored oligo(dT) primers, rather than the oligo(dT) primers, to diminish the generation of truncated cDNAs caused by internal poly(A) priming.

The pattern of gene expression in human CD34+ stem/progenitor cells

We have analyzed the pattern of gene expression in human primary CD34+ stem/progenitor cells. We identified 42,399 unique serial analysis of gene expression (SAGE) tags among 106,021 SAGE tags collected from 2.5 × 106 CD34+ cells purified from bone marrow. Of these unique SAGE tags, 21,546 matched known expressed sequences, including 3,687 known genes, and 20,854 were novel without a match. The SAGE tags that matched known sequences tended to be at higher levels, whereas the novel SAGE tags tended to be at lower levels. By using the generation of longer sequences from SAGE tags for gene identification (GLGI) method, we identified the correct gene for 385 of 440 high-copy SAGE tags that matched multiple genes and we generated 198 novel 3′ expressed sequence tags from 138 high-copy novel SAGE tags. We observed that many different SAGE tags were derived from the same genes, reflecting the high heterogeneity of the 3′ untranslated region in the expressed genes. We compared the quantitative relationship for genes known to be important in hematopoiesis. The qualitative identification and quantitative measure for each known gene, expressed sequence tag, and novel SAGE tag provide a base for studying normal gene expression in hematopoietic stem/progenitor cells and for studying abnormal gene expression in hematopoietic diseases.

Serial Analysis of Gene Expression Study of a Hybrid Rice Strain (LYP9) and Its Parental Cultivars

Using the serial analysis of gene expression technique, we surveyed transcriptomes of three major tissues (panicles, leaves, and roots) of a super-hybrid rice (Oryza sativa) strain, LYP9, in comparison to its parental cultivars, 93-11 (indica) and PA64s (japonica). We acquired 465,679 tags from the serial analysis of gene expression libraries, which were consolidated into 68,483 unique tags. Focusing our initial functional analyses on a subset of the data that are supported by full-length cDNAs and the tags (genes) differentially expressed in the hybrid at a significant level (P < 0.01), we identified 595 up-regulated (22 tags in panicles, 228 in leaves, and 345 in roots) and 25 down-regulated (seven tags in panicles, 15 in leaves, and three in roots) in LYP9. Most of the tag-identified and up-regulated genes were found related to enhancing carbon- and nitrogen-assimilation, including photosynthesis in leaves, nitrogen uptake in roots, and rapid growth in both roots and panicles. Among the down-regulated genes in LYP9, there is an essential enzyme in photorespiration, alanine:glyoxylate aminotransferase 1. Our study adds a new set of data crucial for the understanding of molecular mechanisms of heterosis and gene regulation networks of the cultivated rice.

2.45 GHz radiofrequency fields alter gene expression in cultured human cells

The biological effect of radiofrequency (RF) fields remains controversial. We address this issue by examining whether RF fields can cause changes in gene expression. We used the pulsed RF fields at a frequency of 2.45 GHz that is commonly used in telecommunication to expose cultured human HL‐60 cells. We used the serial analysis of gene expression (SAGE) method to measure the RF effect on gene expression at the genome level. We observed that 221 genes altered their expression after a 2‐h exposure. The number of affected genes increased to 759 after a 6‐h exposure. Functional classification of the affected genes reveals that apoptosis‐related genes were among the upregulated ones and the cell cycle genes among the downregulated ones. We observed no significant increase in the expression of heat shock genes. These results indicate that the RF fields at 2.45 GHz can alter gene expression in cultured human cells through non‐thermal mechanism.

Silencing of B Cell Receptor Signals in Human Naive B Cells

To identify changes in the regulation of B cell receptor (BCR) signals during the development of human B cells, we generated genome-wide gene expression profiles using the serial analysis of gene expression (SAGE) technique for CD34+ hematopoietic stem cells (HSCs), pre-B cells, naive, germinal center (GC), and memory B cells. Comparing these SAGE profiles, genes encoding positive regulators of BCR signaling were expressed at consistently lower levels in naive B cells than in all other B cell subsets. Conversely, a large group of inhibitory signaling molecules, mostly belonging to the immunoglobulin superfamily (IgSF), were specifically or predominantly expressed in naive B cells. The quantitative differences observed by SAGE were corroborated by semiquantitative reverse transcription–polymerase chain reaction (RT-PCR) and flow cytometry. In a functional assay, we show that down-regulation of inhibitory IgSF receptors and increased responsiveness to BCR stimulation in memory as compared with naive B cells at least partly results from interleukin (IL)-4 receptor signaling. Conversely, activation or impairment of the inhibitory IgSF receptor LIRB1 affected BCR-dependent Ca2+ mobilization only in naive but not memory B cells. Thus, LIRB1 and IL-4 may represent components of two nonoverlapping gene expression programs in naive and memory B cells, respectively: in naive B cells, a large group of inhibitory IgSF receptors can elevate the BCR signaling threshold to prevent these cells from premature activation and clonal expansion before GC-dependent affinity maturation. In memory B cells, facilitated responsiveness upon reencounter of the immunizing antigen may result from amplification of BCR signals at virtually all levels of signal transduction.

High-throughput GLGI procedure for converting a large number of serial analysis of gene expression tag sequences into 3′ complementary DNAs

Serial analysis of gene expression (SAGE) is a powerful technique for genome‐wide analysis of gene expression. However, two‐thirds of SAGE tags cannot be used directly for gene identification for two reasons. First, many SAGE tags match several known expressed sequences, owing to the short length of SAGE tag sequences. Second, many SAGE tags do not match any known expressed sequences, presumably because the sequences corresponding to these SAGE tags have not been identified. These two problems can be solved by extension of the SAGE tags into 3′ complementary DNAs (cDNAs) by use of the GLGI technique (generation of longer cDNA fragments from SAGE tags for gene identification). We have improved the original GLGI technique into a high‐throughput procedure for simultaneous conversion of a large number of SAGE tags into corresponding 3′ cDNAs. The whole process is simple, rapid, low‐cost, and highly efficient, as shown by our use of this procedure for analyzing hundreds of SAGE tags. In addition to identifying the correct gene for SAGE tags with multiple matches, GLGI can be used for large‐scale identification of novel genes by converting novel SAGE tags into 3′ cDNAs. Applying this high‐throughput procedure should accelerate the rate of gene identification significantly in the human and other eukaryotic genomes.

The pattern of gene expression in human CD15+ myeloid progenitor cells

We performed a genome-wide analysis of gene expression in primary human CD15+ myeloid progenitor cells. By using the serial analysis of gene expression (SAGE) technique, we obtained quantitative information for the expression of 37,519 unique SAGE-tag sequences. Of these unique tags, (i) 25% were detected at high and intermediate levels, whereas 75% were present as single copies, (ii) 53% of the tags matched known expressed sequences, 34% of which were matched to more than one known expressed sequence, and (iii) 47% of the tags had no matches and represent potentially novel genes. The correct genes were confirmed by application of the generation of longer cDNA fragments from SAGE tags for gene identification (GLGI) technique for high-copy tags with multiple matches. A set of genes known to be important in myeloid differentiation were expressed at various levels and used different spliced forms. This study provides a normal baseline for comparison of gene expression in myeloid diseases. The strategy of using SAGE and GLGI techniques in this study has broad applications to the genome-wide identification of expressed genes.