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Biomedical subjects

Soumitra Ghosh

Publications and source records attributed to Soumitra Ghosh.

10 recordsLinked to original sources

Involvement of eotaxin, eosinophils, and pancreatic predisposition in development of type 1 diabetes mellitus in the BioBreeding rat.

Allergy and autoimmunity are both examples of deregulated immunity characterized by inflammation and injury of targeted tissues that have until recently been considered disparate disease processes. However, recent findings have implicated mast cells, in coordination with granulocytes and other immune effector cells, in the pathology of these two disorders. The BioBreeding (BB) DRlyp/lyp rat develops an autoimmune insulin-dependent diabetes similar to human type 1 diabetes mellitus (T1DM), whereas the BBDR+/+ rat does not. To better understand immune processes during development of T1DM, gene expression profiling at day (d) 40 (before insulitis) and d65 (before disease onset) was conducted on pancreatic lymph nodes of DRlyp/lyp, DR+/+, and Wistar-Furth (WF) rats. The eosinophil-recruiting chemokine, eotaxin, and the high-affinity IgE receptor (FcepsilonRI) were up-regulated >5-fold in d65 DRlyp/lyp vs d65 DR+/+ pancreatic lymph nodes by microarray (p < 0.05) and quantitative RT-PCR studies (p < 0.05). DR+/+, WF, and d40 DRlyp/lyp animals possessed normal pancreatic histology; however, d65 DRlyp/lyp animals possessed eosinophilic insulitis. Therefore, immunohistochemistry for pancreatic eotaxin expression was conducted, revealing positive staining of d65 DRlyp/lyp islets. Islets of d65 DR+/+ rats also stained positively, consistent with underlying diabetic predisposition in the BB lineage, whereas WF islets did not. Other differentially expressed transcripts included those associated with eosinophils, mast cells, and lymphocytes. These data support an important role for these inflammatory mediators in BB rat T1DM and suggest that the lymphopenia due to the Ian5/(lyp) mutation may result in a deregulation of cells involved in insulitis and beta cell destruction.

Animals↗

A comparison between SNaPshot, pyrosequencing, and biplex invader SNP genotyping methods: accuracy, cost, and throughput.

Three methods of Single Nucleotide Polymorphism (SNP) detection: SNaPshot, Pyrosequencing and Biplex Invader, with two different chemistries were investigated to compare, (1) accuracy, (2) ease of use, (3) throughput capability, and (4) cost. We genotyped 192 human DNA samples across 24 SNPs (minor allele frequencies above 30%), of which seven SNPs were genotyped with all three methods. We show that the Biplex Invader genotyping method was found to be the most accurate and easiest to use with lowest cost, although Pyrosequencing provided similar results at a low cost. With little optimization, the accuracy of the SNaPshot method was also comparable to these two methods with a higher cost, if only singleplex reactions are used.

Alleles↗

The T cell activation marker CD150 can be used to identify alloantigen-activated CD4(+)25+ regulatory T cells.

We have been investigating whether alloantigen-specific CD4(+)25+ regulatory T cells can be identified for use in treating graft-versus-host disease. CD150, which is upregulated on the surface of all activated T lymphocytes, was identified as a candidate marker for alloantigen-activated CD4(+)25+ regulatory T cells by gene chip analysis. Freshly isolated CD4(+)25+ cells had only low cell-surface expression of CD150, comparable to that of CD4(+)25- T cells. Increased CD150 expression was observed on all T cells after coculture with allogeneic stimulator cells. When purified CD4(+)25+ cells were precultured with allogeneic stimulator cells, then sorted into CD150+ and CD150- subsets, allosuppressive activity was contained primarily in the CD150+ fraction. These cells also suppressed the proliferation of alloantigen-activated autologous T cells, and they could be expanded in vitro without loss of their suppressive capacity. These results suggest that CD150 can be used as a marker for the identification of purified alloantigen-activated CD4(+)25+ regulatory T cells.

Antigens, CD↗

A large set of Finnish affected sibling pair families with type 2 diabetes suggests susceptibility loci on chromosomes 6, 11, and 14.

The aim of the Finland-United States Investigation of NIDDM Genetics (FUSION) study is to identify genes that predispose to type 2 diabetes or are responsible for variability in diabetes-related traits via a positional cloning and positional candidate gene approach. In a previously published genome-wide scan of 478 Finnish affected sibling pair (ASP) families (FUSION 1), the strongest linkage results were on chromosomes 20 and 11. We now report a second genome-wide scan using an independent set of 242 Finnish ASP families (FUSION 2), a detailed analysis of the combined set of 737 FUSION 1 + 2 families (495 updated FUSION 1 families), and fine mapping of the regions of chromosomes 11 and 20. The strongest FUSION 2 linkage results were on chromosomes 6 (maximum logarithm of odds score [MLS] = 2.30 at 95 cM) and 14 (MLS = 1.80 at 57 cM). For the combined FUSION 1 + 2 families, three results were particularly notable: chromosome 11 (MLS = 2.98 at 82 cM), chromosome 14 (MLS = 2.74 at 58 cM), and chromosome 6 (MLS = 2.66 at 96 cM). We obtained smaller FUSION 1 + 2 MLSs on chromosomes X (MLS = 1.27 at 152 cM) and 20p (MLS = 1.21 at 20 cM). Among the 10 regions that showed nominally significant evidence for linkage in FUSION 1, four (on chromosomes 6, 11, 14, and X) also showed evidence for linkage in FUSION 2 and stronger evidence for linkage in the combined FUSION 1 + 2 sample.

Age of Onset↗

Quantitative quality control in microarray experiments and the application in data filtering, normalization and false positive rate prediction.

Data preprocessing including proper normalization and adequate quality control before complex data mining is crucial for studies using the cDNA microarray technology. We have developed a simple procedure that integrates data filtering and normalization with quantitative quality control of microarray experiments. Previously we have shown that data variability in a microarray experiment can be very well captured by a quality score q(com) that is defined for every spot, and the ratio distribution depends on q(com). Utilizing this knowledge, our data-filtering scheme allows the investigator to decide on the filtering stringency according to desired data variability, and our normalization procedure corrects the q(com)-dependent dye biases in terms of both the location and the spread of the ratio distribution. In addition, we propose a statistical model for false positive rate determination based on the design and the quality of a microarray experiment. The model predicts that a lower limit of 0.5 for the replicate concordance rate is needed in order to be certain of true positives. Our work demonstrates the importance and advantages of having a quantitative quality control scheme for microarrays.

Algorithms↗

Use of a three-color cDNA microarray platform to measure and control support-bound probe for improved data quality and reproducibility.

Construction methodologies for cDNA microarrays lack the ability to determine array integrity prior to hybridization, leaving the array itself a source of uncontrolled experimental variation. We solved this problem through development of a three-color cDNA array platform whereby printed probes are tagged with fluorescein and are compatible with Cy3 and Cy5 target labeling dyes when using confocal laser scanners possessing narrow bandwidths. Here we use this approach to: (i) develop a tracking system to monitor the printing of probe plates at predicted coordinates; (ii) define the quantity of immobilized probe necessary for quality hybridized array data to establish pre-hybridization array selection criteria; (iii) investigate factors that influence probe availability for hybridization; and (iv) explore the feasibility of hybridized data filtering using element fluorescein intensity. A direct and significant relationship (R2 = 0.73, P < 0.001) between pre-hybridization average fluorescein intensity and subsequent hybridized replicate consistency was observed, illustrating that data quality can be improved by selecting arrays that meet defined pre-hybridization criteria. Furthermore, we demonstrate that our three-color approach provides a means to filter spots possessing insufficient bound probe from hybridized data sets to further improve data quality. Collectively, this strategy will improve microarray data and increase its utility as a sensitive screening tool.

Color↗

Three color cDNA microarrays: quantitative assessment through the use of fluorescein-labeled probes.

Gene expression studies using microarrays have great potential to generate new insights into human disease pathogenesis, but data quality remains a major obstacle. In particular, there does not exist a method to determine prior to hybridization whether an array will yield high quality data, given good study design and target preparation. We have solved this problem through development of a three-color cDNA microarray platform where printed probes are fluorescein labeled, but are spectrally compatible with Cy3 and Cy5 dye-labeled targets when using confocal laser scanners possessing narrow bandwidths. This approach enables prehybridization evaluation of array/spot morphology, DNA deposition and retention and background levels. By using these measurements and the intra-slide coefficient of variation for fluorescence intensity we show that slides in the same batch are not equivalent and measurable prehybridization parameters can be predictive of hybridization performance as determined by replicate consistency. When hybridizing target derived from two cell lines to high and low quality replicate pairs (n = 50 pairs), a direct and significant relationship between prehybridization signal-to-background noise and post-hybridization reproducibility (R2 = 0.80, P < 0.001) was observed. We therefore conclude that slide selection based upon prehybridization quality scores will greatly benefit the ability to generate reliable gene expression data.

Carbocyanines↗

A novel approach for high-quality microarray processing using third-dye array visualization technology.

Historically, microarray image processing has been technically challenging in obtaining quality gene expression data. After hybridization of Cy3- and Cy5-labeled samples, images are collected and processed to obtain gene expression ratio measurements for each of the elements on the array. The hybridization process often brings in contaminating noise, which can make correct identification of the signal difficult. In addition, spot intensity levels are highly variable due to the expression differences of different genes, and weak spots are often difficult to detect. These conditions are further complicated by inherent irregularities in spot position, shape, and size commonly found on high-density microarrays, making image processing an often labor-intensive task that is difficult to reliably automate. We previously reported a novel third-dye array visualization (TDAV) technology that allows prehybridization visualization and quality control of printed arrays. Here, we present a new microarray image processing approach utilizing TDAV. By incorporating the third-dye image, we show that overall quality of the microarray data is significantly improved, and automation of processing is feasible and reliable. Furthermore, we demonstrate use of the third-dye image to better quality control microarray image analysis. Both the principle and implementation of the approach are presented in detail, with experimental results.

Algorithms↗

Difference in gene expression profiles between human CD4+CD25+ and CD4+CD25- T cells.

We studied the gene expression profiles of human CD4+CD25+ and CD4+CD25- T cells by using cDNA microarrays. Our preliminary results indicate that there are likely significant differences in the regulation of apoptosis, cell cycle, cytokine receptor, cell-cell interaction, and stress pathway genes between these two subtypes of T cells.

CD4 Antigens↗

The design of a gene chip for functional immunological studies on a high-quality control platform.

We have created an immunology-related microarray chip containing primarily known genes with well-studied functional properties. By looking at known genes rather than expressed sequence tags, we hope to gain a better understanding of immunological pathways and how they work. The immunology gene chip contains genes from the following functional categories: T cell genes; B cell genes; dendritic cell genes; chemokine and cytokine genes; apoptosis genes; cell cycle genes; cell interaction genes; general hematology and immunology genes; and adhesion genes. We have also developed a novel three-color cDNA array platform in which arrays are directly visualized before hybridization, which allows us to select only high-quality chips for our experiments. In an effort to provide quantitative quality control for each array element as well as the entire chip, we have developed Matarray, a software package for image processing and data acquisition. With Matarray, we have built a quantitative data filtering and normalization scheme that has proved to be more efficient than the existing methods. The list of immunology chip genes is available from the authors.

Chemokines↗