Large-scale differential display analysis of T helper cell differentiation.

We have developed a novel large-scale multicapillary fluorescent differential display (FDD) platform amenable to further automation. The power of the method is demonstrated by the analysis of T helper cell differentiation. Eight RNA samples from wild type, Stat4 knockout and Stat6 knockout mice were analyzed with 16 anchoring primers and 24 arbitrary primers, resulting in 285 294 sample peaks. Visually selected patterns of differential expression suggest two major regulatory mechanisms: activation and Stat4 genotype. A subset of the findings is reproduced in the confirmatory differential display (DD) that included technical and biological replicates. In a small fragment identification pilot study, we identify Ifi27 and Cct8 to be up-regulated by T cell activation. We present a method for the analysis of electropherogram similarity across large datasets, based on correlation of low-resolution representations of electrophoretic data. We show how it can be applied to analyze experimental and technical variables. Using this method, we demonstrate the effect of activation and genotype. In addition, agreement of our real experimental data to the theoretical basis of DD, as well as issues in anchoring primer selectivity, are studied.

Computer-assisted identification of multitrace electrophoretic patterns in differential display experiments.

Modern multicapillary devices allow researchers to address increasingly complex biological questions involving comparisons of gene expression patterns across electrophoretic samples under various experimental conditions. As labor-intensive visual evaluation of the electrophoretic results is often the bottleneck of large-scale differential display (DD) studies, one way to further streamline this process is to focus only on a highly compressed list of the most potential patterns that are likely to provide reliable findings. To enable the identification of such candidate patterns, we present a computer-assisted method for objective ranking of multitrace peak patterns in DD experiments. The fundamental component of the multitrace pattern ranking method (MRANK) is the multiple alignment algorithm that allows for discovery of patterns involving sets of peak complexes from various electrophoretic samples. A score value is attached to each detected pattern which characterizes how accurately the pattern resembles the desired pattern query, freely defined by the researcher. The ranked pattern list produced by MRANK is validated against visual evaluation in terms of detecting and ranking a group of relevant patterns in a DD analysis of T-helper cell differentiation. We demonstrate high enrichment of the desired patterns on top of the score-ranked list (e.g., 90% of the visually selected patterns are discovered by looking through the first 3% of patterns in the ranked list of all patterns). The results suggest that a substantial amount of manual labor can be saved without compromising the accuracy of the findings by prioritizing the patterns according to MRANK output in the visual confirmation phase.

Automated pattern ranking in differential display data analysis.

Gene expression analysis by differential display (DD) is limited by the labor-intensive visual evaluation of the electrophoretic data traces. We describe a flexible method for computer-assisted ranking of expression patterns in data from DD experiments. The method is based on a pairwise alignment and comparison of the quantitative trace data with respect to specific expression patterns defined by the investigator. The observed patterns are ranked according to a score value that identifies the most potential findings to be confirmed visually instead of the vast amount of original results. This two-step approach, enabled by the efficient computer algorithm for gene expression pattern comparison, will increase the percentage of true-positive findings chosen for the tedious downstream processing, while minimizing the cost and labor involved in large scale DD data analysis.

Contralateral non-operated nerve to transected rat sciatic nerve shows increased expression of IL-1beta, TGF-beta1, TNF-alpha, and IL-10.

Recent reports indicate that after a peripheral nerve injury, the uninjured contralateral nerve is also affected. Because cytokines play an important role in the peripheral nerve injury, we studied the expression of five different mRNAs (interleukin-1beta (IL-1beta), tumor necrosis factor-alpha (TNF-alpha), interleukin-10 (IL-10), transforming growth factor-beta1 (TGF-beta1) and interleukin-4 (IL-4)) in the contralateral, non-operated, left sciatic nerve when the right rat sciatic nerve was transected. This study extended up to 42 days after the transection. No IL-4 expression was noted. During the first 3 days, high expression of the other studied cytokines was noted in the endoneurium. At day 7, the expression diminished to the control levels. After this, a cyclic expression pattern appeared, which was most pronounced in the endoneurium at 35 days. We also show that the expression pattern in the endoneurium is different from that in the surrounding epi- and perineurium. Also, our present study shows clearly that contralateral nerves are poor controls after injury.

mRNA differential display of gene expression in colonic carcinoma.

We analyzed changes in gene expression in human colonic carcinoma by fluorescent mRNA differential display. RNA isolated from two samples of normal colon and four cases of colonic adenocarcinoma were amplified with a 15 x 32 set of primers resulting in 2880 cDNAs analyzed with an automated sequencer. Electrophoretic patterns implying constitutive gene expression as well as upregulated and downregulated expression in carcinomas were identified. Forty such cDNA fragments were purified by a novel fluorescent polyacrylamide gel electrophoresis (PAGE)-based method and identified by cyclic sequencing. Most genes showing differential expression were upregulated in colonic carcinoma. Upregulated genes included those for various ribosomal and mitochondrial proteins, heat shock proteins, nucleolar RNA-helicase and phosphoserine aminotransferase. Downregulated genes included histone H3.3. In conclusion, genes associated with vital cellular functions such as transcription, protein synthesis and mitochondrial metabolism were upregulated in colonic carcinoma. Fluorescent mRNA differential display can be applied to the identification of novel cancer-related genes for diagnostic, prognostic and therapeutic purposes.