A high-throughput study of gene expression in preterm labor with a subtractive microarray approach.

Abstract

We propose that elucidation of the pathophysiology of preterm labor can be achieved with genome-scale analyses of differential gene expression. CD-1 mice on day 14.5 of a 19- to 20-day gestation were assigned to one of 4 treatment groups modeling different clinical conditions (n = 5 per group): group A, infection with labor (intrauterine injection of 10(10) heat-killed Escherichia coli, which causes delivery within an average of 20 hours); group B, infection without labor (intrauterine injection of 10(7) heat-killed E coli, which leads to normal delivery at term); group C, labor without infection (ovariectomy, which causes delivery within an average of 27 hours); and group D, no infection and no labor (intrauterine injection of vehicle). Total pooled myometrial RNA was prepared 3.5 hours after surgery for groups A, B, and D and 5 hours after surgery for group C. The relative expression of 4963 genes was assayed in these pools by using DNA microarrays. Transcripts specifically involved in infection-induced labor were identified by subtracting from the list of differentially regulated genes in group A those with common expression in groups B and C. In group A 68 differentially expressed transcripts (>or=2-fold upregulation or downregulation) were identified. Among these are 39 characterized genes. Fourteen (45%) are involved in inflammatory responses, 7 (18%) are involved in growth-differentiation-oncogenesis, and 3 (8%) are involved in apoptosis. Subtraction identified 13 gene products most likely to be important for bacterially induced labor, as opposed to labor without infection or bacterial exposure without labor. This study demonstrates the potential of the subtractive DNA microarray technique to identify transcripts important specifically for bacterially induced preterm labor.