SeMa-Trap

SeMa-Trap analyzes bacterial RNA-Seq transcriptomes to identify expression patterns associated with biosynthetic gene clusters (BGCs) and prioritize genes, including regulators, transporters, resistance factors, and precursor biosynthesis pathways, for activation or enhancement of secondary metabolite production.

Key Features:

• RNA-Seq-based transcriptome analysis: Analyzes RNA sequencing data to quantify gene expression across bacterial genomes and biosynthetic gene clusters (BGCs).
• Co-expression pattern identification: Identifies co-expression relationships between specific genes and BGCs to reveal potential regulatory links.
• Optimization of comparative analyses: Highlights gene expression changes across different conditions or strains to inform comparative transcriptomic study design.
• Prioritization for genetic engineering: Ranks genes encoding regulators, transporters, resistance factors, and precursor biosynthesis pathway enzymes as candidates for activation or overexpression to stimulate silent BGCs.

Scientific Applications:

• Natural product and drug discovery: Supports activation and discovery of antibiotics and other bioactive compounds by targeting silent BGCs.
• Target selection for strain engineering: Informs selection of genes for genetic manipulation to enhance secondary metabolite production in bacterial systems.

Methodology:

Utilizes RNA-Seq data for transcriptome analysis; identifies co-expression patterns between genes and BGCs; performs comparative transcriptomic analyses to detect condition- or strain-specific expression changes; ranks genes related to regulators, transporters, resistance factors, and precursor biosynthesis pathways for prioritization.