Analysis of the microbial gene landscape and transcriptome for aromatic pollutants and alkane degradation using a novel internally calibrated microarray system

Abstract

Despite various efforts to develop tools to detect and compare the catabolic potential and activity for pollutant degradation in environmental samples, there is still a need for an open-source, curated and reliable array method. We developed a custom array system including a novel normalization strategy that can be applied to any microarray design, allowing the calculation of the reliability of signals and make cross-experimental comparisons. Array probes, which are fully available to the scientific community, were designed from knowledge-based curated databases for key aromatic catabolic gene families and key alkane degradation genes. This design assigns signals to the respective protein subfamilies, thus directly inferring function and substrate specificity. Experimental procedures were optimized using DNA of four genome sequenced biodegradation strains and reliability of signals assessed through a novel normalization procedure, where a plasmid containing four artificial targets in increased copy numbers and co-amplified with the environmental DNA served as an internal calibration curve. The array system was applied to assess the catabolic gene landscape and transcriptome of aromatic contaminated environmental samples, confirming the abundance of catabolic gene subfamilies previously detected by functional metagenomics but also revealing the presence of previously undetected catabolic groups and specifically their expression under pollutant stress.