Project description:Six bacterial genomes, Geobacter metallireducens GS-15, Chromohalobacter salexigens, Vibrio breoganii 1C-10, Bacillus cereus ATCC 10987, Campylobacter jejuni subsp. jejuni 81-176 and Campylobacter jejuni NCTC 11168, all of which had previously been sequenced using other platforms were re-sequenced using single-molecule, real-time (SMRT) sequencing specifically to analyze their methylomes. In every case a number of new N6-methyladenine (m6A) and N4-methylcytosine (m4C) methylation patterns were discovered and the DNA methyltransferases (MTases) responsible for those methylation patterns were assigned. In 15 cases it was possible to match MTase genes with MTase recognition sequences without further sub-cloning. Two Type I restriction systems required sub-cloning to differentiate their recognition sequences, while four MTases genes that were not expressed in the native organism were sub-cloned to test for viability and recognition sequences. No attempt was made to detect 5-methylcytosine (m5C) recognition motifs from the SMRT sequencing data because this modification produces weaker signals using current methods. However, all predicted m6A and m4C MTases were detected unambiguously. This study shows that the addition of SMRT sequencing to traditional sequencing approaches gives a wealth of useful functional information about a genome showing not only which MTase genes are active, but also revealing their recognition sequences. Examination of the methylomes of six different strains of bacteria using kinetic data from single-molecule, real-time (SMRT) sequencing on the PacBio RS.
Project description:Six bacterial genomes, Geobacter metallireducens GS-15, Chromohalobacter salexigens, Vibrio breoganii 1C-10, Bacillus cereus ATCC 10987, Campylobacter jejuni subsp. jejuni 81-176 and Campylobacter jejuni NCTC 11168, all of which had previously been sequenced using other platforms were re-sequenced using single-molecule, real-time (SMRT) sequencing specifically to analyze their methylomes. In every case a number of new N6-methyladenine (m6A) and N4-methylcytosine (m4C) methylation patterns were discovered and the DNA methyltransferases (MTases) responsible for those methylation patterns were assigned. In 15 cases it was possible to match MTase genes with MTase recognition sequences without further sub-cloning. Two Type I restriction systems required sub-cloning to differentiate their recognition sequences, while four MTases genes that were not expressed in the native organism were sub-cloned to test for viability and recognition sequences. No attempt was made to detect 5-methylcytosine (m5C) recognition motifs from the SMRT sequencing data because this modification produces weaker signals using current methods. However, all predicted m6A and m4C MTases were detected unambiguously. This study shows that the addition of SMRT sequencing to traditional sequencing approaches gives a wealth of useful functional information about a genome showing not only which MTase genes are active, but also revealing their recognition sequences.
Project description:This study examined how transcriptomics tools can be included in a Triad-based soil quality assessment to assess the toxicity of soils from river banks polluted by metals. To that end we measured chemical soil properties and used the standardized ISO guideline for ecotoxicological tests and a newly developed microarray for gene expression in the indicator soil arthropod, Folsomia candida. Microarray analysis revealed that the oxidative stress response pathway was significantly affected in all soils except one. The data indicate that changes in cell redox homeostasis are a significant signature of metal stress. Finally, 32 genes showed significant dose-dependent expression with metal concentrations. They are promising genetic markers providing an early indication of the need for higher tier testing in soil quality. One of the least polluted soils showed toxicity in the bioassay that could be removed by sterilization. The gene expression profile for this soil did not show a metal-related signature, confirming that another factor than metals (most likely of biological origin) caused the toxicity. This study demonstrates the feasibility and advantages of integrating transcriptomics into Triad-based soil quality assessment. Combining molecular and organismal life-history traitM-bM-^@M-^Ys stress responses helps identifying causes of adverse effect in bioassays. Further validation is needed for verifying the set of genes with dose-dependent expression patterns linked with toxic stress. We used a one-color microarray design where each sample was hybridized to a single array