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Bacterial degradation of xenobiotic compounds is an intense field of research already for decades. Lately, this research is complemented by downstream applications including Next Generation Sequencing (NGS), RT-PCR, qPCR, and RNA-seq. For most of these molecular applications, high-quality RNA is a fundamental necessity. However, during the degradation of aromatic substrates, phenolic or polyphenolic compounds such as polycatechols are formed and interact irreversibly with nucleic acids, making RNA extraction from these sources a major challenge. Therefore, we established a method for total RNA extraction from the aromatic degrading Pseudomonas capeferrum TDA1 based on RNAzol® RT, glycogen and a final cleaning step. It yields a high-quality RNA from cells grown on TDA1 and on phenol compared to standard assays conducted in the study. To our knowledge, this is the first report tackling the problem of polyphenolic compound interference with total RNA isolation in bacteria. It might be considered as a guideline to improve total RNA extraction from other bacterial species.

Polyaromatic hydrocarbons (PAH) are common pollutants of water ecosystems originating from incineration processes and contamination with mineral oil. Water solubility of PAHs is generally low; for toxicity tests with aquatic organisms, they are therefore usually dissolved in organic solvents. Here we examined the effects of a typical model PAH, phenanthrene, and a solvent, acetone, on amphipods as relevant aquatic invertebrate models. Two of these species, Eulimnogammarus verrucosus and Eulimnogammarus cyaneus, are common endemics of the oligotrophic and pristine Lake Baikal, while one, Gammarus lacustris, is widespread throughout the Holarctic and inhabits smaller and more eutrophic water bodies in the Baikal area. Neither solvent nor phenanthrene caused mortality at the applied concentrations, but both substances affected gene expression in all species. Differential gene expression was more profound in the species from Lake Baikal than in the Holarctic species. Moreover, in one of the Baikal species, E. cyaneus, we found that many known components of the cellular xenobiotic detoxification system reacted to the treatments. Finally, we detected a negative relationship between changes in transcript abundances in response to the solvent and phenanthrene. This mixture effect, weaker than the impact by a single mixture component, needs further exploration.

In search of new biomarkers suitable for the diagnosis and treatment of prostate cancer, genome-wide transcriptome sequencing was carried out with tissue specimens from 40 prostate cancer (PCa) and 8 benign prostate hyperplasia patients. We identified two intergenic long non-coding transcripts, located in close genomic proximity, which are highly expressed in PCa. Microarray studies on a larger cohort comprising 155 patients showed a profound diagnostic potential of these transcripts (AUC~0.94), which we designated as tumor associated prostate cancer increased lncRNA (TAPIR-1 and -2). To test their therapeutic potential, knockdown experiments with siRNA were carried out. The knockdown caused an increase in the p53/TP53 tumor suppressor protein level followed by downregulation of a large number of cell cycle- and DNA-damage repair key regulators. Furthermore, in radiation therapy resistant tumor cells, the knockdown leads to a renewed sensitization of these cells to radiation treatment. Accordingly, in a preclinical PCa xenograft model in mice, the systemic application of nanoparticles loaded with siRNA targeting TAPIR-1 significantly reduced tumor growth. These findings point to a crucial role of TAPIR-1 and -2 in PCa.

BackgroundProstate cancer (PCa) is the most prevalent solid cancer among men in Western Countries. The clinical behavior of localized PCa is highly variable. Some cancers are aggressive leading to death, while others can even be monitored safely. Hence, there is a high clinical need for precise biomarkers for identification of aggressive disease in addition to established clinical parameters.ObjectiveTo develop an RNA expression-based score for the prediction of PCa prognosis that facilitates clinical decision making.Design, setting, and participantsWe assessed 233 tissue specimens of PCa patients with long-term follow-up data from fresh-frozen radical prostatectomies (RPs), from formalin-fixed and paraffin-embedded RP specimens and biopsies by transcriptome-wide next-generation sequencing and customized expression microarrays.Outcome measurements and statistical analysisWe applied Cox proportional hazard models to the cohorts from different platforms and specimen types. Evidence from these models was combined by fixed-effect meta-analysis to identify genes predictive of the time to death of disease (DoD). Genes were combined by a weighted median approach into a prognostic score called ProstaTrend and transferred for the prediction of biochemical recurrence (BCR) after RP in an independent cohort of The Cancer Genome Atlas (TCGA).Results and limitationsProstaTrend comprising ∼1400 genes was significantly associated with DoD in the training cohort of PCa patients treated by RP (leave-one-out cross-validation, Cox regression: p = 2e-09) and with BCR in the TCGA validation cohort (Cox regression: p = 3e-06). The prognostic impact persisted after multivariable Cox regression analysis adjusting for Gleason grading group (GG) ≥3 and resection status (p = 0.001; DoD, training cohort) and for GG ≥ 3, pathological stage ≥T3, and resection state (p = 0.037; BCR, validation cohort).Conclu

In search of new biomarkers suitable for the diagnosis and treatment of prostate cancer, genome-wide transcriptome sequencing was carried out with tissue specimens from 40 prostate cancer (PCa) and 8 benign prostate hyperplasia patients. We identified two intergenic long non-coding transcripts, located in close genomic proximity, which are highly expressed in PCa. Microarray studies on a larger cohort comprising 155 patients showed a profound diagnostic potential of these transcripts (AUC~0.94), which we designated as tumor associated prostate cancer increased lncRNA (TAPIR-1 and -2). To test their therapeutic potential, knockdown experiments with siRNA were carried out. The knockdown caused an increase in the p53/TP53 tumor suppressor protein level followed by downregulation of a large number of cell cycle- and DNA-damage repair key regulators. Furthermore, in radiation therapy resistant tumor cells, the knockdown leads to a renewed sensitization of these cells to radiation treatment. Accordingly, in a preclinical PCa xenograft model in mice, the systemic application of nanoparticles loaded with siRNA targeting TAPIR-1 significantly reduced tumor growth. These findings point to a crucial role of TAPIR-1 and -2 in PCa.