Inhibition of unwinding and ATPase activities of pea MCM6 DNA helicase by actinomycin and nogalamycin

A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

BACKGROUND

The influence of the Warburg phenomenon on chemotherapy response is unknown. Saccharomyces cerevisiae mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance.

METHODS

Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy.

RESULTS

Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context. We analyzed human homologs of yeast genes exhibiting gene-doxorubicin interaction in cancer pharmacogenomics data to predict causality for differential gene expression associated with doxorubicin cytotoxicity in cancer cells. This analysis suggested conserved cellular responses to doxorubicin due to influences of homologous recombination, sphingolipid homeostasis, telomere tethering at nuclear periphery, actin cortical patch localization, and other gene functions.

CONCLUSIONS

Warburg status alters the genetic network required for yeast to buffer doxorubicin toxicity. Integration of yeast phenomic and cancer pharmacogenomics data suggests evolutionary conservation of gene-drug interaction networks and provides a new experimental approach to model their influence on chemotherapy response. Thus, yeast phenomic models could aid the development of precision oncology algorithms to predict efficacious cytotoxic drugs for cancer, based on genetic and metabolic profiles of individual tumors.

Diversity and activity of marine bacterioplankton during a diatom bloom in the North Sea assessed by total RNA and pyrotag sequencing

A recent investigation of bacterioplankton communities in the German Bight towards the end of a diatom-dominated spring phytoplankton bloom revealed pronounced successions of distinct bacterial clades. A combination of metagenomics and metaproteomics indicated that these clades had distinct substrate spectra and consumed different algal substrates. In this study we re-analyzed samples from the initial study by total community RNA (metatranscriptomics) and 16S rRNA gene amplicon sequencing. This complementary approach provided new insights into the community composition and expressed genes as well as the assessment of metabolic activity levels of distinct clades. Flavobacteria (genera Ulvibacter, Formosa, and Polaribacter), Alphaproteobacteria (SAR11 clade and Rhodobacteraceae) and Gammaproteobacteria (genus Reinekea and SAR92 clade) were the most abundant taxa. Mapping of the metatranscriptome data on assembled and taxonomically classified metagenome data of the same samples substantiated that Formosa and Polaribacter acted as major algal polymer degraders, whereas Rhodobacteraceae and Reinekea spp. exhibited less specialized substrate spectra. In addition, we found that members of the Rhodobacteraceae and SAR92 clade showed high metabolic activity levels, which suggests that these clades played a more important role during the bloom event as indicated by their in situ abundances.