Instability of succinate dehydrogenase in SDHD polymorphism connects reactive oxygen species production to nuclear and mitochondrial genomic mutations in yeast

Top-Down, Knowledge-Based Genetic Reduction of Yeast Central Carbon Metabolism

Saccharomyces cerevisiae, whose evolutionary past includes a whole-genome duplication event, is characterized by a mosaic genome configuration with substantial apparent genetic redundancy. This apparent redundancy raises questions about the evolutionary driving force for genomic fixation of “minor” paralogs and complicates modular and combinatorial metabolic engineering strategies. While isoenzymes might be important in specific environments, they could be dispensable in controlled laboratory or industrial contexts. The present study explores the extent to which the genetic complexity of the central carbon metabolism (CCM) in S. cerevisiae, here defined as the combination of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and a limited number of related pathways and reactions, can be reduced by elimination of (iso)enzymes without major negative impacts on strain physiology. Cas9-mediated, groupwise deletion of 35 of the 111 genes yielded a “minimal CCM” strain which, despite the elimination of 32% of CCM-related proteins, showed only a minimal change in phenotype on glucose-containing synthetic medium in controlled bioreactor cultures relative to a congenic reference strain. Analysis under a wide range of other growth and stress conditions revealed remarkably few phenotypic changes from the reduction of genetic complexity. Still, a well-documented context-dependent role of GPD1 in osmotolerance was confirmed. The minimal CCM strain provides a model system for further research into genetic redundancy of yeast genes and a platform for strategies aimed at large-scale, combinatorial remodeling of yeast CCM.

Construction of a Novel LncRNA Signature Related to Genomic Instability to Predict the Prognosis and Immune Activity of Patients With Hepatocellular Carcinoma

Background

Genomic instability (GI) plays a crucial role in the development of various cancers including hepatocellular carcinoma. Hence, it is meaningful for us to use long non-coding RNAs related to genomic instability to construct a prognostic signature for patients with HCC.

Methods

Combining the lncRNA expression profiles and somatic mutation profiles in The Cancer Genome Atlas database, we identified GI-related lncRNAs (GILncRNAs) and obtained the prognosis-related GILncRNAs through univariate regression analysis. These lncRNAs obtained risk coefficients through multivariate regression analysis for constructing GI-associated lncRNA signature (GILncSig). ROC curves were used to evaluate signature performance. The International Cancer Genomics Consortium (ICGC) cohort, and in vitro experiments were used for signature external validation. Immunotherapy efficacy, tumor microenvironments, the half-maximal inhibitory concentration (IC50), and immune infiltration were compared between the high- and low-risk groups with TIDE, ESTIMATE, pRRophetic, and ssGSEA program.

Results

Five GILncRNAs were used to construct a GILncSig. It was confirmed that the GILncSig has good prognostic evaluation performance for patients with HCC by drawing a time-dependent ROC curve. Patients were divided into high- and low-risk groups according to the GILncSig risk score. The prognosis of the low-risk group was significantly better than that of the high-risk group. Independent prognostic analysis showed that the GILncSig could independently predict the prognosis of patients with HCC. In addition, the GILncSig was correlated with the mutation rate of the HCC genome, indicating that it has the potential to measure the degree of genome instability. In GILncSig, LUCAT1 with the highest risk factor was further validated as a risk factor for HCC in vitro. The ESTIMATE analysis showed a significant difference in stromal scores and ESTIMATE scores between the two groups. Multiple immune checkpoints had higher expression levels in the high-risk group. The ssGSEA results showed higher levels of tumor-antagonizing immune cells in the low-risk group compared with the high-risk group. Finally, the GILncSig score was associated with chemotherapeutic drug sensitivity and immunotherapy efficacy of patients with HCC.

Conclusion

Our research indicates that GILncSig can be used for prognostic evaluation of patients with HCC and provide new insights for clinical decision-making and potential therapeutic strategies.

Mitochondrial complex II and reactive oxygen species in disease and therapy

Increasing evidence points to the respiratory Complex II (CII) as a source and modulator of reactive oxygen species (ROS). Both functional loss of CII as well as its pharmacological inhibition can lead to ROS generation in cells, with a relevant impact on the development of pathophysiological conditions, i.e. cancer and neurodegenerative diseases. While the basic framework of CII involvement in ROS production has been defined, the fine details still await clarification. It is important to resolve these aspects to fully understand the role of CII in pathology and to explore its therapeutic potential in cancer and other diseases.

Transportome-wide engineering of Saccharomyces cerevisiae

Synthetic biology enables the production of small molecules by recombinant microbes for pharma, food, and materials applications. The secretion of products reduces the cost of separation and purification, but it is challenging to engineer due to the limited understanding of the transporter proteins' functions. Here we describe a method for genome-wide transporter disruption that, in combination with a metabolite biosensor, enables the identification of transporters impacting the production of a given target metabolite in yeast Saccharomyces cerevisiae. We applied the method to study the transport of xenobiotic compounds, cis,cis-muconic acid (CCM), protocatechuic acid (PCA), and betaxanthins. We found 22 transporters that influenced the production of CCM or PCA. The transporter of the 12-spanner drug:H(+) antiporter (DHA1) family Tpo2p was further confirmed to import CCM and PCA in Xenopus expression assays. We also identified three transporter proteins (Qdr1p, Qdr2p, and Apl1p) involved in betaxanthins transport. In summary, the described method enables high-throughput transporter identification for small molecules in cell factories.

The Power of Yeast in Modelling Human Nuclear Mutations Associated with Mitochondrial Diseases

The increasing application of next generation sequencing approaches to the analysis of human exome and whole genome data has enabled the identification of novel variants and new genes involved in mitochondrial diseases. The ability of surviving in the absence of oxidative phosphorylation (OXPHOS) and mitochondrial genome makes the yeast Saccharomyces cerevisiae an excellent model system for investigating the role of these new variants in mitochondrial-related conditions and dissecting the molecular mechanisms associated with these diseases. The aim of this review was to highlight the main advantages offered by this model for the study of mitochondrial diseases, from the validation and characterisation of novel mutations to the dissection of the role played by genes in mitochondrial functionality and the discovery of potential therapeutic molecules. The review also provides a summary of the main contributions to the understanding of mitochondrial diseases emerged from the study of this simple eukaryotic organism.

Genes affecting the extension of chronological lifespan in Schizosaccharomyces pombe (fission yeast)

So far, more than 70 genes involved in the chronological lifespan (CLS) of Schizosaccharomyces pombe (fission yeast) have been reported. In this mini‐review, we arrange and summarize these genes based on the reported genetic interactions between them and the physical interactions between their products. We describe the signal transduction pathways that affect CLS in S. pombe: target of rapamycin complex 1, cAMP‐dependent protein kinase, Sty1, and Pmk1 pathways have important functions in the regulation of CLS extension. Furthermore, the Php transcription complex, Ecl1 family proteins, cyclin Clg1, and the cyclin‐dependent kinase Pef1 are important for the regulation of CLS extension in S. pombe. Most of the known genes involved in CLS extension are related to these pathways and genes. In this review, we focus on the individual genes regulating CLS extension in S. pombe and discuss the interactions among them.

Transcriptomic analysis of thermotolerant yeastKluyveromyces marxianusin multiple inhibitors tolerance

Global transcriptional response ofK. marxianusto multiple inhibitors including acetic acid, phenols, furfural and HMF at 42 °C.

Hypoxia-Inducible Factor 2α Mutation-Related Paragangliomas Classify as Discrete Pseudohypoxic Subcluster

Recently, activating mutations of the hypoxia-inducible factor 2α gene (HIF2A/EPAS1) have been recognized to predispose to multiple paragangliomas (PGLs) and duodenal somatostatinomas associated with polycythemia, and ocular abnormalities. Previously, mutations in the SDHA/B/C/D, SDHAF2, VHL, FH, PHD1, and PHD2 genes have been associated with HIF activation and the development of pseudohypoxic (cluster-1) PGLs. These tumors overlap in terms of tumor location, syndromic presentation, and noradrenergic phenotype to a certain extent. However, they also differ especially by clinical outcome and by presence of other tumors or abnormalities. In the present study, we aimed to establish additional molecular differences between HIF2A and non-HIF2A pseudohypoxic PGLs. RNA expression patterns of HIF2A PGLs (n = 6) from 2 patients were compared with normal adrenal medullas (n = 8) and other hereditary pseudohypoxic PGLs (VHL: n = 13, SDHB: n = 15, and SDHD: n = 14). Unsupervised hierarchical clustering showed that HIF2A PGLs made up a separate cluster from other pseudohypoxic PGLs. Significance analysis of microarray yielded 875 differentially expressed genes between HIF2A and other pseudohypoxic PGLs after normalization to adrenal medulla (false discovery rate 0.01). Prediction analysis of microarray allowed correct classification of all HIF2A samples based on as little as three genes (TRHDE, LRRC63, IGSF10; error rate: 0.02). Genes with the highest expression difference between normal medulla and HIF2A PGLs were selected for confirmatory quantitative reverse transcriptase polymerase chain reaction. In conclusion, HIF2A PGLs show a characteristic expression signature that separates them from non-HIF2A pseudohypoxic PGLs. Unexpectedly, the most significantly differentially expressed genes have not been previously described as HIF target genes.