Rhythm of the Night (and Day): Predictive Metabolic Modeling of Diurnal Growth in Chlamydomonas.

Economical production of photosynthetic organisms requires the use of natural day/night cycles. These induce strong circadian rhythms that lead to transient changes in the cells, requiring complex modeling to capture. In this study, we coupled times series transcriptomic data from the model green alga Chlamydomonas reinhardtii to a metabolic model of the same organism in order to develop the first transient metabolic model for diurnal growth of algae capable of predicting phenotype from genotype. We first transformed a set of discrete transcriptomic measurements (D. Strenkert, S. Schmollinger, S. D. Gallaher, P. A. Salomé, et al., Proc Natl Acad Sci U S A 116:2374-2383, 2019, https://doi.org/10.1073/pnas.1815238116) into continuous curves, producing a complete database of the cell's transcriptome that can be interrogated at any time point. We also decoupled the standard biomass formation equation to allow different components of biomass to be synthesized at different times of the day. The resulting model was able to predict qualitative phenotypical outcomes of a starchless mutant. We also extended this approach to simulate all single-knockout mutants and identified potential targets for rational engineering efforts to increase productivity. This model enables us to evaluate the impact of genetic and environmental changes on the growth, biomass composition, and intracellular fluxes for diurnal growth. IMPORTANCE We have developed the first transient metabolic model for diurnal growth of algae based on experimental data and capable of predicting phenotype from genotype. This model enables us to evaluate the impact of genetic and environmental changes on the growth, biomass composition and intracellular fluxes of the model green alga, Chlamydomonas reinhardtii. The availability of this model will enable faster and more efficient design of cells for production of fuels, chemicals, and pharmaceuticals.

Mismatch repair deficiency endows tumors with a unique mutation signature and sensitivity to DNA double-strand breaks.

DNA replication errors that persist as mismatch mutations make up the molecular fingerprint of mismatch repair (MMR)-deficient tumors and convey them with resistance to standard therapy. Using whole-genome and whole-exome sequencing, we here confirm an MMR-deficient mutation signature that is distinct from other tumor genomes, but surprisingly similar to germ-line DNA, indicating that a substantial fraction of human genetic variation arises through mutations escaping MMR. Moreover, we identify a large set of recurrent indels that may serve to detect microsatellite instability (MSI). Indeed, using endometrial tumors with immunohistochemically proven MMR deficiency, we optimize a novel marker set capable of detecting MSI and show it to have greater specificity and selectivity than standard MSI tests. Additionally, we show that recurrent indels are enriched for the 'DNA double-strand break repair by homologous recombination' pathway. Consequently, DSB repair is reduced in MMR-deficient tumors, triggering a dose-dependent sensitivity of MMR-deficient tumor cultures to DSB inducers.

Serum HE4 as a prognostic marker in endometrial cancer--a population based study.

OBJECTIVE: HE4 has emerged as a promising biomarker in gynaecological oncology. The purpose of this study was to evaluate serum HE4 as a biomarker for high-risk phenotypes in a population-based endometrial cancer cohort. METHODS: Peri-operative serum HE4 and CA125 were measured in 373 patients identified from the prospective Australian National Endometrial Cancer Study (ANECS). HE4 and CA125 were quantified on the ARCHITECT instrument in a clinically accredited laboratory. Receiver operator curves (ROC), Spearman rank correlation coefficient, and chi-squared and Mann-Whitney tests were used for statistical analysis. Survival analysis was performed using Kaplan-Meier and Cox multivariate regression analyses. RESULTS: Median CA125 and HE4 levels were higher in stage III and IV tumours (p<0.001) and in tumours with outer-half myometrial invasion (p<0.001). ROC analysis demonstrated that HE4 (area under the curve (AUC)=0.76) was a better predictor of outer-half myometrial invasion than CA125 (AUC=0.65), particularly in patients with low-grade endometrioid tumours (AUC 0.77 vs 0.64 for CA125). Cox multivariate analysis demonstrated that elevated HE4 was an independent predictor of recurrence-free survival (HR=2.40, 95% CI 1.19-4.83, p=0.014) after adjusting for stage and grade of disease, particularly in the endometrioid subtype (HR=2.86, 95% CI 1.25-6.51, p=0.012). CONCLUSION: These findings demonstrate the utility of serum HE4 as a prognostic biomarker in endometrial cancer in a large, population-based study. In particular they highlight the utility of HE4 for pre-operative risk stratification to identify high-risk patients within low-grade endometrioid endometrial cancer patients who might benefit from lymphadenectomy.