The Notch effector gene Hes1 is an ultradian clock exhibiting cyclic gene expression in several progenitor cells, with a period of a few hours. Because of the complexity of studying Hes1 in the endogenous setting, and the difficulty of imaging these fast oscillations in vivo, the mechanism driving oscillations has never been proven. Here, we applied a "build it to understand it" synthetic biology approach to construct simplified "hybrid" versions of the Hes1 ultradian oscillator combining synthetic and natural parts. We successfully constructed a simplified synthetic version of the Hes1 promoter matching the endogenous regulation logic. By mathematical modeling and single-cell real-time imaging, we were able to demonstrate that Hes1 is indeed able to generate stable oscillations by a delayed negative feedback loop. Moreover, we proved that introns in Hes1 contribute to the transcriptional delay but may not be strictly necessary for oscillations to occur. We also developed a novel reporter of endogenous Hes1 oscillations able to amplify the bioluminescence signal 5-fold. Our results have implications also for other ultradian oscillators.
Acute rejection (AR) can lead to allograft dysfunction following renal transplantation, despite immunosuppressive treatments. Accumulating evidence points out a role for epigenetic modification in immune responses. However, the mechanism and contribution of DNA methylation in allograft survival remain unclear. In this study, we followed up patients who successively experienced end‐stage renal disease, renal transplantation with allograft function or dysfunction, and hemodialysis. Peripheral blood mononuclear cells were collected at different time points for analysis of the DNA methylation. Epigenetic modifier analysis was also performed to explore its effect of methylation in a mouse model of AR. Compared with the allograft‐stable cohort, patients who experienced AR‐induced allograft dysfunction demonstrated more changes in methylation patterns. Pathway analysis revealed that the hypermethylated areas in the allograft dysfunction group were associated with genes related to the mechanistic target of rapamycin (mTOR) signaling pathway. Moreover, in the mouse AR model, treatment with the DNA methyltransferase inhibitor—decitabine regulated the Th1/2/17/regulatory T cell (Treg cell) immune response via its demethylating role in the suppressing the activity of the mTOR pathway, which ultimately ameliorated renal allograft‐related inflammatory injuries. These results revealed that changes in methylation accompany AR‐induced allograft dysfunction after renal transplantation. Epigenetics may provide new insights into predicting and improving allograft survival.
We consider the maintenance process of gas turbines used in the Oil and Gas industry: the capital parts are first removed from the gas turbines and replaced by parts of the same type taken from the warehouse; then, they are repaired at the workshop and returned to the warehouse for use in future maintenance events. Experience-based rules are used to manage the flow of the parts for a profitable gas turbine operation. In this article, we formalize the part flow management as a sequential decision problem and propose reinforcement learning for its solution. An application to a scaled-down case study derived from real industrial practice shows that reinforcement learning can find policies outperforming those based on experience-based rules.
Organoids culture provides unique opportunities to study human diseases and to complement animal models. Several organs and tissues can be in vitro cultured in 3D structures resembling in vivo tissue organization. Organoids culture contains most of the cell types of the original tissue and are maintained by growth factors mimicking the in vivo state. However, the system is yet not fully understood, and specific in vivo features especially those driven by cell-extrinsic factors may be lost in culture. Here we show a comprehensive transcriptome-wide characterization of mouse gut organoids derived from different intestinal compartments and from mice of different gender and age. RNA-seq analysis showed that the in vitro culture strongly influences the global transcriptome of the intestinal epithelial cells (~ 60% of the total variance). Several compartment-, age- and gender-related transcriptome features are lost after culturing indicating that they are driven by niche or systemic factors. However, certain intrinsic transcriptional programs, for example, some compartment-related features and a minority of gender- and aging- related features are maintained in vitro which suggested possibilities for these features to be studied in this system. Moreover, our study provides knowledge about the cell-extrinsic or cell-intrinsic origin of intestinal epithelial transcriptional programs. We anticipated that our characterization of this in vitro system is an important reference for scientists and clinicians using intestinal organoids as a research model.
α-Mangostin (aMan) and Paeonol (Pae) have shown anticancer and anti-inflammatory properties. However, these two natural compounds have no clinical value because of their low solubility and low membrane permeability. In this study, we screened chemically synthesized derivatives from these two natural compounds as potential novel chemicals that increase cancer cell cytotoxicity over nontransformed human cells. We found that two derivative compounds, named α-Mangostin-1 (aMan1) and Paeonol-1 (Pae1) more efficiently and more specifically induced cytotoxicity in HCT116, HT29, and SW48 colorectal cancer cell lines than the parental compounds. Both aMan1 and Pae1 arrested HCT116 cells in the G1 phase and HT29 and SW48 cells in the G2–M phase of the cell cycle. Both aMan1 and Pae1 induced apoptosis in human colorectal cancer cells, through a caspase-dependent mechanism. aMan1 and Pae1 induced selective transcriptional responses in colorectal cancer cells involving genes related to metabolic stress and DNA damage response signaling pathways. Finally, experiments on primary colon organoids showed that both derivatives were able to kill cancer-derived organoids without affecting the viability of organoids derived from healthy tissue, where the parental compounds and the currently used chemotherapeutic drug irinotecan failed. In conclusion, our findings expand the knowledge of natural compound derivatives as anticancer agents and open new avenues of research in the derivation of lead compounds aimed at developing novel chemotherapeutic drugs for colorectal cancer treatment that selectively target cancer, but not healthy cells.
Background
Patients with colon adenocarcinoma (COAD) exhibit significant heterogeneity in overall survival. The current tumor-node-metastasis staging system is insufficient to provide a precise prediction for prognosis. Identification and evaluation of new risk models by using big cancer data may provide a good way to identify prognosis-related signature.
Methods
We integrated different datasets and applied bioinformatic and statistical methods to construct a robust immune-associated risk model for COAD prognosis. Furthermore, a nomogram was constructed based on the gene signature and clinicopathological features to improve risk stratification and quantify risk assessment for individual patients.
Results
The immune-associated risk model discriminated high-risk patients in our investigated and validated cohorts. Survival analyses demonstrated that our gene signature served as an independent risk factor for overall survival and the nomogram exhibited high accuracy. Functional analysis interpreted the correlation between our risk model and its role in prognosis by classifying groups with different immune activities. Remarkably, patients in the low-risk group showed higher immune activity, while those in the high-risk group displayed a lower immune activity.
Conclusions
Our study provides a novel tool that may contribute to the optimization of risk stratification for survival and personalized management of COAD.
Graphical Abstract
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