Knockout of Factor-Inhibiting HIF (Hif1an) in Colon Epithelium Attenuates Chronic Colitis but Does Not Reduce Colorectal Cancer in Mice.

Inflammatory bowel disease such as chronic colitis promotes colorectal cancer, which is a common cause of cancer mortality worldwide. Hypoxia is a characteristic of inflammation as well as of solid tumors and enforces a gene expression response controlled by hypoxia-inducible factors (HIFs). Once established, solid tumors are immunosuppressive to escape their abatement through immune cells. Although HIF activity is known to 1) promote cancer development and 2) drive tumor immune suppression through the secretion of adenosine, both prolyl hydroxylases and an asparaginyl hydroxylase termed factor-inhibiting HIF (FIH) negatively regulate HIF. Thus, FIH may act as a tumor suppressor in colorectal cancer development. In this study, we examined the role of colon epithelial FIH in a mouse model of colitis-induced colorectal cancer. We recapitulated colitis-associated colorectal cancer development in mice using the azoxymethane/dextran sodium sulfate model in Vil1-Cre/FIH+f/+f and wild-type siblings. Colon samples were analyzed regarding RNA and protein expression and histology. Vil1-Cre/FIH+f/+f mice showed a less severe colitis progress compared with FIH+f/+f animals and a lower number of infiltrating macrophages in the inflamed tissue. RNA sequencing analyses of colon tissue revealed a lower expression of genes associated with the immune response in Vil1-Cre/FIH+f/+f mice. However, tumor occurrence did not significantly differ between Vil1-Cre/FIH+f/+f and wild-type mice. Thus, FIH knockout in colon epithelial cells did not modulate colorectal cancer development but reduced the inflammatory response in chronic colitis.

When the Brain Yearns for Oxygen.

Nearly 30 years ago hypoxia-inducible factor (HIF) was described as a protein complex bound to regulatory DNA sequences termed hypoxia response elements because HIF binding induced transcription of the erythropoietin gene under hypoxia. However, it soon became clear that HIF is part of a ubiquitous cellular oxygen sensing system, which ensures finely tuned control of HIF abundance and activity in dependence of the cellular oxygen tension. For their discoveries of how cells sense and adapt to oxygen availability Gregg L. Semenza, William G. Kaelin Jr. and Sir Peter J. Ratcliffe received the Nobel Prize in Physiology or Medicine 2019. The Nobel laureates' pioneering work on cellular oxygen sensing has unraveled that HIF has numerous target genes reflecting its multiple functions in cellular metabolism and adaptation to different levels of oxygen. Importantly, HIF is also crucial for the development of the nervous system. HIF has an influence on different neural cell types regarding neurogenesis, maturation and apoptosis. Furthermore, HIF is involved in pathophysiological processes of the brain like stroke and Alzheimer's disease resulting in the development of HIF-related therapeutic approaches.

Optical analysis of cellular oxygen sensing.

Molecular imaging of the assembly of hypoxia inducible factor (HIF) complexes in living cells may lead to a deeper understanding of cellular oxygen sensing. Sophisticated live cell imaging has extended the toolbox to study the molecular response to changes in oxygen supply. In this respect fluorescence resonance energy transfer (FRET) as a technique to investigate protein-protein interaction in the nanoscale range gets increasing interest. Herein, we review FRET studies related to hypoxia research, emphasizing on recent progress, but also demonstrating how FRET studies are complementary or potentially superior to conventional biochemical as well as histochemical techniques. Technical advances in the application of FRET in living cells will overcome restrictions to end-point analysis on the population rather than single cell level and will thereby provide progress in understanding the cellular hypoxic response by HIF.

Fluorescence Lifetime Imaging Microscopy (FLIM) as a Tool to Investigate Hypoxia-Induced Protein-Protein Interaction in Living Cells.

Fluorescence resonance energy transfer (FRET) is widely used as a method to investigate protein-protein interactions in living cells. A FRET pair donor fluorophore in close proximity to an appropriate acceptor fluorophore transfers emission energy to the acceptor, resulting in a shorter lifetime of the donor fluorescence. When the respective FRET donor and acceptor are fused with two proteins of interest, a reduction in donor lifetime, as detected by fluorescence lifetime imaging microscopy (FLIM), can be taken as proof of close proximity between the fluorophores and therefore interaction between the proteins of interest. Here, we describe the usage of time-domain FLIM-FRET in hypoxia-related research when we record the interaction of the hypoxia-inducible factor-1 (HIF-1) subunits HIF-1α and HIF-1ß in living cells in a temperature- and CO2-controlled environment under the microscope.

Computational Modeling of Lipid Metabolism in Yeast.

Lipid metabolism is essential for all major cell functions and has recently gained increasing attention in research and health studies. However, mathematical modeling by means of classical approaches such as stoichiometric networks and ordinary differential equation systems has not yet provided satisfactory insights, due to the complexity of lipid metabolism characterized by many different species with only slight differences and by promiscuous multifunctional enzymes. Here, we present an object-oriented stochastic model approach as a way to cope with the complex lipid metabolic network. While all lipid species are treated objects in the model, they can be modified by the respective converting reactions based on reaction rules, a hybrid method that integrates benefits of agent-based and classical stochastic simulation. This approach allows to follow the dynamics of all lipid species with different fatty acids, different degrees of saturation and different headgroups over time and to analyze the effect of parameter changes, potential mutations in the catalyzing enzymes or provision of different precursors. Applied to yeast metabolism during one cell cycle period, we could analyze the distribution of all lipids to the various membranes in time-dependent manner. The presented approach allows to efficiently treat the complexity of cellular lipid metabolism and to derive conclusions on the time- and location-dependent distributions of lipid species and their properties such as saturation. It is widely applicable, easily extendable and will provide further insights in healthy and diseased states of cell metabolism.