Contribution of soft substrates to malignancy and tumor suppression during colon cancer cell division

Chromatin de-condensation by switching substrate elasticity

Mechanical properties of the cellular environment are known to influence cell fate. Chromatin de-condensation appears as an early event in cell reprogramming. Whereas the ratio of euchromatin versus heterochromatin can be increased chemically, we report herein for the first time that the ratio can also be increased by purely changing the mechanical properties of the microenvironment by successive 24 h-contact of the cells on a soft substrate alternated with relocation and growth for 7 days on a hard substrate. An initial contact with soft substrate caused massive SW480 cancer cell death by necrosis, whereas approximately 7% of the cells did survived exhibiting a high level of condensed chromatin (21% heterochromatin). However, four consecutive hard/soft cycles elicited a strong chromatin de-condensation (6% heterochromatin) correlating with an increase of cellular survival (approximately 90%). Furthermore, cell survival appeared to be reversible, indicative of an adaptive process rather than an irreversible gene mutation(s). This adaptation process is associated with modifications in gene expression patterns. A completely new approach for chromatin de-condensation, based only on mechanical properties of the microenvironment, without any drug mediation is presented.

Functional Genomics of Host-Microbiome Interactions in Humans

The human microbiome has been linked to various host phenotypes and has been implicated in many complex human diseases. Recent genome-wide association studies (GWASs) have used microbiome variation as a complex trait and have uncovered human genetic variants that are associated with the microbiome. Here we summarize results from these studies and illustrate potential regulatory mechanisms by which host genetic variation can interact with microbiome composition. We argue that, similar to human GWASs, it is important to use functional genomics techniques to gain a mechanistic understanding of causal host-microbiome interactions and their role in human disease. We highlight experimental, functional, and computational genomics methodologies for the study of the genomic basis of host-microbiome interactions and describe how these approaches can be utilized to explain how human genetic variation can modulate the effects of the microbiome on the host.