A mesoscale mechanical model of cellular interactions.

Computational models of cell mechanics allow the precise interrogation of cell shape change. These morphological changes are required for cells to survive in diverse tissue environments. Here, we present a mesoscale mechanical model of cell-substrate interactions using the level set method based on experimentally measured parameters. By implementing a viscoelastic mechanical equivalent circuit, we accurately model whole-cell deformations that are important for a variety of cellular processes. To effectively model shape changes as a cell interacts with a substrate, we have included receptor-mediated adhesion, which is governed by catch-slip bond behavior. The effect of adhesion was explored by subjecting cells to a variety of different substrates including flat, curved, and deformable surfaces. Finally, we increased the accuracy of our simulations by including a deformable nucleus in our cells. This model sets the foundation for further exploration into computational analyses of multicellular interactions.

Identification of Transcriptional and Receptor Networks That Control Root Responses to Ethylene.

Transcriptomic analyses with high temporal resolution provide substantial new insight into hormonal response networks. This study identified the kinetics of genome-wide transcript abundance changes in response to elevated levels of the plant hormone ethylene in roots from light-grown Arabidopsis (Arabidopsis thaliana) seedlings, which were overlaid on time-matched developmental changes. Functional annotation of clusters of transcripts with similar temporal patterns revealed rapidly induced clusters with known ethylene function and more slowly regulated clusters with novel predicted functions linked to root development. In contrast to studies with dark-grown seedlings, where the canonical ethylene response transcription factor, EIN3, is central to ethylene-mediated development, the roots of ein3 and eil1 single and double mutants still respond to ethylene in light-grown seedlings. Additionally, a subset of these clusters of ethylene-responsive transcripts were enriched in targets of EIN3 and ERFs. These results are consistent with EIN3-independent developmental and transcriptional changes in light-grown roots. Examination of single and multiple gain-of-function and loss-of-function receptor mutants revealed that, of the five ethylene receptors, ETR1 controls lateral root and root hair initiation and elongation and the synthesis of other receptors. These results provide new insight into the transcriptional and developmental responses to ethylene in light-grown seedlings.

The anthocyanin reduced tomato mutant demonstrates the role of flavonols in tomato lateral root and root hair development.

This study utilized tomato (Solanum lycopersicum) mutants with altered flavonoid biosynthesis to understand the impact of these metabolites on root development. The mutant anthocyanin reduced (are) has a mutation in the gene encoding FLAVONOID 3-HYDROXYLASE (F3H), the first step in flavonol synthesis, and accumulates higher concentrations of the F3H substrate, naringenin, and lower levels of the downstream products kaempferol, quercetin, myricetin, and anthocyanins, than the wild type. Complementation of are with the p35S:F3H transgene reduced naringenin and increased flavonols to wild-type levels. The initiation of lateral roots is reduced in are, and p35S:F3H complementation restores wild-type root formation. The flavonoid mutant anthocyanin without has a defect in the gene encoding DIHYDROFLAVONOL REDUCTASE, resulting in elevated flavonols and the absence of anthocyanins and displays increased lateral root formation. These results are consistent with a positive role of flavonols in lateral root formation. The are mutant has increased indole-3-acetic acid transport and greater sensitivity to the inhibitory effect of the auxin transport inhibitor naphthylphthalamic acid on lateral root formation. Expression of the auxin-induced reporter (DR5-ß-glucuronidase) is reduced in initiating lateral roots and increased in primary root tips of are. Levels of reactive oxygen species are elevated in are root epidermal tissues and root hairs, and are forms more root hairs, consistent with a role of flavonols as antioxidants that modulate root hair formation. Together, these experiments identify positive roles of flavonols in the formation of lateral roots and negative roles in the formation of root hairs through the modulation of auxin transport and reactive oxygen species, respectively.

Evaluating the transcriptional fidelity of cancer models.

BACKGROUND: Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors. METHODS: We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence. RESULTS: We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity. CONCLUSIONS: CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

Tools for computational analysis of moving boundary problems in cellular mechanobiology.

A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non-expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health. This article is categorized under: Cancer > Cancer>Computational Models Cancer > Cancer>Molecular and Cellular Physiology.

Targeting Mechanoresponsive Proteins in Pancreatic Cancer: 4-Hydroxyacetophenone Blocks Dissemination and Invasion by Activating MYH14.

Metastasis is complex, involving multiple genetic, epigenetic, biochemical, and physical changes in the cancer cell and its microenvironment. Cells with metastatic potential are often characterized by altered cellular contractility and deformability, lending them the flexibility to disseminate and navigate through different microenvironments. We demonstrate that mechanoresponsiveness is a hallmark of pancreatic cancer cells. Key mechanoresponsive proteins, those that accumulate in response to mechanical stress, specifically nonmuscle myosin IIA (MYH9) and IIC (MYH14), α-actinin 4, and filamin B, were highly expressed in pancreatic cancer as compared with healthy ductal epithelia. Their less responsive sister paralogs-myosin IIB (MYH10), α-actinin 1, and filamin A-had lower expression differential or disappeared with cancer progression. We demonstrate that proteins whose cellular contributions are often overlooked because of their low abundance can have profound impact on cell architecture, behavior, and mechanics. Here, the low abundant protein MYH14 promoted metastatic behavior and could be exploited with 4-hydroxyacetophenone (4-HAP), which increased MYH14 assembly, stiffening cells. As a result, 4-HAP decreased dissemination, induced cortical actin belts in spheroids, and slowed retrograde actin flow. 4-HAP also reduced liver metastases in human pancreatic cancer-bearing nude mice. Thus, increasing MYH14 assembly overwhelms the ability of cells to polarize and invade, suggesting targeting the mechanoresponsive proteins of the actin cytoskeleton as a new strategy to improve the survival of patients with pancreatic cancer. SIGNIFICANCE: This study demonstrates that mechanoresponsive proteins become upregulated with pancreatic cancer progression and that this system of proteins can be pharmacologically targeted to inhibit the metastatic potential of pancreatic cancer cells.