Force-dependent focal adhesion assembly and disassembly: A computational study.

Cells interact with the extracellular matrix (ECM) via cell-ECM adhesions. These physical interactions are transduced into biochemical signals inside the cell which influence cell behaviour. Although cell-ECM interactions have been studied extensively, it is not completely understood how immature (nascent) adhesions develop into mature (focal) adhesions and how mechanical forces influence this process. Given the small size, dynamic nature and short lifetimes of nascent adhesions, studying them using conventional microscopic and experimental techniques is challenging. Computational modelling provides a valuable resource for simulating and exploring various "what if?" scenarios in silico and identifying key molecular components and mechanisms for further investigation. Here, we present a simplified mechano-chemical model based on ordinary differential equations with three major proteins involved in adhesions: integrins, talin and vinculin. Additionally, we incorporate a hypothetical signal molecule that influences adhesion (dis)assembly rates. We find that assembly and disassembly rates need to vary dynamically to limit maturation of nascent adhesions. The model predicts biphasic variation of actin retrograde velocity and maturation fraction with substrate stiffness, with maturation fractions between 18-35%, optimal stiffness of ∼1 pN/nm, and a mechanosensitive range of 1-100 pN/nm, all corresponding to key experimental findings. Sensitivity analyses show robustness of outcomes to small changes in parameter values, allowing model tuning to reflect specific cell types and signaling cascades. The model proposes that signal-dependent disassembly rate variations play an underappreciated role in maturation fraction regulation, which should be investigated further. We also provide predictions on the changes in traction force generation under increased/decreased vinculin concentrations, complementing previous vinculin overexpression/knockout experiments in different cell types. In summary, this work proposes a model framework to robustly simulate the mechanochemical processes underlying adhesion maturation and maintenance, thereby enhancing our fundamental knowledge of cell-ECM interactions.

Computational evidence for multi-layer crosstalk between the cadherin-11 and PDGFR pathways.

Various cell surface receptors play an important role in the differentiation and self-renewal of human mesenchymal stem cells (hMSCs). One example of such receptors are the cadherins, which maintain cell-cell adhesion and mechanically couple cells together. Recently, cadherin-11, which is a member of the type II classical cadherin family, has been shown to be involved in the fate commitment of hMSCs. Interestingly, cadherin-11 has no known intrinsic signaling activity and is thought to affect cell behavior via interactions with other cell surface receptors. Members of the platelet-derived growth factor receptor (PDGFR) family are hypothesized to be one of the interaction partners of cadherin-11. Experiments confirmed that PDGFR-α binding to extracellular cadherin-11 regions increases the PDGFR-α activity, whereas the interaction between PDGFR-ß and cadherin-11 suppresses the activity of the growth factor receptor. Cadherin-11 knockdown experiments also decreased cell proliferation. These interactions between cadherin-11 and PDGFRs indicate a crosstalk between these receptors and their downstream signaling activities but the nature of this crosstalk is not entirely known. In this study, we used a computational model to represent the experimentally proven interactions between cadherin-11 and the two PDGFRs and we inspected whether the crosstalk also exists downstream of the signaling initiated by the two receptor families. The computational framework allowed us to monitor the relative activity levels of each protein in the network. We performed model simulations to mimic the conditions of previous cadherin-11 knockdown experiments and to predict the effect of crosstalk on cell proliferation. Overall, our predictions suggest the existence of another layer of crosstalk, namely between ß-catenin (downstream to cadherin-11) and an ERK inhibitor protein (e.g. DUSP1), different than the crosstalk at the receptor level between cadherin-11 and PDGFR-α and -ß. By investigating the multi-level crosstalk between cadherin and PDGFRs computationally, this study contributes to an improved understanding of the effect of cell surface receptors on hMSCs proliferation.

Development of Mesoporous Silica Nanoparticle-Based Films with Tunable Arginine-Glycine-Aspartate Peptide Global Density and Clustering Levels to Study Stem Cell Adhesion and Differentiation.

Stem cell adhesion is mediated via the binding of integrin receptors to adhesion motifs present in the extracellular matrix (ECM). The spatial organization of adhesion ligands plays an important role in stem cell integrin-mediated adhesion. In this study, we developed a series of biointerfaces using arginine-glycine-aspartate (RGD)-functionalized mesoporous silica nanoparticles (MSN-RGD) to study the effect of RGD adhesion ligand global density (ligand coverage over the surface), spacing, and RGD clustering levels on stem cell adhesion and differentiation. To prepare the biointerface, MSNs were chemically functionalized with RGD peptides via an antifouling poly(ethylene glycol) (PEG) linker. The RGD surface functionalization ratio could be controlled to create MSNs with high and low RGD ligand clustering levels. MSN films with varying RGD global densities could be created by blending different ratios of MSN-RGD and non-RGD-functionalized MSNs together. A computational simulation study was performed to analyze nanoparticle distribution and RGD spacing on the resulting surfaces to determine experimental conditions. Enhanced cell adhesion and spreading were observed when RGD global density increased from 1.06 to 5.32 nmol cm-2 using highly clustered RGD-MSN-based films. Higher RGD ligand clustering levels led to larger cell spreading and increased formation of focal adhesions. Moreover, a higher RGD ligand clustering level promoted the expression of alkaline phosphatase in hMSCs. Overall, these findings indicate that both RGD global density and clustering levels are crucial variables in regulating stem cell behaviors. This study provides important information about ligand-integrin interactions, which could be implemented into biomaterial design to achieve optimal performance of adhesive functional peptides.

Corrigendum: Win, Lose or Tie: Mathematical Modeling of Ligand Competition at the Cell-Extracellular Matrix Interface.

[This corrects the article DOI: 10.3389/fbioe.2021.657244.].

Comparative analyses of two primate species diverged by more than 60 million years show different rates but similar distribution of genome-wide UV repair events.

BACKGROUND: Nucleotide excision repair is the primary DNA repair mechanism that removes bulky DNA adducts such as UV-induced pyrimidine dimers. Correspondingly, genome-wide mapping of nucleotide excision repair with eXcision Repair sequencing (XR-seq), provides comprehensive profiling of DNA damage repair. A number of XR-seq experiments at a variety of conditions for different damage types revealed heterogenous repair in the human genome. Although human repair profiles were extensively studied, how repair maps vary between primates is yet to be investigated. Here, we characterized the genome-wide UV-induced damage repair in gray mouse lemur, Microcebus murinus, in comparison to human. RESULTS: We derived fibroblast cell lines from mouse lemur, exposed them to UV irradiation, and analyzed the repair events genome-wide using the XR-seq protocol. Mouse lemur repair profiles were analyzed in comparison to the equivalent human fibroblast datasets. We found that overall UV sensitivity, repair efficiency, and transcription-coupled repair levels differ between the two primates. Despite this, comparative analysis of human and mouse lemur fibroblasts revealed that genome-wide repair profiles of the homologous regions are highly correlated, and this correlation is stronger for highly expressed genes. With the inclusion of an additional XR-seq sample derived from another human cell line in the analysis, we found that fibroblasts of the two primates repair UV-induced DNA lesions in a more similar pattern than two distinct human cell lines do. CONCLUSION: Our results suggest that mouse lemurs and humans, and possibly primates in general, share a homologous repair mechanism as well as genomic variance distribution, albeit with their variable repair efficiency. This result also emphasizes the deep homologies of individual tissue types across the eukaryotic phylogeny.

Win, Lose, or Tie: Mathematical Modeling of Ligand Competition at the Cell-Extracellular Matrix Interface.

Integrin transmembrane proteins conduct mechanotransduction at the cell-extracellular matrix (ECM) interface. This process is central to cellular homeostasis and therefore is particularly important when designing instructive biomaterials and organoid culture systems. Previous studies suggest that fine-tuning the ECM composition and mechanical properties can improve organoid development. Toward the bigger goal of fully functional organoid development, we hypothesize that resolving the dynamics of ECM-integrin interactions will be highly instructive. To this end, we developed a mathematical model that enabled us to simulate three main interactions, namely integrin activation, ligand binding, and integrin clustering. Different from previously published computational models, we account for the binding of more than one type of ligand to the integrin. This competition between ligands defines the fate of the system. We have demonstrated that an increase in the initial concentration of ligands does not ensure an increase in the steady state concentration of ligand-bound integrins. The ligand with higher binding rate occupies more integrins at the steady state than does the competing ligand. With cell type specific, quantitative input on integrin-ligand binding rates, this model can be used to develop instructive cell culture systems.

Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks.

The interactions between cells and their extracellular matrix (ECM) are critically important for homeostatic control of cell growth, proliferation, differentiation and apoptosis. Transmembrane integrin molecules facilitate the communication between ECM and the cell. Since the characterization of integrins in the late 1980s, there has been great advancement in understanding the function of integrins at different subcellular levels. However, the versatility in molecular pathways integrins are involved in, the high diversity in their interaction partners both outside and inside the cell as well as on the cell membrane and the short lifetime of events happening at the cell-ECM interface make it difficult to elucidate all the details regarding integrin function experimentally. To overcome the experimental challenges and advance the understanding of integrin biology, computational modeling tools have been used extensively. In this review, we summarize the computational models of integrin signaling while we explain the function of integrins at three main subcellular levels (outside the cell, cell membrane, cytosol). We also discuss how these computational modeling efforts can be helpful in other disciplines such as biomaterial design. As such, this review is a didactic modeling summary for biomaterial researchers interested in complementing their experimental work with computational tools or for seasoned computational scientists that would like to advance current in silico integrin models.

Anti-metastatic effect of ranolazine in an in vivo rat model of prostate cancer, and expression of voltage-gated sodium channel protein in human prostate.

BACKGROUND: Voltage-gated Na+ channels (VGSCs) are functionally upregulated in rat and human prostate cancer (PCa) where channel activity promotes cellular invasiveness in vitro and metastasis in vivo. Ranolazine is a clinically used VGSC inhibitor/anti-anginal drug, which has been shown previously to inhibit breast cancer metastasis in vivo. METHODS: Using the Dunning model of rat PCa, the effect of ranolazine applied systemically (by gavage) was tested on the development of primary tumours and metastases following subcutaneous inoculation of Mat-LyLu cells into Copenhagen rats. In addition, human prostate tissue microarrays were used to determine VGSC protein expression in cancerous versus non-cancerous tissue. Several public databases were searched to compare Nav1.7/ SCN9A expression levels in 'normal' vs. PCa tissues. RESULTS: Ranolazine (2.5 and 5 µM) decreased the number of lung metastases by up to 63%. In contrast, primary tumourigenesis was not affected. Ranolazine also reduced the percentage of cells in the metastases expressing Nav1.7, the main VGSC subtype expressed in PCa, but the expression level was higher. In prostate tissue microarrays, VGSC protein expression was significantly higher in cancerous versus non-cancerous tissue. There was no correlation between the VGSC expression and either prostate-specific antigen or Gleason score. In public databases, little information could be found on Nav1.7 protein expression in PCa. In addition, the database information on Nav1.7 mRNA (SCN9A) expression levels did not correlate with previously reported upregulation in PCa cells and tissues. CONCLUSIONS: The main conclusions were (i) ranolazine inhibited metastasis and (ii) it was a subpopulation of cells with particularly high levels of Nav1.7 protein that reached the metastatic sites. These data extend earlier studies and suggest that Nav1.7 expression could serve as a functional biomarker of metastatic PCa and that VGSC blockers may be useful as anti-metastatic agents.

Gabapentin, an Analgesic Used Against Cancer-Associated Neuropathic Pain: Effects on Prostate Cancer Progression in an In Vivo Rat Model.

A major problem associated with clinical management of cancer is controlling the accompanying pain, and various analgesics are in common use for this purpose. Recent evidence suggests that some of the targets of analgesics, such as ion channels and receptors, may also be involved in the cancer process, thereby raising the possibility that such use of some analgesics may impact upon cancer itself. The main aim of this study was to determine whether gabapentin, a common adjuvant analgesic in current use against cancer-associated neuropathic pain, would affect tumour development and progression in vivo. The Dunning rat model of prostate cancer was used. Strongly metastatic Mat-LyLu cells were implanted subcutaneously into syngeneic Copenhagen rats which were then treated every other day with 4.6-16.8 µg/kg gabapentin by gavage. Primary tumourigenesis was monitored daily. Lung metastases were counted and measured after killing the rats 21 days later. Gabapentin had no effect on primary tumourigenesis but produced dose-dependent effects on lung metastasis. Whilst 4.6 µg/kg had no effect, 9.1 µg/kg gabapentin decreased the number of lung metastases significantly by 64%. In contrast, 16.8 µg/kg gabapentin promoted metastasis significantly by 112% and showed a strong tendency to shorten mean survival time. It is concluded that gabapentin prescribed to cancer patients against pain could impact upon the cancer process itself.