Mathematical models for collective cell spreading

Collective cell spreading is frequently observed in development, tissue repair and disease progression. Mathematical modelling used in conjunction with experimental investigation can provide key insights into the mechanisms driving the spread of cell populations. In this study, we investigated how experimental and modelling frameworks can be used to identify several key features underlying collective cell spreading. In particular, we were able to independently quantify the roles of cell motility and cell proliferation in a spreading cell population, and investigate how these roles are influenced by factors such as the initial cell density, type of cell population and the assay geometry.

Mutations in the gene encoding IFT dynein complex component WDR34 cause jeune asphyxiating thoracic dystrophy

Bidirectional (anterograde and retrograde) motor-based intraflagellar transport (IFT) governs cargo transport and delivery processes that are essential for primary cilia growth and maintenance and for hedgehog signaling functions. The IFT dynein-2 motor complex that regulates ciliary retrograde protein transport contains a heavy chain dynein ATPase/motor subunit, DYNC2H1, along with other less well functionally defined subunits. Deficiency of IFT proteins, including DYNC2H1, underlies a spectrum of skeletal ciliopathies. Here, by using exome sequencing and a targeted next-generation sequencing panel, we identified a total of 11 mutations in WDR34 in 9 families with the clinical diagnosis of Jeune syndrome (asphyxiating thoracic dystrophy). WDR34 encodes a WD40 repeat-containing protein orthologous to Chlamydomonas FAP133, a dynein intermediate chain associated with the retrograde intraflagellar transport motor. Three-dimensional protein modeling suggests that the identified mutations all affect residues critical for WDR34 protein-protein interactions. We find that WDR34 concentrates around the centrioles and basal bodies in mammalian cells, also showing axonemal staining. WDR34 coimmunoprecipitates with the dynein-1 light chain DYNLL1 in vitro, and mining of proteomics data suggests that WDR34 could represent a previously unrecognized link between the cytoplasmic dynein-1 and IFT dynein-2 motors. Together, these data show that WDR34 is critical for ciliary functions essential to normal development and survival, most probably as a previously unrecognized component of the mammalian dynein-IFT machinery.

The cross-talk of LDL-cholesterol with cell migration: Insights from the Niemann Pick Type C1 mutation

Cholesterol is considered indispensible for the recruitment and functioning of integrins in focal adhesions for cell migration. However, the physiological cholesterol pools that control integrin trafficking and focal adhesion assembly remain unclear. Using Niemann Pick Type C1 (NPC) mutant cells, which accumulate Low Density lipoprotein (LDL)-derived cholesterol in late endosomes (LE), several recent studies indicate that LDL-cholesterol has multiple roles in regulating focal adhesion dynamics. Firstly, targeting of endocytosed LDL-cholesterol from LE to focal adhesions controls their formation at the leading edge of migrating cells. Other newly emerging literature suggests that this may be coupled to vesicular transport of integrins, Src kinase and metalloproteases from the LE compartment to focal adhesions. Secondly, our recent work identified LDL-cholesterol as a key factor that determines the distribution and ability of several Soluble NSF Attachment Protein (SNAP) Receptor (SNARE) proteins, key players in vesicle transport, to control integrin trafficking to the cell surface and extracellular matrix (ECM) secretion. Collectively, dietary, genetic and pathological changes in cholesterol metabolism may link with efficiency and speed of integrin and ECM cell surface delivery in metastatic cancer cells. This commentary will summarize how direct and indirect pathways enable LDL-cholesterol to modulate cell motility.

The role of H4 flagella in Escherichia coli ST131 virulence

Escherichia coli sequence type 131 (ST131) is a globally dominant multidrug resistant clone associated with urinary tract and bloodstream infections. Most ST131 strains exhibit resistance to multiple antibiotics and cause infections associated with limited treatment options. The largest sub-clonal ST131 lineage is resistant to fluoroquinolones, contains the type 1 fimbriae fimH30 allele and expresses an H4 flagella antigen. Flagella are motility organelles that contribute to UPEC colonisation of the upper urinary tract. In this study, we examined the specific role of H4 flagella in ST131 motility and interaction with host epithelial and immune cells. We show that the majority of H4-positive ST131 strains are motile and are enriched for flagella expression during static pellicle growth. We also tested the role of H4 flagella in ST131 through the construction of specific mutants, over-expression strains and isogenic mutants that expressed alternative H1 and H7 flagellar subtypes. Overall, our results revealed that H4, H1 and H7 flagella possess conserved phenotypes with regards to motility, epithelial cell adhesion, invasion and uptake by macrophages. In contrast, H4 flagella trigger enhanced induction of the anti-inflammatory cytokine IL-10 compared to H1 and H7 flagella, a property that may contribute to ST131 fitness in the urinary tract.

Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model

Background: Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model. Results: The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF. Conclusions: Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

Modelling the movement of interacting cell populations: A moment dynamics approach

Mathematical models describing the movement of multiple interacting subpopulations are relevant to many biological and ecological processes. Standard mean-field partial differential equation descriptions of these processes suffer from the limitation that they implicitly neglect to incorporate the impact of spatial correlations and clustering. To overcome this, we derive a moment dynamics description of a discrete stochastic process which describes the spreading of distinct interacting subpopulations. In particular, we motivate our model by mimicking the geometry of two typical cell biology experiments. Comparing the performance of the moment dynamics model with a traditional mean-field model confirms that the moment dynamics approach always outperforms the traditional mean-field approach. To provide more general insight we summarise the performance of the moment dynamics model and the traditional mean-field model over a wide range of parameter regimes. These results help distinguish between those situations where spatial correlation effects are sufficiently strong, such that a moment dynamics model is required, from other situations where spatial correlation effects are sufficiently weak, such that a traditional mean-field model is adequate.

Kallikrein-related peptidase 4 induces tumour microenvironment alterations that support tumour growth

Kallikrein-related peptidase 4 (KLK4) is a protease with elevated production in prostate cancer versus benign tissue. KLK4 expression is associated with prostate cancer risk, and its activity favours tumour progression through increasing cell motility and growth. Importantly, over-production of KLK4 in prostate glandular cells precedes tumour formation, positioning the enzyme to play a role in early remodelling of the tumour microenvironment, a process essential for tumour growth. We sought to identify the proteins and downstream signalling pathways targeted by KLK4 activity, to define its role in tumour microenvironment remodelling and evaluate the efficacy of KLK4 inhibition as a cancer therapy.