Biology subjects

Molenaar, J.

Publications and source records attributed to Molenaar, J..

8 recordsLinked to original sources

bioRxiv2026

A microscopy-based readout to assess tumour-specific viability in neuroblastoma co-cultures and short-term cultured patient samples

High-risk neuroblastoma patients face poor survival despite intensive treatment. Drug testing using patient-derived models can support therapy prioritization for precision medicine and drug development. Models incorporating tumour microenvironmental components, such as co-cultures and short-term cultured patient samples containing substantial non-malignant cell fractions, could better recapitulate microenvironment-dependent drug responses. However, conventional viability assays measure the combined signal from all viable cells in a well and therefore cannot determine tumour-specific drug responses. Here, we establish a microscopy-based readout to quantify cell-type-specific viability in two complementary settings: neuroblastoma-PBMC co-cultures and freshly dissociated patient tumour samples. In the co-cultures, PBMCs were pre-labelled with a cell-tracking dye, and Calcein staining was used to independently quantify the viability of tumour cells and PBMCs in the same well. The Calcein-based viability readout correlated strongly with conventional CellTiter-Glo measurements and was compatible with automated high-throughput drug screening. The imaging workflow enabled identification of compounds with differential efficacy in co-culture versus monoculture and distinguished tumour-specific effects from PBMC toxicity. The microscopy-based viability readout was further adapted to short-term cultured patient samples. Neuroblastoma tumour cells were distinguished from the non-malignant cells using a combination of tumour-specific surface markers NCAM, L1CAM and B7H3. This enabled determination of tumour fractions and measurement of tumour-specific drug responses. Tumour fractions varied substantially between patient samples, highlighting the importance of tumour-specific viability measurements. Together, the microscopy-based viability readout for co-cultures and patient samples enables scalable assessment of tumour-specific drug responses.

Cancer Biology↗

bioRxiv2024

Protoxylem microtubule patterning requires ROP pattern co-alignment, realistic microtubule-based nucleation, and sufficient microtubule flexibility.

The development of the water transporting xylem tissue in plants involves an intricate interplay of Rho-of-Plants (ROP) proteins and cortical microtubules to generate highly functional secondary cell wall patterns, such as the ringed or spiral patterns in early-developing protoxylem. We study the requirements of protoxylem microtubule band formation with simulations in CorticalSim, extended to include finite microtubule persistence length and a novel algorithm for microtubule-based nucleation. We find that microtubule flexibility is required to facilitate pattern formation for all realistic degrees of mismatch between array and pattern orientation. At the same time, flexibility leads to more density loss, both from collisions and the microtubule-hostile gap regions, making it harder to maintain microtubule bands. Microtubule-dependent nucleation helps to counteract this effect by gradually shifting nucleation from the gap regions to the bands as microtubules disappear from the gaps. Our results reveal the main mechanisms required for efficient protoxylem band formation.

cell biology↗

bioRxiv2024

EPA induces an anti-inflammatory transcriptomic landscape in T cells implicating a pathway independent of triglyceride lowering in CVD risk reduction

A twice-daily dose of highly purified eicosapentaenoic acid (EPA) reduces the risk of atherosclerotic cardiovascular disease among patients with high triglycerides and either known cardiovascular disease or those at high risk for developing it. However, the process by which EPA exerts its beneficial effects remains poorly understood. Here, we show that EPA can induce an anti-inflammatory transcriptional profile in non-activated CD4+ T cells. We find that EPA-exposed CD4+ T cells downregulate immune response related genes, such as HLA-DRA, CD69, and IL2RA, while upregulating genes involved in oxidative stress prevention, such as NQO1. Furthermore, transcription footprint analysis based on ATAC-sequencing reveals downregulation of GATA3 and PU.1, key transcription factors in TH2 and TH9 differentiation, and upregulation of REV-ERB, an antagonist of TH17 differentiation. By in parallel examining T cell responses to oleic acid, a monounsaturated fatty acid, and palmitic acid, a saturated fatty acid, we find that both the intensity of the transcriptomic response and the involvement of anti-inflammatory pathways is highly specific for EPA. Thus, EPA can induce an anti-inflammatory transcriptomic landscape in CD4+ T cells, a process that may contribute to the unexpectedly strong beneficial effects of EPA on the risk of atherosclerotic cardiovascular disease in clinical trials.

genomics↗

bioRxiv2023

Spectral methods for prediction uncertainty quantification in Systems Biology

Uncertainty is ubiquitous in biological systems. These uncertainties can be the result of lack of knowledge or due to a lack of appropriate data. Additionally, the natural variability of biological systems caused by intrinsic noise, e.g. in stochastic gene expression, leads to uncertainties. With the help of numerical simulations the impact of these uncertainties on the model predictions can be assessed, i.e. the impact of the propagation of uncertainty in model parameters on the model response can be quantified. Taking this into account is crucial when the models are used for experimental design, optimisation, or decision-making, as model uncertainty can have a significant effect on the accuracy of model predictions. We focus here on spectral methods to quantify prediction uncertainty based on a probabilistic framework. Such methods have a basis in, e.g., computational mathematics, engineering, physics, and fluid dynamics, and, to a lesser extent, systems biology. In this chapter, we highlight the advantages these methods can have for modelling purposes in systems biology and do so by providing a novel and intuitive scheme. By applying the scheme to an array of examples we show its power, especially in challenging situations where slow converge due to high-dimensionality, bifurcations, and spatial discontinuities play a role.

systems biology↗

bioRxiv2022

A small dynamic leaf-level model predicting photosynthesis in greenhouse tomatoes

The conversion of supplemental greenhouse light energy into biomass is not always optimal. Recent trends in global energy prices and discussions on climate change highlight the need to reduce our energy footprint associated with the use of supplemental light in greenhouse crop production. This can be achieved by implementing "smart" lighting regimens which in turn rely on a good understanding of how fluctuating light influences photosynthetic physiology. Here, a simple fit-for-purpose dynamic model is presented. It accurately predicts net leaf photosynthesis under natural fluctuating light. It comprises two ordinary differential equations predicting: 1) the total stomatal conductance to CO2 diffusion and 2) the CO2 concentration inside a leaf. It contains elements of the Farquhar-von Caemmerer-Berry model and the successful incorporation of this model suggests that for tomato (Solanum lycopersicum L.), it is sufficient to assume that Rubisco remains activated despite rapid fluctuations in irradiance. Furthermore, predictions of the net photosynthetic rate under both 400ppm and enriched 800ppm ambient CO2 concentrations indicate a strong correlation between the dynamic rate of photosynthesis and the rate of electron transport. Finally, we are able to indicate whether dynamic photosynthesis is Rubisco or electron transport rate limited. Author summaryThe cultivation of greenhouse crops under optimised conditions will become increasingly important, with supplemental lighting playing a vital role. However, converting light energy into plant photosynthesis is not always optimal. A potential venue that may lead to the efficient conversion of light energy involves a model-based implementation of "smart" lighting control strategy. This approach does however necessitate a good understanding of how plants harness light energy under natural fluctuating irradiance. Accordingly, as a first step, we have developed a small leaf-level model that predicts dynamic photosynthesis in natural fluctuating light. It may potentially be used in future supplemental light control applications.

plant biology↗

bioRxiv2022

Nucleation complex behaviour is critical for cortical microtubule array homogeneity and patterning

Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem. The orientation and patterning of cellulose fibrils is guided by dynamic cortical microtubules. New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it. Here, in a combined simulation and experimental approach, we show that the naturally limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot. We observe that nucleation complexes are preferentially inserted at microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behaviour of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics - as in developing protoxylem - can quickly turn a homogeneous array into a patterned one. Our results provide insight into how the plant cytoskeleton is wired to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies. Significance statementThe plant cortical microtubule array is an established model system for self-organisation, with a rich history of complementary experiments, computer simulations, and analytical theory. Understanding how array homogeneity is maintained given that new microtubules nucleate from existing microtubules has been a major hurdle for using mechanistic (simulation) models to predict future wall structures. We overcome this hurdle with detailed observations of the nucleation process from which we derive a more "natural" nucleation algorithm. With this algorithm, we enable various new lines of quantitative, mechanistic research into how cells dynamically control their cell wall properties. At a mechanistic level, moreover, this work relates to the theory on cluster coexistence in Turing-like continuum models and demonstrates its relevance for discrete stochastic entities.

plant biology↗

bioRxiv2019

Robust banded protoxylem pattern formation through microtubule-based directional ROP diffusion restriction

In plant vascular tissue development, different cell wall patterns are formed, offering different mechanical properties optimised for different growth stages. Critical in these patterning processes are Rho of Plants (ROP) proteins, a class of evolutionarily conserved small GTPase proteins responsible for local membrane domain formation in many organisms. While the spotted metaxylem pattern can easily be understood as a result of a Turing-style reaction-diffusion mechanism, it remains an open question how the consistent orientation of evenly spaced bands and spirals as found in protoxylem is achieved. We hypothesise that this orientation results from an interaction between ROPs and an array of transversely oriented cortical microtubules that acts as a directional diffusion barrier. Here, we explore this hypothesis using partial differential equation models with anisotropic ROP diffusion and show that a horizontal microtubule array acting as a vertical diffusion barrier to active ROP can yield a horizontally banded ROP pattern. We then study the underlying mechanism in more detail, finding that it can only orient curved pattern features but not straight lines. This implies that, once formed, banded and spiral patterns cannot be reoriented by this mechanism. Finally, we observe that ROPs and microtubules together only form ultimately static patterns if the interaction is implemented with sufficient biological realism.

biophysics↗

bioRxiv2018

Small GTPase patterning: How to stabilise cluster coexistence

Many biological processes have to occur at specific locations on the cell membrane. These locations are often specified by the localised activity of small GTPase proteins. Some processes require the formation of a single cluster of active GTPase, also called unipolar polarisation (here \"polarisation\"), whereas others need multiple coexisting clusters. Moreover, sometimes the pattern of GTPase clusters is dynamically regulated after its formation. This raises the question how the same interacting protein components can produce such a rich variety of naturally occurring patterns. Most currently used models for GTPase-based patterning inherently yield polarisation. Such models may at best yield transient coexistence of at most a few clusters, and hence fail to explain several important biological phenomena. These existing models are all based on mass conservation of total GTPase and some form of direct or indirect positive feedback. Here, we show that either of two biologically plausible modifications can yield stable coexistence: including explicit GTPase turnover, i.e., breaking mass conservation, or negative feedback by activation of an inhibitor like a GAP. Since we start from two different polarising models our findings seem independent of the precise self-activation mechanism. By studying the net GTPase flows among clusters, we provide insight into how these mechanisms operate. Our coexistence models also allow for dynamical regulation of the final pattern, which we illustrate with examples of pollen tube growth and the branching of fungal hyphae. Together, these results provide a better understanding of how cells can tune a single system to generate a wide variety of biologically relevant patterns.\n\nAuthor summaryWhere to form a bud? Where to reinforce the cell wall? In which direction to move? These are all important decisions a cell may have to make. Proper patterning of the cell membrane is a critical part of such decisions. These patterns are often specified by the local activity of proteins called small GTPases. Mathematical models have been an important tool in understanding the mechanisms behind small GTPase-based patterning. Most of these models, however, only allow for the formation of a single cluster of active GTPase and thus cannot explain patterns of multiple coexisting GTPase clusters. A previously proposed mechanism for such coexistence can only explain a temporary, unstable coexistence, and fails to explain several key biological phenomena. In this manuscript, we investigate two mechanisms that can produce patterns of many stably coexisting GTPase clusters. Using a combination of modelling techniques, we show why these mechanisms work. We also show that these mechanisms allow for the addition of new clusters to an existing pattern, as is observed for example during the branching of fungal hyphae. With our results, we now have handles to explain the full range of naturally occurring small GTPase patterns.

biophysics↗