Publications of Liesbet Geris
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See detailRibosome exit tunnel electrostatics
Joiret, Marc ULiege; Kerff, Frédéric ULiege; Rapino, Francesca ULiege et al

in Physical Review E (2022), 105(1), 014409-1--014409-43

The impact of ribosome exit tunnel electrostatics on the protein elongation rate or on forces acting upon the nascent polypeptide chain are currently not fully elucidated. In the past, researchers have ... [more ▼]

The impact of ribosome exit tunnel electrostatics on the protein elongation rate or on forces acting upon the nascent polypeptide chain are currently not fully elucidated. In the past, researchers have measured the electrostatic potential inside the ribosome polypeptide exit tunnel at a limited number of spatial points, at least in rabbit reticulocytes. Here we present a basic electrostatic model of the exit tunnel of the ribosome, providing a quantitative physical description of the tunnel interaction with the nascent proteins at all centro-axial points inside the tunnel. We show that a strong electrostatic screening is due to water molecules (not mobile ions) attracted to the ribosomal nucleic acid phosphate moieties buried in the immediate vicinity of the tunnel wall. We also show how the tunnel wall components and local ribosomal protein protrusions impact on the electrostatic potential profile and impede charged amino acid residues from progressing through the tunnel, affecting the elongation rate in a range of −40% to +85% when compared to the average elongation rate. The time spent by the ribosome to decode the genetic encrypted message is constrained accordingly. We quantitatively derive, at single-residue resolution, the axial forces acting on the nascent peptide from its particular sequence embedded in the tunnel. The model sheds light on how the experimental data point measurements of the potential are linked to the local structural chemistry of the inner wall, shape, and size of the tunnel. The model consistently connects experimental observations coming from different fields in molecular biology, x-ray crystallography, physical chemistry, biomechanics, and synthetic and multiomics biology. Our model should be a valuable tool to gain insight into protein synthesis dynamics, translational control, and the role of the ribosome's mechanochemistry in the cotranslational protein folding. [less ▲]

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See detailTumor exposed-lymphatic endothelial cells promote primary tumor growth via IL6.
Van de Velde, Maureen; Ebroin, Marie ULiege; Durré, Tania ULiege et al

in Cancer Letters (2021), 497

Solid tumors are composed of tumor cells and stromal cells including lymphatic endothelial cells (LEC), which are mainly viewed as cells forming lymphatic vessels involved in the transport of metastatic ... [more ▼]

Solid tumors are composed of tumor cells and stromal cells including lymphatic endothelial cells (LEC), which are mainly viewed as cells forming lymphatic vessels involved in the transport of metastatic and immune cells. We here reveal a new mechanism by which tumor exposed-LEC (teLEC) exert mitogenic effects on tumor cells. Our conclusions are supported by morphological and molecular changes induced in teLEC that in turn enhance cancer cell invasion in 3D cultures and tumor cell proliferation in vivo. The characterization of teLEC secretome by RNA-Sequencing and cytokine array revealed that interleukine-6 (IL6) is one of the most modulated molecules in teLEC, whose production was negligible in unexposed LEC. Notably, neutralizing anti-human IL6 antibody abrogated teLEC-mediated mitogenic effects in vivo, when LEC were mixed with tumor cells in the ear sponge assay. We here assign a novel function to teLEC that is beyond their role of lymphatic vessel formation. This work highlights a new paradigm, in which teLEC exert "fibroblast-like properties", contribute in a paracrine manner to the control of tumor cell properties and are worth considering as key stromal determinant in future studies. [less ▲]

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See detailEstetrol combined to progestogen for menopause or contraception indication is neutral on breast cancer
Gallez, Anne ULiege; Blacher, Silvia ULiege; Maquoi, Erik ULiege et al

in Cancers (2021)

Hormonal treatments, especially those used to treat menopause symptoms are known to increase breast cancer risk. It is thus necessary to identify new formulations with a better benefit/risk pro-file. The ... [more ▼]

Hormonal treatments, especially those used to treat menopause symptoms are known to increase breast cancer risk. It is thus necessary to identify new formulations with a better benefit/risk pro-file. The aim of this translational study was to evaluate the breast cancer risk associated to a combination of a natural estrogen, named estetrol, with progestogens such as natural progesterone and drospirenone. Since the assessment of breast cancer risk in patients during drug development is not possible given the requirement of long-term studies in large populations, this study provides new evidences that a therapeutic dose of estetrol for menopause treatment or contraception, combined with progesterone or drospirenone, may provide a better benefit/risk profile towards breast cancer risk compared to hormonal treatments currently available for patients. [less ▲]

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See detailWobble tRNA modification and hydrophilic amino acid patterns dictate protein fate.
Rapino, Francesca ULiege; ZHOU, ZHAOLI; RONCERO SANCHEZ, Ana Maria et al

in Nature Communications (2021), 12(1), 2170

Regulation of mRNA translation elongation impacts nascent protein synthesis and integrity and plays a critical role in disease establishment. Here, we investigate features linking regulation of codon ... [more ▼]

Regulation of mRNA translation elongation impacts nascent protein synthesis and integrity and plays a critical role in disease establishment. Here, we investigate features linking regulation of codon-dependent translation elongation to protein expression and homeostasis. Using knockdown models of enzymes that catalyze the mcm(5)s(2) wobble uridine tRNA modification (U(34)-enzymes), we show that gene codon content is necessary but not sufficient to predict protein fate. While translation defects upon perturbation of U(34)-enzymes are strictly dependent on codon content, the consequences on protein output are determined by other features. Specific hydrophilic motifs cause protein aggregation and degradation upon codon-dependent translation elongation defects. Accordingly, the combination of codon content and the presence of hydrophilic motifs define the proteome whose maintenance relies on U(34)-tRNA modification. Together, these results uncover the mechanism linking wobble tRNA modification to mRNA translation and aggregation to maintain proteome homeostasis. [less ▲]

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See detailCancer modeling: From mechanistic to data-driven approaches, and from fundamental insights to clinical applications
Bekisz, Sophie ULiege; Geris, Liesbet ULiege

in Journal of Computational Science (2020), 46(101198),

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See detailProtein synthesis at the speed of codons
Joiret, Marc ULiege; Geris, Liesbet ULiege; Close, Pierre ULiege

Speech/Talk (2020)

Introduction to open boundaries transport model on a 1D lattice and presentation of the totally asymmetric simple exclusion process and its application to protein synthesis modeling.

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See detailIn silico tools predict effects of drugs on bone remodelling.
Geris, Liesbet ULiege

in Nature Reviews Rheumatology (2020)

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See detailOptimizing neotissue growth inside perfusion bioreactors with respect to culture and labor cost: a multi-objective optimization study using evolutionary algorithms.
Mehrian, Mohammad; Geris, Liesbet ULiege

in Computer methods in biomechanics and biomedical engineering (2020), 23(7), 285-294

Tissue engineering is a fast progressing domain where solutions are provided for organ failure or tissue damage. In this domain, computer models can facilitate the design of optimal production process ... [more ▼]

Tissue engineering is a fast progressing domain where solutions are provided for organ failure or tissue damage. In this domain, computer models can facilitate the design of optimal production process conditions leading to robust and economically viable products. In this study, we use a previously published computationally efficient model, describing the neotissue growth (cells + their extracellular matrix) inside 3D scaffolds in a perfusion bioreactor. In order to find the most cost-effective medium refreshment strategy for the bioreactor culture, a multi-objective optimization strategy was developed aimed at maximizing the neotissue growth while minimizing the total cost of the experiment. Four evolutionary optimization algorithms (NSGAII, MOPSO, MOEA/D and GDEIII) were applied to the problem and the Pareto frontier was computed in all methods. All algorithms led to a similar outcome, albeit with different convergence speeds. The simulation results indicated that, given the actual cost of the labor compared to the medium cost, the most cost-efficient way of refreshing the medium was obtained by minimizing the refreshment frequency and maximizing the refreshment amount. [less ▲]

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See detailUse of Computational Modeling to Study Joint Degeneration: A Review.
Mukherjee, Satanik; Nazemi, Majid; Jonkers, Ilse et al

in Frontiers in bioengineering and biotechnology (2020), 8

Osteoarthritis (OA), a degenerative joint disease, is the most common chronic condition of the joints, which cannot be prevented effectively. Computational modeling of joint degradation allows to estimate ... [more ▼]

Osteoarthritis (OA), a degenerative joint disease, is the most common chronic condition of the joints, which cannot be prevented effectively. Computational modeling of joint degradation allows to estimate the patient-specific progression of OA, which can aid clinicians to estimate the most suitable time window for surgical intervention in osteoarthritic patients. This paper gives an overview of the different approaches used to model different aspects of joint degeneration, thereby focusing mostly on the knee joint. The paper starts by discussing how OA affects the different components of the joint and how these are accounted for in the models. Subsequently, it discusses the different modeling approaches that can be used to answer questions related to OA etiology, progression and treatment. These models are ordered based on their underlying assumptions and technologies: musculoskeletal models, Finite Element models, (gene) regulatory models, multiscale models and data-driven models (artificial intelligence/machine learning). Finally, it is concluded that in the future, efforts should be made to integrate the different modeling techniques into a more robust computational framework that should not only be efficient to predict OA progression but also easily allow a patient's individualized risk assessment as screening tool for use in clinical practice. [less ▲]

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See detailComputational Modeling of Human Mesenchymal Stromal Cell Proliferation and Extra-Cellular Matrix Production in 3D Porous Scaffolds in a Perfusion Bioreactor: The Effect of Growth Factors.
Mehrian, Mohammad; Lambrechts, Toon; Papantoniou, Ioannis et al

in Frontiers in bioengineering and biotechnology (2020), 8

Stem cell expansion on 3D porous scaffolds cultured in bioreactor systems has been shown to be beneficial for maintenance of the original cell functionality in tissue engineering strategies (TE). However ... [more ▼]

Stem cell expansion on 3D porous scaffolds cultured in bioreactor systems has been shown to be beneficial for maintenance of the original cell functionality in tissue engineering strategies (TE). However, the production of extracellular matrix (ECM) makes harvesting the progenitor cell population from 3D scaffolds a challenge. Medium composition plays a role in stimulating cell proliferation over extracellular matrix (ECM) production. In this regard, a computational model describing tissue growth inside 3D scaffolds can be a great tool in designing optimal experimental conditions. In this study, a computational model describing cell and ECM growth in a perfusion bioreactor is developed, including a description of the effect of a (generic) growth factor on the biological processes taking place inside the 3D scaffold. In the model, the speed of cell and ECM growth depends on the flow-induced shear stress, curvature and the concentrations of oxygen, glucose, lactate, and growth factor. The effect of the simulated growth factor is to differentially enhance cell proliferation over ECM production. After model calibration with historic in-house data, a multi-objective optimization procedure is executed aiming to minimize the total experimental cost whilst maximizing cell growth during culture. The obtained results indicate there are multiple optimum points for the medium refreshment regime and the initial growth factor concentration where a trade-off is made between the final amount of cells and the culture cost. Finally, the model is applied to experiments reported in the literature studying the effects of perfusion-based cell culture and/or growth factor supplementation on cell expansion. The qualitative similarities between the simulation and experimental results, even in the absence of proper model calibration, reinforces the generic character of the proposed modeling framework. The model proposed in this study can contribute to the cost efficient production of cell-based TE products, ultimately contributing to their affordability and accessibility. [less ▲]

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See detailPredicting in vitro human mesenchymal stromal cell expansion based on individual donor characteristics using machine learning.
Mehrian, Mohammad; Lambrechts, Toon; Marechal, Marina et al

in Cytotherapy (2020), 22(2), 82-90

BACKGROUND: Human mesenchymal stromal cells (hMSCs) have become attractive candidates for advanced medical cell-based therapies. An in vitro expansion step is routinely used to reach the required clinical ... [more ▼]

BACKGROUND: Human mesenchymal stromal cells (hMSCs) have become attractive candidates for advanced medical cell-based therapies. An in vitro expansion step is routinely used to reach the required clinical quantities. However, this is influenced by many variables including donor characteristics, such as age and gender, and culture conditions, such as cell seeding density and available culture surface area. Computational modeling in general and machine learning in particular could play a significant role in deciphering the relationship between the individual donor characteristics and their growth dynamics. METHODS: In this study, hMSCs obtained from 174 male and female donors, between 3 and 64 years of age with passage numbers ranging from 2 to 27, were studied. We applied a Random Forests (RF) technique to model the cell expansion procedure by predicting the population doubling time (PDT) for each passage, taking into account individual donor-related characteristics. RESULTS: Using the RF model, the mean absolute error between model predictions and experimental results for the PDT in passage 1 to 4 is significantly lower compared with the errors obtained with theoretical estimates or historical data. Moreover, statistical analysis indicate that the PD and PDT in different age categories are significantly different, especially in the youngest group (younger than 10 years of age) compared with the other age groups. DISCUSSION: In summary, we introduce a predictive computational model describing in vitro cell expansion dynamics based on individual donor characteristics, an approach that could greatly assist toward automation of a cell expansion culture process. [less ▲]

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See detailDevelopmentally Engineered Callus Organoid Bioassemblies Exhibit Predictive In Vivo Long Bone Healing.
Nilsson Hall, Gabriella; Mendes, Luís Freitas; Gklava, Charikleia et al

in Advanced science (2020), 7(2), 1902295

Clinical translation of cell-based products is hampered by their limited predictive in vivo performance. To overcome this hurdle, engineering strategies advocate to fabricate tissue products through ... [more ▼]

Clinical translation of cell-based products is hampered by their limited predictive in vivo performance. To overcome this hurdle, engineering strategies advocate to fabricate tissue products through processes that mimic development and regeneration, a strategy applicable for the healing of large bone defects, an unmet medical need. Natural fracture healing occurs through the formation of a cartilage intermediate, termed "soft callus," which is transformed into bone following a process that recapitulates developmental events. The main contributors to the soft callus are cells derived from the periosteum, containing potent skeletal stem cells. Herein, cells derived from human periosteum are used for the scalable production of microspheroids that are differentiated into callus organoids. The organoids attain autonomy and exhibit the capacity to form ectopic bone microorgans in vivo. This potency is linked to specific gene signatures mimicking those found in developing and healing long bones. Furthermore, callus organoids spontaneously bioassemble in vitro into large engineered tissues able to heal murine critical-sized long bone defects. The regenerated bone exhibits similar morphological properties to those of native tibia. These callus organoids can be viewed as a living "bio-ink" allowing bottom-up manufacturing of multimodular tissues with complex geometric features and inbuilt quality attributes. [less ▲]

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See detailLipid availability determines fate of skeletal progenitor cells via SOX9
van Gastel, N.; Stegen, S.; Eelen, G. et al

in Nature (2020), 579(7797), 111-117

The avascular nature of cartilage makes it a unique tissue1–4, but whether and how the absence of nutrient supply regulates chondrogenesis remain unknown. Here we show that obstruction of vascular ... [more ▼]

The avascular nature of cartilage makes it a unique tissue1–4, but whether and how the absence of nutrient supply regulates chondrogenesis remain unknown. Here we show that obstruction of vascular invasion during bone healing favours chondrogenic over osteogenic differentiation of skeletal progenitor cells. Unexpectedly, this process is driven by a decreased availability of extracellular lipids. When lipids are scarce, skeletal progenitors activate forkhead box O (FOXO) transcription factors, which bind to the Sox9 promoter and increase its expression. Besides initiating chondrogenesis, SOX9 acts as a regulator of cellular metabolism by suppressing oxidation of fatty acids, and thus adapts the cells to an avascular life. Our results define lipid scarcity as an important determinant of chondrogenic commitment, reveal a role for FOXO transcription factors during lipid starvation, and identify SOX9 as a critical metabolic mediator. These data highlight the importance of the nutritional microenvironment in the specification of skeletal cell fate. © 2020, The Author(s), under exclusive licence to Springer Nature Limited. [less ▲]

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See detailOptimising 3D bioprinter nozzle design through in silico modelling
Mandal, Sourav ULiege; Reina-Romo, Esther; Steenvoort, Nina Van et al

Poster (2019, November 15)

3D bioprinting is a flourishing technology, in addressing tissue-engineering construct manufacturing related challenges. However, the realization of the potential of this developing technique is hindered ... [more ▼]

3D bioprinting is a flourishing technology, in addressing tissue-engineering construct manufacturing related challenges. However, the realization of the potential of this developing technique is hindered by multiple technical hurdles which restrict the printability and cell survivability. In addition, commonly employed experimental trial and error approaches are time consuming and resource intensive, especially when a new material needs to be printed. To address these issues, computational or in silico modelling of specific parts of the system can be a viable option to optimize the relevant design as well as the printing and material parameters. Shear stress is proven to be a crucial factor for cell survivability in extrusion-based 3D bioprinting. Here, we sought to provide the appropriate choice for nozzle design in order to minimize the maximum shear stress occurring in the nozzle during bioprinting. We have modelled three widely used natural and synthetic shear-thinning hydrogel materials, namely alginate, alginate-gelatine and pluronic F127 (PF127) in two different nozzle configurations (conical and blunted). The model started with varying all the design parameters in the range relevant to practical application, using space-filling latin hypercube sampling (LHS) and running computational fluid dynamics (CFD) models to obtain flow profile and shear stress responses for each design. The outcomes from 1200 different in silico tested combinations are fitted into a machine learning method, known as Gaussian process to obtain the response of individual design parameters on the maximum shear stress generated in the hydrogel. It is found that the lower nozzle length and nozzle exit radius are the most important parameters for blunted nozzle designs whereas for conical designs middle and exit radii of the nozzle are crucial factors influencing shear stress. In addition, shear-thinning material properties were also shown to have important effects. In summary, we demonstrate the efficacy of CFD and ML based in silico modelling as a feasible pathway to overcome costly experimental trial and errors. This will help in optimising printing parameters, quantification and cost reduction for the development of new bio-printable materials. [less ▲]

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