Discrete adipose-derived stem cell subpopulations may display differential functionality after in vitro expansion despite convergence to a common phenotype distribution

BACKGROUND: Complex immunophenotypic repertoires defining discrete adipose-derived stem cell (ASC) subpopulations may hold a key toward identifying predictors of clinical utility. To this end, we sorted out of the freshly established ASCs four subpopulations (SPs) according to a specific pattern of co-expression of six surface markers, the CD34, CD73, CD90, CD105, CD146, and CD271, using polychromatic flow cytometry. METHOD: Using flow cytometry-associated cell sorting and analysis, gating parameters were set to select for a CD73(+)CD90(+)CD105(+) phenotype plus one of the four following combinations, CD34(−)CD146(−)CD271(−) (SP1), CD34(−)CD146(+)CD271(−) (SP2), CD34(+)CD146(+)CD271(−) (SP3), and CD34(−)CD146(+)CD271(+) (SP4). The SPs were expanded 700- to 1000-fold, and their surface repertoire, trilineage differentiation, and clonogenic potential, and the capacity to support wound healing were assayed. RESULTS: Upon culturing, the co-expression of major epitopes, the CD73, CD90, and CD105 was maintained, while regarding the minor markers, all SPs reverted to resemble the pre-sorted population with CD34(−)CD146(−)CD271(−) and CD34(−)CD146(+)CD271(−) representing the most prevalent combinations, followed by less frequent CD34(+)CD146(−)CD271(−) and CD34(+)CD146(+)CD271(−) variants. There was no difference in the efficiency of adipo-, osteo-, or chondrogenesis by cytochemistry and real-time RT-PCR or the CFU capacity between the individual SPs, however, the SP2(CD73+90+105+34-146+271-) outperformed others in terms of wound healing. CONCLUSIONS: Our study shows that ASCs upon culturing inherently maintain a stable distribution of immunophenotype variants, which may potentially disguise specific functional properties of particular downstream lines. Furthermore, the outlined approach suggests a paradigm whereby discrete subpopulations could be identified to provide for a therapeutically most relevant cell product. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13287-016-0435-8) contains supplementary material, which is available to authorized users

Physiological map to study kidney toxicity in the ONTOX project

editorial reviewedBackground and Objectives: Continuous improvements of computational approaches also increase the predictive performances of toxicological in silico models [1]. However, being mainly based on animal test data, these computational models lack a good correlation with human toxicity, and, being often based uniquely on chemical structures, they are unable to explain toxicological processes. To overcome these limitations, we have developed a new semi-automated strategy to build a Physiological Map (PM), a framework to study human toxicological mechanisms. Materials and Methods: Our method is useful to build a PM or to validate an existing PM. To retrieve information, a manual literature review was accompanied by computational interrogation of ontologies (e.g. Gene Ontology), thus creating a network of genes, proteins, molecules and phenotypes [2]. The network was converted manually into a PM using the CellDesigner software and visualized on the web using the MINERVA platform. The entire procedure was supported and revised by field experts. Results: We present here the human kidney PM, developed in the framework of ONTOX, a European project aimed at improving risk assessment avoiding the use of animal tests [3]. With the purpose to better understand tubular necrosis and nephrolithiasis, the PM represents the normal physiology in proximal tubule, the loop of Henle, distal tubule, and collecting duct cells, displaying the vitamin D metabolism and the urine production processes: filtration, reabsorption and secretion. Discussion and Conclusions: Our method assists the user to build a PM even starting from limited data. The PM is initially a static representation of physiological processes, also useful to study and develop new adverse outcome pathways. Subsequently, we could add kinetic parameters, transforming the PM into a dynamic model able to represent cellular perturbations. This approach presents an opportunity to investigate human toxicities, improving the toxicological predictions from a qualitative and quantitative perspective. References: [1] Manganelli S, Gamba A, Colombo E, Benfenati E (2022) 'Using VEGAHUB Within a Weight-of-Evidence Strategy'. In: Benfenati E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 2425. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1960-5_18 [2] Gamba A, Salmona M, Bazzoni G (2020) 'Quantitative analysis of proteins which are members of the same protein complex but cause locus heterogeneity in disease', Sci Rep 10, 10423. https://doi.org/10.1038/s41598-020-66836-7 [3] Vinken M., et al. (2021) 'Safer chemicals using less animals: kick-off of the European ONTOX project', Toxicology 458, 152846. https://doi.org/10.1016/j.tox.2021.15284

Mapping the use of computational modelling and simulation in clinics: A survey

In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&S in clinical practice is not always timely and accurately reflected in the literature. A clear view on the current awareness, actual usage and opinions from the clinicians is needed to identify barriers and opportunities for the future of in silico medicine. The aim of this study was capturing the state of CM&S in clinics by means of a survey toward the clinical community. Responses were collected online using the Virtual Physiological Human institute communication channels, engagement with clinical societies, hospitals and individual contacts, between 2020 and 2021. Statistical analyses were done with R. Participants (n = 163) responded from all over the world. Clinicians were mostly aged between 35 and 64 years-old, with heterogeneous levels of experience and areas of expertise (i.e., 48% cardiology, 13% musculoskeletal, 8% general surgery, 5% paediatrics). The CM&S terms “Personalised medicine” and “Patient-specific modelling” were the most well-known within the respondents. “In silico clinical trials” and “Digital Twin” were the least known. The familiarity with different methods depended on the medical specialty. CM&S was used in clinics mostly to plan interventions. To date, the usage frequency is still scarce. A well-recognized benefit associated to CM&S is the increased trust in planning procedures. Overall, the recorded level of trust for CM&S is high and not proportional to awareness level. The main barriers appear to be access to computing resources, perception that CM&S is slow. Importantly, clinicians see a role for CM&S expertise in their team in the future. This survey offers a snapshot of the current situation of CM&S in clinics. Although the sample size and representativity could be increased, the results provide the community with actionable data to build a responsible strategy for accelerating a positive uptake of in silico medicine. New iterations and follow-up activities will track the evolution of responses over time and contribute to strengthen the engagement with the medical community

Human pluripotent stem cell-derived cartilaginous organoids promote scaffold-free healing of critical size long bone defects.

peer reviewedBACKGROUND: Bones have a remarkable capacity to heal upon fracture. Yet, in large defects or compromised conditions healing processes become impaired, resulting in delayed or non-union. Current therapeutic approaches often utilize autologous or allogeneic bone grafts for bone augmentation. However, limited availability of these tissues and lack of predictive biological response result in limitations for clinical demands. Tissue engineering using viable cell-based implants is a strategic approach to address these unmet medical needs. METHODS: Herein, the in vitro and in vivo cartilage and bone tissue formation potencies of human pluripotent stem cells were investigated. The induced pluripotent stem cells were specified towards the mesodermal lineage and differentiated towards chondrocytes, which subsequently self-assembled into cartilaginous organoids. The tissue formation capacity of these organoids was then challenged in an ectopic and orthotopic bone formation model. RESULTS: The derived chondrocytes expressed similar levels of collagen type II as primary human articular chondrocytes and produced stable cartilage when implanted ectopically in vivo. Upon targeted promotion towards hypertrophy and priming with a proinflammatory mediator, the organoids mediated successful bridging of critical size long bone defects in immunocompromised mice. CONCLUSIONS: These results highlight the promise of induced pluripotent stem cell technology for the creation of functional cartilage tissue intermediates that can be explored for novel bone healing strategies

Physiological maps and chemical-induced disease ontologies: tools to support NAMs development for next-generation risk assessment

editorial reviewedPhysiological maps (PM) can be defined as a graphical representation of cellular and molecular processes associated to specific organ functions (Vinken et al. 2021). Within the ONTOX project, we designed a total of 6 PMs describing physiological processes in the liver, the kidney and the brain. These PMs are then used as a tool to assess relevant mechanistic coverage and linkage between a specific organ function and a toxicological endpoint. Based on the Disease Maps project (Mazein et al. 2018) pipeline, we developed the first version of 6 PMs describing the following physiological processes: bile secretion & lipid metabolism (liver), vitamin D metabolism & urine composition (kidney), neural tube closure (update of the work of Heusinkveld et al. 2021) & brain development (brain). Our workflow included: (i) data collection from expert curated literature (ii) identification of the relevant biological mechanisms, (iii) screening of online databases (e.g. Wikipathways, Reactome, and KEGG) for previously described pathways, (iv) manual curation and integration of the data into a PM using CellDesigner, and (v) visualization on the MINERVA platform (Hoksza et al. 2019). These qualitative PMs represent an important tool for exploring curated literature, analyzing networks and benchmarking the development of new adverse outcome pathways (AOPs). These PMs provide the basis for developing quantitative disease ontologies, integrating different layers of pathological and toxicological information, chemical information (drug-induced pathways) and kinetic data. The resulting chemical-induced disease ontologies will provide a multi-layered platform for integration and visualization of such information. The ontologies will contribute to improving understanding of organ/disease related pathways in response to chemicals, visualize omics datasets, develop quantitative methods for computational disease modeling and for predicting toxicity, set up an in vitro & in silico test battery to detect a specific type of toxicity, and develop new animal-free approaches for next generation risk assessment

An in silico approach to study Osteoarthritis development and identify potential intervention target

Oral presentation + posterstatus: publishe

Reverse engineering methods to study chondrogenic regulatory networks

Poster presentationstatus: publishe

Reverse engineering methods to study chondrogenic regulatory networks

Poster presentationstatus: publishe

Reverse Engineering Methods to Study Osteochondral Regulatory Networks

published abstract and oral presentationstatus: Published onlin

Mapping the use of computational modelling and simulation in clinics: A survey

In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&S in clinical practice is not always timely and accurately reflected in the literature. A clear view on the current awareness, actual usage and opinions from the clinicians is needed to identify barriers and opportunities for the future of in silico medicine. The aim of this study was capturing the state of CM&S in clinics by means of a survey toward the clinical community. Responses were collected online using the Virtual Physiological Human institute communication channels, engagement with clinical societies, hospitals and individual contacts, between 2020 and 2021. Statistical analyses were done with R. Participants (n = 163) responded from all over the world. Clinicians were mostly aged between 35 and 64 years-old, with heterogeneous levels of experience and areas of expertise (i.e., 48% cardiology, 13% musculoskeletal, 8% general surgery, 5% paediatrics). The CM&S terms “Personalised medicine” and “Patient-specific modelling” were the most well-known within the respondents. “In silico clinical trials” and “Digital Twin” were the least known. The familiarity with different methods depended on the medical specialty. CM&S was used in clinics mostly to plan interventions. To date, the usage frequency is still scarce. A well-recognized benefit associated to CM&S is the increased trust in planning procedures. Overall, the recorded level of trust for CM&S is high and not proportional to awareness level. The main barriers appear to be access to computing resources, perception that CM&S is slow. Importantly, clinicians see a role for CM&S expertise in their team in the future. This survey offers a snapshot of the current situation of CM&S in clinics. Although the sample size and representativity could be increased, the results provide the community with actionable data to build a responsible strategy for accelerating a positive uptake of in silico medicine. New iterations and follow-up activities will track the evolution of responses over time and contribute to strengthen the engagement with the medical community