Abstract
Background The current lack of predictable central nervous system (CNS) models in pharmaceutical industry early stage development strongly contributes for the high attrition rates registered for new therapeutics [1]. Thus, there is an increasing need for a paradigm shift towards more human relevant cell models, which can closely recapitulate the in vivo cell-cell interactions, presenting higher physiological relevance by bridging the gap between animal models and human clinical trials. In this context, human 3D in vitro models are promising tools with great potential for preclinical research, as they can mimic some of the main features of tissues, such as cell-cell and cell-extracellular matrix (ECM) interactions [2,3]. Moreover these complex cell models are suitable for high-throughput screening (HTS) platforms, essential in drug discovery pipelines by reducing both costs and time in clinical trials [2,4]. However, despite important advances in the last years and the increasing clinical and biological relevance, the full establishment of human 3D in vitro models in pre-clinical research requires a significant increase in the power of the available analytical methodologies towards more robust and comprehensive readouts [4]. With the emergence of systems biology field and several “-omics” technologies, such as metabolomics, it became possible to have a more mechanistic approach in the understanding of cellular programs. H-nuclear magnetic resonance (H-NMR) spectroscopy is a powerful and widely accepted high resolution methodology for a number of applications, including metabolic profiling [5]. Despite the low sensitivity when compared with mass spectrometry (MS), H-NMR profiling presents several advantages, enabling a non-invasive and non-destructive quantitative analysis requiring only minimal sample preparation [5]. In this work we present the development of a robust and optimized workflow for the exometabolome profiling of 3D in vitro cultures of human midbrain-derived neural progenitor cells (hmNPC).
Highlights
The current lack of predictable central nervous system (CNS) models in pharmaceutical industry early stage development strongly contributes for the high attrition rates registered for new therapeutics [1]
The approach applied in this study for metabolic profiling of the human midbrain-derived neural progenitor cells (hmNPC) cultures using 1H-nuclear magnetic resonance (1H-NMR) enables an accurate screening of a wide range of metabolites in the extracellular environment (Figure 1A), including amino acids, glucose, lactate, among other substrates and by-products
Our results showed that the hmNPC in an undifferentiated state presented a highly glycolytic metabolism, with high glucose consumption and lactate production rates (Figure 1B), in agreement with previous reports for murine NPC [10]
Summary
The current lack of predictable central nervous system (CNS) models in pharmaceutical industry early stage development strongly contributes for the high attrition rates registered for new therapeutics [1]. There is an increasing need for a paradigm shift towards more human relevant cell models, which can closely recapitulate the in vivo cell-cell interactions, presenting higher physiological relevance by bridging the gap between animal models and human clinical trials In this context, human 3D in vitro models are promising tools with great potential for preclinical research, as they can mimic some of the main features of tissues, such as cell-cell and cell-extracellular matrix (ECM) interactions [2,3]. Human 3D in vitro models are promising tools with great potential for preclinical research, as they can mimic some of the main features of tissues, such as cell-cell and cell-extracellular matrix (ECM) interactions [2,3] These complex cell models are suitable for high-throughput screening (HTS) platforms, essential in drug discovery pipelines by reducing both costs and time in clinical trials [2,4]. Despite the low sensitivity when compared with mass spectrometry (MS), 1H-NMR profiling presents several advantages, enabling a non-invasive
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call