Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.06.28.546952

3D Cell Cultures Amplify Diffusion Signals

Abstract

Biophysical models can predict the behavior of cell cultures including 3D cell aggregates (3DCAs), thereby reducing the need for costly and time-consuming experiments. Specifically, mass transfer models enable studying the transport of nutrients, oxygen, signaling molecules, and drugs in 3DCA. These models require the defining of boundary conditions (BC) between the 3DCA and surrounding medium. However, accurately modeling the BC that relates the inner and outer boundary concentrations at the border between the 3DCA and the medium remains a challenge that this paper addresses using both theoretical and experimental methods. The provided biophysical analysis indicates that the concentration of molecules inside boundary is higher than that at the outer boundary, revealing an amplification factor that is confirmed by a particle-based simulator (PBS). Due to the amplification factor, the PBS confirms that when a 3DCA with a low concentration of target molecules is introduced to a culture medium with a higher concentration, the molecule concentration in the medium rapidly decreases. The theoretical model and PBS simulations were used to design a pilot experiment with liver spheroids as the 3DCA and glucose as the target molecule. Experimental results agree with the proposed theory and derived properties. Author summaryThe primary objective of our research was to enable the development of reliable biophysical models for three-dimensional cell aggregates (3DCAs). To achieve this goal, we employed a combination of theoretical and experimental methods to derive and characterize the amplification boundary condition (BC), which represents the relation of inner and outer boundary concentrations at the border between a 3DCA and its surrounding medium. By understanding the amplificaiton BC, we can better comprehend the transport and diffusion processes that occur within 3DCAs. The significance of our research lies in its potential to advance the understanding of 3DCAs and their underlying biophysical processes. This knowledge is crucial for a wide range of applications, including drug design and analysis of drug dosages within tissues. This factor may provide insight into the mechanisms behind tumor development and morphogenesis. In particular, the packed structure of cancer tumors enables them to receive and trap a higher concentration of nutrients and oxygen molecules based on the amplification factor. Thus, this study could contribute to the development of novel approaches to manage and treat cancerous tissues.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Arjmandi, H., Kanebratt, K. P., Vilen, L., Gennemark, P., Noel, A.. 2023-06-29. 3D Cell Cultures Amplify Diffusion Signals. https://doi.org/10.1101/2023.06.28.546952

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Expression-System Biases Compromise the Functional Assessment of KCNH2 Variants and Clinical Risk Assessment

Background: Functional characterization of KCNH2 variants is essential for assessing pathogenicity in long QT syndrome type 2. Because hERG channels assemble as tetramers, the relative expression of wild-type (WT) and variant subunits critically influences channel function and pathogenicity assessment. However, commonly used experimental systems may not reproduce the balanced allelic expression observed in heterozygous patients. Methods: Allele-specific KCNH2 expression was analyzed in two independent RNA-sequencing datasets from human left ventricular tissue. Using the dominant-negative T74R hERG variant as a model, we calibrated the relationship between WT-to-variant expression ratios and hERG current amplitude. Using automated patch-clamp electrophysiology, we compared 3 dual-expression strategies: internal ribosome entry site (IRES), P2A-linked tandem constructs, and dual cytomegalovirus promoter (dCMV) constructs. Co-electroporation of WT and variant plasmids in different ratios was the reference. Results: Allele-specific expression analysis supported balanced KCNH2 expression in human left ventricular tissue. At a 1:1 WT-to-T74R expression ratio, hERG current amplitude was reduced to 31.0% of WT, consistent with a dominant-negative mechanism in which incorporation of 2 or more T74R subunits renders the channel nonfunctional. All 3 dual-expression strategies produced substantial expression imbalances, with the first cassette consistently favored. IRES constructs showed the greatest asymmetry. P2A constructs partially improved expression balance but introduced an additional N-terminal proline in the second cassette altering T74R-associated trafficking and channel biophysics. The dCMV system also failed to achieve balanced expression, including after stable integration. Co-electroporation of separate WT and variant plasmids provided the most reliable means of controlling their relative expression. Conclusions: Commonly used dual-expression constructs do not reliably reproduce balanced WT and variant hERG expression, potentially distorting assessments of dominant-negative effects and variant pathogenicity. Co-electroporation of separate plasmids provides a robust approach for high-throughput functional phenotyping under heterozygous conditions, with implications for the interpretation of KCNH2 variants and potentially other genes encoding multimeric ion channels.

biophysics↗

Learning from Hi-C reveals nuclear dynamical reorganization in budding yeast across the cell cycle

Hi-C contact maps provide population-averaged measurements of chromosomal contacts. Converting these measurements, however, into three-dimensional structures and associated dynamics remains an underdetermined problem. Existing approaches broadly fall into two classes. Data-driven reconstruction methods that infer either a consensus structure or an ensemble of conformations, but do not inform on chromosome dynamics. Physics-based models, which generate dynamical trajectories, but require prior assumptions about nuclear geometry, chromatin mechanics, tethering, or molecular interactions. Here, we bridge these approaches using the Full-Inversion Chromatin model, a data-driven whole-genome polymer framework that learns an effective force field directly from Hi-C contact probabilities, integrated with Serpentine, a tool to quantify contact-map discrepancies while accounting for differences in sequencing coverage and sparsity. This generates structural ensembles of chromosomes and effective chromatin dynamics. We apply this method at 5-kb resolution to Saccharomyces cerevisiae in G1, mid-S, S/G2, G2/M, anaphase, and quiescence. Without explicitly imposing the spindle pole body, centromere or telomere tethering, predefined chromatin states, or nuclear-envelope interactions, the inferred ensembles recover these major features of yeast nuclear organization. Importantly, although dynamical information is not used during model training, the resulting polymer trajectories reproduce the subdiffusive scaling and chromosomal variations of independently measured chromatin motion. The model further predicts heterogeneous mobility along chromosomes and a distinctive telomere-dependent dynamical organization. Thus, population-averaged Hi-C contacts contain sufficient information to infer not only three-dimensional genome organization, but also effective, locus-dependent chromatin dynamics.

biophysics↗

One high-order ion-coupling mechanism generates multiple SLC1A stoichiometries

Human excitatory amino acid transporter 2 (hEAAT2) is a glial transporter that clears glutamate and aspartate from the extracellular space to terminate neurotransmission. When this essential role is disrupted, excess extracellular glutamate causes excitotoxicity and neurological disease. hEAAT2 transports amino acids into cells against their concentration gradients by coupling uptake to the co-transport of Na+ and H+, and counter-transport of K+. Substrate transport also activates a thermodynamically uncoupled Cl- conductance, whose significance is unknown. Here, to dissect the molecular mechanisms underlying coupled and uncoupled ion transport by EAATs, we leverage the tractable Drosophila melanogaster homologue dEAAT2, which transports taurine as well as glutamate and aspartate. By functionally characterising dEAAT2, we confirmed it has features of a canonical EAAT transport cycle, including an uncoupled Cl- conductance. However, it functions an ion-independent electroneutral exchanger, in stark contrast to its ion-coupled electrogenic human counterpart. Cryo-electron microscopy (cryo-EM) and computational simulations confirmed the inability of dEAAT2 to transport cations, but just two point mutations conferred Na+, H+, and K+ dependence, reconstituting the complex ion coupling profile of human transporters in the Drosophila exchanger. We also showed that dEAAT2 transports taurine in a complex with Cl-, bestowing a unique Cl--dependence on taurine transport, independent of uncoupled Cl- flux. Our findings show that ancestral exchangers in the EAAT family preserve the machinery to achieve complex ion-coupled transport, revealing the molecular basis of high-order ion coupling in hEAATs.

biophysics↗