Biology subjects

Sancho, J.

Publications and source records attributed to Sancho, J..

5 recordsLinked to original sources

bioRxiv2023

CD38 promotes hematopoietic stem cell dormancy via c-Fos

A subpopulation of deeply quiescent, so-called dormant hematopoietic stem cells (dHSCs) resides at the top of the hematopoietic hierarchy and serves as a reserve pool for HSCs possessing the greatest long-term blood repopulation capacity. The state of dormancy protects the HSC pool from exhaustion throughout life, however excessive dormancy may block an efficient response to hematological stresses. The mechanisms of HSC dormancy remain elusive, mainly due to the absence of surface markers that allow dHSC prompt isolation. Here, we identify CD38 as a novel surface marker for murine dHSCs that is broadly applicable. Moreover, we demonstrate that cyclic adenosine diphosphate ribose (cADPR), the product of CD38 cyclase activity, regulates the expression of the transcription factor c-Fos by increasing cytoplasmic Ca2+ concentration. Strikingly, we uncover that c-Fos drives HSCs dormancy through the induction of the cell cycle inhibitor p57Kip2. Moreover, we found that CD38 ecto-enzymatic activity at the neighboring CD38-positive cells can promote human HSC quiescence. Together, CD38/cADPR/Ca2+/cFos/p57Kip2 axis maintains HSC dormancy. Pharmacological manipulations of this pathway can provide new strategies to expand dHSCs for transplantation or to activate them during hematological stresses.

cell biology↗

bioRxiv2023

Calculation of Protein Folding Thermodynamics using Molecular Dynamics Simulations

Despite impressive advances by AlphaFold2 in the field of computational biology, the protein folding problem remains an enigma to be solved. The continuous development of algorithms and methods to explore longer simulation timescales of biological systems, as well as the enhanced accuracy of potential functions (force fields and solvent models) have not yet led to significant progress in the calculation of the thermodynamics quantities associated to protein folding from first principles. Progress in this direction can help boost related fields such as protein engineering, drug design, or genetic interpretation, but the task seems not to have been addressed by the scientific community. Following an initial explorative study, we extend here the application of a Molecular Dynamics-based approach -with the most accurate force field/water model combination previously found (Charmm22-CMAP/Tip3p)- to computing the folding energetics of a set of two-state and three-state proteins that do or do not carry a bound cofactor. The proteins successfully computed are representative of the main protein structural classes, their sequences range from 84 to 169 residues, and their isoelectric points from 4.0 to 8.9. The devised approach enables accurate calculation of two essential magnitudes governing the stability of proteins -the changes in enthalpy and in heat capacity associated to protein unfolding-, which are used to obtain accurate values of the change in Gibbs free-energy, also known as the protein conformational stability. The method proves to be also suitable to obtain changes in stability due to changes in solution pH, or stability differences between a wild-type protein and a variant. The approach addresses the calculation by difference, a shortcut that avoids having to simulate the protein folding time, which is very often unfeasible computationally.

molecular biology↗

bioRxiv2023

Molecular Interactions and Forces that Make Proteins Stable: A Quantitative Inventory from Atomistic Molecular Dynamics Simulations

Protein design requires a deep control of protein folding energetics, which can be determined experimentally on a case-by-case basis but is not understood in sufficient detail. Calorimetry, protein engineering and biophysical modeling have outlined the fundamentals of protein stability, but these approaches face difficulties in elucidating the specific contributions of the intervening molecules and elementary interactions to the folding energy balance. Recently, we showed that, using Molecular Dynamics (MD) simulations of native proteins and their unfolded ensembles, one can calculate, within experimental error, the enthalpy and heat capacity changes of the folding reaction. Analyzing MD simulations of four model proteins (CI2, barnase, SNase and apoflavodoxin) whose folding enthalpy and heat capacity changes have been successfully calculated, we dissect here the energetic contributions to protein stability made by the different molecular players (polypeptide and solvent molecules) and elementary interactions (electrostatic, van der Waals and bonded) involved. Although the proteins analyzed differ in length (65-168 amino acid residues), isoelectric point (4.0-8.99) and overall fold, their folding energetics is governed by the same quantitative pattern. Relative to the unfolded ensemble, the native conformation is enthalpically stabilized by comparable contributions from protein-protein and solvent-solvent interactions, and it is nearly equally destabilized by interactions between protein and solvent molecules. From the perspective of elementary physical interactions, the native conformation is stabilized by van de Waals and coulombic interactions and is destabilized by bonded interactions. Also common to the four proteins, the sign of the heat capacity change is set by protein-solvent interactions or, from the alternative perspective, by coulombic interactions.

molecular biology↗

bioRxiv2022

Accurate and efficient constrained molecular dynamics of polymers through Newton's method and special purpose code

In molecular dynamics simulations we can often increase the time step by imposing constraints on internal degrees of freedom, such as bond lengths and bond angles. This allows us to extend the length of the time interval and therefore the range of physical phenomena that we can afford to simulate. In this article we analyse the impact of the accuracy of the constraint solver. We present ILVES-PC, an algorithm for imposing constraints on proteins accurately and efficiently. ILVES-PC solves the same system of differential algebraic equations as the celebrated SHAKE algorithm, but uses Newtons method for solving the nonlinear constraint equations. It solves the necessary linear systems of equations using a specialised linear solver that utilises the molecular structure. ILVES-PC can rapidly solve the nonlinear constraint equations to nearly the limit of machine precision. This eliminates the spurious forces introduced to simulations through the very common use of inaccurate approximations. The run-time of ILVES-PC is proportional to the number of constraints. We have integrated ILVES-PC into GROMACS and simulated proteins of different sizes. Compared with SHAKE, we have achieved speedups of up to 4.9x in single-threaded executions and up to 76x in shared-memory multi-threaded executions. Moreover, we find that ILVES-PC is more accurate than the P-LINCS algorithm. Our work is a proof-of-concept of the utility of software designed specifically for the simulation of polymers. Author summaryMolecular dynamics simulates the time evolution of molecular systems. It has become a tool of extraordinary importance for e.g. understanding biological processes and designing drugs and catalysts. This article presents an algorithm for computing the forces needed to impose constraints in molecular dynamics, i.e., the constraint forces; moreover, it analyses the effect of the accuracy of the constraint solver. Presently, it is customary to calculate the constraint forces with a relative error that that is not tiny. This is due to the high computational cost associated with the available software. Accurate calculations are possible, but they are very time-consuming. The algorithm that we present solves this problem: it computes the constraint forces accurately and efficiently. Our work will improve the accuracy and reliability of molecular dynamics simulations beyond the present state-of-the-art. The results that we present are also a proof-of-concept that special-purpose code can increase the performance of software for the simulation of polymers. The algorithm is implemented into a popular molecular simulation package, and is now available for the research community.

molecular biology↗

bioRxiv2021

Disrupted microglial iron homeostasis in progressive multiple sclerosis

Multiple Sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system (CNS). Despite therapies that reduce relapses, many patients eventually develop secondary progressive MS (SPMS), characterized by ongoing and irreversible neurodegeneration and worsening clinical symptoms. Microglia are the resident innate immune cells of the CNS. While the cellular and molecular determinants of disability progression in MS remain incompletely understood, they are thought to include non-resolving microglial activation and chronic oxidative injury. In this study, our aim was to better characterize microglia in SPMS tissues to identify disease-related changes at the single cell level. We performed single nucleus RNA-seq (snRNA-seq) on cryopreserved post-mortem brain cortex and identified disease associated changes in multiple cell types and in particular distinct SPMS-enriched microglia subsets. When compared to the cluster most enriched in healthy controls (i.e. homeostatic microglia), we found a number of SPMS-enriched clusters with transcriptional profiles reflecting increased oxidative stress and perturbed iron homeostasis. Using histology and RNA-scope, we confirmed the presence of iron accumulating, ferritin-light chain (FTL)-expressing microglia in situ. Among disease-enriched clusters, we found evidence for divergent responses to iron accumulation and identified the antioxidant enzyme GPX4 as a key fate determinant. These data help elucidate processes that occur in progressive MS brains, and highlight novel nodes for therapeutic intervention.

neuroscience↗