Elucidation of molecular kinetic schemes from macroscopic traces using system identification

Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully applied to accurately derive molecular kinetic schemes from experimental macroscopic traces, and we anticipate that it may be useful in the study of a wide variety of biological systems

An analytical tool for elucidating ion-channel molecular mechanisms from macroscopic current traces

Building models to describe the dynamics of macroscopic currents through ion channels has been the object of numerous studies in the literature with the aim of understanding ion-channel function. Following a perturbation, typically a step in voltage or ligand concentration, the response is formed by a combination of different processes such as activation or inactivation that pull the measured quantity (macroscopic current) in the same or opposite directions with different strengths and different time constants. Although this dynamic response can be readily recorded in time, the relationship between the underlying processes cannot be easily teased apart without structural analysis or single-channel recordings. An example is the classic problem of determining from sodium-channel macroscopic traces whether the activation and inactivation processes occur in parallel or inactivation is dependent on previous activation. We present a mathematical tool to analyze electrophysiological traces and derive molecular kinetic schemes that reflect the interplay between the different processes involved. This tool is based on system-identification algorithms and consists of three modules as summarized in Figure 1. The identifier takes the input and output signals in the time domain and applies autoregressive ARX methods to obtain a transfer function in the Laplace domain yielding a set of poles, zeros and gain that provide a unique signature of the channel response. The classifier capitalizes on this signature to reveal the block diagram associated with the interplay of the processes, that are here described as first order systems in classic engineering terms (a relaxation with one time constant and a gain for each process). Finally, the molecular kinetic converter uses the transfer function together with the block diagram and maps them into a molecular kinetic scheme, a description with states associated with a system of differential equations

Development of an Analytical Tool to Characterize the Dynamics of Biological Systems Using Electrophysiological Traces

Las respuestas celulares a estímulos críticos para su función están organizadas en forma de redes que integran múltiples procesos más sencillos. Las técnicas experimentales actuales únicamente nos permiten visualizar y medir estos procesos a nivel molecular en algunos casos extremadamente favorables. Por tanto, y para el avance de nuestro entendimiento de las respuestas fisiológicas, es crucial el desarrollo de herramientas y métodos que nos permitan extraer a partir de la respuesta celular global (macroscópica) que podemos medir, la dinámica de los distintos procesos a nivel molecular (microscópicos) así como la relación entre los mismos. En esta tesis se presenta el desarrollo de un método híbrido computacional/analítico para realizar dicha tarea: la herramienta SYSMOLE (SYStems-based MOLecular kinetic scheme Extractor). SYSMOLE utiliza teoría de identificación de sistemas con el fin de obtener una función de transferencia entre el estímulo (entrada) y la respuesta global de la célula (salida) en el dominio transformado de Laplace. Una vez caracterizada dicha función de transferencia, SYSMOLE obtiene una cadena de Markov o modelo cinético molecular asociado a la misma utilizando un proceso de clasificación e imponiendo ciertas restricciones biológicas para condicionar el problema. Primero utilizamos trazas sintéticas para evaluar las prestaciones de SYSMOLE en términos de velocidad de convergencia, obtención del modelo cinético molecular correcto, y robustez frente al ruido. Después examinamos el funcionamiento de SYSMOLE en su aplicación al análisis de trazas electrofisiológicas de canales de calcio activados durante la despolarización de la membrana, y mostramos que SYSMOLE no sólo obtiene el modelo cinético molecular que describe la activación e inactivación de dichos canales, sino que también identifica correctamente el mecanismo de acción de la nifedipina, un bloqueador de canales de calcio utilizado clínicamente para tratar enfermedades cardiovasculares. Finalmente, presentamos la aplicación de SYSMOLE al estudio de la farmacología y señalización de una nueva clase de fármacos antipsicóticos cuya diana es un complejo heteromérico de receptores acoplados a proteínas G. Los resultados indican que la herramienta desarrollada en esta tesis es capaz de obtener modelos cinéticos moleculares relevantes a partir de trazas electrofisiológicas y que puede ser de utilidad para el estudio de una amplia gama de sistemas biológicos. ----------ABSTRACT---------- Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this still only possible in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. In this thesis we describe the development of a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calciumcurrent traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully applied to accurately derive molecular kinetic schemes from experimental macroscopic traces, and we anticipate that it may be useful in the study of a wide variety of biological systems

Erythropoietin administration expands regulatory T cells in patients with autoimmune hepatitis

OBJECTIVE: Autoimmune hepatitis (AIH) is a chronic liver disease associated with impaired regulatory T cell (Treg) number and function. Erythropoietin (EPO) is a kidney-produced erythropoietic hormone that has known immune-modulating effects, including Treg induction. Whether EPO administration increases Treg in patients with AIH is unknown.METHODS: We treated six stable AIH patients with a single 1000 IU dose of EPO and comprehensively characterized changes in Treg overall and in Treg subsets before and at 4 and 12 weeks after treatment using mass cytometry (CyTOF) combined with an unbiased clustering approach (Phenograph) based on 22 Treg-relevant cell-surface markers.RESULTS: EPO was well-tolerated and no patients showed significant changes in hematological parameters, liver enzymes, or IgG levels from baseline to 12 weeks following EPO administration. Total Treg and Treg/CD8+ T cell ratios significantly increased at 4 weeks and returned to baseline levels at 12 weeks after EPO injection. We identified 17 Treg subsets of which CD4+CD25HICD127NEG HLADR+ Treg had the highest increase and the most favorable Treg/CD8+ ratio upon EPO treatment. At 12 weeks after EPO administration, the HLADR+ Treg subset also returned to values comparable to those at baseline. Ex vivo assays documented that Treg were functional and the ones isolated at 12 weeks after EPO injection were significantly more suppressive than the ones isolated at baseline. In Treg-depleted assays, EPO did not show a significant effect on IFN-gamma+, IL-2+, and IL-17+ CD4+ T cells.CONCLUSION: In stable AIH patients, EPO increases overall Treg and particularly those expressing the high function marker HLA-DR. These results provide the rationale for future studies testing the hypothesis that EPO or EPO analogues improve outcomes of AIH patients by increasing Treg

Correction: Elucidation of molecular kinetic schemes from macroscopic traces using system identification.

[This corrects the article DOI: 10.1371/journal.pcbi.1005376.]

Self-Assembled Lanthanide Antenna Glutathione Sensor for the Study of Immune Cells

The small molecule 8-methoxy-2-oxo-1,2,4,5- tetrahydrocyclopenta[de]quinoline-3-carboxylic acid (2b) behaves as a reactive non-fluorescent Michael acceptor, which after reaction with thiols becomes fluorescent, and an efficient Eu3+ antenna, after self-assembling with this cation in water. This behavior makes 2b a highly selective GSH biosensor, which has demonstrated high potential for studies in murine and human cells of the immune system (CD4+ T, CD8 + T, and B cells) using flow cytometry. GSH can be monitored by the fluorescence of the product of addition to 2b (445 nm) or by the luminescence of Eu3+ (592 nm). 2b was able to capture baseline differences in GSH intracellular levels among murine and human CD4 + T, CD8 + T, and B cells. We also successfully used 2b to monitor intracellular changes in GSH associated with the metabolic variations governing the induction of CD4+ naï ve T cells into regulatory T cells (TREG ).This work was supported by grants CTQ2017-85658-R, BFU2015-67284-R, and PID2019-104366RB-C22 funded by MCIN/AEI/10.13039/501100011033/FEDER “Una manera de hacer Europa”; grant PID2020-114256RB-I00 funded by MCIN/AEI/10.13039/501100011033; grant A-FQM-386- UGR20 funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades, and the CSIC grant 201580E073. Funding for open access charge: Universidad de Granada/CBUA.Peer reviewe