Periodic Reporting for period 1 - NanoNonEq (Nanoprobes for Nonequilibrium Driven Systems)
Período documentado: 2022-10-01 hasta 2025-03-31
Understanding the fundamental workings of biological systems requires a deep exploration of nonequilibrium processes, which are at the heart of life’s dynamic and energy-driven nature. Biological activities such as cell division, transport, and molecular movement rely on a network of molecular motors that transform chemical energy from fuel molecules, like ATP, into mechanical work while dissipating heat. This process of energy dissipation, also known as entropy production, is essential for sustaining cellular functions and maintaining homeostasis. However, accurately measuring the dissipation of free energy in such complex systems remains a challenge due to limited experimental access to all interacting components and degrees of freedom.
The overarching objective of this project is to bridge the gap between theoretical tools in stochastic thermodynamics and their application in real-world biological experiments. Existing theoretical frameworks provide mathematical methods for quantifying nonequilibrium behavior, but their practical utility is often constrained by incomplete experimental data, which can obscure true measurements of energy loss and cause the system’s activity to appear as passive thermal fluctuations.
To tackle this challenge, the project aims to develop and implement innovative experimental tools—specifically, fluorescent nanosensors based on single-walled carbon nanotubes (SWCNTs). These nanosensors, tailored with precise functionalizations, are designed to detect and transduce the activity of molecular motors into measurable changes in fluorescence. This novel approach introduces a new dimension of observation by allowing the emitted fluorescence of SWCNTs to act as a phase-space coordinate for tracking energy dissipation in living and synthetic systems.
The project focuses on integrating these sensors into controlled biomimetic systems, such as DNA-gel matrices and reconstituted cytoskeletons, to map and understand energy dissipation in simplified but active environments. Subsequently, the research extends to internalizing these nanosensors in live cells to estimate entropy production at the cellular level, offering insights into intracellular organization and energy dynamics.
In parallel with experimental work, the project develops theoretical tools that use advanced data analysis techniques, including algorithms for assessing time-irreversibility and entropy production from partial data. By refining these tools, we aim to provide more reliable and practical methods for evaluating dissipation, even when only partial or coarse-grained experimental data is available.
The expected impact of this research is the enhancement of our understanding of the thermodynamics underlying biological systems and the development of non-invasive methods for measuring cellular and molecular activity.
The overarching objective of this project is to bridge the gap between theoretical tools in stochastic thermodynamics and their application in real-world biological experiments. Existing theoretical frameworks provide mathematical methods for quantifying nonequilibrium behavior, but their practical utility is often constrained by incomplete experimental data, which can obscure true measurements of energy loss and cause the system’s activity to appear as passive thermal fluctuations.
To tackle this challenge, the project aims to develop and implement innovative experimental tools—specifically, fluorescent nanosensors based on single-walled carbon nanotubes (SWCNTs). These nanosensors, tailored with precise functionalizations, are designed to detect and transduce the activity of molecular motors into measurable changes in fluorescence. This novel approach introduces a new dimension of observation by allowing the emitted fluorescence of SWCNTs to act as a phase-space coordinate for tracking energy dissipation in living and synthetic systems.
The project focuses on integrating these sensors into controlled biomimetic systems, such as DNA-gel matrices and reconstituted cytoskeletons, to map and understand energy dissipation in simplified but active environments. Subsequently, the research extends to internalizing these nanosensors in live cells to estimate entropy production at the cellular level, offering insights into intracellular organization and energy dynamics.
In parallel with experimental work, the project develops theoretical tools that use advanced data analysis techniques, including algorithms for assessing time-irreversibility and entropy production from partial data. By refining these tools, we aim to provide more reliable and practical methods for evaluating dissipation, even when only partial or coarse-grained experimental data is available.
The expected impact of this research is the enhancement of our understanding of the thermodynamics underlying biological systems and the development of non-invasive methods for measuring cellular and molecular activity.
The primary objective of our ERC project is to monitor nonequilibrium processes in biological systems influenced by molecular motors using functionalized single-walled carbon nanotubes (SWCNTs). This research involved both experimental and theoretical approaches to bridge the gap between complex biological systems and the quantification of energy dissipation.
Our experimental work focuses on developing systems where SWCNTs, functionalized with DNA and actin, act as sensors for real-time monitoring of nonequilibrium behavior. Initial results showed that these sensors could detect mechanical changes in active systems driven by molecular motors. The fluorescence of SWCNTs modulated in response to dynamic shifts in these systems, offering insight into energy dissipation processes.
Theoretical advancements were detailed in several significant publications. One first paper introduced a novel method to establish tight lower bounds on the entropy production rate (EPR) in systems with limited observability. This approach optimized the use of observed transitions and waiting times, providing more accurate estimates even under coarse-grained data conditions. Another publication expanded on this by comparing various EPR estimators, including Kullback-Leibler Divergence (KLD) and machine learning techniques, to evaluate their effectiveness in estimating dissipation from partially observed systems. These studies underscored the potential of combining experimental fluorescence data from SWCNTs with advanced theoretical frameworks to infer time-irreversibility and entropy production.
The main outcomes of the project include establishing SWCNTs as reliable nanosensors for tracking nonequilibrium activity, developing new tools for entropy estimation in biological systems, and enhancing our understanding of the thermodynamics underlying cellular and molecular processes. This work paves the way for further integration of these methods into live-cell studies and more complex biological analyses.
Our experimental work focuses on developing systems where SWCNTs, functionalized with DNA and actin, act as sensors for real-time monitoring of nonequilibrium behavior. Initial results showed that these sensors could detect mechanical changes in active systems driven by molecular motors. The fluorescence of SWCNTs modulated in response to dynamic shifts in these systems, offering insight into energy dissipation processes.
Theoretical advancements were detailed in several significant publications. One first paper introduced a novel method to establish tight lower bounds on the entropy production rate (EPR) in systems with limited observability. This approach optimized the use of observed transitions and waiting times, providing more accurate estimates even under coarse-grained data conditions. Another publication expanded on this by comparing various EPR estimators, including Kullback-Leibler Divergence (KLD) and machine learning techniques, to evaluate their effectiveness in estimating dissipation from partially observed systems. These studies underscored the potential of combining experimental fluorescence data from SWCNTs with advanced theoretical frameworks to infer time-irreversibility and entropy production.
The main outcomes of the project include establishing SWCNTs as reliable nanosensors for tracking nonequilibrium activity, developing new tools for entropy estimation in biological systems, and enhancing our understanding of the thermodynamics underlying cellular and molecular processes. This work paves the way for further integration of these methods into live-cell studies and more complex biological analyses.
A significant achievement of our project has been demonstrating the potential of functionalized single-walled carbon nanotubes (SWCNTs) as innovative tools for monitoring nonequilibrium dynamics. Unlike conventional fluorescent markers, SWCNTs inherently provide stable NIR fluorescence, which remains unaffected by photobleaching or blinking, making them ideal for prolonged studies of biological systems.
The theoretical advancements of this project, as outlined in our published work, have set new benchmarks in entropy production rate (EPR) estimation for systems with limited observability. One study established a novel optimization framework for calculating tight lower bounds on EPR using only partial data, such as transition events and waiting-time distributions. This method overcomes challenges faced by traditional approaches that often yield trivial or non-informative bounds under complex conditions. The second publication provided a comprehensive evaluation of various EPR estimation techniques, including Kullback-Leibler Divergence (KLD) and machine learning-based estimators. The research highlighted that integrating advanced analysis tools with coarse-grained experimental data can yield reliable and actionable insights into the nonequilibrium behavior of biological systems.
The potential impact of this project lies in creating a robust platform for studying energy dissipation in synthetic and biological systems, applicable to fields ranging from biophysics to medical diagnostics. To ensure further uptake and success, continued research on refining theoretical models and expanding their use in live-cell applications will be necessary. Demonstration projects showcasing the combined use of SWCNT sensors and theoretical frameworks in real-world scenarios will aid broader adoption.
Overall, this project has produced a versatile approach that merges experimental advancements with cutting-edge theoretical tools, paving the way for more precise studies of biological energy landscapes and opening up new opportunities for interdisciplinary research and applications.
The theoretical advancements of this project, as outlined in our published work, have set new benchmarks in entropy production rate (EPR) estimation for systems with limited observability. One study established a novel optimization framework for calculating tight lower bounds on EPR using only partial data, such as transition events and waiting-time distributions. This method overcomes challenges faced by traditional approaches that often yield trivial or non-informative bounds under complex conditions. The second publication provided a comprehensive evaluation of various EPR estimation techniques, including Kullback-Leibler Divergence (KLD) and machine learning-based estimators. The research highlighted that integrating advanced analysis tools with coarse-grained experimental data can yield reliable and actionable insights into the nonequilibrium behavior of biological systems.
The potential impact of this project lies in creating a robust platform for studying energy dissipation in synthetic and biological systems, applicable to fields ranging from biophysics to medical diagnostics. To ensure further uptake and success, continued research on refining theoretical models and expanding their use in live-cell applications will be necessary. Demonstration projects showcasing the combined use of SWCNT sensors and theoretical frameworks in real-world scenarios will aid broader adoption.
Overall, this project has produced a versatile approach that merges experimental advancements with cutting-edge theoretical tools, paving the way for more precise studies of biological energy landscapes and opening up new opportunities for interdisciplinary research and applications.