Biophysical Tools to Study Cellular Mechanotransduction

The cell membrane is the interface that volumetrically isolates cellular components from the cell’s environment. Proteins embedded within and on the membrane have varied biological functions: reception of external biochemical signals, as membrane channels, amplification and regulation of chemical signals through secondary messenger molecules, controlled exocytosis, endocytosis, phagocytosis, organized recruitment and sequestration of cytosolic complex proteins, cell division processes, organization of the cytoskeleton and more. The membrane’s bioelectrical role is enabled by the physiologically controlled release and accumulation of electrochemical potential modulating molecules across the membrane through specialized ion channels (e.g., Na+, Ca2+, K+ channels). The membrane’s biomechanical functions include sensing external forces and/or the rigidity of the external environment through force transmission, specific conformational changes and/or signaling through mechanoreceptors (e.g., platelet endothelial cell adhesion molecule (PECAM), vascular endothelial (VE)-cadherin, epithelial (E)-cadherin, integrin) embedded in the membrane. Certain mechanical stimulations through specific receptor complexes induce electrical and/or chemical impulses in cells and propagate across cells and tissues. These biomechanical sensory and biochemical responses have profound implications in normal physiology and disease. Here, we discuss the tools that facilitate the understanding of mechanosensitive adhesion receptors. This article is structured to provide a broad biochemical and mechanobiology background to introduce a freshman mechano-biologist to the field of mechanotransduction, with deeper study enabled by many of the references cited herein

Disaster-Resilient Control Plane Design and Mapping in Software-Defined Networks

Communication networks, such as core optical networks, heavily depend on their physical infrastructure, and hence they are vulnerable to man-made disasters, such as Electromagnetic Pulse (EMP) or Weapons of Mass Destruction (WMD) attacks, as well as to natural disasters. Large-scale disasters may cause huge data loss and connectivity disruption in these networks. As our dependence on network services increases, the need for novel survivability methods to mitigate the effects of disasters on communication networks becomes a major concern. Software-Defined Networking (SDN), by centralizing control logic and separating it from physical equipment, facilitates network programmability and opens up new ways to design disaster-resilient networks. On the other hand, to fully exploit the potential of SDN, along with data-plane survivability, we also need to design the control plane to be resilient enough to survive network failures caused by disasters. Several distributed SDN controller architectures have been proposed to mitigate the risks of overload and failure, but they are optimized for limited faults without addressing the extent of large-scale disaster failures. For disaster resiliency of the control plane, we propose to design it as a virtual network, which can be solved using Virtual Network Mapping techniques. We select appropriate mapping of the controllers over the physical network such that the connectivity among the controllers (controller-to-controller) and between the switches to the controllers (switch-to-controllers) is not compromised by physical infrastructure failures caused by disasters. We formally model this disaster-aware control-plane design and mapping problem, and demonstrate a significant reduction in the disruption of controller-to-controller and switch-to-controller communication channels using our approach.Comment: 6 page

Constructing Modular and Universal Single Molecule Tension Sensor Using Protein G to Study Mechano-sensitive Receptors

Recently a variety of molecular force sensors have been developed to study cellular forces acting through single mechano-sensitive receptors. A common strategy adopted is to attach ligand molecules on a surface through engineered molecular tethers which report cell-exerted tension on receptor-ligand bonds. This approach generally requires chemical conjugation of the ligand to the force reporting tether which can be time-consuming and labor-intensive. Moreover, ligand-tether conjugation can severely reduce the activity of protein ligands. To address this problem, we developed a Protein G (ProG)-based force sensor in which force-reporting tethers are conjugated to ProG instead of ligands. A recombinant ligand fused with IgG-Fc is conveniently assembled with the force sensor through ProG:Fc binding, therefore avoiding ligand conjugation and purification processes. Using this approach, we determined that molecular tension on E-cadherin is lower than dsDNA unzipping force (nominal value: 12 pN) during initial cadherin-mediated cell adhesion, followed by an escalation to forces higher than 43 pN (nominal value). This approach is highly modular and potentially universal as we demonstrate using two additional receptor-ligand interactions, P-selectin & PSGL-1 and Notch & DLL1

Defining single molecular forces required for Notch activation using nano yoyo

Notch signaling, involved in development and tissue homeostasis, is activated at the cell-cell interface through ligand-receptor interactions. Previous studies have implicated mechanical forces in the activation of Notch receptor upon binding to its ligand. Here we aimed to determine the single molecular force required for Notch activation by developing a novel low tension gauge tether (LTGT). LTGT utilizes the low unbinding force between single-stranded DNA (ssDNA) and E. coli ssDNA binding protein (SSB) (~4 pN dissociation force at 500 nm/s pulling rate). The ssDNA wraps around SSB and, upon application of force, unspools from SSB, much like the unspooling of a yoyo. One end of this nano yoyo is attached to the surface though SSB while the other end presents a ligand. A Notch receptor, upon binding to its ligand, is believed to undergo force-induced conformational changes required for activating downstream signaling. If the required force for such activation is larger than 4 pN, ssDNA will unspool from SSB and downstream signaling will not be activated. Using these LTGTs, in combination with the previously reported TGTs that rupture double stranded DNA at defined forces, we demonstrate that Notch activation requires forces between 4-12 pN, assuming an in vivo loading rate of 60 pN/s. Taken together, our study provides a direct link between single-molecular forces and Notch activation

On the optimality of the radical-pair quantum compass

Quantum sensing enables the ultimate precision attainable in parameter estimation. Circumstantial evidence suggests that certain organisms, most notably migratory songbirds, also harness quantum-enhanced magnetic field sensing via a radical-pair-based chemical compass for the precise detection of the weak geomagnetic field. However, what underpins the acuity of such a compass operating in a noisy biological setting, at physiological temperatures, remains an open question. Here, we address the fundamental limits of inferring geomagnetic field directions from radical-pair spin dynamics. Specifically, we compare the compass precision, as derived from the directional dependence of the radical-pair recombination yield, to the ultimate precision potentially realisable by a quantum measurement on the spin system under steady-state conditions. To this end, we probe the quantum Fisher information and associated Cram\'er--Rao bound in spin models of realistic complexity, accounting for complex inter-radical interactions, a multitude of hyperfine couplings, and asymmetric recombination kinetics, as characteristic for the magnetosensory protein cryptochrome. We compare several models implicated in cryptochrome magnetoreception and unveil their optimality through the precision of measurements ostensibly accessible to nature. Overall, the comparison provides insight into processes honed by nature to realise optimality whilst constrained to operating with mere reaction yields. Generally, the inference of compass orientation from recombination yields approaches optimality in the limits of complexity, yet plateaus short of the theoretical optimal precision bounds by up to one or two orders of magnitude, thus underscoring the potential for improving on design principles inherent to natural systems

iWAP: ASingle Pass Approach for Web Access Sequential Pattern Mining

With the explosive growth of data availability on the World Wide Web, web usage mining becomes very essential for improving designs of websites, analyzing system performance as well as network communications, understanding user reaction, motivation and building adaptive websites. Web Access Pattern mining (WAP-mine) is a sequential pattern mining technique for discovering frequent web log access sequences. It first stores the frequent part of original web access sequence database on a prefix tree called WAP-tree and mines the frequent sequences from that tree according to a user given minimum support threshold. Therefore, this method is not applicable for incremental and interactive mining. In this paper, we propose an algorithm, improved Web Access Pattern (iWAP) mining, to find web access patterns from web logs more efficiently than the WAP-mine algorithm. Our proposed approach can discover all web access sequential patterns with a single pass of web log databases. Moreover, it is applicable for interactive and incremental mining which are not provided by the earlier one. The experimental and performance studies show that the proposed algorithm is in general an order of magnitude faster than the existing WAP-mine algorithm

Quantum Control of Radical Pair Dynamics beyond Time-Local Optimization

We realize arbitrary waveform-based control of spin-selective recombination reactions of radical pairs in the low magnetic field regime. To this end, we extend the Gradient Ascent Pulse Engineering (GRAPE) paradigm to allow for optimizing reaction yields. This overcomes drawbacks of previously suggested time-local optimization approaches for the reaction control of radical pairs, which were limited to high biasing fields. We demonstrate how efficient time-global optimization of the recombination yields can be realized by gradient based methods augmented by time-blocking, sparse sampling of the yield, and evaluation of the central single time-step propagators and their Fr\'echet derivatives using iterated Trotter-Suzuki splittings. Results are shown for both a toy model, previously used to demonstrate coherent control of radical pair reactions in the simpler high-field scenario, and furthermore for a realistic exciplex-forming donor-acceptor system comprising 16 nuclear spins. This raises prospects for the spin-control of actual radical pair systems in ambient magnetic fields, by suppressing or boosting radical reaction yields using purpose-specific radio-frequency waveforms, paving the way for reaction-yield-dependent quantum magnetometry and potentially applications of quantum control to biochemical radical pair reactions. We demonstrate the latter aspect for two radical pairs implicated in quantum biology.Comment: 17 pages, 9 figures, plus supplementary material (8 pagese, 8 figures

Rapid Activation of Rac GTPase in Living Cells by Force Is Independent of Src

It is well known that mechanical forces are crucial in regulating functions of every tissue and organ in a human body. However, it remains unclear how mechanical forces are transduced into biochemical activities and biological responses at the cellular and molecular level. Using the magnetic twisting cytometry technique, we applied local mechanical stresses to living human airway smooth muscle cells with a magnetic bead bound to the cell surface via transmembrane adhesion molecule integrins. The temporal and spatial activation of Rac, a small guanosine triphosphatase, was quantified using a fluorescent resonance energy transfer (FRET) method that measures changes in Rac activity in response to mechanical stresses by quantifying intensity ratios of ECFP (enhanced cyan fluorescent protein as a donor) and YPet (a variant yellow fluorescent protein as an acceptor) of the Rac biosensor. The applied stress induced rapid activation (less than 300 ms) of Rac at the cell periphery. In contrast, platelet derived growth factor (PDGF) induced Rac activation at a much later time (>30 sec). There was no stress-induced Rac activation when a mutant form of the Rac biosensor (RacN17) was transfected or when the magnetic bead was coated with transferrin or with poly-L-lysine. It is known that PDGF-induced Rac activation depends on Src activity. Surprisingly, pre-treatment of the cells with specific Src inhibitor PP1 or knocking-out Src gene had no effects on stress-induced Rac activation. In addition, eliminating lipid rafts through extraction of cholesterol from the plasma membrane did not prevent stress-induced Rac activation, suggesting a raft-independent mechanism in governing the Rac activation upon mechanical stimulation. Further evidence indicates that Rac activation by stress depends on the magnitudes of the applied stress and cytoskeletal integrity. Our results suggest that Rac activation by mechanical forces is rapid, direct and does not depend on Src activation. These findings suggest that signaling pathways of mechanical forces via integrins might be fundamentally different from those of growth factors

Mining Sequential Patterns in Uncertain Databases Using Hierarchical Index Structure

In this uncertain world, data uncertainty is inherent in many applications and its importance is growing drastically due to the rapid development of modern technologies. Nowadays, researchers have paid more attention to mine patterns in uncertain databases. A few recent works attempt to mine frequent uncertain sequential patterns. Despite their success, they are incompetent to reduce the number of false-positive pattern generation in their mining process and maintain the patterns efficiently. In this paper, we propose multiple theoretically tightened pruning upper bounds that remarkably reduce the mining space. A novel hierarchical structure is introduced to maintain the patterns in a space-efficient way. Afterward, we develop a versatile framework for mining uncertain sequential patterns that can effectively handle weight constraints as well. Besides, with the advent of incremental uncertain databases, existing works are not scalable. There exist several incremental sequential pattern mining algorithms, but they are limited to mine in precise databases. Therefore, we propose a new technique to adapt our framework to mine patterns when the database is incremental. Finally, we conduct extensive experiments on several real-life datasets and show the efficacy of our framework in different applications.Comment: Accepted at PAKDD 2021. arXiv admin note: text overlap with arXiv:2404.0074