Globular-protein-based hydrogels that combine the advantages of (un)folding mechanics, wettability, and biocompatibility derived from their main building unit, folded proteins, have the potential to be a platform for studying protein mechanics and developing new “smart” biomaterials. However, a reliable method that can investigate the proteins (un)folding mechanics and characterize the mechanical properties of protein-based hydrogels is essential. In the first part of this talk, I will introduce a custom-made force-clamp rheometer that can measure the extension of an extremely low-volume protein-based hydrogel sample polymerized via photoactivated reaction, while clamping the force at a pre-defined setpoint. The second part will be allocated to how protein-polymer interaction and the physical folding code of a protein can be translated into engineering new biomaterials. Finally, I would like to discuss with you, would a science-kitchen fusion contribute to biomaterials science and make the culinary field to more interesting?
As an injury heals, an embryo develops, or a carcinoma spreads, epithelial cells systematically change
their shape. In each of these processes cell shape is studied extensively whereas variability of shape
from cell-to-cell is regarded most often as biological noise. But where do cell shape and its variability
come from? In this talk I will show that cell shape and shape variability are mutually constrained through
a relationship that is purely geometrical. That relationship is shown to govern processes as diverse as
maturation of the pseudostratified bronchial epithelial layer cultured from non-asthmatic or asthmatic
donors, and formation of the ventral furrow in the Drosophila embryo. Across these and other epithelial
systems, shape variability collapses to a family of distributions that is common to all. That distribution, in
turn, is accounted for by a mechanistic theory of cell-cell interaction showing that cell shape becomes
progressively less elongated and less variable as the layer becomes progressively more jammed and
solid-like. These findings suggest that, in diverse multicellular organisms, jamming behavior sets
overriding geometrical constraints. Such constraints along with the well-recognized role of cellular
geometry as a fundamental regulator of cell behavior, may provide the missing physical picture of
cancer invasion and growth. This perspective points to the hypothesis that the malignant primary tumor
is unjammed and fluid-like, and thus, through the agency of elongated cell shapes, may shed clusters of
metastasizing cells and retain high mitotic capacity even in dense cell packing.
The heart is a fascinatingly efficient pump with intricate design criteria. While many aspects of
heart function remain a mystery, investigations through the prism of mechanics, physics, and
mathematics can provide invaluable insights – presented as three examples in this talk. First, we
consider the problem of automatically characterizing cardiac tissue architecture over multiple
length-scales. Through, the use of existing and creation of new order parameters, multiple
discoveries were made such as the existence of consistently sized spontaneous patches of
organization in isotropic cardiac tissues. Second, we explore the relationship between cell
organization and tissue force generation. Through a tissue engineering trick, the global (~1mm)
and local (~100 microns) architecture effects were separated, and it was discovered that the
reduction in developed force due purely to changes in global tissue architecture can be predicted
by an astonishingly simple physical model, while local changes trigger complex biological
responses. Third, we investigate the relationship among genetic mutations to the nuclear lamina
protein, Lamin A/C (LMNA), detrimental consequences to cellular architecture, and cardiac
function. LMNA mutations can lead to a devastating early aging disease (progeria) or have a
subtler effect with patients presenting only with heart disease symptoms. However, the
mechanisms by which the LMNA mutation emerges in the heart muscle are unknown. Thus far
we have uncovered a relationship between nuclear defects in patient-specific cells and the age at
which these patients present with heart disease symptoms. Additionally, we have found that the
pathology that takes decades to develop in patients can be recapitulated in a dish within a few
weeks. Through all three of these examples, we will also explore newly generated mysteries that
can again be elucidated in the future through the application of physical principles.
Cells sense and interact with their environment using chemical and physical signals including cell-matrix and cell-cell contacts. These signals often control the global and local shapes of cells by modulating the cytoskeletal structure, but can the local shape alone provide functionally relevant information? We hypothesize that physiologically relevant shapes can encode information needed to maintain the cell in a differentiated state. This conjecture raises two follow-on questions: (i) how is the information stored in cell shape retrieved; and (ii) how does this information contribute to cellular phenotype? Theoretical analyses, based on reaction-diffusion system and optimal control theory, indicate that information from cell shape can be resolved from physical signals and uniquely retrieved by adopting shapes with distinct surface-to-volume relationships. We used microfabricated 3-D biomimetic chips to validate the predictions from the theoretical analyses. We constructed single-cell patterns representing simplified versions of the in vivo morphology of two cell types, kidney podocytes, and smooth muscle cells. In both types, cells in the shapes showed marked phenotypic changes, as measured by expression levels of physiologically important proteins and localization of these proteins to the appropriate subcellular compartment. Using differential proteomics and functional ablation assays, we found that β3 integrin and its binding partners from the ezrin-radixin-moesin (ERM) family are involved in the transduction of shape signals. These observations indicate that physiological cell shape, including local specialization, embodies information obtained during the development, which is utilized to maintain the cell in the differentiated state.
About the speaker: Amit Ron received the M.Sc. (2008) and Ph.D. (2012) degrees in Biomedical and Electrical Engineering respectively from Tel Aviv University. Currently he is a postdoctoral fellow in the Department of Mechanical Engineering and the Center for Mechanical Biology at Columbia University. His main areas of interest include cellular mechanobiology and biophysics and bioengineering of the cellular microenvironment.
Tracking individual proteins on the surface of live mammalian cells reveals complex dynamics involving anomalous diffusion and clustering into nanoscale domains. Theoretical models indicate that anomalous diffusion can be caused by vastly different processes. By performing time series and ensemble analysis of extensive single-molecule tracking in combination with stochastic modeling, we show that most trajectories violate the ergodic hypothesis, one of the cornerstones of statistical physics. In particular, ergodicity breaking manifests as substantial differences between the time-averaged and the ensemble-averaged observables. We find that ergodicity breaking is caused by the transient localization of membrane proteins within nanoscale domains, such as endocytic pits and protein clusters. Furthermore, using a combination of dynamic super-resolution imaging and single-particle tracking, we observe that the actin cytoskeleton introduces barriers leading to the compartmentalization of the plasma membrane and that proteins are transiently confined within actin-delimited domains. Our results show that the actin-induced compartments are scale free and that the actin cortex forms a self-similar fractal structure.
Cells exhibit rich repertoire of dynamical behaviors, which depend on cell phenotype and microenvironment. The collective dynamics of cells has gathered increasing attention inspiring experimental and theoretical studies in an attempt to unravel the underlying physical principles. Using in vitro experiments, we show that very different cell types self-organize in a bi-dimensional nematic phase with characteristic ±1/2 nematic defects. I will present examples of (1) spontaneous symmetry breaking and emergence of shear flows of spindle-shaped cells when confined in adhesive stripes; (2) existence of nematic turbulent phase driven by cell activity in epithelial cell monolayers; and (3) conditions for appearance of activity driven turbulence in confined environment. I will discuss physical mechanisms of these out of equilibrium phenomena and their effect on tissue organization and biological function.
Gene activity is mediated by the specificity of binding interactions between special proteins, called transcription factors, and short regulatory sequences on the DNA, where different protein species preferentially bind different DNA targets. Limited interaction specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to spurious interactions or remains erroneously inactive. Since each protein can potentially interact with numerous DNA targets, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyze the effects of global crosstalk on gene regulation, using statistical mechanics. We find that crosstalk in regulatory interactions puts fundamental limits on the reliability of gene regulation that are not easily mitigated by tuning proteins concentrations or by complex regulatory schemes proposed in the literature. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.
Copper's ability to accept and donate single electrons makes it an ideal redox cofactor, and thus one of the most essential metal ions to the survival of the cell. However, copper ions are also involved in the Fenton reaction and hence capable of driving the generation of deleterious hydroxyl radicals, which are deleterious to the cell. Moreover, since Cu(II) is at the top of the Irving-Williams series, it can compete with other metals in metalloproteins. Hence, both prokaryotic systems as well as eukaryotic system have developed a considerable regulation mechanism to maintain negligible copper concentration, in the femtomolar concentration. E.coli cells, in common with the vast majority of bacterial cells, require copper for several important enzymes such as ubiquinole oxidases, Cu,Zn-superoxide dismutases, or cytochrome c oxidase. However, as was mentioned above, copper can be deleterious, making protective mechanisms necessary. Understanding this regulation mechanism in bacteria, is tremendously important from two specific reasons: one over 70% of the putative cuproproteins identified in prokaryotes have homologs in eukaryotes, and thus resolving the copper cycle in prokaryotic systems will also shed light on the copper cycle in eukaryotic systems. Second, copper has been used throughout much of the human civilization as an antimicrobial agent. Hence, understanding in detail the copper resistance mechanism in bacteria, is significantly important for understanding the microorganisms' degree of survival in the mammalian cell. In this talk we will shed some light on two important copper regulation systems in E.coli: the copper periplasmic efflux system, CusCFBA, and the Cu(I) metal sensor, gene expression regulation system, CueR. Using Electron Paramagnetic Resonance (EPR) spectroscopy, together with biochemical experiments and computational methods we will show the essentiality of methionine and lysine residues to the interaction between two proteins in the CusCFBA system. We will also present a structural model for the CueR-Cu(I)-DNA complex, shedding light on the transcription mechanism of the CueR protein. This work will show the importance of EPR as a biophysical tool to study cellular metal ion transfer pathways.
The motion of molecules across channels and pores is critically important for understanding mechanisms of many biological, chemical, physical and industrial processes. Here we investigate the role of different types of interactions in the channel-facilitated molecular transport by analyzing exactly solvable discrete-state stochastic models. According to this approach, the channel transport is a non-equilibrium process that can be viewed as a set of coupled quasi-chemical transitions between discrete spatially separated states. It allows us to obtain a full dynamic description of the translocation via the pore, clarifying many aspects of these complex processes. We show that the strength and the spatial distribution of the molecule/channel interactions can strongly modify the particle fluxes through the system. Our analysis indicates that the most optimal transport is achieved when the binding sites are near the entrance or near the exit of the pore, depending on the sign of interaction potentials. These observations agree with single-molecule experiments on translocation of polypeptides through biological channels. We also suggest that intermolecular interactions during the channel transport might also significantly influence the translocation dynamics. Our explicit calculations show that the increase in the flux can be observed for some optimal interaction strengths. The relevance of these results for biological systems is discussed. The physical-chemical mechanisms of these phenomena are analyzed from the microscopic point of view.
We will overview the utilization of single molecule and superresolution imaging tools to the study of molecular machines, interactions, and circuits in-vitro, in live cells and in small organisms.
The ability to manipulate and direct neuronal growth has great importance in the field of tissue engineering, both for neuronal repair and potential medical devices. Since mammalian neurons have limited regeneration abilities creating scaffolds for enhanced regeneration is beneficial. Moreover, guiding and directing neuronal outgrowth can enhance neuronal repair and recovery. Previous studies, including in our lab examined nanoparticles for enhancing neuronal regeneration. Here, we designed a 3D collagen gel-scaffold for neuronal cultures. We further modulated the gel system to create alignment of collagen fibers for directing neuronal growth using nanoparticles.
A collagen hydrogel system was chosen as a 3D ECM analog to best mimic the natural environment of cells. The gels mechanical properties were examined and tuned to achieve desired properties similar to nervous tissue. We compared the neuronal growth in 3D to a 2D model and showed that neurons grown in 3D collagen gels develop significantly longer dendritic trees and neurites. To manipulate neuronal growth we developed a method to align collagen fiber matrix by incorporating magnetic nanoparticles within gels, and exposing the gel to an external magnetic field We showed fiber directionality by analysis of light microscope images via Fast Fourier transform (FFT) and by SEM imaging. We grew neurons in aligned gels for 7 days and followed regeneration process of single cells for up to 7 days. For this purpose we used both primary leech (Hirudo medicinale) neuronal culture, and PC12 as a mammalian analog. Using a designed Matlab script we evaluated cellular direction of growth and compared it to collagen matrix orientation. We further measured morphometric parameters of neuronal growth. Using aligned gels we've elongated and directed neuronal growth coinciding with collagen matrix orientation. We also found aligned gels initiate neurite growth patterns similar to growth in 3D control gel.
The assimilation of carbon dioxide into organic material also known as carbon fixation is largest biosynthetic processes in the biosphere. While carbon fixation pathways offer a renewable alternative for biofuels and numerous chemicals, integrating a non-native carbon fixation pathway into a microbial host is still a standing challenge. I will present a metabolic engineering framework, which enforces a heterotrophic to be dependent upon carbon fixation even in the presence of a carbon source. By rewiring the native metabolic network of E.coli, expressing Calvin-Benson cycle components and selecting on specific growth conditions we engineered strains in which non-native RuBisCO dependent carbon fixation is essential for growth. Such selection systems are beneficial both as a direct selection tools for carbon fixation enzymes, as well as a metabolic engineering tool for the integration of non-native pathways. We analyze the metabolic and physiological effects of such RuBisCO dependent growth modes and explore the feasibility for expressing a fully functional non-native Calvin-Benson cycle using a directed evolution approach. Beyond practical implications for the design, construction and testing of synthetic carbon fixation pathways, we believe such an approach can be implemented for a variety of other metabolic pathways.
Traumatic brain injury (TBI) affects 1.7 million people annually in the United States and is now commonly acknowledged as a risk factor for neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and amyotrophic lateral sclerosis. Yet there is a lack of understanding of the disease mechanisms underlying TBI and no effective therapeutic strategies. To date, there are no U.S. Food and Drug Administration (FDA)-approved biomarkers for the diagnosis or prognosis of TBI, and the molecular mechanisms of TBI response remain poorly understood. This lack of understanding reflects the complex, multifactorial nature of cellular responses to TBI and the need for better models for TBI study. By using our novel in vitro system for studying TBI we studied what is the cell response to mechanical injury, this includes proteomics, electrophysiology and metabolic changes. Our data enabled us to identify the main pathways affected by TBI, the time frame by which these changes occur and to identify 8 potential drugs to treat TBI. Furthermore, due to the importance of new more “in vivo like” TBI models, we developed a unique in vitro tri-synaptic pathway which incorporates 3 different brain regions and enabled us to identify how TBI affect each brain region (prefrontal cortex, amygdala, hippocampus) independently and collectively. Interestingly we found that in vitro cells, originated from different brain regions show significant differences before and after TBI and stress out the significant for implementation of cells from different brain regions in in vitro models. This work demonstrates how new tools for brain research contributes to more understanding of the mechanisms underline TBI and gives new avenues to identify and test therapeutics.
An essential and highly regulated step in gene expression is transcription initiation. After promoter binding and DNA unwinding (‘bubble opening’) and in the presence of nucleoside triphosphates (NTPs), the RNA polymerase (RNAP)-promoter initial transcribing complex (RPitc) engages in ‘abortive initiation’, a process in which RNAP cycles between synthesis and release of short RNA transcripts. In abortive initiation, RPitc is believed to undergo a sequence of transitions between different initiation sub-states. The kinetics of the production of a full RNA transcript starting at a late initiation sub-state is expected to be similar or faster than the kinetics measured from an earlier initiation sub-state. To test this hypothesis, we developed a novel in vitro single-run quenched kinetics transcription assay based on the detection and quantification of run-off transcripts. Using this assay and corroborating it with gel-based and magnetic tweezer assays, testing two different promoters, we surprisingly found that run-off transcription kinetics starting from late initiation sub-states is slower than kinetics starting from earlier initiation sub-states. When the same kinetic measurements were performed in the presence of the transcription elongation factor GreA, the kinetics starting from a late initiation sub-state was accelerated.
Experimental results suggest that as a function of shortage in NTPs RPitc can enter an off-pathway state in which the nascent RNA is in a backtracked, paused position, awaiting incorporation of the missing NTP. Our findings suggest that pausing at distinct stages of transcription initiation could regulate gene expression under stressed conditions.
We have been developing targetable voltage sensing inorganic nanoparticles (vsNPs) that are designed to self-insert into the cell membrane and optically record, non-invasively, action potential on the single-particle level, at multi-sites and in a large field-of-view. Using the first generation of vsNPs, we have measured large quantum confined Stark effect (QCSE) shifts as function of voltage (in-vitro, using electrodes). We have recently developed functionalization and membrane insertion schemes for these probes, and have demonstrated, for the first time, membrane voltage sensing with them.
The copy number of any protein varies among cells even in a genetically homogenous
population. This variation causes changes in the shape, structure and behavior of individuals
within the population. Characterizing and understanding this variation and its sources is a
fundamental problem in biophysics. In my talk I will discuss our recent results which show that
the protein distribution measured under a broad range of biological realizations exhibit universal
features that stem from the cellular dynamics that control protein expression. I will also show
that the essential features of the universal distribution can be captured by a reduced
characterization of the entire complexity of intra-generation processes using a single stochastic
variable, namely the rate of exponential protein accumulation.
Patients with retinal degeneration lose sight due to gradual demise of photoreceptors. Electrical stimulation of the surviving retinal neurons provides an alternative route for delivery of visual information. Subretinal photovoltaic arrays with hexagonal 70mm pixels are used to convert pulsed light into bi-phasic pulses of current to stimulate the nearby inner retinal neurons. Bright pulsed illumination is provided by image projection from video goggles and avoids photophobic effects by using near-infrared (NIR, 880-915nm) light. Retinal network mediated responses of the ganglion cells (RGCs) are modulated by pulse width (1-20ms) and irradiance (0.5-10 mW/mm2). Stimulation threshold of 0.3 mW/mm2 with 10 ms pulses is more than two orders of magnitude below the ocular safety limit. Similarly to normal vision, retinal response to prosthetic stimulation exhibits flicker fusion at high frequencies, adaptation to static images and non-linear spatial summation. Spatial resolution was assessed in-vitro and in-vivo using stroboscopic illumination (20-40Hz) of alternating gratings with variable stripe width. RGCs responded to grating stripes down to 67mm using photovoltaic stimulation in degenerate rat retina, and 28mm with visible light in normal retina. In-vivo, visual acuity in normally-sighted controls was 29mm/stripe, vs. 64mm/stripe in rats with subretinal photovoltaic arrays, matching the spacing of the adjacent pixel rows in the array, and corresponding to 20/250 acuity in human eye. Extrapolating from the observed stimulation thresholds, pixel size can be further reduced by a factor of two, thereby supporting even higher spatial resolution. Ease of implantation and tiling of these wireless arrays to cover a large visual field, combined with their high resolution opens the door to highly functional restoration of sight.
Interactions between cells and their surrounding matrix play defining roles in biological processes. The biological cell can be thought of as a 'living rheometer' continuously probing the mechanical properties of its environment by exerting contractile forces through the actomyosin machinery. It is clear by now that substrate mechanical properties strongly influence cell behavior. Furthermore, recent lines of evidence indicate that cells can respond to mechanical deformations generated by neighboring cells. The basis for this phenomenon and the role of mechanical communication between cells through the matrix is unknown. In my talk, I will describe the progress made in our lab focusing on the role of cell mechanosensing in cardiac cell synchronized beating. In addition I will describe our progress towards design of protein-engineered biomaterials that promote mechanical coupling between cells.
Matrix elasticity and thickness differ widely between tissues, but pathways by which microenvironment mechanics impact cell and nuclear phenotypes are largely unknown. Mesenchymal stem cells (MSCs) exhibit mechanosensitive differentiation as they spread and deform their nuclei more on thin-and-soft or stiff matrices compared to soft matrices that suppress contractility. A tactile length scale of microns is determined based on morphologies and transcript profiles that revealed a subset of nuclear envelope genes which are not only mechanosensitive in MSCs but also vary across tissues. Lamin-A is a key gene that increases together in tissue with myosin-II's that generate cell tension, and both lamin-A and nuclear deformation in MSCs increase with matrix thin-ness and stiffness coupled to myosin-II activity. In turn, lamin-A levels also regulate myosin-II in a broad transcriptional program that stresses the nucleus, with nuclear mechanosensitivity depending upstream on tension-suppressed phosphorylation/cleavage of lamin-A. Matrix stiffness thus reveals how deeply cells feel inside and out.
Retinal degenerative diseases, such as Retinitis Pigmentosa (RP) and Age related Macular Degeneration (AMD), lead to loss of sight due to degeneration of photoreceptors, yet the inner retinal neurons which process the visual signals and relay them to the brain are relatively well preserved. Patterned electrical stimulation of the inner retinal neurons can elicit patterned visual perception, thereby restoring sight to some degree, as was demonstrated in recent clinical trials. However, current RF-powered implants require bulky electronics and trans-scleral cables, making implantation very complex and prone to failures. Even more importantly, low visual acuity achieved with the current implants limits their applicability to very small fraction of patients.
We have developed a wireless photovoltaic retinal prosthesis, in which camera-captured images are projected onto the retina using pulsed near-IR light. Each pixel in the subretinal implant directly converts pulsed light into local electric current to stimulate the nearby inner retinal neurons. Implants with pixel sizes of 280, 140 and 70µm were successfully implanted in the subretinal space of wild type and degenerate rats, and elicited robust cortical responses (eVEP) upon stimulation with NIR light. Amplitude of the eVEP increased with peak irradiance and pulse duration, and decreased with frequency in the range of 2-20Hz, similar to the visible light response.
Modular design of the arrays allows scalability to a large number of pixels, and combined with the ease of implantation, offers a promising approach to restoration of sight in patients blinded by retinal degenerative diseases.
Activation of the retinal bipolar cells by the implant makes our model a unique tool for studying retinal circuitry by comparing the response to stimuli elicited by the subretinal implant to those naturally elicited by visible light. I will discuss our novel approach to quantitative assessment of the visual acuity provided by the implant, as well as some unique aspects of prosthetic vision, such as stroboscopic stimulation. The theoretical and practical limits of visual acuity will be discussed along with future directions for restoration of sight to the blind.
I will also discuss another example for application of electric field on cells – namely, irreversible electroporation, a novel approach for non-thermal cell ablation. We have recently reported that short pulses of high electric field can cause tumor ablation in uveal melanoma, the most common intraocular malignancy in adults.
המארח: פרופ' יובל גרעיני
לתיאום פגישות נא לפנות אליו
Biological environments are complex and dynamic. Numerous entities constantly interact, diffuse and form structural motifs. Due to their complexity, such systems are commonly studied through the emergent motion of key factors in the system. A canonical example can be found in the cellular nucleus, as accurate expression of various genes demands that DNA interact with functional molecules, undergo packaging modifications and maintain a flexible yet organized structure. Thus, we track the temporal motion of chromatin loci (DNA with its accompanying proteins) across several orders of time. This measurement is performed through single cell in vivo fluorescent microscopy, i.e. a minimally invasive technique allowing us to capture the natural mechanisms in the system.
Once trajectories of biological entities are gathered, it is possible to dive into the stochastic data in order to extract the relevant mathematical and physical picture for the system. Through the implementation of advanced mathematical testing, we have shown that the anomalous diffusion of chromatin can be described as fractional Brownian motion – a framework that can also capture the dynamics of dense viscoelastic media or polymer melts. However, by modifying the expression levels of key nuclear proteins, such as Lamin A, the dynamics of chromatin can be completely transformed. A 'normal' diffusion process emerges, in contradiction to physical theories of polymer dynamics and our current understanding of the nucleus. In another study vector, long range inter locus interactions are found. Surprisingly, these interactions are not isotropic, and reveal three spatial regimes of relative chromatin motion.
These observations lead to a rich and complex picture of chromatin motion that we are only starting to unravel. They serve as an example of the power of dynamic measurements coupled to stochastic analysis in exploring biological systems.
Many experiments have shown that the substrates upon which cells are placed or the extracellular matrix (ECM) in which cells reside in 3D can regulate cellular structure and function. From fate “decision making” of mesenchymal stem cells to rigidity driven durotaxis, the contractile, active acto-myosin network plays a major role in the mechanosensing and transduction of elastic signals, which in turn depends on the elastic properties of the substrate or ECM.
Previous theoretical models of elastic interactions assumed that cells exert constant force or strain when interacting with other cells and that the energy cost of deformation of the substrate or matrix in the presence of other cells lies at the origin of elastically mediated interactions among cells. Similar ideas are used to predict cytoskeletal orientation and registry as a function of substrate rigidity as observed in experiments. Here, we present a new suggestion for why cells “care” about the elastic deformations of the substrate or matrix induced by their neighbors. Cells that maintain a homeostasis that governs the local stress or strain in their vicinity can actively adjust their contractility to complement strains or stresses induced by other cells or other mechanical perturbations. This active response can be modeled as an “ideal” induced force that cancels out the external fields so that stress or strain homeostasis in the cell neighborhood is maintained. We propose that by actively adjusting its force to complement those of its neighbors or external perturbations and thereby maintain homeostasis, the cell senses its environment and interacts with the neighboring cells. In particular, this predicts that even circularly (spherically) symmetric cells on isotropic substrates (in isotropic ECM) interact elastically, in contrast to the vanishing interactions for the case of “dead inclusions” under these situations. Furthermore, it is reasonable to assume that cells tend to minimize the energy cost associated with these induced forces by reorienting or otherwise modifying their cytoskeletal network and adhesions. Cells also “care” about the qualitative nature of the matrix or substrate elasticity as we show theoretically by contrasting cell deformations and interactions in linear vs. non-linear, shear-stiffening elastic networks. The latter are characteristic of biopolymers such as actin, collagen, fibrin and fibronectin. For a cell modeled as an isotropically contractile sphere, the non-linearity leads to a highly amplified far-field strain. This effect also amplifies the interactions between two such cells in a non-linear elastic medium and can lead to a significantly larger interactions. The role of non-linear substrate elasticity has been the focus on recent experiments that show anomalously long-range cellular correlations in such systems.
Single-molecule methods are providing new and powerful tools for exploring proteins folding, DNA conformations and protein-DNA interactions. These processes are important in cellular activities, and their understanding requires to combine substantial interesting physical and biological considerations.
I will present a method we developed for measuring and characterizing individual protein-folding pathways and DNA-protein interactions based on tethered particle motion (TPM). Combining the TPM data with force and AFM measurements provides important insight on DNA-protein interactions and protein folding.
For decades, our basic notion of how proteins fold has been rooted in the Anfinsenian idea that sequence determines structure reversibly through the preference of a native state at thermodynamic equilibrium. In the present day, advances in our understanding of biochemistry and cell biology have suggested such a view of folding may apply as an exception more than a rule: many proteins require help from ATPase chaperones in order to fold, and modulate their folding state substantially depending on their available interaction partners. Proteins also frequently become irreversibly trapped in non-functional aggregates, and the cell must deploy an elaborate quality control machinery to prevent aggregation from getting out of hand. In all of these cases, it is necessary to think beyond the physics of thermal equilibrium in order to make sense of folding in the cell. This talk will consist of several vignettes about chaperones, aggregation, and cellular protein quality control where nonequilibrium ideas about the folding and transport of proteins yield insight into experimental results both in vitro and in vivo.
Nanopores can be used to detect and characterize unlabeled biomolecules, and widely believed to be a main future platform for direct, single molecule sequencing of DNA, RNA and perhaps proteins. Controlling and tuning the translocation speed of biomolecules through nanopores remains to be a main challenge for this technology. We have recently shown1 that low-power visible light focused at the nano-pore can be used to control its surface charge and thus influence the translocation dynamics of DNA and proteins, by creating a counter electro-osmotic flow in the pore. The optoelectronic effect is analogically tunable on sub-millisecond time scales by simply adjusting the photon density. Specifically, a few mW of green light reduces translocation speed of double-stranded DNA by more than an order of magnitude, by more than two orders of magnitude for small globular proteins such as ubiquitin.
Nanpores can also be used to detect and map DNA and RNA-protein interactions. I will discuss single molecule nanopore measurements of Poly Adenine Binding Proteins (PABPs) associated with translation regulation with poly-Adenine RNAs2, as well as the interactions of transcription factors with genomic DNA.
- 1. Di Fiori, N., Squires, A., Bar, D., Gilboa, T., Moustakas, T. and A. Meller. Optoelectronic control of surface charge andtranslocation dynamics in solid-state nanopores. Nature Nanotechnol 8, 946–951 (2013).
- 2. Lin, J., Fabian, M., Sonenberg, N. and A. Meller, Nanopore Detachment Kinetics of Poly(A) Binding Proteins from RNA Molecules Reveals the Critical Role of C-Terminus Interactions. Biophysical Journal 102, 1427–1434 (2012).
The ability of our immune system to recognize ever-evolving threats is critical to survival. Initial recognition of pathogens depends on generating a diverse repertoire of antibodies through recombination of gene segments. This naïve repertoire is dynamically modified as activated B cells undergo cycles of division, somatic hypermutation and affinity-dependent selection. This affinity maturation process produces expanded memory B cell clones expressing mutated antibodies with high-affinity for the pathogen. Analyzing the collection of receptors expressed by naïve and memory B cells offers insights into the infection history of individuals. It can teach us about fundamental immune processes, and reveal disregulation. The recent development of high-throughput sequencing brings exciting possibilities, allowing for large-scale characterization of antibody repertoires. However, the statistical methods and models to plan these high-throughput experiments and analyze their results are lacking. Hereby, I will present several new computational tools that were designed to address three crucial steps in lymphocyte receptor repertoire analysis: process raw data, quantify affinity dependent selection and build a targeting model for the observed mutation spectrum. Examples of the applicability of these tools will be demonstrated through the analysis of several studies involving next generation antibody sequencing datasets. I will share my view of the major obstacles that still need to be confronted before we can utilize lymphocyte receptor repertoire analysis for diagnosis and prognosis.
Adult tissue-specific stem cells are small populations of cells that reside in key locations within each tissue and are responsible for its maintenance and regeneration through carefully controlled proliferation and differentiation. In cancer, where the regeneration mechanism has been distorted, the tumors are maintained and regenerated by a small sub-population of cancer stem cells that are most likely responsible for relapse and metastasis. However, with contemporary technologies, it is challenging to locate and study the stem cells, which are a small minority.
In order to study the cellular composition of colon epithelial tissues and tumors we used a combination of flow cytometry and microfluidic single cell qPCR to measure the expression of up to 96 genes simultaneously in hundreds of individual cells. This provided us with a single cell genomic "dissection" of primary epithelial tissues and tumors from both human and mouse colon.
We find that human colon cancer tissues contain distinct cell populations whose transcriptional identities mirror those of the different cellular lineages of normal colon. However, some populations were consistently absent in colon tumors and xenografts, specifically, the population of differentiated mature enterocytes expressing the gene SLC26a3 (also known as DRA or "Down-Regulated in Adenoma"), which is a membrane protein responsible for Chloride reabsorption in the colon. In the mouse colon we find a novel sub-population of goblet cells in the crypt base that overexpress cKit, Dll1, Dll4 (Notch ligand), and epidermal growth factor (EGF). These crypt-base goblet cells are adjacent to Lgr5+ cells and provide several crucial factors for crypt homeostasis and Lgr5+ stem cell proliferation, similar to Paneth cells in the small intestine. Finally, we show that contrary to tissues and tumors, gene expression heterogeneity in cell lines originates mainly from cell size and cell cycle phase.
During the 20th century, the protein sequence-structure-function paradigm was uniformly accepted as a key concept in molecular cell-biology. The central dogma of structural biology is that the biological function of proteins is inherently encoded in their folded 3D structures. This idea, introduced in 1894 by Emil Fischer and known as the “lock-and-key” model, explained the high specificity of enzyme-substrate recognition and was validated over and over to create the basis of modern proteomics. Protein folding occurs mainly due to short-ranged specific interactions between amino-acids encoded in its sequence. This is the core reason why point mutations have a dramatic effect on protein conformation which in-turn significantly distorts protein-protein recognition.
The concept that a given amino-acid sequence will not form a 3D folded structure but still have biological functionality has developed only in the last ~15 years. The discovery rate and characterization of intrinsically disordered proteins has been increasing continually, becoming one of the fastest growing areas of proteomics. It is now estimated that over 50% of eukaryotic proteins contain large intrinsically disordered regions, involved in a wide range of cellular functions including transcription, translation, signalling and regulation of protein assembly. Structural flexibility and plasticity originating from the lack of an ordered structure suggest a major functional advantage for these proteins, enabling them to interact with a broad range of binding partners.
Utilizing experimental and computational progress in the field we are now able to explore dynamic and flexible biological materials that lack 3D order using small-angle X-ray scattering. In this talk I will present some of our recent experimental results aiming to address the fundamental relation between order and disorder in functional biological complexes.
In Förster Resonance Energy Transfer (FRET), the fluorescence of the acceptor fluorophore is a direct reporter of the energy transfer process. Several events that affect the fluorescence of the acceptor fluorophore are relative to the moment of the donor fluorophore excitation. One interesting event is the spatio-temporal dependency of FRET due to the different energy transfer rate constants for different donor-acceptor distances, in a situation where there is an equilibrium distance distribution and where distances might change due to fast fluctuations. We devised a method that harnesses pulsed donor-excitation laser and acceptor stimulated-emission-laser in order to get FRET-driven acceptor fluorescence decays, resulting out of spontaneous emission, not necessarily after the donor-excitation moment, but rather at any given moment after that. Using this methodology, we will show how we diminish the effects of direct-acceptor excitation from fluorescence decays. We will show how our method aids in reducing background from acceptor-driven FRET-FLIM (Fluorescence Lifetime Imaging) images. Finally we will show how we can achieve higher accuracy in finding the end-to-end distance distribution as well as diffusion coefficient out of PASE-FRET experiments. We hope to use the methodology in order to solve a long-lasting theoretical question – are unfolded proteins necessarily random?
Cells lack eyes to see and ears to hear but can physically feel into the depths their microenvironment by actively deforming their surroundings. To study how deeply cells feel, adult stem cells, as prototypical yet particularly sensitive adhesive cells, were cultured on collagen-coated gel-based microfilms of controlled elasticity and thickness. Cells spread and nuclei stretched significantly less on soft, marrow-like gels, as compared with soft but thin or bone-like stiff films. As indicated by the transition from small to large spreading, the tactile length scale for mechanosensitivty was ~10 microns. Novel physicochemical transcriptional analysis of titrated DNA microarray binding curves combined with protein profiling revealed a set of four most malleable nuclear envelope genes across tissues and in a dish. Overexpression and siRNA knockdown of nucleostructural lamina components induced ‘stiff’ versus ‘soft’ phenotypes while maintaining proportionality with myosin-facilitated cellular contractility. Rates of fluorescence recovery after photobleaching of phospho-mimetic laminA mutants were indicative of stiffness-dependent nuclear remodeling during early stages of matrix engagement. Nuclear tension was shown to suppress lamin phosphorylation while nucleus rounding induced degradation. Matrix-directed nuclear remodeling is important for maintaining normal functions within physically-diverse cellular compartments by nuclear mechanotranduction.
A fundamental question in neuroscience is how multiple synaptic connections develop into neural circuits that generate behavior and adapt to changing external inputs. Indeed, deficiencies in synaptic connections are associated with sleep disorders and psychomotor retardation. Which circuits are deficient and what is the molecular mechanism of these diseases remains mostly unknown, since the circuit wiring is hidden within the opaque mammalian brain. The high throughput transparent zebrafish model allows to non-invasively determine patterns of structural synaptic plasticity and to study in live vertebrate the genetic basis of brain disorders. Importantly, it provides a system to visualize longitudinally structural changes of multiple brain circuits in the live vertebrate at single synapse resolution. Using genetic manipulation, two-photon imaging in live fish and video-tracking of behavior, we determine functional interactions between genes, structural synaptic plasticity, sleep disorders and psychomotor retardation.
We have recently demonstrated the paradoxical potentiation of antibacterial PDT activity of methylene blue (MB) by azide, the known singlet oxygen quencher and scavenger of hydroxyl radicals. Interestingly, azide allowed MB-PDT bacterial killing even in the absence of oxygen. In a most recent study, we have observed that thiocyanate, another pseudohalide, which interacts efficiently with hydroxyl radicals, also enhanced the methylene blue-mediated PDT efficacy against Gram-positive and Gram-negative bacteria. Antimicrobial PDT efficiency is of considerable importance, particularly in view of the increasing pervasiveness of antibiotic resistant bacteria. This paper is concerned with the photochemical mechanisms of key processes that might be responsible for the potentiating effects of the pseudohalides.. The MB-photosensitized formation and decay of singlet oxygen was measured by time-resolved phosphorescence at 1270 nm. The formation of superoxide anion, azide and sulfur trioxide radicals was monitored by electron paramagnetic resonance (EPR)-spin trapping using DMPO as a spin trap. Progress of photosensitized oxidation reactions was monitored by EPR-oximetry. In the presence of high concentration of azide, the photoexcited MB predominantly generated relatively long-lived azidyl radical responsible for oxidative damage. On the other hand, singlet oxygen, generated in the presence of high concentration of thiocyanate, converted this pseudohalide to the oxidizing sulfur trioxide radical. Our study suggests that in the presence of pseudohalides, the MB-photosensitized killing of bacteria is mediated by mildly oxidizing radicals formed directly by photosensitized electron transfer or indirectly via the interaction with singlet oxygen.
By measuring the dynamics of genomic entities in the nucleus of a living cell,
we identified a mechanism that maintains its order.
In normal cells, all the sites in the genome exhibit anomalous diffusion with a
power law of ~0.4. The diffusion was characterized through different tests and
was found to belong to the family of fractional Brownian motion anomalous
Based on that, we rationalized that the source of the visco-elasticity is a protein
that can temporarily bind chromatin. We identified the source protein and
showed that a phase transition from viscoelastic to viscous diffusion occurs
when its expression is inhibited. This was verified by other dynamic
It is quite intuitive that disorder causes things to slow down, but we will see
that different kinds of disorder exhibit different characteristics.
We start by discussing the most general definition of slow dynamics, namely
subdiffusion, where the mean squared displacement grows sublinearly with
time. In this context one analyzes the dynamics of an individual object slowed
down by its surrounding (static) environment. Different physical realities may
lead to subdiffusive behavior. The objective will be to determine
the relevant underlying physical reality from experimental data of singe
trajectories. To this end we present a set of tools, focusing on a test for
discerning between ergodic models. We will also consider the case of
Next we discuss glasses, physical systems exhibiting collective slow
processes, which are due to the interaction with a disordered and dynamic
environment. Glassy behavior is ubiquitous and universal, exhibited also in
protein dynamics. We will specifically discuss the electron glass, presenting a
model that successfully explains memory effects demonstrated by 'two-dip'
Faithful devotion to Moore’s Law has led to the scaling of transistor features to only a few tens of nanometers – about the size of large biomolecules. This has created new opportunities where the tools of micro- and nanofabrication can be used to address questions in biology and medicine, and, conversely, where biomaterials may play a role in a future nanoelectronics technology. We are presently developing new strategies which combine traditional lithographic patterning with new surface chemistries and biomolecular assembly to control the placement of individual molecules and functional nanostructures with high precision over macroscopic dimensions. These strategies are broadly applicable, and we are exploring their use in both biological and nanoengineering studies. In our biological studies, we create biomimetic surfaces which simulate specific aspects of the extracellular environment, such as matrix rigidity and geometry. By monitoring cellular response to variations of these factors, we can gain insight into their role in certain basic cellular functions, such as adhesion and spreading, as well as immune response in T-lymphocytes. Using a similar approach, we are able to study DNA-protein interactions at the single-molecule level in a massively parallel fashion. On the nanoengineering front, we have been exploring the combination of molecular-scale lithographic patterning and DNA-mediated assembly as a means toward integrating electronically and optically functional nanostructures. Such an approach, which combines precision engineering with selective biomolecular recognition, may lead to the development of complex new systems that exploit the best properties of natural and engineered materials.
Visualization of the three-dimensional (3-D) organization of a eukaryotic cell, with its dynamic organelles, cytoskeletal structures, and distinct protein complexes in their native context, requires a non-invasive imaging technique of high resolution combined with a method of arresting cellular elements in their momentary state of function. Vitrification of cells ensures close-to-life preservation of the molecular architecture of actin networks and organelles. With the advent of automated electron tomography it has becomes possible to obtain tomographic data sets of frozen hydrated specimen. By electron tomography 3-D information from large pleomorphous structures, as cell organelles or whole cells can be retrieved with ‘molecular resolution’. At that resolution it becomes possible to detect and identify specific macromolecular complexes on the basis of their structural signature.
Here we employed cryo-electron tomography to eukaryotic cells grown directly on an EM grid. Combining fluorescent microscopy we can navigate within cells and acquire meaningful tomographic reconstructions. Thus, we have analysed unlabelled cellular structures within intact eukaryotic, such as the nuclear periphery and the cell adhesion machinery.
Much like the bones in our bodies, the cytoskeleton consisting of filamentous proteins
largely determines the mechanical response and stability of cells. Unlike passive materials,
however, living cells are kept far out of equilibrium by metabolic processes and energyconsuming
molecular motors that generate forces to drive the machinery behind various
cellular processes. We describe recent advances both in theoretical modeling of such
networks, as well as experiments on reconstituted in vitro acto-myosin networks and living
cells. We show how such internal force generation by motors can lead to dramatic
mechanical effects, including strong mechanical stiffening. Furthermore, stochastic motor
activity can give rise to diffusive-like motion in elastic networks. We also show how the
collective activity of myosin motors generically organizes actin filaments into contractile
structures, in a multistage non-equilibrium process. This can be understood in terms of the
highly asymmetric load response of actin filaments: they can support large tensions, but
they buckle easily under piconewton compressive loads.
Manmade electronics and living systems are foreign to each other in all aspects. They are constructed from dissimilar materials using different strategies, employ different charge carriers, and use distinctively different logics for their computation. The fusing of these two fields therefore poses major conceptual and practical challenges but at the same time holds a great promise to both electronics and healthcare. Learning a lesson from biology where functional interfaces are realized through mutual recognition of two molecules we propose and demonstrate a generic bio-electronic synapse comprising a manmade device having two states and engineered T-cells expressing receptors that bind the electronic device exclusively in its "on" state. Application of -0.6V to the device sets it to its "off" state where the cells remain unbound and inactivated. Subsequent application of +0.6V to the device sets it to its "on" state where cells recognize it and as a result trigger their immune response. The talk will cover conceptual and practical issues associated with the implementation of this first link between electronics and biology as well as details of the recognition mechanism.
While x-ray crystallography and NMR approaches have determined many protein structures yielding great insight into the behavior of proteins in solution, there are no solved structures of proteins interacting with a solid surface. Yet, protein interactions with solid surfaces are critical for formation of hard tissue such as bone or shell, and the design of biomaterials or nanobiotechnology components will require engineering of protein interactions with surfaces. We have used computational protein structure prediction and design approaches to investigate and control the behavior of proteins on solid surfaces. In this talk, I will briefly review our predictions of the structure of statherin on hydroxyapatite incorporating solid-state NMR measurements, and then I will discuss recent efforts to affect calcite growth by the addition of computationally designed peptides. Mutant proteins are compared both by computational analysis and by experimental explorations of the resulting mineral structure by SEM and SAED. Energetic determinants of peptide interactions in silico largely correspond to morphological observations in vitro, but significant work remains to be able to create custom materials through computationally designed proteins.
Hairy nanopores are narrow channels with polymers grafted to the walls, that can act as selective molecular sieves. They can be made by end-grafting of synthetic polymers, disordered proteins or DNA molecules to the inner walls of pores made of thin SiN or gold slabs. The nuclear pore complex (NPC) that controls the nucleo-cytoplasmic traffic in eukaryotic cells is another example of a hairy pore in which the selection is done by a large number of nucleoporins (FG nups) that fill the inner space of the NPC. Using molecular mean-field theory methods we study the effects of geometry, hydrophobicity and electrostatics on the morphology of hairy nanochannels and apply this methodology to the modeling of NPC of yeast.
In this talk, I shall discuss the fractal characteristics of natively folded proteins and their relation to protein dynamics and function. A universal equation of state, describing the relation between the spectral and fractal dimensions of a protein and the number of amino acids, will be shown. Using structural data from the protein data bank of about 5,000 proteins, and the Gaussian network model, I shall demonstrate that the equation of state is well obeyed. Various dynamical quantities will be shown to evolve anomalously. The effect of the hydrodynamic interaction between amino acids will be also elucidated. Finally, I will discuss the dynamic structure factor S(k,t) of proteins at large wavenumbers k, that are sensitive to the protein internal dynamics, and demonstrate its stretched exponential decay.