Efficient unfolding pattern recognition in single molecule force spectroscopy data

BackgroundSingle-molecule force spectroscopy (SMFS) is a technique that measures the force necessary to unfold a protein. SMFS experiments generate Force-Distance (F-D) curves. A statistical analysis of a set of F-D curves reveals different unfolding pathways. Information on protein structure, conformation, functional states, and inter- and intra-molecular interactions can be derived.ResultsIn the present work, we propose a pattern recognition algorithm and apply our algorithm to datasets from SMFS experiments on the membrane protein bacterioRhodopsin (bR). We discuss the unfolding pathways found in bR, which are characterised by main peaks and side peaks. A main peak is the result of the pairwise unfolding of the transmembrane helices. In contrast, a side peak is an unfolding event in the alpha-helix or other secondary structural element. The algorithm is capable of detecting side peaks along with main peaks.Therefore, we can detect the individual unfolding pathway as the sequence of events labeled with their occurrences and co-occurrences special to bR\u27s unfolding pathway. We find that side peaks do not co-occur with one another in curves as frequently as main peaks do, which may imply a synergistic effect occurring between helices. While main peaks co-occur as pairs in at least 50% of curves, the side peaks co-occur with one another in less than 10% of curves. Moreover, the algorithm runtime scales well as the dataset size increases.ConclusionsOur algorithm satisfies the requirements of an automated methodology that combines high accuracy with efficiency in analyzing SMFS datasets. The algorithm tackles the force spectroscopy analysis bottleneck leading to more consistent and reproducible results

Conformation-regulated mechanosensory control via titin domains in cardiac muscle

The giant filamentous protein titin is ideally positioned in the muscle sarcomere to sense mechanical stimuli and transform them into biochemical signals, such as those triggering cardiac hypertrophy. In this review, we ponder the evidence for signaling hotspots along the titin filament involved in mechanosensory control mechanisms. On the way, we distinguish between stress and strain as triggers of mechanical signaling events at the cardiac sarcomere. Whereas the Z-disk and M-band regions of titin may be prominently involved in sensing mechanical stress, signaling hotspots within the elastic I-band titin segment may respond primarily to mechanical strain. Common to both stress and strain sensor elements is their regulation by conformational changes in protein domains

Genetics of Mechanosensation in the Heart

Mechanosensation (the ultimate conversion of a mechanical stimulus into a biochemical signal) as well as mechanotransduction (transmission of mechanically induced signals) belong to the most fundamental processes in biology. These effects, because of their dynamic nature, are particularly important for the cardiovascular system. Therefore, it is not surprising that defects in cardiac mechanosensation, are associated with various types of cardiomyopathy and heart failure. However, our current knowledge regarding the genetic basis of impaired mechanosensation in the cardiovascular system is beginning to shed light on this subject and is at the centre of this brief review

Stretching Actin Filaments within Cells Enhances their Affinity for the Myosin II Motor Domain

To test the hypothesis that the myosin II motor domain (S1) preferentially binds to specific subsets of actin filaments in vivo, we expressed GFP-fused S1 with mutations that enhanced its affinity for actin in Dictyostelium cells. Consistent with the hypothesis, the GFP-S1 mutants were localized along specific portions of the cell cortex. Comparison with rhodamine-phalloidin staining in fixed cells demonstrated that the GFP-S1 probes preferentially bound to actin filaments in the rear cortex and cleavage furrows, where actin filaments are stretched by interaction with endogenous myosin II filaments. The GFP-S1 probes were similarly enriched in the cortex stretched passively by traction forces in the absence of myosin II or by external forces using a microcapillary. The preferential binding of GFP-S1 mutants to stretched actin filaments did not depend on cortexillin I or PTEN, two proteins previously implicated in the recruitment of myosin II filaments to stretched cortex. These results suggested that it is the stretching of the actin filaments itself that increases their affinity for the myosin II motor domain. In contrast, the GFP-fused myosin I motor domain did not localize to stretched actin filaments, which suggests different preferences of the motor domains for different structures of actin filaments play a role in distinct intracellular localizations of myosin I and II. We propose a scheme in which the stretching of actin filaments, the preferential binding of myosin II filaments to stretched actin filaments, and myosin II-dependent contraction form a positive feedback loop that contributes to the stabilization of cell polarity and to the responsiveness of the cells to external mechanical stimuli

Cytoskeletal protein kinases: titin and its relations in mechanosensing

Titin, the giant elastic ruler protein of striated muscle sarcomeres, contains a catalytic kinase domain related to a family of intrasterically regulated protein kinases. The most extensively studied member of this branch of the human kinome is the Ca2+–calmodulin (CaM)-regulated myosin light-chain kinases (MLCK). However, not all kinases of the MLCK branch are functional MLCKs, and about half lack a CaM binding site in their C-terminal autoinhibitory tail (AI). A unifying feature is their association with the cytoskeleton, mostly via actin and myosin filaments. Titin kinase, similar to its invertebrate analogue twitchin kinase and likely other “MLCKs”, is not Ca2+–calmodulin-activated. Recently, local protein unfolding of the C-terminal AI has emerged as a common mechanism in the activation of CaM kinases. Single-molecule data suggested that opening of the TK active site could also be achieved by mechanical unfolding of the AI. Mechanical modulation of catalytic activity might thus allow cytoskeletal signalling proteins to act as mechanosensors, creating feedback mechanisms between cytoskeletal tension and tension generation or cellular remodelling. Similar to other MLCK-like kinases like DRAK2 and DAPK1, TK is linked to protein turnover regulation via the autophagy/lysosomal system, suggesting the MLCK-like kinases have common functions beyond contraction regulation

Molecular Biomechanics: The Molecular Basis of How Forces Regulate Cellular Function

Recent advances have led to the emergence of molecular biomechanics as an essential element of modern biology. These efforts focus on theoretical and experimental studies of the mechanics of proteins and nucleic acids, and the understanding of the molecular mechanisms of stress transmission, mechanosensing and mechanotransduction in living cells. In particular, single-molecule biomechanics studies of proteins and DNA, and mechanochemical coupling in biomolecular motors have demonstrated the critical importance of molecular mechanics as a new frontier in bioengineering and life sciences. To stimulate a more systematic study of the basic issues in molecular biomechanics, and attract a broader range of researchers to enter this emerging field, here we discuss its significance and relevance, describe the important issues to be addressed and the most critical questions to be answered, summarize both experimental and theoretical/computational challenges, and identify some short-term and long-term goals for the field. The needs to train young researchers in molecular biomechanics with a broader knowledge base, and to bridge and integrate molecular, subcellular and cellular level studies of biomechanics are articulated.National Institutes of Health (U.S.) (grant UO1HL80711-05 to GB)National Institutes of Health (U.S.) (grant R01GM076689-01)National Institutes of Health (U.S.) (grant R01AR033236-26)National Institutes of Health (U.S.) (grant R01GM087677-01A1)National Institutes of Health (U.S.) (grant R01AI44902)National Institutes of Health (U.S.) (grant R01AI38282)National Science Foundation (U.S.) (grant CMMI-0645054)National Science Foundation (U.S.) (grant CBET-0829205)National Science Foundation (U.S.) (grant CAREER-0955291

Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics

The assessment of oocyte quality in human in vitro fertilization (IVF) is getting increasing attention from embryologists. Oocyte selection and the identification of the best oocytes, in fact, would help to limit embryo overproduction and to improve the results of oocyte cryostorage programs. Follicular fluid (FF) is easily available during oocyte pick-up and theorically represents an optimal source on non-invasive biochemical predictors of oocyte quality. Unfortunately, however, the studies aiming to find a good molecular predictor of oocyte quality in FF were not able to identify substances that could be used as reliable markers of oocyte competence to fertilization, embryo development and pregnancy. In the last years, a well definite trend toward passing from the research of single molecular markers to more complex techniques that study all metabolites of FF has been observed. The metabolomic approach is a powerful tool to study biochemical predictors of oocyte quality in FF, but its application in this area is still at the beginning. This review provides an overview of the current knowledge about the biochemical predictors of oocyte quality in FF, describing both the results coming from studies on single biochemical markers and those deriving from the most recent studies of metabolomic

Single-Molecule Force Spectroscopy: Experiments, Analysis, and Simulations

International audienceThe mechanical properties of cells and of subcellular components are important to obtain a mechanistic molecular understanding of biological processes. The quantification of mechanical resistance of cells and biomolecules using biophysical methods matured thanks to the development of nanotechnologies such as optical and magnetic tweezers, the biomembrane force probe and atomic force microscopy (AFM). The quantitative nature of force spectroscopy measurements has converted AFM into a valuable tool in biophysics. Force spectroscopy allows the determination of the forces required to unfold protein domains and to disrupt individual receptor/ligand bonds. Molecular simulation as a computational microscope allows investigation of similar biological processes with an atomistic detail. In this chapter, we first provide a step-by-step protocol of force spectroscopy including sample preparation, measurement and analysis of force spectroscopy using AFM and its interpretation in terms of available theories. Next, we present the background for molecular dynamics (MD) simulations focusing on steered molecular dynamics (SMD) and the importance of bridging of computational tools with experimental technique

Single molecule evaluation of fluorescent protein photoactivation efficiency using an in vivo nanotemplate

Photoswitchable fluorescent probes are central to localization-based super-resolution microscopy. Among these probes, fluorescent proteins are appealing because they are genetically encoded. Moreover, the ability to achieve a 1:1 labeling ratio between the fluorescent protein and the protein of interest makes these probes attractive for quantitative single-molecule counting. The percentage of fluorescent protein that is photoactivated into a fluorescently detectable form (i.e., the photoactivation efficiency) plays a crucial part in properly interpreting the quantitative information. It is important to characterize the photoactivation efficiency at the single-molecule level under the conditions used in super-resolution imaging. Here, we used the human glycine receptor expressed in Xenopus oocytes and stepwise photobleaching or single-molecule counting photoactivated localization microcopy (PALM) to determine the photoactivation efficiency of fluorescent proteins mEos2, mEos3.1, mEos3.2, Dendra2, mClavGR2, mMaple, PA-GFP and PA-mCherry. This analysis provides important information that must be considered when using these fluorescent proteins in quantitative super-resolution microscopy.Peer ReviewedPostprint (author's final draft