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Register a new userAnalysis tools for single-monomer measurements of self-assembly processes
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Protein assembly plays an important role throughout all phyla of life, both physiologically and pathologically. In particular, aggregation and polymerization of proteins are key-strategies that regulate cellular function. In recent years, methods to experimentally study the assembly process on a single-molecule level have been developed. This progress concomitantly has triggered the question of how to analyze this type of single-filament data adequately and what experimental conditions are necessary to allow a meaningful interpretation of the analysis. Here, we developed two analysis methods for single-filament data: the visitation analysis and the average-rate analysis. We benchmarked and compared both approaches with the classic dwell-time-analysis frequently used to study microscopic association and dissociation rates. In particular, we tested the limitations of each analysis method along the lines of the signal-to-noise ratio, the sampling rate, and the labeling efficiency and bleaching rate of the fluorescent dyes used in single-molecule fluorescence experiments. Finally, we applied our newly developed methods to study the monomer assembly of actin at the single-molecule-level in the presence of the class II nucleator Cappuccino and the WH2 repeats of Spire. For Cappuccino, our data indicated fast elongation circumventing a nucleation phase whereas, for spire, we found that the four WH2 motifs are not sufficient to promote de novo nucleation of actin.
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We study a system of self-propelled disks that perform run-and-tumble motion, where particles can adopt more than one internal state. One of those internal states can be transmitted to another particle if the particle carrying this state maintains physical contact with another particle for a finite period of time. We refer to this process as a reaction process and to the different internal states as particle species making an analogy to chemical reactions. The studied system may fall into an absorbing phase, where due to the disappearance of one of the particle species no further reaction can occur or remain in an active phase where particles constantly react. Combining individual-based simulations and mean-field arguments, we study the dependence of the equilibrium densities of particle species with motility parameters, specifically the active speed $v_0$ and tumbling frequency $lambda$. We find that the equilibrium densities of particle species exhibit two very distinct, non-trivial scaling regimes with $v_0$ and $lambda$ depending on whether the system is in the so-called ballistic or diffusive regime. Our mean-field estimates lead to an effective renormalization of reaction rates that allow building the phase-diagram $v_0$--$lambda$ that separates the absorbing and active phase. We find an excellent agreement between numerical simulations and estimates. This study is a necessary step to an understanding of phase transitions into an absorbing state in active systems and sheds light on the spreading of information/signaling among moving elements.
Under many in vitro conditions, some small viruses spontaneously encapsidate a single stranded (ss) RNA into a protein shell called the capsid. While viral RNAs are found to be compact and highly branched because of long distance base-pairing between nucleotides, recent experiments reveal that in a head-to-head competition between a ssRNA with no secondary or higher order structure and a viral RNA, the capsid proteins preferentially encapsulate the linear polymer! In this paper, we study the impact of genome stiffness on the encapsidation free energy of the complex of RNA and capsid proteins. We show that an increase in effective chain stiffness because of base-pairing could be the reason why under certain conditions linear chains have an advantage over branched chains when it comes to encapsidation efficiency. While branching makes the genome more compact, RNA base-pairing increases the effective Kuhn length of the RNA molecule, which could result in an increase of the free energy of RNA confinement, that is, the work required to encapsidate RNA, and thus less efficient packaging.
The bipolar organization of the microtubule-based mitotic spindle is essential for the faithful segregation of chromosomes in cell division. Despite our extensive knowledge of genes and proteins, the physical mechanism of how the ensemble of microtubules can assemble into a proper bipolar shape remains elusive. Here, we study the pathways of spindle self-organization using cell-free Xenopus egg extracts and computer-based automated shape analysis. Our microscopy assay allows us to simultaneously record the growth of hundreds of spindles in the bulk cytoplasm and systematically analyze the shape of each structure over the course of self-organization. We find that spindles that are maturing into a bipolar shape take a route that is distinct from those ending up with faulty structures, such as those of a tripolar shape. Moreover, matured structures are highly stable with little occasions of transformation between different shape phenotypes. Visualizing the movement of microtubules further reveals a fraction of microtubules that assemble between extra poles and push the poles apart, suggesting the presence of active extensile force that prevents pole coalescence. Together, we propose that a proper control over the magnitude and location of the extensile, pole-pushing force is crucial for establishing spindle bipolarity while preventing multipolarity.
Network Forensics (NFs) is a branch of digital forensics which used to detect and capture potential digital crimes over computer networked environments crime. Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs) have abilities to examine networks, collect all normal and abnormal traffic/data, help in network incident analysis, and assist in creating an appropriate incident detection and reaction and also create a forensic hypothesis that can be used in a court of law. Also, it assists in examining the internal incidents and exploitation of assets, attack goals, executes threat evaluation, also by evaluating network performance. According to existing literature, there exist quite a number of NFTs and NTPs that are used for identification, collection, reconstruction, and analysing the chain of incidents that happen on networks. However, they were vary and differ in their roles and functionalities. The main objective of this paper, therefore, is to assess and see the distinction that exist between Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs). Precisely, this paper focuses on comparing among four famous NFTs: Xplico, OmniPeek, NetDetector, and NetIetercept. The outputs of this paper show that the Xplico tool has abilities to identify, collect, reconstruct, and analyse the chain of incidents that happen on networks than other NF tools.
We demonstrate wafer-scale integration of single electron memories based on carbon nanotube field effect transistors (cnfets) by a complete self assembly process. First, a dry self assembly based on a Hot Filament assisted Chemical Vapor Deposition technique allows both localized growth and in situ electrical connection of carbon nanotubes on predefined catalytic electrodes. The semiconducting carbon nanotubes integration yield can exceed 50% for a batch. Secondly, a wet self-assembly attaches single 30 nm-diameter gold bead in the nanotube vicinity via chemical functionalization. The bead acts as the memory storage node while the cnfet operated in the subthreshold regime is an electrometer having exponential gain. Below 50 K, the transfer characteristics of some functionalized cnfets show highly reproducible hysteretical steps whose height can reach one decade of current. Evaluation of the capacitance confirms these current steps originate from single electron transfers between the bead and the nanotubes with a time retention exceeding 550s at 1.5K.
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