An Activity-Based Nanosensor for Traumatic Brain Injury.

Currently, traumatic brain injury (TBI) is detected by medical imaging; however, medical imaging requires expensive capital equipment, is time- and resource-intensive, and is poor at predicting patient prognosis. To date, direct measurement of elevated protease activity has yet to be utilized to detect TBI. In this work, we engineered an activity-based nanosensor for TBI (TBI-ABN) that responds to increased protease activity initiated after brain injury. We establish that a calcium-sensitive protease, calpain-1, is active in the injured brain hours within injury. We then optimize the molecular weight of a nanoscale polymeric carrier to infiltrate into the injured brain tissue with minimal renal filtration. A calpain-1 substrate that generates a fluorescent signal upon cleavage was attached to this nanoscale polymeric carrier to generate an engineered TBI-ABN. When applied intravenously to a mouse model of TBI, our engineered sensor is observed to locally activate in the injured brain tissue. This TBI-ABN is the first demonstration of a sensor that responds to protease activity to detect TBI

Geometric constrains for detecting short actin filaments by cryogenic electron tomography

Polymerization of actin into filaments can push membranes forming extensions like filopodia or lamellipodia, which are important during processes such as cell motility and phagocytosis. Similarly, small organelles or pathogens can be moved by actin polymerization. Such actin filaments can be arranged in different patterns and are usually hundreds of nanometers in length as revealed by various electron microscopy approaches. Much shorter actin filaments are involved in the motility of apicomplexan parasites. However, these short filaments have to date not been visualized in intact cells. Here, we investigated Plasmodium sporozoites, the motile forms of the malaria parasite that are transmitted by the mosquito, using cryogenic electron tomography. We detected filopodia-like extensions of the plasma membrane and observed filamentous structures in the supra-alveolar space underneath the plasma membrane. However, these filaments could not be unambiguously assigned as actin filaments. In silico simulations of EM data collection and tomographic reconstruction identify the limits in revealing the filaments due to their length, concentration and orientation

Integral Neutron Multiplicity Measurements from Cosmic Ray Interactions in Lead

Sixty element 3He neutron multiplicity detector systems were designed, constructed and tested for use in cosmic ray experiments with a 30-cm cube lead target. A series of measurements were performed for the cosmic ray configuration at ground level (3 meters water equivalent, mwe), in the St. Petersburg metro tunnel (185 mwe), and in the Pyhäsalmi mine in Finland (583 and 1185 mwe). Anomalous coincidence events with charged cosmic ray particles at sea level produced events with 100-120 neutrons due possibly to the total disintegration of the Pb nucleus. These events were also detected at 185 mwe, but the particles causing such disintegration are currently unidentified. We present examples of preliminary data from the various measurements and discuss future plans for underground experiments including possible searches for Weakly Interacting Massive Particles (WIMP, dark matter)

Recent progress in structure and dynamics of dual-membrane-spanning bacterial nanomachines

Advances in hard-ware and soft-ware for electron cryo-microscopy and tomography have provided unprecedented structural insights into large protein complexes in bacterial membranes. Tomographic volumes of native complexes in situ, combined with other structural and functional data, reveal functionally important conformational changes. Here, we review recent progress in elucidating the structure and mechanism of dual-membrane-spanning nanomachines involved in bacterial motility, adhesion, pathogenesis and biofilm formation, including the type IV pilus assembly machinery and the type III and VI secretions systems. We highlight how these new structural data shed light on the assembly and action of such machines and discuss future directions for more detailed mechanistic understanding of these massive, fascinating complexes

Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model

Light microscopy is a widespread and inexpensive imaging technique facilitating biomedical discovery and diagnostics. However, light diffraction barrier and imperfections in optics limit the level of detail of the acquired images. The details lost can be reconstructed among others by deep learning models. Yet, deep learning models are prone to introduce artefacts and hallucinations into the reconstruction. Recent state-of-the-art image synthesis models like the denoising diffusion probabilistic models (DDPMs) are no exception to this. We propose to address this by incorporating the physical problem of microscopy image formation into the model's loss function. To overcome the lack of microscopy data, we train this model with synthetic data. We simulate the effects of the microscope optics through the theoretical point spread function and varying the noise levels to obtain synthetic data. Furthermore, we incorporate the physical model of a light microscope into the reverse process of a conditioned DDPM proposing a physics-informed DDPM (PI-DDPM). We show consistent improvement and artefact reductions when compared to model-based methods, deep-learning regression methods and regular conditioned DDPMs.Comment: 16 pages, 5 figure

A weak-labelling and deep learning approach for in-focus object segmentation in 3D widefield microscopy

Three-dimensional information is crucial to our understanding of biological phenomena. The vast majority of biological microscopy specimens are inherently three-dimensional. However, conventional light microscopy is largely geared towards 2D images, while 3D microscopy and image reconstruction remain feasible only with specialized equipment and techniques. Inspired by the working principles of one such technique - confocal microscopy, we propose a novel approach to 3D widefield microscopy reconstruction through semantic segmentation of in-focus and out-of-focus pixels. For this, we explore a number of rule-based algorithms commonly used for software-based autofocusing and apply them to a dataset of widefield focal stacks. We propose a computation scheme allowing the calculation of lateral focus score maps of the slices of each stack using these algorithms. Furthermore, we identify algorithms preferable for obtaining such maps. Finally, to ensure the practicality of our approach, we propose a surrogate model based on a deep neural network, capable of segmenting in-focus pixels from the out-of-focus background in a fast and reliable fashion. The deep-neural-network-based approach allows a major speedup for data processing making it usable for online data processing

Cryoelectron tomography reveals periodic material at the inner side of subpellicular microtubules in apicomplexan parasites

Microtubules are dynamic cytoskeletal structures important for cell division, polarity, and motility and are therefore major targets for anticancer and antiparasite drugs. In the invasive forms of apicomplexan parasites, which are highly polarized and often motile cells, exceptionally stable subpellicular microtubules determine the shape of the parasite, and serve as tracks for vesicle transport. We used cryoelectron tomography to image cytoplasmic structures in three dimensions within intact, rapidly frozen Plasmodium sporozoites. This approach revealed microtubule walls that are extended at the luminal side by an additional 3 nm compared to microtubules of mammalian cells. Fourier analysis revealed an 8-nm longitudinal periodicity of the luminal constituent, suggesting the presence of a molecule interacting with tubulin dimers. In silico generation and analysis of microtubule models confirmed this unexpected topology. Microtubules from extracted sporozoites and Toxoplasma gondii tachyzoites showed a similar density distribution, suggesting that the putative protein is conserved among Apicomplexa and serves to stabilize microtubules

Determining the structure of the bacterial voltage-gated sodium channel NaChBac embedded in liposomes by cryo electron tomography and subtomogram averaging

Voltage-gated sodium channels shape action potentials that propagate signals along cells. When the membrane potential reaches a certain threshold, the channels open and allow sodium ions to flow through the membrane depolarizing it, followed by the deactivation of the channels. Opening and closing of the channels is important for cellular signalling and regulates various physiological processes in muscles, heart and brain. Mechanistic insights into the voltage-gated channels are difficult to achieve as the proteins are typically extracted from membranes for structural analysis which results in the loss of the transmembrane potential that regulates their activity. Here, we report the structural analysis of a bacterial voltage-gated sodium channel, NaChBac, reconstituted in liposomes under an electrochemical gradient by cryo electron tomography and subtomogram averaging. We show that the small channel, most of the residues of which are embedded in the membrane, can be localized using a genetically fused GFP. GFP can aid the initial alignment to an average resulting in a correct structure, but does not help for the final refinement. At a moderate resolution of ˜16 Å the structure of NaChBac in an unrestricted membrane bilayer is 10% wider than the structure of the purified protein previously solved in nanodiscs, suggesting the potential movement of the peripheral voltage-sensing domains. Our study explores the limits of structural analysis of membrane proteins in membranes