Magneto-optical tweezers with super-resolution fluorescence microscopy

This thesis describes the design, construction and application of a novel magneto-optical tweezers with super-resolution fluorescence microscopy for manipulation, force/torque measurement and imaging of single biomolecules. The optical tweezers component offers force or position clamping in three dimensions. The 3D-printed magnetic tweezers is designated for rotation in the vertical plane. The separation of rotation from force transduction results in the capability of precise torque measurement. The filamentous biomolecules to be used in the device will lie in a transverse direction in the imaging plane to allow fluorescence imaging with techniques including Blinking assisted Localisation Microscopy (BaLM) and total internal reflection fluorescence microscopy (TIRF). Also included are features such as acousto-optic deflection and multiplexing of laser traps, interferometry based tracking with quadrant photodiode and piezoelectric actuated nanostage for active feedback. These tweezers have been developed to enable direct observation of molecular topological transformation and protein binding event localisation with mechanical perturbation, which traditional tweezers could not achieve

Developing a new biophysical tool to combine magneto-optical tweezers with super-resolution fluorescence microscopy

We present a novel experimental setup in which magnetic and optical tweezers are combined for torque and force transduction onto single filamentous molecules in a transverse configuration to allow simultaneous mechanical measurement and manipulation. Previously we have developed a super-resolution imaging module which, in conjunction with advanced imaging techniques such as Blinking assisted Localisation Microscopy (BaLM), achieves localisation precision of single fluorescent dye molecules bound to DNA of 30 nm along the contour of the molecule; our work here describes developments in producing a system which combines tweezing and super-resolution fluorescence imaging. The instrument also features an acousto-optic deflector that temporally divides the laser beam to form multiple traps for high throughput statistics collection. Our motivation for developing the new tool is to enable direct observation of detailed molecular topological transformation and protein binding event localisation in a stretching/twisting mechanical assay that previously could hitherto only be deduced indirectly from the end-to-end length variation of DNA. Our approach is simple and robust enough for reproduction in the lab without the requirement of precise hardware engineering, yet is capable of unveiling the elastic and dynamic properties of filamentous molecules that have been hidden using traditional tools

Spikformer: When Spiking Neural Network Meets Transformer

We consider two biologically plausible structures, the Spiking Neural Network (SNN) and the self-attention mechanism. The former offers an energy-efficient and event-driven paradigm for deep learning, while the latter has the ability to capture feature dependencies, enabling Transformer to achieve good performance. It is intuitively promising to explore the marriage between them. In this paper, we consider leveraging both self-attention capability and biological properties of SNNs, and propose a novel Spiking Self Attention (SSA) as well as a powerful framework, named Spiking Transformer (Spikformer). The SSA mechanism in Spikformer models the sparse visual feature by using spike-form Query, Key, and Value without softmax. Since its computation is sparse and avoids multiplication, SSA is efficient and has low computational energy consumption. It is shown that Spikformer with SSA can outperform the state-of-the-art SNNs-like frameworks in image classification on both neuromorphic and static datasets. Spikformer (66.3M parameters) with comparable size to SEW-ResNet-152 (60.2M,69.26%) can achieve 74.81% top1 accuracy on ImageNet using 4 time steps, which is the state-of-the-art in directly trained SNNs models

Spike-driven Transformer

Spiking Neural Networks (SNNs) provide an energy-efficient deep learning option due to their unique spike-based event-driven (i.e., spike-driven) paradigm. In this paper, we incorporate the spike-driven paradigm into Transformer by the proposed Spike-driven Transformer with four unique properties: 1) Event-driven, no calculation is triggered when the input of Transformer is zero; 2) Binary spike communication, all matrix multiplications associated with the spike matrix can be transformed into sparse additions; 3) Self-attention with linear complexity at both token and channel dimensions; 4) The operations between spike-form Query, Key, and Value are mask and addition. Together, there are only sparse addition operations in the Spike-driven Transformer. To this end, we design a novel Spike-Driven Self-Attention (SDSA), which exploits only mask and addition operations without any multiplication, and thus having up to $87.2\times$ lower computation energy than vanilla self-attention. Especially in SDSA, the matrix multiplication between Query, Key, and Value is designed as the mask operation. In addition, we rearrange all residual connections in the vanilla Transformer before the activation functions to ensure that all neurons transmit binary spike signals. It is shown that the Spike-driven Transformer can achieve 77.1\% top-1 accuracy on ImageNet-1K, which is the state-of-the-art result in the SNN field. The source code is available at https://github.com/BICLab/Spike-Driven-Transformer

High-speed single-molecule tracking of CXCL13 in the B-Follicle

Soluble factors are an essential means of communication between cells and their environment. However, many molecules readily interact with extracellular matrix components, giving rise to multiple modes of diffusion. The molecular quantification of diffusion in situ is thus a challenging imaging frontier, requiring very high spatial and temporal resolution. Overcoming this methodological barrier is key to understanding the precise spatial patterning of the extracellular factors that regulate immune function. To address this, we have developed a high-speed light microscopy system capable of millisecond sampling in ex vivo tissue samples and sub-millisecond sampling in controlled in vitro samples to characterize molecular diffusion in a range of complex microenvironments. We demonstrate that this method outperforms competing tools for determining molecular mobility of fluorescence correlation spectroscopy (FCS) and fluorescence recovery after photobleaching (FRAP) for evaluation of diffusion. We then apply this approach to study the chemokine CXCL13, a key determinant of lymphoid tissue architecture, and B-cell mediated immunity. Super-resolution single-molecule tracking of fluorescently labeled CCL19 and CXCL13 in collagen matrix was used to assess the heterogeneity of chemokine mobility behaviors, with results indicating an immobile fraction and a mobile fraction for both molecules, with distinct diffusion rates of 8.4 ± 0.2 µm2s-1 and 6.2 ± 0.3 µm2s-1 respectively. To better understand mobility behaviors in situ we analyzed CXCL13-AF647 diffusion in murine lymph node tissue sections and observed both an immobile fraction and a mobile fraction with a diffusion coefficient of 6.6 ± 0.4 µm2s 1, suggesting that mobility within the follicle is also multimodal. In quantitatively studying mobility behaviors at the molecular level, we have obtained an increased understanding of CXCL13 bioavailability within the follicle. Our high-speed single-molecule tracking approach affords a novel perspective from which to understand the mobility of soluble factors relevant to the immune system

Physiological roles of fatty acyl desaturases and elongases in marine fish: Characterisation of cDNAs of fatty acyl delta6 desaturase and elovl5 elongase of cobia (Rachycentron canadum)

In the present paper, we investigated the expression of fatty acyl desaturase and elongase genes in a marine teleost, cobia, a species of great interest due to its considerable aquaculture potential. A cDNA was cloned that, when expressed in yeast, was shown to result in desaturation of 18:3n-3 and 18:2n-6, indicating that it coded for a Δ6 desaturase enzyme. Very low desaturation of 20:4n-3 and 20:3n-6 indicated only trace Δ5 activity. Another cloned cDNA enabled elongation of 18:4n-3, 18:3n-6, 20:5n-3 and 20:4n-6 in the yeast expression system, indicating that it had C18-20 and C20-22 elongase activity. Sequence comparison and phylogenetic analysis confirmed that it was homologous to human ELOVL5 elongase. However, the cobia Elovl5 elongase also had low activity toward C24 HUFA. The cobia Δ6 desaturase had a preference for 18:3n-3, but the elongase was generally equally active with both n-3 and n-6 substrates. Expression of both genes was 1-2 orders of magnitude greater in brain than other tissues suggesting an important role, possibly to ensure sufficient docosahexaenoic acid (DHA, 22:6n-3) synthesis in neural tissues through elongation and desaturation of eicosapentaenoic acid (EPA; 20:5n-3)

Superresolution imaging of single DNA molecules using stochastic photoblinking of minor groove and intercalating dyes

As proof-of-principle for generating superresolution structural information from DNA we applied a method of localization microscopy utilizing photoblinking comparing intercalating dye YOYO-1 against minor groove binding dye SYTO-13, using a bespoke multicolor single-molecule fluorescence microscope. We used a full-length ∼49kbp λ DNA construct possessing oligo inserts at either terminus allowing conjugation of digoxigenin and biotin at opposite ends for tethering to a glass coverslip surface and paramagnetic microsphere respectively. We observed stochastic DNA-bound dye photoactivity consistent with dye photoblinking as opposed to binding/unbinding events, evidenced through both discrete simulations and continuum kinetics analysis. We analyzed dye photoblinking images of immobilized DNA molecules using superresolution reconstruction software from two existing packages, rainSTORM and QuickPALM, and compared the results against our own novel home-written software called ADEMS code. ADEMS code generated lateral localization precision values of 30-40nm and 60-70nm for YOYO-1 and SYTO-13 respectively at video-rate sampling, similar to rainSTORM, running more slowly than rainSTORM and QuickPALM algorithms but having a complementary capability over both in generating automated centroid distribution and cluster analyses. Our imaging system allows us to observe dynamic topological changes to single molecules of DNA in real-time, such as rapid molecular snapping events. This will facilitate visualization of fluorescently-labeled DNA molecules conjugated to a magnetic bead in future experiments involving newly developed magneto-optical tweezers combined with superresolution microscopy