Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy

Single image Fourier ring correlation

We address resolution assessment for (light super-resolution) microscopy imaging. In modalities where imaging is not diffraction limited, correlation between two noise independent images is the standard way to infer the resolution. Here we take away the need for two noise independent images by computationally splitting one image acquisition into two noise independent realizations. This procedure generates two Poisson noise distributed images if the input is Poissonian distributed. As most modern cameras are shot-noise limited this procedure is directly applicable. However, also in the presence of readout noise we can compute the resolution faithfully via a correction factor. We evaluate our method on simulations and experimental data of widefield microscopy, STED microscopy, rescan confocal microscopy, image scanning microscopy, conventional confocal microscopy, and transmission electron microscopy. In all situations we find that using one image instead of two results in the same computed image resolution.

Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy

Computational super-resolution methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells. Here, we develop zero-shot deconvolution networks (ZS-DeconvNet) that instantly enhance the resolution of microscope images by more than 1.5-fold over the diffraction limit with 10-fold lower fluorescence than ordinary super-resolution imaging conditions, in an unsupervised manner without the need for either ground truths or additional data acquisition. We demonstrate the versatile applicability of ZS-DeconvNet on multiple imaging modalities, including total internal reflection fluorescence microscopy, three-dimensional wide-field microscopy, confocal microscopy, two-photon microscopy, lattice light-sheet microscopy, and multimodal structured illumination microscopy, which enables multi-color, long-term, super-resolution 2D/3D imaging of subcellular bioprocesses from mitotic single cells to multicellular embryos of mouse and C. elegans.

Build and operation of a custom 3D, multicolor, single-molecule localization microscope

Single-molecule localization microscopy (SMLM) enables imaging scientists to visualize biological structures with unprecedented resolution. Particularly powerful implementations of SMLM are capable of three-dimensional, multicolor and high-throughput imaging and can yield key biological insights. However, widespread access to these technologies is limited, primarily by the cost of commercial options and complexity of de novo development of custom systems. Here we provide a comprehensive guide for interested researchers who wish to establish a high-end, custom-built SMLM setup in their laboratories. We detail the initial configuration and subsequent assembly of the SMLM, including the instructions for the alignment of all the optical pathways, the software and hardware integration, and the operation of the instrument. We describe the validation steps, including the preparation and imaging of test and biological samples with structures of well-defined geometries, and assist the user in troubleshooting and benchmarking the system's performance. Additionally, we provide a walkthrough of the reconstruction of a super-resolved dataset from acquired raw images using the Super-resolution Microscopy Analysis Platform. Depending on the instrument configuration, the cost of the components is in the range US$95,000-180,000, similar to other open-source advanced SMLMs, and substantially lower than the cost of a commercial instrument. A builder with some experience of optical systems is expected to require 4-8 months from the start of the system construction to attain high-quality three-dimensional and multicolor biological images.

Optimal sparsity allows reliable system-aware restoration of fluorescence microscopy images

Fluorescence microscopy is one of the most indispensable and informative driving forces for biological research, but the extent of observable biological phenomena is essentially determined by the content and quality of the acquired images. To address the different noise sources that can degrade these images, we introduce an algorithm for multiscale image restoration through optimally sparse representation (MIRO). MIRO is a deterministic framework that models the acquisition process and uses pixelwise noise correction to improve image quality. Our study demonstrates that this approach yields a remarkable restoration of the fluorescence signal for a wide range of microscopy systems, regardless of the detector used (e.g., electron-multiplying charge-coupled device, scientific complementary metal-oxide semiconductor, or photomultiplier tube). MIRO improves current imaging capabilities, enabling fast, low-light optical microscopy, accurate image analysis, and robust machine intelligence when integrated with deep neural networks. This expands the range of biological knowledge that can be obtained from fluorescence microscopy.

Single-molecule tracking (SMT): a window into live-cell transcription biochemistry

How molecules interact governs how they move. Single-molecule tracking (SMT) thus provides a unique window into the dynamic interactions of biomolecules within live cells. Using transcription regulation as a case study, we describe how SMT works, what it can tell us about molecular biology, and how it has changed our perspective on the inner workings of the nucleus. We also describe what SMT cannot yet tell us and how new technical advances seek to overcome its limitations. This ongoing progress will be imperative to address outstanding questions about how dynamic molecular machines function in live cells.

Enhancing Weak-Signal Extraction for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) has been widely used in biological imaging due to its ultrahigh spatial resolution. However, due to the strategy of reducing photodamage to living cells, the fluorescence signals of emitters are usually weak and the detector noises become non-negligible, which leads to localization misalignments and signal losses, thus deteriorating the imaging capability of SMLM. Here, we propose an active modulation method to control the fluorescence of the probe emitters. It actually marks the emitters with artificial blinking character, which directly distinguishes weak signals from multiple detector noises. We demonstrated from simulations and experiments that this method improves the signal-to-noise ratio by about 10 dB over the non-modulated method and boosts the sensitivity of single-molecule localization down to -4 dB, which significantly reduces localization misalignments and signal losses in SMLM. This signal-noise decoupling strategy is generally applicable to the super-resolution system with versatile labeled probes to improve their imaging capability. We also showed its application to the densely labeled sample, showing its flexibility in super-resolution nanoscopy.

The miEye: Bench-top super-resolution microscope with cost-effective equipment

Commercial super-resolution (SR) imaging systems require a high budget, while current more affordable open source microscopy systems lack modularity and sometimes are too complex or lack reliability. We present miEye - a cost-effective microscope designed for high-resolution wide-field fluorescence imaging. The build is constructed using a CNC milled aluminum microscope body and commercially available optomechanics, with open-source Python-based microscope control, data visualization, and analysis software integration. The data acquisition software works robustly with commonly used industrial-grade complementary metal oxide semiconductor (iCMOS) cameras, performs IR beam back-reflection-based automatic focus stabilization, and allows for laser control via an Arduino-based laser relay. The open-source nature of the design is aimed to facilitate adaptation by the community. The build can be constructed for a cost of roughly 50 k €. It contains SM-fiber and MM-fiber excitation paths that are easy to interchange and an adaptable emission path. Also, it ensures <5 nm/min stability of the sample on all axes, and allows achieving <30 nm lateral resolution for dSTORM and DNA-PAINT single-molecule localization microscopy (SMLM) experiments. Thus it serves as a cost-effective and adaptable addition to the open source microscopy community and potentially will allow high-quality SR imaging even for limited-budget research groups.