Adaptive optics improves multiphoton super-resolution imaging

Digital Redepleted of Stimulated Emission Depletion Microscopy for Noise Reduction and Resolution Improvement

Stimulated emission depletion microscopy (STED) achieves resolution beyond the diffraction limit by employing a donut-shaped depletion laser that selectively reduces fluorescence at the periphery of the excitation area. The imaging quality of STED microscopy is closely tied to minimizing the intermediate light from the ring-depletion laser. In this study, we introduce a method termed "digital redepleted STED," which uses frequency domain filtering to generate an optimal donut profile by subtracting the "perfect donut" signal from the original STED data. This approach effectively reduces background noise and enhances the STED resolution. Through simulation experiments, we demonstrate that digitally redepleted STED doubled the resolution. This method is compatible with a wide range of biological samples and can be adapted for two-organelle-structure STED and 3D STED applications. We compare the performance of digitally redepleted STED with that of digitally enhanced STED (De STED) and deconvolution methods (STED Decon) in terms of the signal-to-background ratio (SBR) and resolution as evaluation metrics, and we find that our method doubled the resolution and SBR for different samples compared with origin STED. Our results indicate that digitally redepleted STED outperforms both De STED and STED Decon for complicated sample like mitochondria. We anticipate that the digitally redepleted STED will have broad applicability due to its enhanced resolution, improved SBR, and ease of implementation.

Deep-Penetrating and High-Resolution Continuous-Wave Nonlinear Microscopy Based on Homologous Dual-Emission Upconversion Adaptive Optics

Lanthanide-doped upconversion nanoparticles (UCNPs) are emerging as innovative nonlinear probes in biomedical studies, offering the unique capability to simultaneously emit both visible (VIS) and near-infrared (NIR) photons under continuous-wave (CW) NIR excitation. However, deep-tissue high-resolution imaging remains challenging due to the trade-off between VIS emission (higher resolution, limited penetration) and NIR emission (deeper penetration, lower resolution). Here we present a CW nonlinear microscopy based on homologous dual-emission upconversion adaptive optics, leveraging Tm3+/Yb3+ co-doped UCNPs' dual 455 nm/800 nm emission: the 800 nm emission for aberration measurement (guide-star) in deep tissues and the 455 nm emission for high-resolution imaging at matching depths. Using a home-built nonlinear laser scanning microscope with a 975 nm CW laser, we achieved near-diffraction-limited imaging (480 nm laterally) at a 500 μm depth in the mouse brain environment with significant optical aberrations. This strategy expands UCNPs' applications and innovates the exploration of deep-tissue optical features.

Multidimensional Characterization of the Physiological State of Hematococcuspluvialis Using Scanning Structured Illumination Super-Resolution Microscopy

Haematococcus pluvialis (HP) is a freshwater alga known for its ability to accumulate the potent antioxidant astaxanthin, which has extensive applications in aquaculture, pharmaceuticals, and cosmetics. Astaxanthin rapidly accumulates under unfavorable environmental conditions. However, the mechanisms of astaxanthin accumulation under various stress conditions remain unclear. This mainly stems from the limitations of current imaging techniques, which lack super-resolution, label-free, and three-dimensional (3D) imaging capabilities. In this study, we employed scanning structured illumination microscopy (SSIM) to achieve dynamic 3D ultrastructural reconstructions of HP cells under various stress conditions. This advanced imaging approach allowed us to closely observe the stress responses of HP cells, revealing significant morphological changes induced by different stressors. Additionally, we examined alterations in the HP cell wall under these conditions and explored the relationship between these morphological changes and the rate of astaxanthin accumulation during identical stress durations. The results clearly demonstrate that light stress, which induces a more comprehensive disruption of the entire cell, leads to a faster rate of astaxanthin accumulation compared to salt stress, which exerts its effects from the exterior inward. The rate of astaxanthin accumulation under light stress is approximately twice that observed under salt stress conditions. Our findings offer new insights into the subcellular dynamics of astaxanthin accumulation in HP, underscoring the effectiveness of super-resolution techniques in clarifying these processes.

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations and experiments to show that applying the trained 'de-aberration' networks outperforms alternative methods, providing restoration on par with adaptive optics techniques; and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.

Lanthanide ion-doped upconversion nanoparticles for low-energy super-resolution applications

Energy-intensive technologies and high-precision research require energy-efficient techniques and materials. Lens-based optical microscopy technology is useful for low-energy applications in the life sciences and other fields of technology, but standard techniques cannot achieve applications at the nanoscale because of light diffraction. Far-field super-resolution techniques have broken beyond the light diffraction limit, enabling 3D applications down to the molecular scale and striving to reduce energy use. Typically targeted super-resolution techniques have achieved high resolution, but the high light intensity needed to outperform competing optical transitions in nanomaterials may result in photo-damage and high energy consumption. Great efforts have been made in the development of nanomaterials to improve the resolution and efficiency of these techniques toward low-energy super-resolution applications. Lanthanide ion-doped upconversion nanoparticles that exhibit multiple long-lived excited energy states and emit upconversion luminescence have enabled the development of targeted super-resolution techniques that need low-intensity light. The use of lanthanide ion-doped upconversion nanoparticles in these techniques for emerging low-energy super-resolution applications will have a significant impact on life sciences and other areas of technology. In this review, we describe the dynamics of lanthanide ion-doped upconversion nanoparticles for super-resolution under low-intensity light and their use in targeted super-resolution techniques. We highlight low-energy super-resolution applications of lanthanide ion-doped upconversion nanoparticles, as well as the related research directions and challenges. Our aim is to analyze targeted super-resolution techniques using lanthanide ion-doped upconversion nanoparticles, emphasizing fundamental mechanisms governing transitions in lanthanide ions to surpass the diffraction limit with low-intensity light, and exploring their implications for low-energy nanoscale applications.

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations and experiments to show that applying the trained 'de-aberration' networks outperforms alternative methods, providing restoration on par with adaptive optics techniques; and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.

Live-cell imaging powered by computation

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preserving cell viability. Computational methods can help to address this challenge and are now shifting the boundaries of what is possible to capture in living systems. In this Review, we discuss these computational methods focusing on artificial intelligence-based approaches that can be layered on top of commonly used existing microscopies as well as hybrid methods that integrate computation and microscope hardware. We specifically discuss how computational approaches can improve the signal-to-noise ratio, spatial resolution, temporal resolution and multi-colour capacity of live-cell imaging.

Phase diversity-based wavefront sensing for fluorescence microscopy

Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than λ/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror > 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding λ/2), restoring diffraction-limited imaging on extended biological samples.

Accurate piecewise centroid calculation algorithm for wavefront measurement in adaptive optics

Adaptive optics using direct wavefront sensing (direct AO) is widely used in two-photon microscopy to correct sample-induced aberrations and restore diffraction-limited performance at high speeds. In general, the direct AO method employs a Sharked-Hartman wavefront sensor (SHWS) to directly measure the aberrations through a spot array. However, the signal-to-noise ratio (SNR) of spots in SHWS varies significantly within deep tissues, presenting challenges for accurately locating spot centroids over a large SNR range, particularly under extremely low SNR conditions. To address this issue, we propose a piecewise centroid calculation algorithm called GCP, which integrates three optimal algorithms for accurate spot centroid calculations under high-, medium-, and low-SNR conditions. Simulations and experiments demonstrate that the GCP can accurately measure aberrations over a large SNR range and exhibits robustness under extremely low-SNR conditions. Importantly, GCP improves the AO working depth by 150 µm compared to the conventional algorithm.

Label-free adaptive optics single-molecule localization microscopy for whole zebrafish

Specimen-induced aberration has been a major factor limiting the imaging depth of single-molecule localization microscopy (SMLM). Here, we report the application of label-free wavefront sensing adaptive optics to SMLM for deep-tissue super-resolution imaging. The proposed system measures complex tissue aberrations from intrinsic reflectance rather than fluorescence emission and physically corrects the wavefront distortion more than three-fold stronger than the previous limit. This enables us to resolve sub-diffraction morphologies of cilia and oligodendrocytes in whole zebrafish as well as dendritic spines in thick mouse brain tissues at the depth of up to 102 μm with localization number enhancement by up to 37 times and localization precision comparable to aberration-free samples. The proposed approach can expand the application range of SMLM to whole zebrafish that cause the loss of localization number owing to severe tissue aberrations.

Efficient framework of solving time-gated reflection matrix for imaging through turbid medium

Imaging through turbid medium is a long pursuit in many research fields, such as biomedicine, astronomy and automatic vehicle, in which the reflection matrix-based method is a promising solution. However, the epi-detection geometry suffers from round-trip distortion and it is challenging to isolate the input and output aberrations in non-ideal cases due to system imperfections and measurement noises. Here, we present an efficient framework based on single scattering accumulation together with phase unwrapping that can accurately separate input and output aberrations from the noise-affected reflection matrix. We propose to only correct the output aberration while suppressing the input aberration by incoherent averaging. The proposed method is faster in convergence and more robust against noise, avoiding precise and tedious system adjustments. In both simulations and experiments, we demonstrate the diffraction-limited resolution capability under optical thickness beyond 10 scattering mean free paths, showing the potential of applications in neuroscience and dermatology.

Two-photon synthetic aperture microscopy for minimally invasive fast 3D imaging of native subcellular behaviors in deep tissue

Holistic understanding of physio-pathological processes requires noninvasive 3D imaging in deep tissue across multiple spatial and temporal scales to link diverse transient subcellular behaviors with long-term physiogenesis. Despite broad applications of two-photon microscopy (TPM), there remains an inevitable tradeoff among spatiotemporal resolution, imaging volumes, and durations due to the point-scanning scheme, accumulated phototoxicity, and optical aberrations. Here, we harnessed the concept of synthetic aperture radar in TPM to achieve aberration-corrected 3D imaging of subcellular dynamics at a millisecond scale for over 100,000 large volumes in deep tissue, with three orders of magnitude reduction in photobleaching. With its advantages, we identified direct intercellular communications through migrasome generation following traumatic brain injury, visualized the formation process of germinal center in the mouse lymph node, and characterized heterogeneous cellular states in the mouse visual cortex, opening up a horizon for intravital imaging to understand the organizations and functions of biological systems at a holistic level.

Adaptive optics for optical microscopy [Invited]

Optical microscopy is widely used to visualize fine structures. When applied to bioimaging, its performance is often degraded by sample-induced aberrations. In recent years, adaptive optics (AO), originally developed to correct for atmosphere-associated aberrations, has been applied to a wide range of microscopy modalities, enabling high- or super-resolution imaging of biological structure and function in complex tissues. Here, we review classic and recently developed AO techniques and their applications in optical microscopy.

Real-time wavefront correction using diffractive optical networks

Real-time wavefront correction is a challenging problem to present for conventional adaptive optics systems. Here, we present an all-optical system to realize real-time wavefront correction. Using deep learning, the system, which contains only multiple transmissive diffractive layers, is trained to realize high-quality imaging for unknown, random, distorted wavefronts. Once physically fabricated, this passive optical system is physically positioned between the imaging lens and the image plane to all-optically correct unknown, new wavefronts whose wavefront errors are within the training range. Simulated experiments showed that the system designed for the on-axis field of view increases the average imaging Strehl Ratio from 0.32 to 0.94, and the other system intended for multiple fields of view increases the resolvable probability of binary stars from 30.5% to 69.5%. Results suggested that DAOS performed well when performing wavefront correction at the speed of light. The solution of real-time wavefront correction can be applied to other wavelengths and has great application potential in astronomical observation, laser communication, and other fields.

Multi-Photon Microscopy

In this series of papers on light microscopy imaging, we have covered the fundamentals of microscopy, super-resolution microscopy, and lightsheet microscopy. This last review covers multi-photon microscopy with a brief reference to intravital imaging and Brainbow labeling. Multi-photon microscopy is often referred to as two-photon microscopy. Indeed, using two-photon microscopy is by far the most common way of imaging thick tissues; however, it is theoretically possible to use a higher number of photons, and three-photon microscopy is possible. Therefore, this review is titled "multi-photon microscopy." Another term for describing multi-photon microscopy is "non-linear" microscopy because fluorescence intensity at the focal spot depends upon the average squared intensity rather than the squared average intensity; hence, non-linear optics (NLO) is an alternative name for multi-photon microscopy. It is this non-linear relationship (or third exponential power in the case of three-photon excitation) that determines the axial optical sectioning capability of multi-photon imaging. In this paper, the necessity for two-photon or multi-photon imaging is explained, and the method of optical sectioning by multi-photon microscopy is described. Advice is also given on what fluorescent markers to use and other practical aspects of imaging thick tissues. The technique of Brainbow imaging is discussed. The review concludes with a description of intravital imaging of the mouse. © 2023 Wiley Periodicals LLC.

Live-cell imaging reveals the cellular dynamics in seed development

Seed development in flowering plants is highly complex and governed by three genetically distinct tissues: the fertilization products, the diploid embryo and triploid endosperm, as well as the seed coat that has maternal origin. There are diverse cellular dynamics such as nuclear movement in gamete cells for fertilization, cell polarity establishment for embryo development, and multinuclear endosperm formation. These tissues also coordinate and synchronize the developmental timing for proper seed formation through cell-to-cell communications. Live-cell imaging using advanced microscopy techniques enables us to decipher the dynamics of these events. Especially, the establishment of a less-invasive semi-in vivo live-cell imaging approach has allowed us to perform time-lapse analyses for long period observation of Arabidopsis thaliana intact seed development dynamics. Here we highlight the recent trends of live-cell imaging for seed development and discuss where we are heading.

Recent advances in optical imaging through deep tissue: imaging probes and techniques

Optical imaging has been essential for scientific observations to date, however its biomedical applications has been restricted due to its poor penetration through tissues. In living tissue, signal attenuation and limited imaging depth caused by the wave distortion occur because of scattering and absorption of light by various molecules including hemoglobin, pigments, and water. To overcome this, methodologies have been proposed in the various fields, which can be mainly categorized into two stategies: developing new imaging probes and optical techniques. For example, imaging probes with long wavelength like NIR-II region are advantageous in tissue penetration. Bioluminescence and chemiluminescence can generate light without excitation, minimizing background signals. Afterglow imaging also has high a signal-to-background ratio because excitation light is off during imaging. Methodologies of adaptive optics (AO) and studies of complex media have been established and have produced various techniques such as direct wavefront sensing to rapidly measure and correct the wave distortion and indirect wavefront sensing involving modal and zonal methods to correct complex aberrations. Matrix-based approaches have been used to correct the high-order optical modes by numerical post-processing without any hardware feedback. These newly developed imaging probes and optical techniques enable successful optical imaging through deep tissue. In this review, we discuss recent advances for multi-scale optical imaging within deep tissue, which can provide reseachers multi-disciplinary understanding and broad perspectives in diverse fields including biophotonics for the purpose of translational medicine and convergence science.

Multiscale fluorescence imaging of living samples

Fluorescence microscopy is a highly effective tool for interrogating biological structure and function, particularly when imaging across multiple spatiotemporal scales. Here we survey recent innovations and applications in the relatively understudied area of multiscale fluorescence imaging of living samples. We discuss fundamental challenges in live multiscale imaging and describe successful examples that highlight the power of this approach. We attempt to synthesize general strategies from these test cases, aiming to help accelerate progress in this exciting area.

Wavefront shaping: A versatile tool to conquer multiple scattering in multidisciplinary fields

Optical techniques offer a wide variety of applications as light-matter interactions provide extremely sensitive mechanisms to probe or treat target media. Most of these implementations rely on the usage of ballistic or quasi-ballistic photons to achieve high spatial resolution. However, the inherent scattering nature of light in biological tissues or tissue-like scattering media constitutes a critical obstacle that has restricted the penetration depth of non-scattered photons and hence limited the implementation of most optical techniques for wider applications. In addition, the components of an optical system are usually designed and manufactured for a fixed function or performance. Recent advances in wavefront shaping have demonstrated that scattering- or component-induced phase distortions can be compensated by optimizing the wavefront of the input light pattern through iteration or by conjugating the transmission matrix of the scattering medium. This offers unprecedented opportunities in many applications to achieve controllable optical delivery or detection at depths or dynamically configurable functionalities by using scattering media to substitute conventional optical components. In this article, the recent progress of wavefront shaping in multidisciplinary fields is reviewed, from optical focusing and imaging with scattering media, functionalized devices, modulation of mode coupling, and nonlinearity in multimode fiber to multimode fiber-based applications. Apart from insights into the underlying principles and recent advances in wavefront shaping implementations, practical limitations and roadmap for future development are discussed in depth. Looking back and looking forward, it is believed that wavefront shaping holds a bright future that will open new avenues for noninvasive or minimally invasive optical interactions and arbitrary control inside deep tissues. The high degree of freedom with multiple scattering will also provide unprecedented opportunities to develop novel optical devices based on a single scattering medium (generic or customized) that can outperform traditional optical components.

The Effects of Optical Aberrations to Illumination Beam Thickness in Two-Photon Excitation Microscopes

When performing in vivo imaging of live samples, it is a big challenge to penetrate thick tissues while still maintaining high resolution and a large field of view because of the sample-induced aberrations. These requirements can be met by combining the benefits of two-photon excitation, beam modulation and adaptive optics in an illumination path. However, the relationship between aberrations and the performance of such a microscopy system has never been systematically and comprehensively assessed. Here, two-photon Gaussian and Bessel beams are modulated as illumination beams, and how aberrations affect the thickness of the illumination beams is evaluated. It is found that the thickness variation is highly related to the azimuthal order of Zernike modes. The thickness of the two-photon Gaussian beam is more sensitive to Zernike modes with lower azimuthal order, while the thickness of the two-photon Bessel beam is more sensitive to the higher-azimuthal-order Zernike modes. So, it is necessary to design a new strategy to correct aberrations according to the effects of different Zernike modes in order to maximize the correction capability of correctors and reduce the correction errors for those insensitive Zernike modes. These results may provide important guidance for the design and evaluation of adaptive optical systems in a two-photon excitation microscope.

Single-shot quantitative aberration and scattering length measurements in mouse brain tissues using an extended-source Shack-Hartmann wavefront sensor

Deep fluorescence imaging in mammalian brain tissues remains challenging due to scattering and optical aberration-induced loss in signal and resolution. Correction of aberrations using adaptive optics (AO) requires their reliable measurement in the tissues. Here, we show that an extended-source Shack-Hartmann wavefront sensor (ESSH) allows quantitative aberration measurements through fixed brain slices with a thickness up to four times their scattering length. We demonstrate in particular that this wavefront measurement method based on image correlation is more robust to scattering compared to the standard centroid-based approach. Finally, we obtain a measurement of the tissue scattering length taking advantage of the geometry of a Shack-Hartmann sensor.

Answering some questions about structured illumination microscopy

Structured illumination microscopy (SIM) provides images of fluorescent objects at an enhanced resolution greater than that of conventional epifluorescence wide-field microscopy. Initially demonstrated in 1999 to enhance the lateral resolution twofold, it has since been extended to enhance axial resolution twofold (2008), applied to live-cell imaging (2009) and combined with myriad other techniques, including interferometric detection (2008), confocal microscopy (2010) and light sheet illumination (2012). Despite these impressive developments, SIM remains, perhaps, the most poorly understood 'super-resolution' method. In this article, we provide answers to the 13 questions regarding SIM proposed by Prakash et al. along with answers to a further three questions. After providing a general overview of the technique and its developments, we explain why SIM as normally used is still diffraction-limited. We then highlight the necessity for a non-polynomial, and not just nonlinear, response to the illuminating light in order to make SIM a true, diffraction-unlimited, super-resolution technique. In addition, we present a derivation of a real-space SIM reconstruction approach that can be used to process conventional SIM and image scanning microscopy (ISM) data and extended to process data with quasi-arbitrary illumination patterns. Finally, we provide a simple bibliometric analysis of SIM development over the past two decades and provide a short outlook on potential future work. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Super-resolution microscopy: a brief history and new avenues

Super-resolution microscopy (SRM) is a fast-developing field that encompasses fluorescence imaging techniques with the capability to resolve objects below the classical diffraction limit of optical resolution. Acknowledged with the Nobel prize in 2014, numerous SRM methods have meanwhile evolved and are being widely applied in biomedical research, all with specific strengths and shortcomings. While some techniques are capable of nanometre-scale molecular resolution, others are geared towards volumetric three-dimensional multi-colour or fast live-cell imaging. In this editorial review, we pick on the latest trends in the field. We start with a brief historical overview of both conceptual and commercial developments. Next, we highlight important parameters for imaging successfully with a particular super-resolution modality. Finally, we discuss the importance of reproducibility and quality control and the significance of open-source tools in microscopy. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Multiple asters organize the yolk microtubule network during dclk2-GFP zebrafish epiboly

It is known that the organization of microtubule (MT) networks in cells is orchestrated by subcellular structures named MT organizing centers (MTOCs). In this work, we use Light Sheet Fluorescence and Confocal Microscopy to investigate how the MT network surrounding the spherical yolk is arranged in the dclk2-GFP zebrafish transgenic line. We found that during epiboly the MT network is organized by multiple aster-like MTOCS. These structures form rings around the yolk sphere. Importantly, in wt embryos, aster-like MTOCs are only found upon pharmacological or genetic induction. Using our microscopy approach, we underscore the variability in the number of such asters in the transgenic line and report on the variety of global configurations of the yolk MT network. The asters’ morphology, dynamics, and their distribution in the yolk sphere are also analyzed. We propose that these features are tightly linked to epiboly timing and geometry. Key molecules are identified which support this asters role as MTOCs, where MT nucleation and growth take place. We conclude that the yolk MT network of dclk2-GFP transgenic embryos can be used as a model to organize microtubules in a spherical geometry by means of multiple MTOCs.

Label-Free Multiphoton Imaging of Microbes in Root, Mineral, and Soil Matrices with Time-Gated Coherent Raman and Fluorescence Lifetime Imaging

Imaging biogeochemical interactions in complex microbial systems─such as those at the soil-root interface─is crucial to studies of climate, agriculture, and environmental health but complicated by the three-dimensional (3D) juxtaposition of materials with a wide range of optical properties. We developed a label-free multiphoton nonlinear imaging approach to provide contrast and chemical information for soil microorganisms in roots and minerals with epi-illumination by simultaneously imaging two-photon excitation fluorescence (TPEF), coherent anti-Stokes Raman scattering (CARS), second-harmonic generation (SHG), and sum-frequency mixing (SFM). We used fluorescence lifetime imaging (FLIM) and time gating to correct CARS for the autofluorescence background native to soil particles and fungal hyphae (TG-CARS) using time-correlated single-photon counting (TCSPC). We combined TPEF, TG-CARS, and FLIM to maximize image contrast for live fungi and bacteria in roots and soil matrices without fluorescence labeling. Using this instrument, we imaged symbiotic arbuscular mycorrhizal fungi (AMF) structures within unstained plant roots in 3D to 60 μm depth. High-quality imaging was possible at up to 30 μm depth in a clay particle matrix and at 15 μm in complex soil preparation. TG-CARS allowed us to identify previously unknown lipid droplets in the symbiotic fungus, Serendipita bescii. We also visualized unstained putative bacteria associated with the roots of Brachypodium distachyon in a soil microcosm. Our results show that this multimodal approach holds significant promise for rhizosphere and soil science research.

Characterization of cell-induced astigmatism in high-resolution imaging

High-resolution and super-resolution techniques become more frequently used in thick, inhomogeneous samples. In particular for imaging life cells and tissue in which one wishes to observe a biological process at minimal interference and in the natural environment, sample inhomogeneities are unavoidable. Yet sample-inhomogeneities are paralleled by refractive index variations, for example between the cell organelles and the surrounding medium, that will result in the refraction of light, and therefore lead to sample-induced astigmatism. Astigmatism in turn will result in positional inaccuracies of observations that are at the heart of all super-resolution techniques. Here we introduce a simple model and define a figure-of-merit that allows one to quickly assess the importance of astigmatism for a given experimental setting. We found that astigmatism caused by the cell's nucleus can easily lead to aberrations up to hundreds of nanometers, well beyond the accuracy of all super-resolution techniques. The astigmatism generated by small objects, like bacteria or vesicles, appear to be small enough to be of any significance in typical super-resolution experimentation.

Multiview confocal super-resolution microscopy

Confocal microscopy1 remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching2. Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than 20 distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae and adults; myoblasts in imaginal disks of Drosophila wings; and mouse renal, oesophageal, cardiac and brain tissues.

Resolution-enhanced OCT and expanded framework of information capacity and resolution in coherent imaging

Spatial resolution in conventional optical microscopy has traditionally been treated as a fixed parameter of the optical system. Here, we present an approach to enhance transverse resolution in beam-scanned optical coherence tomography (OCT) beyond its aberration-free resolution limit, without any modification to the optical system. Based on the theorem of invariance of information capacity, resolution-enhanced (RE)-OCT navigates the exchange of information between resolution and signal-to-noise ratio (SNR) by exploiting efficient noise suppression via coherent averaging and a simple computational bandwidth expansion procedure. We demonstrate a resolution enhancement of 1.5 × relative to the aberration-free limit while maintaining comparable SNR in silicone phantom. We show that RE-OCT can significantly enhance the visualization of fine microstructural features in collagen gel and ex vivo mouse brain. Beyond RE-OCT, our analysis in the spatial-frequency domain leads to an expanded framework of information capacity and resolution in coherent imaging that contributes new implications to the theory of coherent imaging. RE-OCT can be readily implemented on most OCT systems worldwide, immediately unlocking information that is beyond their current imaging capabilities, and so has the potential for widespread impact in the numerous areas in which OCT is utilized, including the basic sciences and translational medicine.

Two-photon activated precision molecular photosensitizer targeting mitochondria

Mitochondria metabolism is an emergent target for the development of novel anticancer agents. It is amply recognized that strategies that allow for modulation of mitochondrial function in specific cell populations need to be developed for the therapeutic potential of mitochondria-targeting agents to become a reality in the clinic. In this work, we report dipolar and quadrupolar quinolizinium and benzimidazolium cations that show mitochondria targeting ability and localized light-induced mitochondria damage in live animal cells. Some of the dyes induce a very efficient disruption of mitochondrial potential and subsequent cell death under two-photon excitation in the Near-infrared (NIR) opening up possible applications of azonia/azolium aromatic heterocycles as precision photosensitizers. The dipolar compounds could be excited in the NIR due to a high two-photon brightness while exhibiting emission in the red part of the visible spectra (600-700 nm). Interaction with the mitochondria leads to an unexpected blue-shift of the emission of the far-red emitting compounds, which we assign to emission from the locally excited state. Interaction and possibly aggregation at the mitochondria prevents access to the intramolecular charge transfer state responsible for far-red emission.

Super-Resolution Microscopy: Shedding New Light on In Vivo Imaging

Over the past two decades, super-resolution microscopy (SRM), which offered a significant improvement in resolution over conventional light microscopy, has become a powerful tool to visualize biological activities in both fixed and living cells. However, completely understanding biological processes requires studying cells in a physiological context at high spatiotemporal resolution. Recently, SRM has showcased its ability to observe the detailed structures and dynamics in living species. Here we summarized recent technical advancements in SRM that have been successfully applied to in vivo imaging. Then, improvements in the labeling strategies are discussed together with the spectroscopic and chemical demands of the fluorophores. Finally, we broadly reviewed the current applications for super-resolution techniques in living species and highlighted some inherent challenges faced in this emerging field. We hope that this review could serve as an ideal reference for researchers as well as beginners in the relevant field of in vivo super resolution imaging.

DiLFM: an artifact-suppressed and noise-robust light-field microscopy through dictionary learning

Light field microscopy (LFM) has been widely used for recording 3D biological dynamics at camera frame rate. However, LFM suffers from artifact contaminations due to the illness of the reconstruction problem via naïve Richardson-Lucy (RL) deconvolution. Moreover, the performance of LFM significantly dropped in low-light conditions due to the absence of sample priors. In this paper, we thoroughly analyze different kinds of artifacts and present a new LFM technique termed dictionary LFM (DiLFM) that substantially suppresses various kinds of reconstruction artifacts and improves the noise robustness with an over-complete dictionary. We demonstrate artifact-suppressed reconstructions in scattering samples such as Drosophila embryos and brains. Furthermore, we show our DiLFM can achieve robust blood cell counting in noisy conditions by imaging blood cell dynamic at 100 Hz and unveil more neurons in whole-brain calcium recording of zebrafish with low illumination power in vivo.

Adaptive optics for dynamic aberration compensation using parallel model-based controllers based on a field programmable gate array

Adaptive optics (AO) is an effective technique for compensating the aberrations in optical systems and restoring their performance for various applications such as image formation, laser processing, and beam shaping. To reduce the controller complexity and extend the compensation capacity from static aberrations to dynamic disturbances, the present study proposes an AO system consisting of a self-built Shack-Hartmann wavefront sensor (SHWS), a deformable mirror (DM), and field programmable gate array (FPGA)-based controllers. This AO system is developed for tracking static and dynamic disturbances and tuning the controller parameters as required to achieve rapid compensation of the incoming wavefront. In the proposed system, the FPGA estimates the coefficients of the eight Zernike modes based on the SHWS with CameraLink operated at 200 Hz. The estimated coefficients are then processed by eight parallel independent discrete controllers to generate the voltage vectors to drive the DM to compensate the aberrations. To have the DM model for controller design, the voltage vectors are identified offline and are optimized by closed-loop controllers. Furthermore, the controller parameters are tuned dynamically in accordance with the main frequency of the aberration as determined by a fast Fourier transform (FFT) process. The experimental results show that the AO system provides a low complexity and effective means of compensating both static aberrations and dynamic disturbance up to 20 Hz.

Subcellular three-dimensional imaging deep through multicellular thick samples by structured illumination microscopy and adaptive optics

Structured Illumination Microscopy enables live imaging with sub-diffraction resolution. Unfortunately, optical aberrations can lead to loss of resolution and artifacts in Structured Illumination Microscopy rendering the technique unusable in samples thicker than a single cell. Here we report on the combination of Adaptive Optics and Structured Illumination Microscopy enabling imaging with 150 nm lateral and 570 nm axial resolution at a depth of 80 µm through Caenorhabditis elegans. We demonstrate that Adaptive Optics improves the three-dimensional resolution, especially along the axial direction, and reduces artifacts, successfully realizing 3D-Structured Illumination Microscopy in a variety of biological samples.

Super-resolved live-cell imaging using random illumination microscopy

Current super-resolution microscopy (SRM) methods suffer from an intrinsic complexity that might curtail their routine use in cell biology. We describe here random illumination microscopy (RIM) for live-cell imaging at super-resolutions matching that of 3D structured illumination microscopy, in a robust fashion. Based on speckled illumination and statistical image reconstruction, easy to implement and user-friendly, RIM is unaffected by optical aberrations on the excitation side, linear to brightness, and compatible with multicolor live-cell imaging over extended periods of time. We illustrate the potential of RIM on diverse biological applications, from the mobility of proliferating cell nuclear antigen (PCNA) in U2OS cells and kinetochore dynamics in mitotic S. pombe cells to the 3D motion of myosin minifilaments deep inside Drosophila tissues. RIM's inherent simplicity and extended biological applicability, particularly for imaging at increased depths, could help make SRM accessible to biology laboratories.

3D super-resolution deep-tissue imaging in living mice

Stimulated emission depletion (STED) microscopy enables the three-dimensional (3D) visualization of dynamic nanoscale structures in living cells, offering unique insights into their organization. However, 3D-STED imaging deep inside biological tissue is obstructed by optical aberrations and light scattering. We present a STED system that overcomes these challenges. Through the combination of two-photon excitation, adaptive optics, red-emitting organic dyes, and a long-working-distance water-immersion objective lens, our system achieves aberration-corrected 3D super-resolution imaging, which we demonstrate 164 µm deep in fixed mouse brain tissue and 76 µm deep in the brain of a living mouse.

3D Whole-Brain Imaging Approaches to Study Brain Tumors

Simple Summary

Brain tumors integrate into the brain and consist of tumor cells with different molecular alterations. During brain tumor pathogenesis, a variety of cell types surround the tumors to either inhibit or promote tumor growth. These cells are collectively referred to as the tumor microenvironment. Three-dimensional and/or longitudinal visualization approaches are needed to understand the growth of these tumors in time and space. In this review, we present three imaging modalities that are suitable or that can be adapted to study the volumetric distribution of malignant or tumor-associated cells in the brain. In addition, we highlight the potential clinical utility of some of the microscopy approaches for brain tumors using exemplars from solid tumors.

Abstract

Although our understanding of the two-dimensional state of brain tumors has greatly expanded, relatively little is known about their spatial structures. The interactions between tumor cells and the tumor microenvironment (TME) occur in a three-dimensional (3D) space. This volumetric distribution is important for elucidating tumor biology and predicting and monitoring response to therapy. While static 2D imaging modalities have been critical to our understanding of these tumors, studies using 3D imaging modalities are needed to understand how malignant cells co-opt the host brain. Here we summarize the preclinical utility of in vivo imaging using two-photon microscopy in brain tumors and present ex vivo approaches (light-sheet fluorescence microscopy and serial two-photon tomography) and highlight their current and potential utility in neuro-oncology using data from solid tumors or pathological brain as examples.

Watching the embryo: Evolution of the microscope for the study of embryogenesis

Embryos and microscopes share a long, remarkable history and biologists have always been intrigued to watch how embryos develop under the microscope. Here we discuss the advances in microscopy which have greatly influenced our current understanding of embryogenesis. We highlight the evolution of microscopes and the optical technologies that have been instrumental in studying various developmental processes. These imaging modalities provide mechanistic insights into the dynamic cellular and molecular events which drive lineage commitment and morphogenetic changes in the developing embryo. We begin the journey with a brief history of microscopy to study embryos. First, we review the principles and optics of light, fluorescence, confocal, and electron microscopy which have been key techniques for imaging cellular and molecular events during embryonic development. Next, we discuss recent key imaging modalities such as light-sheet microscopy, which are suitable for whole embryo imaging. Further, we highlight imaging techniques like multiphoton and super resolution microscopy for beyond light diffraction limit, high resolution imaging. Lastly, we review some of the scattering-based imaging methods and techniques used for imaging human embryos.

Adaptive optics for structured illumination microscopy based on deep learning

Structured illumination microscopy (SIM) is widely used in biological imaging for its high resolution, fast imaging speed, and simple optical setup. However, when imaging thick samples, the structured illumination patterns in SIM will suffer from optical aberrations, leading to a serious deterioration in resolution. Therefore, it is necessary to reconstruct structured illumination patterns with high quality and efficiency in deep tissue imaging. Here we demonstrate an adaptive optics (AO) correction method based on deep learning in wide-field SIM imaging system. The mapping between the coefficients of the first 15 Zernike modes and their corresponding distorted patterns is established to train the convolution neural network (CNN). The results show that the optimized CNN can predict the aberration phase within ~10.1 ms with a personal computer. The correlation index between the aberration phases and their corresponding predicted aberration phase is up to 0.9986. This method is highly robust and effective for patterns with various spatial densities and illumination conditions and able to effectively correct the imaging distortion caused by optical aberration in SIM system.

Laser scanning reflection-matrix microscopy for aberration-free imaging through intact mouse skull

A mouse skull is a barrier for high-resolution optical imaging because its thick and inhomogeneous internal structures induce complex aberrations varying drastically from position to position. Invasive procedures creating either thinned-skull or open-skull windows are often required for the microscopic imaging of brain tissues underneath. Here, we propose a label-free imaging modality termed laser scanning reflection-matrix microscopy for recording the amplitude and phase maps of reflected waves at non-confocal points as well as confocal points. The proposed method enables us to find and computationally correct up to 10,000 angular modes of aberrations varying at every 10 × 10 µm² patch in the sample plane. We realized reflectance imaging of myelinated axons in vivo underneath an intact mouse skull, with an ideal diffraction-limited spatial resolution of 450 nm. Furthermore, we demonstrated through-skull two-photon fluorescence imaging of neuronal dendrites and their spines by physically correcting the aberrations identified from the reflection matrix.

Adaptive optics via pupil ring segmentation improves spherical aberration correction for two-photon imaging of optically cleared tissues

Optical clearing methods reduce the optical scattering of biological samples and thereby extend optical imaging penetration depth. However, refractive index mismatch between the immersion media of objectives and clearing reagents induces spherical aberration (SA), causing significant degradation of fluorescence intensity and spatial resolution. We present an adaptive optics method based on pupil ring segmentation to correct SA in optically cleared samples. Our method demonstrates superior SA correction over a modal-based adaptive optics method and restores the fluorescence intensity and resolution at high imaging depth. Moreover, the method can derive an SA correction map for the whole imaging volume based on three representative measurements. It facilitates SA correction during image acquisition without intermittent SA measurements. We applied this method in mouse brain tissues treated with different optical clearing methods. The results illustrate that the synaptic structures of neurons within 900 μm depth can be clearly resolved after SA correction.

Axial resolution improvement of two-photon microscopy by multi-frame reconstruction and adaptive optics

Two-photon microscopy (TPM) has been widely used in biological imaging owing to its intrinsic optical sectioning and deep penetration abilities. However, the conventional TPM suffers from poor axial resolution, which makes it difficult to recognize some three-dimensional fine features. We present multi-frame reconstruction two-photon microscopy (MR-TPM) using a liquid lens as a fast axial scanning engine. A sensorless adaptive optics (AO) approach is adopted to correct the aberrations caused by both the liquid lens and the optical system. By overcoming the effect of optical aberrations, inadequate sampling, and poor focusing capability of a conventional TPM, the axial resolution can be improved by a factor of 3 with a high signal-to-noise ratio. The proposed technology is compatible with the conventional TPM and requires no optical post-processing. We demonstrate the proposed method by imaging fluorescent beads, in vitro imaging of the neural circuit of mouse brain slice, and in vivo time-lapse imaging of the morphological changes of microglial cells in septic mice model. The results suggest that the axon of the neural circuit and the process of microglia along the axial direction, which cannot be resolved using conventional TPM, become distinguishable using the proposed AO MR-TPM.

Advances in fluorescence microscopy techniques to study kidney function

Fluorescence microscopy, in particular immunofluorescence microscopy, has been used extensively for the assessment of kidney function and pathology for both research and diagnostic purposes. The development of confocal microscopy in the 1950s enabled imaging of live cells and intravital imaging of the kidney; however, confocal microscopy is limited by its maximal spatial resolution and depth. More recent advances in fluorescence microscopy techniques have enabled increasingly detailed assessment of kidney structure and provided extraordinary insights into kidney function. For example, nanoscale precise imaging by rapid beam oscillation (nSPIRO) is a super-resolution microscopy technique that was originally developed for functional imaging of kidney microvilli and enables detection of dynamic physiological events in the kidney. A variety of techniques such as fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS) and Förster resonance energy transfer (FRET) enable assessment of interaction between proteins. The emergence of other super-resolution techniques, including super-resolution stimulated emission depletion (STED), photoactivated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM) and structured illumination microscopy (SIM), has enabled functional imaging of cellular and subcellular organelles at ≤50 nm resolution. The deep imaging via emission recovery (DIVER) detector allows deep, label-free and high-sensitivity imaging of second harmonics, enabling assessment of processes such as fibrosis, whereas fluorescence lifetime imaging microscopy (FLIM) enables assessment of metabolic processes.

Upconversion Nonlinear Structured Illumination Microscopy

Video-rate super-resolution imaging through biological tissue can visualize and track biomolecule interplays and transportations inside cellular organisms. Structured illumination microscopy allows for wide-field super resolution observation of biological samples but is limited by the strong extinction of light by biological tissues, which restricts the imaging depth and degrades its imaging resolution. Here we report a photon upconversion scheme using lanthanide-doped nanoparticles for wide-field super-resolution imaging through the biological transparent window, featured by near-infrared and low-irradiance nonlinear structured illumination. We demonstrate that the 976 nm excitation and 800 nm upconverted emission can mitigate the aberration. We found that the nonlinear response of upconversion emissions from single nanoparticles can effectively generate the required high spatial frequency components in the Fourier domain. These strategies lead to a new modality in microscopy with a resolution below 131 nm, 1/7th of the excitation wavelength, and an imaging rate of 1 Hz.

Conformal convolutional neural network (CCNN) for single-shot sensorless wavefront sensing

Wavefront sensing technique is essential in deep tissue imaging, which guides spatial light modulator to compensate wavefront distortion for better imaging quality. Recently, convolutional neural network (CNN) based sensorless wavefront sensing methods have achieved remarkable speed advantages via single-shot measurement methodology. However, the low efficiency of convolutional filters dealing with circular point-spread-function (PSF) features makes them less accurate. In this paper, we propose a conformal convolutional neural network (CCNN) that boosts the performance by pre-processing circular features into rectangular ones through conformal mapping. The proposed conformal mapping reduces the number of convolutional filters that need to describe a circular feature, thus enables the neural network to recognize PSF features more efficiently. We demonstrate our CCNN could improve the wavefront sensing accuracy over 15% compared to a traditional CNN through simulations and validate the accuracy improvement in experiments. The improved performances make the proposed method promising in high-speed deep tissue imaging.

Two-photon image-scanning microscopy with SPAD array and blind image reconstruction

Two-photon excitation (2PE) laser scanning microscopy is the imaging modality of choice when one desires to work with thick biological samples. However, its spatial resolution is poor, below confocal laser scanning microscopy. Here, we propose a straightforward implementation of 2PE image scanning microscopy (2PE-ISM) that, by leveraging our recently introduced single-photon avalanche diode (SPAD) array detector and a novel blind image reconstruction method, is shown to enhance the effective resolution, as well as the overall image quality of 2PE microscopy. With our adaptive pixel reassignment procedure ∼1.6 times resolution increase is maintained deep into thick semi-transparent samples. The integration of Fourier ring correlation based semi-blind deconvolution is shown to further enhance the effective resolution by a factor of ∼2 - and automatic background correction is shown to boost the image quality especially in noisy images. Most importantly, our 2PE-ISM implementation requires no calibration measurements or other input from the user, which is an important aspect in terms of day-to-day usability of the technique.

Structured illumination imaging with quasi-periodic patterns

Structured illumination microscopy (SIM) is a well-established method for optical sectioning and super-resolution. The core of structured illumination is using a periodic pattern to excite image signals. This work reports a method for estimating minor pattern distortions from the raw image data and correcting these distortions during SIM image processing. The method was tested with both simulated and experimental image data from two-photon Bessel light-sheet SIM. The results proves the method is effective in challenging situations, where strong scattering background exists, signal-to-noise ratio (SNR) is low and the sample structure is sparse. Experimental results demonstrate restoring synaptic structures in deep brain tissue, despite the presence of strong light scattering and tissue-induced SIM pattern distortion.

Two-photon image-scanning microscopy with SPAD array and blind image reconstruction

Two-photon excitation (2PE) laser scanning microscopy is the imaging modality of choice when one desires to work with thick biological samples. However, its spatial resolution is poor, below confocal laser scanning microscopy. Here, we propose a straightforward implementation of 2PE image scanning microscopy (2PE-ISM) that, by leveraging our recently introduced single-photon avalanche diode (SPAD) array detector and a novel blind image reconstruction method, is shown to enhance the effective resolution, as well as the overall image quality of 2PE microscopy. With our adaptive pixel reassignment procedure ∼1.6 times resolution increase is maintained deep into thick semi-transparent samples. The integration of Fourier ring correlation based semi-blind deconvolution is shown to further enhance the effective resolution by a factor of ∼2 - and automatic background correction is shown to boost the image quality especially in noisy images. Most importantly, our 2PE-ISM implementation requires no calibration measurements or other input from the user, which is an important aspect in terms of day-to-day usability of the technique.

A new deep learning method for image deblurring in optical microscopic systems

Deconvolution is the most commonly used image processing method in optical imaging systems to remove the blur caused by the point-spread function (PSF). While this method has been successful in deblurring, it suffers from several disadvantages, such as slow processing time due to multiple iterations required to deblur and suboptimal in cases where the experimental operator chosen to represent PSF is not optimal. In this paper, we present a deep-learning-based deblurring method that is fast and applicable to optical microscopic imaging systems. We tested the robustness of proposed deblurring method on the publicly available data, simulated data and experimental data (including 2D optical microscopic data and 3D photoacoustic microscopic data), which all showed much improved deblurred results compared to deconvolution. We compared our results against several existing deconvolution methods. Our results are better than conventional techniques and do not require multiple iterations or pre-determined experimental operator. Our method has several advantages including simple operation, short time to compute, good deblur results and wide application in all types of optical microscopic imaging systems. The deep learning approach opens up a new path for deblurring and can be applied in various biomedical imaging fields.

Advances in adaptive optics-based two-photon fluorescence microscopy for brain imaging

Deep tissue imaging using two-photon fluorescence (TPF) techniques have revolutionized the optical imaging community by providing in depth molecular information at the single-cell level. These techniques provide structural and functional aspects of mammalian brain at unprecedented depth and resolution. However, wavefront distortions introduced by the optical system as well as the biological sample (tissue) limit the achievable fluorescence signal-to-noise ratio and resolution with penetration depth. In this review, we discuss on the advances in TPF microscopy techniques for in vivo functional imaging and offer guidelines as to which technologies are best suited for different imaging applications with special reference to adaptive optics.