Best practices and tools for reporting reproducible fluorescence microscopy methods

Information Encryption and Decryption Based on Excitation-Emission Matrix Fluorescence Hyperspectral Imaging and Multiway Chemometrics

As the demand for information integrity and privacy protection grows, interdisciplinary research is becoming increasingly essential for advancing information security technologies. This work proposed an information encryption and decryption strategy based on excitation-emission matrix fluorescence hyperspectral imaging (EEM-HSI) and multiway chemometrics. A novel algorithm, augmented three-directional intersection alternating trilinear decomposition (Augmented TDR-ATLD), was developed to process EEM-HSI data for decrypting information. Initially, the feasibility of this strategy was exemplified using simulated 4D and 5D EEM-HSI data containing encrypted information with 5D data being used for encryption for the first time. Two signal overlap conditions were designed to control the strength of the information encryption. By decrypting mixed signals at the pixel level to extract pure component signals and reconstructing pixels, we successfully decoded the encrypted information. Additionally, the practicality of this strategy was validated through real experimentation. Three rhodamine fluorescent dyes were added to a red watercolor to prepare anticounterfeiting ink, which were used to produce 2D and 3D anticounterfeiting patterns. The excitation-emission matrix fluorescence of each pixel was measured by using the front-face fluorescence instrument to generate EEM-HSI data. Augmented TDR-ATLD was then applied to decrypt mixed signals under scattering and an unknown interference. The results demonstrated that the anticounterfeiting patterns conveyed by different rhodamine fluorescent dyes were accurately decoded. In summary, this strategy, based on EEM-HSI and multiway chemometrics, provides a promising approach for advanced information security technology. It has the potential to be extended to more fields, thereby contributing to enhanced comprehensive information security protection.

Bridging imaging-based in vitro methods from biomedical research to regulatory toxicology

Imaging technologies are being increasingly used in biomedical research and experimental toxicology to gather morphological and functional information from cellular models. There is a concrete opportunity of incorporating imaging-based in vitro methods in international guidelines to respond to regulatory requirements with human relevant data. To translate these methods from R&D to international regulatory acceptance, the community needs to implement test methods under quality management systems, assess inter-laboratory transferability, and demonstrate data reliability and robustness. This article summarises current challenges associated with image acquisition, image analysis, including artificial intelligence, and data management of imaging-based methods, with examples from the developmental neurotoxicity in vitro battery and phenotypic profiling assays. The article includes considerations on specific needs and potential solutions to design and implement future validation and transferability studies.

Standardized measurements for monitoring and comparing multiphoton microscope systems

The goal of this protocol is to improve the characterization and performance standardization of multiphoton microscopy hardware across a large user base. We purposefully focus on hardware and only briefly touch on software and data analysis routines where relevant. Here we cover the measurement and quantification of laser power, pulse width optimization, field of view, resolution and photomultiplier tube performance. The intended audience is scientists with little expertise in optics who either build or use multiphoton microscopes in their laboratories. They can use our procedures to test whether their multiphoton microscope performs well and produces consistent data over the lifetime of their system. Individual procedures are designed to take 1-2 h to complete without the use of expensive equipment. The procedures listed here help standardize the microscopes and facilitate the reproducibility of data across setups.

Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues

Artificial intelligence (AI) transforms image data analysis across many biomedical fields, such as cell biology, radiology, pathology, cancer biology, and immunology, with object detection, image feature extraction, classification, and segmentation applications. Advancements in deep learning (DL) research have been a critical factor in advancing computer techniques for biomedical image analysis and data mining. A significant improvement in the accuracy of cell detection and segmentation algorithms has been achieved as a result of the emergence of open-source software and innovative deep neural network architectures. Automated cell segmentation now enables the extraction of quantifiable cellular and spatial features from microscope images of cells and tissues, providing critical insights into cellular organization in various diseases. This review aims to examine the latest AI and DL techniques for cell analysis and data mining in microscopy images, aid the biologists who have less background knowledge in AI and machine learning (ML), and incorporate the ML models into microscopy focus images.

MIBLood-EV: An Online Reporting Tool to Facilitate the Standardized Reporting of Preanalytical Variables and Quality Control of Plasma and Serum to Enhance Rigor and Reproducibility in Liquid Biopsy Research

Pre-analytical variability significantly impacts the reproducibility of liquid biopsy research, which is critical for precision medicine and biomedical research. This report highlights the challenges and variability in the pre-analytical processes of liquid biopsies, especially regarding extracellular vesicles (EVs), which are crucial for diagnostics in oncology. The MIBlood-EV initiative aims to standardize the reporting of pre-analytical variables and the quality control of plasma and serum samples to enhance reproducibility in EV research. By providing a comprehensive and flexible reporting framework, MIBlood-EV seeks to improve the reliability of EV studies and facilitate the development of evidence-based protocols, ultimately advancing the field of liquid biopsy research.

Deep learning-enabled filter-free fluorescence microscope

Optical filtering is an indispensable part of fluorescence microscopy for selectively highlighting molecules labeled with a specific fluorophore and suppressing background noise. However, the utilization of optical filtering sets increases the complexity, size, and cost of microscopic systems, making them less suitable for multifluorescence channel, high-speed imaging. Here, we present filter-free fluorescence microscopic imaging enabled with deep learning-based digital spectral filtering. This approach allows for automatic fluorescence channel selection after image acquisition and accurate prediction of fluorescence by computing color changes due to spectral shifts with the presence of excitation scattering. Fluorescence prediction for cells and tissues labeled with various fluorophores was demonstrated under different magnification powers. The technique offers accurate identification of labeling with robust sensitivity and specificity, achieving consistent results with the reference standard. Beyond fluorescence microscopy, the deep learning-enabled spectral filtering strategy has the potential to drive the development of other biomedical applications, including cytometry and endoscopy.

Pixelation with concentration-encoded effective photons for quantitative molecular optical sectioning microscopy

Irreproducibility in molecular optical sectioning microscopy has hindered the transformation of acquired digital images from qualitative descriptions to quantitative data. Although numerous tools, metrics, and phantoms have been developed, accurate quantitative comparisons of data from different microscopy systems with diverse acquisition conditions remains a challenge. Here, we develop a simple tool based on an absolute measurement of bulk fluorophore solutions with related Poisson photon statistics, to overcome this obstacle. Demonstrated in a prototypical multiphoton microscope, our tool unifies the unit of pixelated measurement to enable objective comparison of imaging performance across different modalities, microscopes, components/settings, and molecular targets. The application of this tool in live specimens identifies an attractive methodology for quantitative imaging, which rapidly acquires low signal-to-noise frames with either gentle illumination or low-concentration fluorescence labeling.

Calibrating Fluorescence Microscopy With 3D-Speckler (3D Fluorescence Speckle Analyzer)

Fluorescence microscopy has been widely accessible and indispensable in cell biology research. This technique enables researchers to label targets, ranging from individual entities to multiple groups, with fluorescent markers. It offers precise determinations of localization, size, and shape, along with accurate quantifications of fluorescence signal intensities. Furthermore, an ideal fluorescence microscope can achieve approximately 250 nm in lateral and 600 nm in axial resolution. Despite its integral role in these measurements, the calibration of fluorescence microscopes is often overlooked. This protocol introduces the use of 3D-Speckler (3D fluorescence speckle analyzer), a semi-automated software tool we have recently developed, for calibrating fluorescence microscopy. Calibration of fluorescence microscopy includes determining resolution limits, validating accuracy in size measurements, evaluating illumination flatness, and determining chromatic aberrations. 3D-Speckler is user-friendly and enables precise quantification of fluorescence puncta, including nanoscale 2D/3D particle size, precise locations, and intensity information. By utilizing multispectral fluorescence beads of known sizes alongside 3D-Speckler, the software can effectively calibrate imaging systems. We emphasize the importance of routine calibration for imaging systems to maintain their integrity and reproducibility, ensuring accurate quantification. This protocol provides a detailed step-by-step guide on using 3D-Speckler to calibrate imaging systems. Key features • Semi-automated particle detection. • Accurate three-dimensional measurement of fluorescent particle sizes. • High-precision three-dimensional localization of fluorescent particles. • Precision analysis of point spread function and chromatic aberration in fluorescence microscopy.

Best practices for data management and sharing in experimental biomedical research

Effective data management is crucial for scientific integrity and reproducibility, a cornerstone of scientific progress. Well-organized and well-documented data enable validation and building on results. Data management encompasses activities including organization, documentation, storage, sharing, and preservation. Robust data management establishes credibility, fostering trust within the scientific community and benefiting researchers' careers. In experimental biomedicine, comprehensive data management is vital due to the typically intricate protocols, extensive metadata, and large datasets. Low-throughput experiments, in particular, require careful management to address variations and errors in protocols and raw data quality. Transparent and accountable research practices rely on accurate documentation of procedures, data collection, and analysis methods. Proper data management ensures long-term preservation and accessibility of valuable datasets. Well-managed data can be revisited, contributing to cumulative knowledge and potential new discoveries. Publicly funded research has an added responsibility for transparency, resource allocation, and avoiding redundancy. Meeting funding agency expectations increasingly requires rigorous methodologies, adherence to standards, comprehensive documentation, and widespread sharing of data, code, and other auxiliary resources. This review provides critical insights into raw and processed data, metadata, high-throughput versus low-throughput datasets, a common language for documentation, experimental and reporting guidelines, efficient data management systems, sharing practices, and relevant repositories. We systematically present available resources and optimal practices for wide use by experimental biomedical researchers.

DEPArray™ single-cell technology: A validation study for forensic applications

In forensics investigations, it is common to encounter biological mixtures consisting of homogeneous or heterogeneous components from multiple individuals and with different genetic contributions. One promising mixture deconvolution strategy is the DEPArray™ technology, which enables the separation of cell populations before genetic analysis. While technological advances are fundamental, their reliable validation is crucial for successful implementation and use for casework. Thus, this study aimed to 1) systematically validate the DEPArray™ system concerning specificity, sensitivity, repeatability, and contamination occurrences for blood, epithelial, and sperm cells, and 2) evaluate its potential for single-cell analysis in the field of forensic science. Our findings confirmed the effective identification of different cell types and the correct assignment of successfully genotyped single cells to their respective donor(s). Using the NGM Detect™ Amplification Kit, the average profile completeness for diploid cells was approximately 80%, with ∼ 290 RFUs. In contrast, haploid sperm analysis yielded an average completeness of 51% referring to the haploid reference profile, accompanied by mean peak heights of ∼ 176 RFUs. Although certain alleles of heterozygous loci in diploid cells showed strong imbalances, the overall peak balances yielded acceptable values above ≥ 60% with a mean value of 72% ± 0.21, a median of 77%, but with a maximum imbalance of 9% between heterozygous peaks. Locus dropouts were considered stochastic events, exhibiting variations among donors and cell types, with a notable failure incidence observed for TH01. Within the wet-lab experimentation with >500 single cells for the validation, profiling was performed using the consensus approach, where profiles were selected randomly from all data to better mirror real casework results. Nevertheless, complete profiles could be achieved with as few as three diploid cells, while the average success rate increased to 100% when using profiles of 6-10 cells. For sperms, however, a consensus profile with completeness >90% of the autosomal diploid genotype could be attained using ≥15 cells. In addition, the robustness of the consensus approach was evaluated in the absence of the respective reference profile without severe deterioration. Here, increased stutter peaks (≥ 15%) were found as the main artifact in single-cell profiles, while contamination and drop-ins were ascertained as rare events. Lastly, the technique's potential and limitations are discussed, and practical guidance is provided, particularly valuable for cold cases, multiple perpetrator rapes, and analyses of homogeneous mixed evidence.

Automated analysis of gray matter damage in aged mice reveals impaired remyelination in the cuprizone model

Multiple sclerosis is a chronic autoimmune disease of the central nervous system characterized by myelin loss, axonal damage, and glial scar formation. Still, the underlying processes remain unclear, as numerous pathways and factors have been found to be involved in the development and progression of the disease. Therefore, it is of great importance to find suitable animal models as well as reliable methods for their precise and reproducible analysis. Here, we describe the impact of demyelination on clinically relevant gray matter regions of the hippocampus and cerebral cortex, using the previously established cuprizone model for aged mice. We could show that bioinformatic image analysis methods are not only suitable for quantification of cell populations, but also for the assessment of de- and remyelination processes, as numerous objective parameters can be considered for reproducible measurements. After cuprizone-induced demyelination, subsequent remyelination proceeded slowly and remained incomplete in all gray matter areas studied. There were regional differences in the number of mature oligodendrocytes during remyelination suggesting region-specific differences in the factors accounting for remyelination failure, as, even in the presence of oligodendrocytes, remyelination in the cortex was found to be impaired. Upon cuprizone administration, synaptic density and dendritic volume in the gray matter of aged mice decreased. The intensity of synaptophysin staining gradually restored during the subsequent remyelination phase, however the expression of MAP2 did not fully recover. Microgliosis persisted in the gray matter of aged animals throughout the remyelination period, whereas extensive astrogliosis was of short duration as compared to white matter structures. In conclusion, we demonstrate that the application of the cuprizone model in aged mice mimics the impaired regeneration ability seen in human pathogenesis more accurately than commonly used protocols with young mice and therefore provides an urgently needed animal model for the investigation of remyelination failure and remyelination-enhancing therapies.

Community-developed checklists for publishing images and image analyses

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.

Standardised Measurements for Monitoring and Comparing Multiphoton Microscope Systems

The goal of this protocol is to enable better characterisation of multiphoton microscopy hardware across a large user base. The scope of this protocol is purposefully limited to focus on hardware, touching on software and data analysis routines only where relevant. The intended audiences are scientists using and building multiphoton microscopes in their laboratories. The goal is that any scientist, not only those with optical expertise, can test whether their multiphoton microscope is performing well and producing consistent data over the lifetime of their system.

Believing is seeing - the deceptive influence of bias in quantitative microscopy

The visual allure of microscopy makes it an intuitively powerful research tool. Intuition, however, can easily obscure or distort the reality of the information contained in an image. Common cognitive biases, combined with institutional pressures that reward positive research results, can quickly skew a microscopy project towards upholding, rather than rigorously challenging, a hypothesis. The impact of these biases on a variety of research topics is well known. What might be less appreciated are the many forms in which bias can permeate a microscopy experiment. Even well-intentioned researchers are susceptible to bias, which must therefore be actively recognized to be mitigated. Importantly, although image quantification has increasingly become an expectation, ostensibly to confront subtle biases, it is not a guarantee against bias and cannot alone shield an experiment from cognitive distortions. Here, we provide illustrative examples of the insidiously pervasive nature of bias in microscopy experiments - from initial experimental design to image acquisition, analysis and data interpretation. We then provide suggestions that can serve as guard rails against bias.

Cell Cycle Mapping Using Multiplexed Immunofluorescence

The development of technologies that allow measurement of the cell cycle at the single-cell level has revealed novel insights into the mechanisms that regulate cell cycle commitment and progression through DNA replication and cell division. These studies have also provided evidence of heterogeneity in cell cycle regulation among individual cells, even within a genetically identical population. Cell cycle mapping combines highly multiplexed imaging with manifold learning to visualize the diversity of "paths" that cells can take through the proliferative cell cycle or into various states of cell cycle arrest. In this chapter, we describe a general protocol of the experimental and computational components of cell cycle mapping. We also provide a comprehensive guide for the design and analysis of experiments, discussing key considerations in detail (e.g., antibody library preparation, analysis strategies, etc.) that may vary depending on the research question being addressed.

Protocol for quantifying the germination properties of individual bacterial endospores using PySpore

PySpore is a Python program that tracks the germination of individual bacterial endospores. Here, we present a protocol for segmenting spores and quantifying the germination properties of individual bacterial endospores using PySpore. We describe steps for using GUI-based tools to optimize image processing, annotating data, setting gates, and joining datasets for downstream analyses. We then describe procedures for plotting functionality tools without the user needing to modify the underlying code. For complete details on the use and execution of this protocol, please refer to Ribis et al. (2023).1.

The analysis of protein recruitment to laser microirradiation-induced DNA damage in live cells: Best practices for data analysis

Laser microirradiation coupled with live-cell fluorescence microscopy is a powerful technique that has been used widely in studying the recruitment and retention of proteins at sites of DNA damage. Results obtained from this technique can be found in published works by both seasoned and infrequent users of microscopy. However, like many other microscopy-based techniques, the presentation of data from laser microirradiation experiments is inconsistent; papers report a wide assortment of analytic techniques, not all of which result in accurate and/or appropriate representation of the data. In addition to the varied methods of analysis, experimental and analytical details are commonly under-reported. Consequently, publications reporting data from laser microirradiation coupled with fluorescence microscopy experiments need to be carefully and critically assessed by readers. Here, we undertake a systematic investigation of commonly reported corrections used in the analysis of laser microirradiation data. We validate the critical need to correct data for photobleaching and we identify key experimental parameters that must be accounted for when presenting data from laser microirradiation experiments. Furthermore, we propose a straightforward, four-step analytical protocol that can readily be applied across platforms and that aims to improve the quality of data reporting in the DNA damage field.

Prevalence and practices of immunofluorescent cell image processing: a systematic review

Background

We performed a systematic review that identified at least 9,000 scientific papers on PubMed that include immunofluorescent images of cells from the central nervous system (CNS). These CNS papers contain tens of thousands of immunofluorescent neural images supporting the findings of over 50,000 associated researchers. While many existing reviews discuss different aspects of immunofluorescent microscopy, such as image acquisition and staining protocols, few papers discuss immunofluorescent imaging from an image-processing perspective. We analyzed the literature to determine the image processing methods that were commonly published alongside the associated CNS cell, microscopy technique, and animal model, and highlight gaps in image processing documentation and reporting in the CNS research field.

Methods

We completed a comprehensive search of PubMed publications using Medical Subject Headings (MeSH) terms and other general search terms for CNS cells and common fluorescent microscopy techniques. Publications were found on PubMed using a combination of column description terms and row description terms. We manually tagged the comma-separated values file (CSV) metadata of each publication with the following categories: animal or cell model, quantified features, threshold techniques, segmentation techniques, and image processing software.

Results

Of the almost 9,000 immunofluorescent imaging papers identified in our search, only 856 explicitly include image processing information. Moreover, hundreds of the 856 papers are missing thresholding, segmentation, and morphological feature details necessary for explainable, unbiased, and reproducible results. In our assessment of the literature, we visualized current image processing practices, compiled the image processing options from the top twelve software programs, and designed a road map to enhance image processing. We determined that thresholding and segmentation methods were often left out of publications and underreported or underutilized for quantifying CNS cell research.

Discussion

Less than 10% of papers with immunofluorescent images include image processing in their methods. A few authors are implementing advanced methods in image analysis to quantify over 40 different CNS cell features, which can provide quantitative insights in CNS cell features that will advance CNS research. However, our review puts forward that image analysis methods will remain limited in rigor and reproducibility without more rigorous and detailed reporting of image processing methods.

Conclusion

Image processing is a critical part of CNS research that must be improved to increase scientific insight, explainability, reproducibility, and rigor.

Comparing and Correcting Spectral Sensitivities between Multispectral Microscopes: A Prerequisite to Clinical Implementation

Multispectral, multiplex immunofluorescence (mIF) microscopy has been used to great effect in research to identify cellular co-expression profiles and spatial relationships within tissue, providing a myriad of diagnostic advantages. As these technologies mature, it is essential that image data from mIF microscopes is reproducible and standardizable across devices. We sought to characterize and correct differences in illumination intensity and spectral sensitivity between three multispectral microscopes. We scanned eight melanoma tissue samples twice on each microscope and calculated their average tissue region flux intensities. We found a baseline average standard deviation of 29.9% across all microscopes, scans, and samples, which was reduced to 13.9% after applying sample-specific corrections accounting for differences in the tissue shown on each slide. We used a basic calibration model to correct sample- and microscope-specific effects on overall brightness and relative brightness as a function of the image layer. We tested the generalizability of the calibration procedure and found that applying corrections to independent validation subsets of the samples reduced the variation to 2.9 ± 0.03%. Variations in the unmixed marker expressions were reduced from 15.8% to 4.4% by correcting the raw images to a single reference microscope. Our findings show that mIF microscopes can be standardized for use in clinical pathology laboratories using a relatively simple correction model.

Understanding spatiotemporal coupling of gene expression using single molecule RNA imaging technologies

Across all kingdoms of life, gene regulatory mechanisms underlie cellular adaptation to ever-changing environments. Regulation of gene expression adjusts protein synthesis and, in turn, cellular growth. Messenger RNAs are key molecules in the process of gene expression. Our ability to quantitatively measure mRNA expression in single cells has improved tremendously over the past decades. This revealed an unexpected coordination between the steps that control the life of an mRNA, from transcription to degradation. Here, we provide an overview of the state-of-the-art imaging approaches for measurement and quantitative understanding of gene expression, starting from the early visualizations of single genes by electron microscopy to current fluorescence-based approaches in single cells, including live-cell RNA-imaging approaches to FISH-based spatial transcriptomics across model organisms. We also highlight how these methods have shaped our current understanding of the spatiotemporal coupling between transcriptional and post-transcriptional events in prokaryotes. We conclude by discussing future challenges of this multidisciplinary field.Abbreviations: mRNA: messenger RNA; rRNA: ribosomal rDNA; tRNA: transfer RNA; sRNA: small RNA; FISH: fluorescence in situ hybridization; RNP: ribonucleoprotein; smFISH: single RNA molecule FISH; smiFISH: single molecule inexpensive FISH; HCR-FISH: Hybridization Chain-Reaction-FISH; RCA: Rolling Circle Amplification; seqFISH: Sequential FISH; MERFISH: Multiplexed error robust FISH; UTR: Untranslated region; RBP: RNA binding protein; FP: fluorescent protein; eGFP: enhanced GFP, MCP: MS2 coat protein; PCP: PP7 coat protein; MB: Molecular beacons; sgRNA: single guide RNA.

A biologist's guide to planning and performing quantitative bioimaging experiments

Technological advancements in biology and microscopy have empowered a transition from bioimaging as an observational method to a quantitative one. However, as biologists are adopting quantitative bioimaging and these experiments become more complex, researchers need additional expertise to carry out this work in a rigorous and reproducible manner. This Essay provides a navigational guide for experimental biologists to aid understanding of quantitative bioimaging from sample preparation through to image acquisition, image analysis, and data interpretation. We discuss the interconnectedness of these steps, and for each, we provide general recommendations, key questions to consider, and links to high-quality open-access resources for further learning. This synthesis of information will empower biologists to plan and execute rigorous quantitative bioimaging experiments efficiently.

Blocking autofluorescence in brain tissues affected by ischemic stroke, hemorrhagic stroke, or traumatic brain injury

Autofluorescence is frequently observed in animal tissues, interfering with an experimental analysis and leading to inaccurate results. Sudan black B (SBB) is a staining dye widely used in histological studies to eliminate autofluorescence. In this study, our objective was to characterize brain tissue autofluorescence present in three models of acute brain injury, including collagenase-induced intracerebral hemorrhage (ICH), traumatic brain injury (TBI), and middle cerebral artery occlusion, and to establish a simple method to block autofluorescence effectively. Using fluorescence microscopy, we examined autofluorescence in brain sections affected by ICH and TBI. In addition, we optimized a protocol to block autofluorescence with SBB pretreatment and evaluated the reduction in fluorescence intensity. Compared to untreated, pretreatment with SBB reduced brain tissue autofluorescence in the ICH model by 73.68% (FITC), 76.05% (Tx Red), and 71.88% (DAPI), respectively. In the TBI model, the ratio of pretreatment to untreated decreased by 56.85% (FITC), 44.28% (Tx Red), and 46.36% (DAPI), respectively. Furthermore, we tested the applicability of the protocol using immunofluorescence staining or Cyanine-5.5 labeling in the three models. SBB treatment is highly effective and can be applied to immunofluorescence and fluorescence label imaging techniques. SBB pretreatment effectively reduced background fluorescence but did not significantly reduce the specific fluorescence signal and greatly improved the signal-to-noise ratio of fluorescence imaging. In conclusion, the optimized SBB pretreatment protocol blocks brain section autofluorescence of the three acute brain injury models.

Cellulose nanocrystal as an enhancing core for antitumor polymeric micelles to overcome biological barriers

Polymeric micelles are extensively studied nanocarriers to improve the solubility, blood circulation, biodistribution, and adverse effects of chemotherapeutic drugs. However, the antitumor efficacy of polymeric micelles is often restricted due to multiple biological barriers, including blood fluid shear stress (FSS) and limited tumor penetration in vivo. Herein, cellulose nanocrystal (CNC) as a green material with rigidity and rod-shaped structure is developed to be an enhancing core for polymeric micelles to overcome these biological barriers. Doxorubicin (DOX) loaded methoxy poly (ethylene glycol)-block-poly (D, L-lactic acid) (mPEG-PLA, PP) ligated CNC nanoparticles (PPC/DOX NPs) are fabricated via one-pot synthesis. In comparison to the self-assembled DOX loaded mPEG-PLA micelles (PP/DOX NPs), PPC/DOX NPs exhibit remarkable improvements in FSS resistance, cellular internalization, blood circulation, tumor penetration, and antitumor efficacy owing to the unique rigidity and rod-shaped structure of CNC core. Moreover, PPC/DOX NPs present various advantages beyond DOX·HCl and CNC/DOX NPs. The superiority of PPC/DOX NPs in antitumor efficacy reveals the effectiveness of adopting CNC as the enhancing core for polymeric micelles, suggesting that CNC is a promising biomaterial in advancing nanomedicine.

Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology

The exchange of large and complex slide microscopy imaging data in biomedical research and pathology practice is impeded by a lack of data standardization and interoperability, which is detrimental to the reproducibility of scientific findings and clinical integration of technological innovations. We introduce Slim, an open-source, web-based slide microscopy viewer that implements the internationally accepted Digital Imaging and Communications in Medicine (DICOM) standard to achieve interoperability with a multitude of existing medical imaging systems. We showcase the capabilities of Slim as the slide microscopy viewer of the NCI Imaging Data Commons and demonstrate how the viewer enables interactive visualization of traditional brightfield microscopy and highly-multiplexed immunofluorescence microscopy images from The Cancer Genome Atlas and Human Tissue Atlas Network, respectively, using standard DICOMweb services. We further show how Slim enables the collection of standardized image annotations for the development or validation of machine learning models and the visual interpretation of model inference results in the form of segmentation masks, spatial heat maps, or image-derived measurements.

Reporting reproducible imaging protocols

A reproducible imaging protocol should include four main detailed sections. The first should describe the sample preparation and include details about the tissue and/or cell culture preparation, the staining procedure, the optical grade of the coverslip, and the type of mounting media used to mount the sample. The second section should describe the configuration and components of the microscope and include the type of stand, stage, illumination, and detector, as well as the emission (EM) and excitation (EX) filters, objective, and immersion medium specifications. Specialized microscopes may have other important components in the optical path to include. The third section should describe the settings used to acquire an image like the exposure and/or dwell time, final magnification and optical resolution, the pixel and field of view (FOV) sizes, time intervals for any time lapse, total power at the objective (i.e., directed at your sample) and number of planes and step size used to collect a 3-dimensional image, and order of operations used in multi-dimensional image acquisitions. The final section should include details about the image analysis workflow such as the image processing steps, segmentation and measurement methods used to extract information from the image, data size, and necessary computing hardware and networking requirements if data sets are >1 GB, as well as citations and versions for the software and code used to perform any of these steps. Every effort should be made to make an example dataset with accurate metadata available online. Finally, specifics about the type of replicates included in the experiment and details about the statistical analysis conducted are also necessary.

Improving quantification of myotube width and nuclear/cytoplasmic ratio in myogenesis research

BACKGROUND AND OBJECTIVE

The culture of skeletal muscle cells is particularly relevant to basic biomedical research and translational medicine. The incubation of dissociated cells under controlled conditions has helped to dissect several molecular mechanisms associated with muscle cell differentiation, in addition to contributing for the evaluation of drug effects and prospective cell therapies for patients with degenerative muscle pathologies. The formation of mature multinucleated myotubes is a stepwise process involving well defined events of cell proliferation, commitment, migration, and fusion easily identified through optical microscopy methods including immunofluorescence and live cell imaging. The characterization of each step is usually based on muscle cell morphology and nuclei number, as well as the presence and intracellular location of specific cell markers. However, manual quantification of these parameters in large datasets of images is work-intensive and prone to researcher's subjectivity, mostly because of the extremely elongated cell shape of large myotubes and because myotubes are multinucleated.

METHODS

Here we provide two semi-automated ImageJ macros aimed to measure the width of myotubes and the nuclear/cytoplasmic localization of molecules in fluorescence images. The width measuring macro automatically determines the best angle, perpendicular to most cells, to draw a profile plot and identify and measure individual myotubes. The nuclear/cytoplasmic ratio macro compares the intensity values along lines, drawn by the user, over cytoplasm and nucleus.

RESULTS

We show that the macro measurements are more consistent than manual measurements by comparing with our own results and with the literature.

CONCLUSIONS

By relying on semi-automated muscle specific ImageJ macros, we seek to improve measurement accuracy and to alleviate the laborious routine of counting and measuring muscle cell features.

The K2: Open-source simultaneous triple-color TIRF microscope for live-cell and single-molecule imaging

Imaging the dynamics and interactions of biomolecules at the single-molecule level in live cells and reconstituted systems has generated unprecedented knowledge about the biomolecular processes underlying many cellular functions. To achieve the speed and sensitivity needed to detect and follow individual molecules, these experiments typically require custom-built microscopes or custom modifications of commercial systems. The costs of such single-molecule microscopes, their technical complexity and the lack of open-source documentation on how to build custom setups therefore limit the accessibility of single-molecule imaging techniques. To advance the adaptation of dynamic single-molecule imaging by a wider community, we present the "K2": an open-source, simultaneous triple-color total internal reflection fluorescence (TIRF) microscope specifically designed for live-cell and single-molecule imaging. We explain our design considerations and provide step-by-step building instructions, parts list and full CAD models. The modular design of this TIRF microscope allows users to customize it to their scientific and financial needs, or to re-use parts of our design to improve the capabilities of their existing setups without necessarily having to build a full copy of the K2 microscope.

Semi-automated 3D fluorescence speckle analyzer (3D-Speckler) for microscope calibration and nanoscale measurement

The widespread use of fluorescence microscopy has prompted the ongoing development of tools aiming to improve resolution and quantification accuracy for study of biological questions. Current calibration and quantification tools for fluorescence images face issues with usability/user experience, lack of automation, and comprehensive multidimensional measurement/correction capabilities. Here, we developed 3D-Speckler, a versatile, and high-throughput image analysis software that can provide fluorescent puncta quantification measurements such as 2D/3D particle size, spatial location/orientation, and intensities through semi-automation in a single, user-friendly interface. Integrated analysis options such as 2D/3D local background correction, chromatic aberration correction, and particle matching/filtering are also encompassed for improved precision and accuracy. We demonstrate 3D-Speckler microscope calibration capabilities by determining the chromatic aberrations, field illumination uniformity, and response to nanometer-scale emitters above and below the diffraction limit of our imaging system using multispectral beads. Furthermore, we demonstrated 3D-Speckler quantitative capabilities for offering insight into protein architectures and composition in cells.

Comprehensive Investigation of Parameters Influencing Fluorescence Lifetime Imaging Microscopy in Frequency- and Time-Domain Illustrated by Phasor Plot Analysis

Having access to fluorescence lifetime, researchers can reveal in-depth details about the microenvironment as well as the physico-chemical state of the molecule under investigation. However, the high number of influencing factors might be an explanation for the strongly deviating values of fluorescent lifetimes for the same fluorophore reported in the literature. This could be the reason for the impression that inconsistent results are obtained depending on which detection and excitation scheme is used. To clarify this controversy, the two most common techniques for measuring fluorescence lifetimes in the time-domain and in the frequency-domain were implemented in one single microscopy setup and applied to a variety of fluorophores under different environmental conditions such as pH-value, temperature, solvent polarity, etc., along with distinct state forms that depend, for example, on the concentration. From a vast amount of measurement results, both setup- and sample-dependent parameters were extracted and represented using a single display form, the phasor-plot. The measurements showed consistent results between the two techniques and revealed which of the tested parameters has the strongest influence on the fluorescence lifetime. In addition, quantitative guidance as to which technique is most suitable for which research task and how to perform the experiment properly to obtain consistent fluorescence lifetimes is discussed.

Multiphoton intravital microscopy of rodents

Tissues are heterogeneous with respect to cellular and non-cellular components and in the dynamic interactions between these elements. To study the behaviour and fate of individual cells in these complex tissues, intravital microscopy (IVM) techniques such as multiphoton microscopy have been developed to visualize intact and live tissues at cellular and subcellular resolution. IVM experiments have revealed unique insights into the dynamic interplay between different cell types and their local environment, and how this drives morphogenesis and homeostasis of tissues, inflammation and immune responses, and the development of various diseases. This Primer introduces researchers to IVM technologies, with a focus on multiphoton microscopy of rodents, and discusses challenges, solutions and practical tips on how to perform IVM. To illustrate the unique potential of IVM, several examples of results are highlighted. Finally, we discuss data reproducibility and how to handle big imaging data sets.

Quality assessment in light microscopy for routine use through simple tools and robust metrics

Although there is a need to demonstrate reproducibility in light microscopy acquisitions, the lack of standardized guidelines monitoring microscope health status over time has so far impaired the widespread use of quality control (QC) measurements. As scientists from 10 imaging core facilities who encounter various types of projects, we provide affordable hardware and open source software tools, rigorous protocols, and define reference values to assess QC metrics for the most common fluorescence light microscopy modalities. Seven protocols specify metrics on the microscope resolution, field illumination flatness, chromatic aberrations, illumination power stability, stage drift, positioning repeatability, and spatial-temporal noise of camera sensors. We designed the MetroloJ_QC ImageJ/Fiji Java plugin to incorporate the metrics and automate analysis. Measurements allow us to propose an extensive characterization of the QC procedures that can be used by any seasoned microscope user, from research biologists with a specialized interest in fluorescence light microscopy through to core facility staff, to ensure reproducible and quantifiable microscopy results.

Imaging flow cytometry: a primer

Imaging flow cytometry combines the high throughput nature of flow cytometry with the advantages of single cell image acquisition associated with microscopy. The measurement of large numbers of features from the resulting images provides rich datasets which have resulted in a wide range of novel biomedical applications. In this primer we discuss the typical imaging flow instrumentation, the form of data acquired and the typical analysis tools that can be applied to this data. Using examples from the literature we discuss the progression of the analysis methods that have been applied to imaging flow cytometry data. These methods start from the use of simple single image features and multiple channel gating strategies, followed by the design and use of custom features for phenotype classification, through to powerful machine and deep learning methods. For each of these methods, we outline the processes involved in analyzing typical datasets and provide details of example applications. Finally we discuss the current limitations of imaging flow cytometry and the innovations which are addressing these challenges.

Rapid single-molecule characterisation of enzymes involved in nucleic-acid metabolism

The activity of enzymes is traditionally characterised through bulk-phase biochemical methods that only report on population averages. Single-molecule methods are advantageous in elucidating kinetic and population heterogeneity but are often complicated, time consuming, and lack statistical power. We present a highly-generalisable and high-throughput single-molecule assay to rapidly characterise proteins involved in DNA metabolism. The assay exclusively relies on changes in total fluorescence intensity of surface-immobilised DNA templates as a result of DNA synthesis, unwinding or digestion. Combined with an automated data-analysis pipeline, our method provides enzymatic activity data of thousands of molecules in less than an hour. We demonstrate our method by characterising three fundamentally different enzyme activities: digestion by the phage λ exonuclease, synthesis by the phage Phi29 polymerase, and unwinding by the E. coli UvrD helicase. We observe the previously unknown activity of the UvrD helicase to remove neutravidin bound to 5'-, but not 3'-ends of biotinylated DNA.

Application of Fluorescence In Situ Hybridization Assisted by Fluorescence Microscope in Detection of Her2 Gene in Breast Cancer Patients

In order to study the important factors for evaluating the prognosis of breast cancer patients, a fluorescence microscopy-assisted fluorescence in situ hybridization technique was proposed. Compared with other detection techniques, fluorescence in situ hybridization (FISH) technology assisted by a fluorescence microscope has gradually gained favor in related fields due to its advantages of high detection specificity, high sensitivity, and strong experimental period. Combined with the basic overview of fluorescence microscopy and FISH technology, the advantages and application points of FISH technology assisted by fluorescence microscopy in the detection of the Her2 gene in breast cancer patients were studied and discussed. The results show that IHC can be used as the primary screening for HER2 gene status detection; IHC (2+) and IHC (3+) have false positives, which are related to chromosome 17 polysomy, so FISH should be done to confirm the diagnosis.

Reconstitution of Phase-Separated Signaling Clusters and Actin Polymerization on Supported Lipid Bilayers

Liquid-liquid phase separation driven by weak interactions between multivalent molecules contributes to the cellular organization by promoting the formation of biomolecular condensates. At membranes, phase separation can promote the assembly of transmembrane proteins with their cytoplasmic binding partners into micron-sized membrane-associated condensates. For example, phase separation promotes clustering of nephrin, a transmembrane adhesion molecule, resulting in increased Arp2/3 complex-dependent actin polymerization. In vitro reconstitution is a powerful approach to understand phase separation in biological systems. With a bottom-up approach, we can determine the molecules necessary and sufficient for phase separation, map the phase diagram by quantifying de-mixing over a range of molecular concentrations, assess the material properties of the condensed phase using fluorescence recovery after photobleaching (FRAP), and even determine how phase separation impacts downstream biochemical activity. Here, we describe a detailed protocol to reconstitute nephrin clusters on supported lipid bilayers with purified recombinant protein. We also describe how to measure Arp2/3 complex-dependent actin polymerization on bilayers using fluorescence microscopy. These different protocols can be performed independently or combined as needed. These general techniques can be applied to reconstitute and study phase-separated signaling clusters of many different receptors or to generally understand how actin polymerization is regulated at membranes.

Qudi-HiM: an open-source acquisition software package for highly multiplexed sequential and combinatorial optical imaging

Multiplexed sequential and combinatorial imaging enables the simultaneous detection of multiple biological molecules, e.g. proteins, DNA, or RNA, enabling single-cell spatial multi-omics measurements at sub-cellular resolution. Recently, we designed a multiplexed imaging approach (Hi-M) to study the spatial organization of chromatin in single cells. In order to enable Hi-M sequential imaging on custom microscope setups, we developed Qudi-HiM, a modular software package written in Python 3. Qudi-HiM contains modules to automate the robust acquisition of thousands of three-dimensional multicolor microscopy images, the handling of microfluidics devices, and the remote monitoring of ongoing acquisitions and real-time analysis. In addition, Qudi-HiM can be used as a stand-alone tool for other imaging modalities.

Qudi-HiM: an open-source acquisition software package for highly multiplexed sequential and combinatorial optical imaging

Multiplexed sequential and combinatorial imaging enables the simultaneous detection of multiple biological molecules, e.g. proteins, DNA, or RNA, enabling single-cell spatial multi-omics measurements at sub-cellular resolution. Recently, we designed a multiplexed imaging approach (Hi-M) to study the spatial organization of chromatin in single cells. In order to enable Hi-M sequential imaging on custom microscope setups, we developed Qudi-HiM, a modular software package written in Python 3. Qudi-HiM contains modules to automate the robust acquisition of thousands of three-dimensional multicolor microscopy images, the handling of microfluidics devices, and the remote monitoring of ongoing acquisitions and real-time analysis. In addition, Qudi-HiM can be used as a stand-alone tool for other imaging modalities.

Quantification of ruffle area and dynamics in live or fixed lung adenocarcinoma cells

Ruffles are actin-rich membrane protrusions implicated in actin reorganization and initiation of cell motility. Here, we describe methods for measuring and analyzing ruffle dynamics in live cells and average ruffle area per cell in fixed samples. The specific steps described are for the analysis of A549 lung adenocarcinoma cells, but the protocol can be applied to other cell types. The protocol has applications for dissecting the signaling events linked to ruffling. For complete details on the use and execution of this protocol, please refer to Cooke et al. (2021).

Multi-Modal Optical Imaging and Combined Phototherapy of Nasopharyngeal Carcinoma Based on a Nanoplatform

Nasopharyngeal carcinoma (NPC) is a common malignant tumor of the head and neck with a high incidence rate worldwide, especially in southern China. Phototheranostics in combination with nanoparticles is an integrated strategy for enabling simultaneous diagnosis, real-time monitoring, and administration of precision therapy for nasopharyngeal carcinoma (NPC). It has shown great potential in the field of cancer diagnosis and treatment owing to its unique noninvasive advantages. Many Chinese and international research teams have applied nano-targeted drugs to optical diagnosis and treatment technology to conduct multimodal imaging and collaborative treatment of NPC, which has become a hot research topic. In this review, we aimed to introduce the recent developments in phototheranostics of NPC based on a nanoplatform. This study aimed to elaborate on the applications of nanoplatform-based optical imaging strategies and treatment modalities, including fluorescence imaging, photoacoustic imaging, Raman spectroscopy imaging, photodynamic therapy, and photothermal therapy. This study is expected to provide a scientific basis for further research and development of NPC diagnosis and treatment.

Live cell microscopy: From image to insight

Live-cell microscopy is a powerful tool that can reveal cellular behavior as well as the underlying molecular processes. A key advantage of microscopy is that by visualizing biological processes, it can provide direct insights. Nevertheless, live-cell imaging can be technically challenging and prone to artifacts. For a successful experiment, many careful decisions are required at all steps from hardware selection to downstream image analysis. Facing these questions can be particularly intimidating due to the requirement for expertise in multiple disciplines, ranging from optics, biophysics, and programming to cell biology. In this review, we aim to summarize the key points that need to be considered when setting up and analyzing a live-cell imaging experiment. While we put a particular focus on yeast, many of the concepts discussed are applicable also to other organisms. In addition, we discuss reporting and data sharing strategies that we think are critical to improve reproducibility in the field.

Quiescent cancer cells resist T cell attack by forming an immunosuppressive niche

Immunotherapy is a promising treatment for triple-negative breast cancer (TNBC), but patients relapse, highlighting the need to understand the mechanisms of resistance. We discovered that in primary breast cancer, tumor cells that resist T cell attack are quiescent. Quiescent cancer cells (QCCs) form clusters with reduced immune infiltration. They also display superior tumorigenic capacity and higher expression of chemotherapy resistance and stemness genes. We adapted single-cell RNA-sequencing with precise spatial resolution to profile infiltrating cells inside and outside the QCC niche. This transcriptomic analysis revealed hypoxia-induced programs and identified more exhausted T cells, tumor-protective fibroblasts, and dysfunctional dendritic cells inside clusters of QCCs. This uncovered differential phenotypes in infiltrating cells based on their intra-tumor location. Thus, QCCs constitute immunotherapy-resistant reservoirs by orchestrating a local hypoxic immune-suppressive milieu that blocks T cell function. Eliminating QCCs holds the promise to counteract immunotherapy resistance and prevent disease recurrence in TNBC.

Strain-Level Variation and Diverse Host Bacterial Responses in Episymbiotic Saccharibacteria

Saccharibacteria (TM7), which are obligate episymbionts growing on the surface of host bacteria, may play an important role in oral disease, such as periodontitis (1, 2). As TM7 is a newly cultured lineage of bacteria, its research is limited by the small number of isolated representatives relative to the number of TM7 genomes assembled from culture-independent studies (3–5). A comprehensive view of both TM7 taxa and TM7 strain-level variations remains opaque. In this study, we expanded our previously developed TM7 baiting method into using many host bacteria in parallel, which allowed us to obtain 37 TM7 strains from the human oral cavity. These strains were further classified into low-enrichment (LE, n = 24) and high-enrichment (HE, n = 13) groups based on their proficiency at propagating on host bacteria. Of the 13 HE strains, 10 belong to “Candidatus Nanosynbacter sp.” strain HMT-352 (human microbial taxon) (6), enabling us to explore both the phenotypic and genomic strain variations within a single TM7 species. We show that TM7 HMT-352 strains exhibit a diverse host range and varied growth dynamics during the establishment of their episymbiotic relationship with host bacteria. Furthermore, despite HMT-352 strains sharing a majority of their genes, we identified several gene clusters that may play a pivotal role in host affinity. More importantly, our comparative analyses also provide TM7 gene candidates associated with strain-level phenotypic variation that may be important for episymbiotic interactions with host bacteria.

IMPORTANCE Candidate phylum radiation (CPR) bacteria comprise a poorly understood phylum that is estimated to encompass ∼26% of all diversity of domain bacteria. Among CPR bacteria, the Saccharibacteria lineage (TM7) is of particular interest, as it is found in high abundance in the mammal microbiome and has been associated with oral disease. While many CPR genomes, TM7 included, have been acquired through culture-independent methods, only a small number of representatives have been isolated. Such isolated representatives, however, shed light on the physiology, pathogenesis, and episymbiotic interactions of TM7. Combined with genomic analyses, experiments involving isolated representatives can distinguish phylogenetic to phenotypic discrepancies and better identify genes of importance. In this study, we utilized multiple host bacteria in parallel to isolate TM7 bacteria and examined strain-level variation in TM7 to reveal key genes that may drive TM7-host interactions. Our findings accentuate that broad phylogenetic characterization of CPR is the next step in understanding these bacteria.

Trends in selected fields of reference material production

For more than 110 years, BAM has been producing reference materials for a wide range of application fields. With the development of new analytical methods and new applications as well as continuously emerging more stringent requirements of laboratory accreditation with regard to quality control and metrological traceability, the demand and requirements for reference materials are increasing. This trend article gives an overview of general developments in the field of reference materials as well as developments in selected fields of application in which BAM is active. This includes inorganic and metal analysis, gas analysis, food and consumer products, and geological samples. In addition to these more traditional fields of application, developments in the areas of optical spectroscopy, particularly fluorescence methods, and nanomaterials are considered.

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model

Rigorous record-keeping and quality control are required to ensure the quality, reproducibility and value of imaging data. The 4DN Initiative and BINA here propose light Microscopy Metadata specifications that extend the OME data model, scale with experimental intent and complexity, and make it possible for scientists to create comprehensive records of imaging experiments.

What is the structure of our infrastructure? -A Review of UK Light Microscopy Facilities

Core Facilities and Technology Platforms are increasingly important components of the science research landscape. However, data on facility operations and staff careers are lacking to inform their development. Here we have surveyed 114 people working in 46 Light Microscopy (LM) facilities within the United Kingdom. Our survey explores issues around Career Progression, Facility Operations, and Funding. The data show that facilities are substantial repositories of equipment and knowledge which adapt to meet the needs of their local environments. Our report highlights the challenges faced by facility managers, institutions, and funders in evaluating facility performance and devising strategies to maximize the return on research funding investment. This article is protected by copyright. All rights reserved.