A Nanoplasmonic Assay for Point-of-Care Detection of Mannose-Binding Lectin in Human Serum.

Mannose-binding lectin (MBL) activates the complement system lectin pathway and subsequent inflammatory mechanisms. The incidence and outcome of many human diseases, such as brain ischemia and infections, are associated with and influenced by the activity and serum concentrations of MBL in body fluids. To quantify MBL levels, tests based on ELISA are used, requiring several incubation and washing steps and lengthy turnaround times. Here, we aimed to develop a nanoplasmonic assay for direct MBL detection in human serum at the point of care. Our assay is based on gold nanorods (GNRs) functionalized with mannose (Man-GNRs) via an amphiphilic linker. We experimentally determined the effective amount of sugar linked to the nanorods' surface, resulting in an approximate grafting density of 4 molecules per nm2, and an average number of 11 to 13 MBL molecules binding to a single nanoparticle. The optimal Man-GNRs concentration to achieve the highest sensitivity in MBL detection was 15 µg·mL-1. The specificity of the assay for MBL detection both in simple buffer and in complex pooled human sera was confirmed. Our label-free biosensor is able to detect MBL concentrations as low as 160 ng·mL-1 within 15 min directly in human serum via a one-step reaction and by using a microplate reader. Hence, it forms the basis for a fast, noninvasive, point-of-care assay for diagnostic indications and monitoring of disease and therapy.

Automatic quantification of myocardial remodeling features in human ventricular tissue from label-free microscopy.

The procedures used routinely for collagen and lipofuscin evaluation are, in many cases, qualitative, observer dependent, and disregard spatial distribution. Here, we present a protocol for automatic quantification and spatial characterization of collagen and lipofuscin from label-free microscopy images of human ventricular tissues. We describe the steps for sample collection, tissue processing, image acquisition, and quantification of collagen and lipofuscin. This protocol avoids discrepancies between observers and can be adapted to other tissues and species. For complete details on the use and execution of this protocol, please refer to García-Mendívil et al. (2022).1.

Live-Cell SOFI Correlation with SMLM and AFM Imaging.

Standard optical imaging is diffraction-limited and lacks the resolving power to visualize many of the organelles and proteins found within the cell. The advent of super-resolution techniques overcame this barrier, enabling observation of subcellular structures down to tens of nanometers in size; however these techniques require or are typically applied to fixed samples. This raises the question of how well a fixed-cell image represents the system prior to fixation. Here we present the addition of live-cell Super-Resolution Optical Fluctuation Imaging (SOFI) to a previously reported correlative process using Single Molecule Localization Microscopy (SMLM) and Atomic Force Microscopy (AFM). SOFI was used with fluorescent proteins and low laser power to observe cellular ultrastructure in live COS-7 cells. SOFI-SMLM-AFM of microtubules showed minimal changes to the microtubule network in the 20 min between live-cell SOFI and fixation. Microtubule diameters were also analyzed through all microscopies; SOFI found diameters of 249 ± 68 nm and SMLM was 71 ± 33 nm. AFM height measurements found microtubules to protrude 26 ± 13 nm above the surrounding cellular material. The correlation of SMLM and AFM was extended to two-color SMLM to image both microtubules and actin. Two target SOFI was performed with various fluorescent protein combinations. rsGreen1-rsKAME, rsGreen1-Dronpa, and ffDronpaF-rsKAME fluorescent protein combinations were determined to be suitable for two target SOFI imaging. This correlative application of super-resolution live-cell and fixed-cell imaging revealed minimal artifacts created for the imaged target structures through the sample preparation procedure and emphasizes the power of correlative microscopy.

Analysis of age-related left ventricular collagen remodeling in living donors: Implications in arrhythmogenesis.

Age-related fibrosis in the left ventricle (LV) has been mainly studied in animals by assessing collagen content. Using second-harmonic generation microscopy and image processing, we evaluated amount, aggregation and spatial distribution of LV collagen in young to old pigs, and middle-age and elder living donors. All collagen features increased when comparing adult and old pigs with young ones, but not when comparing adult with old pigs or middle-age with elder individuals. Remarkably, all collagen parameters strongly correlated with lipofuscin, a biological age marker, in humans. By building patient-specific models of human ventricular tissue electrophysiology, we confirmed that amount and organization of fibrosis modulated arrhythmia vulnerability, and that distribution should be accounted for arrhythmia risk assessment. In conclusion, we characterize the age-associated changes in LV collagen and its potential implications for ventricular arrhythmia development. Consistency between pig and human results substantiate the pig as a relevant model of age-related LV collagen dynamics.

Nanoscale characterization of drug-induced microtubule filament dysfunction using super-resolution microscopy.

BACKGROUND: The integrity of microtubule filament networks is essential for the roles in diverse cellular functions, and disruption of its structure or dynamics has been explored as a therapeutic approach to tackle diseases such as cancer. Microtubule-interacting drugs, sometimes referred to as antimitotics, are used in cancer therapy to target and disrupt microtubules. However, due to associated side effects on healthy cells, there is a need to develop safer drug regimens that still retain clinical efficacy. Currently, many questions remain open regarding the extent of effects on cellular physiology of microtubule-interacting drugs at clinically relevant and low doses. Here, we use super-resolution microscopies (single-molecule localization and optical fluctuation based) to reveal the initial microtubule dysfunctions caused by nanomolar concentrations of colcemid. RESULTS: We identify previously undetected microtubule (MT) damage caused by clinically relevant doses of colcemid. Short exposure to 30-80 nM colcemid results in aberrant microtubule curvature, with a trend of increased curvature associated to increased doses, and curvatures greater than 2 rad/µm, a value associated with MT breakage. Microtubule fragmentation was detected upon treatment with ≥ 100 nM colcemid. Remarkably, lower doses (< 20 nM after 5 h) led to subtle but significant microtubule architecture remodelling characterized by increased curvature and suppression of microtubule dynamics. CONCLUSIONS: Our results support the emerging hypothesis that microtubule-interacting drugs induce non-mitotic effects in cells, and establish a multi-modal imaging assay for detecting and measuring nanoscale microtubule dysfunction. The sub-diffraction visualization of these less severe precursor perturbations compared to the established antimitotic effects of microtubule-interacting drugs offers potential for improved understanding and design of anticancer agents.

Photochromic Fluorophores Enable Imaging of Lowly Expressed Proteins in the Autofluorescent Fungus Candida albicans.

Fluorescence microscopy is a standard research tool in many fields, although collecting reliable images can be difficult in systems characterized by low expression levels and/or high background fluorescence. We present the combination of a photochromic fluorescent protein and stochastic optical fluctuation imaging (SOFI) to deliver suppression of the background fluorescence. This strategy makes it possible to resolve lowly or endogenously expressed proteins, as we demonstrate for Gcn5, a histone acetyltransferase required for complete virulence, and Erg11, the target of the azole antifungal agents in the fungal pathogen Candida albicans We expect that our method can be readily used for sensitive fluorescence measurements in systems characterized by high background fluorescence.IMPORTANCE Understanding the spatial and temporal organization of proteins of interest is key to unraveling cellular processes and identifying novel possible antifungal targets. Only a few therapeutic targets have been discovered in Candida albicans, and resistance mechanisms against these therapeutic agents are rapidly acquired. Fluorescence microscopy is a valuable tool to investigate molecular processes and assess the localization of possible antifungal targets. Unfortunately, fluorescence microscopy of C. albicans suffers from extensive autofluorescence. In this work, we present the use of a photochromic fluorescent protein and stochastic optical fluctuation imaging to enable the imaging of lowly expressed proteins in C. albicans through the suppression of autofluorescence. This method can be applied in C. albicans research or adapted for other fungal systems, allowing the visualization of intricate processes.

Structure-Function Dataset Reveals Environment Effects within a Fluorescent Protein Model System

Anisotropic environments can drastically alter the spectroscopy and photochemistry of molecules, leading to complex structure-function relationships. We examined this using fluorescent proteins as easy-to-modify model systems. Starting from a single scaffold, we have developed a range of 27 photochromic fluorescent proteins that cover a broad range of spectroscopic properties, including the determination of 43 crystal structures. Correlation and principal component analysis confirmed the complex relationship between structure and spectroscopy, but also allowed us to identify consistent trends and to relate these to the spatial organization. We find that changes in spectroscopic properties can come about through multiple underlying mechanisms, of which polarity, hydrogen bonding and presence of water molecules are key modulators. We anticipate that our findings and rich structure/spectroscopy dataset can open opportunities for the development and evaluation of new and existing protein engineering methods.

Separation of spectrally overlapping fluorophores using intra-exposure excitation modulation.

Multicolor fluorescence imaging is an excellent method for the simultaneous visualization of multiple structures, although it is limited by the available spectral window. More labels can be measured by distinguishing these on properties, such as their fluorescence dynamics, but usually these dynamics must be directly resolvable by the instrument. We propose an approach to distinguish emitters over a much broader range of light-induced dynamics by combining fast modulation of the light source with the detection of the time-integrated fluorescence. We demonstrate our method by distinguishing four spectrally overlapping photochromic fluorophores within Escherichia coli bacteria, showing that we can accurately classify all four probes by acquiring just two to four fluorescence images. Our strategy expands the range of probes and processes that can be used for fluorescence multiplexing.

QCM-D Study of Time-Resolved Cell Adhesion and Detachment: Effect of Surface Free Energy on Eukaryotes and Prokaryotes.

Cell-material interactions are crucial for many biomedical applications, including medical implants, tissue engineering, and biosensors. For implants, while the adhesion of eukaryotic host cells is desirable, bacterial adhesion often leads to infections. Surface free energy (SFE) is an important parameter that controls short- and long-term eukaryotic and prokaryotic cell adhesion. Understanding its effect at a fundamental level is essential for designing materials that minimize bacterial adhesion. Most cell adhesion studies for implants have focused on correlating surface wettability with mammalian cell adhesion and are restricted to short-term time scales. In this work, we used quartz crystal microbalance with dissipation monitoring (QCM-D) and electrical impedance analysis to characterize the adhesion and detachment of S. cerevisiae and E. coli, serving as model eukaryotic and prokaryotic cells within extended time scales. Measurements were performed on surfaces displaying different surface energies (Au, SiO2, and silanized SiO2). Our results demonstrate that tuning the surface free energy of materials is a useful strategy for selectively promoting eukaryotic cell adhesion and preventing bacterial adhesion. Specifically, we show that under flow and steady-state conditions and within time scales up to ∼10 h, a high SFE, especially its polar component, enhances S. cerevisiae adhesion and hinders E. coli adhesion. In the long term, however, both cells tend to detach, but less detachment occurs on surfaces with a high dispersive SFE contribution. The conclusions on S. cerevisiae are also valid for a second eukaryotic cell type, being the human embryonic kidney (HEK) cells on which we performed the same analysis for comparison. Furthermore, each cell adhesion phase is associated with unique cytoskeletal viscoelastic states, which are cell-type-specific and surface free energy-dependent and provide insights into the underlying adhesion mechanisms.

An extended quantitative model for super-resolution optical fluctuation imaging (SOFI).

Super-resolution optical fluctuation imaging (SOFI) provides super-resolution (SR) fluorescence imaging by analyzing fluctuations in the fluorophore emission. The technique has been used both to acquire quantitative SR images and to provide SR biosensing by monitoring changes in fluorophore blinking dynamics. Proper analysis of such data relies on a fully quantitative model of the imaging. However, previous SOFI imaging models made several assumptions that can not be realized in practice. In this work we address these limitations by developing and verifying a fully quantitative model that better approximates real-world imaging conditions. Our model shows that (i) SOFI images are free of bias, or can be made so, if the signal is stationary and fluorophores blink independently, (ii) allows a fully quantitative description of the link between SOFI imaging and probe dynamics, and (iii) paves the way for more advanced SOFI image reconstruction by offering a computationally fast way to calculate SOFI images for arbitrary probe, sample and instrumental properties.

Optimizing the fluorescent protein toolbox and its use.

Fluorescent proteins (FPs) and fluorescent protein-derived biosensors are indispensable tools in life sciences. They make it possible to probe the location, activity, or interaction of molecules of interest from a subcellular to a multicellular scale. The desire for high-resolution and multidimensional information imposes continuously increasing demands on the performance of the employed probes leading to a continued need for optimization and integration of additional features, such as phototransformable behavior. This review highlights the latest advances in FP engineering, which increase throughput and tailor the improvements directly to the envisioned experiments. Additionally, we discuss recent alternative approaches to introduce or alter phototransformable behavior and describe selected applications of phototransformable behavior in biosensors.

Sensitive and specific detection of E. coli using biomimetic receptors in combination with a modified heat-transfer method.

We report on a novel biomimetic sensor that allows sensitive and specific detection of Escherichia coli (E. coli) bacteria in a broad concentration range from 102 up to 106 CFU/mL in both buffer fluids and relevant food samples (i.e. apple juice). The receptors are surface-imprinted polyurethane layers deposited on stainless-steel chips. Regarding the transducer principle, the sensor measures the increase in thermal resistance between the chip and the liquid due to the presence of bacteria captured on the receptor surface. The low noise level that enables the low detection limit originates from a planar meander element that serves as both a heater and a temperature sensor. Furthermore, the experiments show that the presence of bacteria in a liquid enhances the thermal conductivity of the liquid itself. Reference tests with a set of other representative species of Enterobacteriaceae, closely related to E. coli, indicate a very low cross-sensitivity with a sensor response at or below the noise level.

Reduced Fluorescent Protein Switching Fatigue by Binding-Induced Emissive State Stabilization.

Reversibly switchable fluorescent proteins (RSFPs) enable advanced fluorescence imaging, though the performance of this imaging crucially depends on the properties of the labels. We report on the use of an existing small binding peptide, named Enhancer, to modulate the spectroscopic properties of the recently developed rsGreen series of RSFPs. Fusion constructs of Enhancer with rsGreen1 and rsGreenF revealed an increased molecular brightness and pH stability, although expression in living E. coli or HeLa cells resulted in a decrease of the overall emission. Surprisingly, Enhancer binding also increased off-switching speed and resistance to switching fatigue. Further investigation suggested that the RSFPs can interconvert between fast- and slow-switching emissive states, with the overall protein population gradually converting to the slow-switching state through irradiation. The Enhancer modulates the spectroscopic properties of both states, but also preferentially stabilizes the fast-switching state, supporting the increased fatigue resistance. This work demonstrates how the photo-physical properties of RSFPs can be influenced by their binding to other small proteins, which opens up new horizons for applications that may require such modulation. Furthermore, we provide new insights into the photoswitching kinetics that should be of general consideration when developing new RSFPs with improved or different photochromic properties.

Correcting for photodestruction in super-resolution optical fluctuation imaging.

Super-resolution optical fluctuation imaging overcomes the diffraction limit by analyzing fluctuations in the fluorophore emission. A key assumption of the imaging is that the fluorophores are independent, though this is invalidated in the presence of photodestruction. In this work, we evaluate the effect of photodestruction on SOFI imaging using theoretical considerations and computer simulations. We find that photodestruction gives rise to an additional signal that does not present an easily interpretable view of the sample structure. This additional signal is strong and the resulting images typically exhibit less noise. Accordingly, these images may be mis-interpreted as being more visually pleasing or more informative. To address this uncertainty, we develop a procedure that can robustly estimate to what extent any particular experiment is affected by photodestruction. We also develop a detailed assessment methodology and use it to evaluate the performance of several correction algorithms. We identify two approaches that can correct for the presence of even strong photodestruction, one of which can be implemented directly in the SOFI calculation software.

Model-free uncertainty estimation in stochastical optical fluctuation imaging (SOFI) leads to a doubled temporal resolution.

Stochastic optical fluctuation imaging (SOFI) is a super-resolution fluorescence imaging technique that makes use of stochastic fluctuations in the emission of the fluorophores. During a SOFI measurement multiple fluorescence images are acquired from the sample, followed by the calculation of the spatiotemporal cumulants of the intensities observed at each position. Compared to other techniques, SOFI works well under conditions of low signal-to-noise, high background, or high emitter densities. However, it can be difficult to unambiguously determine the reliability of images produced by any superresolution imaging technique. In this work we present a strategy that enables the estimation of the variance or uncertainty associated with each pixel in the SOFI image. In addition to estimating the image quality or reliability, we show that this can be used to optimize the signal-to-noise ratio (SNR) of SOFI images by including multiple pixel combinations in the cumulant calculation. We present an algorithm to perform this optimization, which automatically takes all relevant instrumental, sample, and probe parameters into account. Depending on the optical magnification of the system, this strategy can be used to improve the SNR of a SOFI image by 40% to 90%. This gain in information is entirely free, in the sense that it does not require additional efforts or complications. Alternatively our approach can be applied to reduce the number of fluorescence images to meet a particular quality level by about 30% to 50%, strongly improving the temporal resolution of SOFI imaging.

Sparse deconvolution of high-density super-resolution images.

In wide-field super-resolution microscopy, investigating the nanoscale structure of cellular processes, and resolving fast dynamics and morphological changes in cells requires algorithms capable of working with a high-density of emissive fluorophores. Current deconvolution algorithms estimate fluorophore density by using representations of the signal that promote sparsity of the super-resolution images via an L1-norm penalty. This penalty imposes a restriction on the sum of absolute values of the estimates of emitter brightness. By implementing an L0-norm penalty--on the number of fluorophores rather than on their overall brightness--we present a penalized regression approach that can work at high-density and allows fast super-resolution imaging. We validated our approach on simulated images with densities up to 15 emitters per µm(-2) and investigated total internal reflection fluorescence (TIRF) data of mitochondria in a HEK293-T cell labeled with DAKAP-Dronpa. We demonstrated super-resolution imaging of the dynamics with a resolution down to 55 nm and a 0.5 s time sampling.

RefSOFI for Mapping Nanoscale Organization of Protein-Protein Interactions in Living Cells.

It has become increasingly clear that protein-protein interactions (PPIs) are compartmentalized in nanoscale domains that define the biochemical architecture of the cell. Despite tremendous advances in super-resolution imaging, strategies to observe PPIs at sufficient resolution to discern their organization are just emerging. Here we describe a strategy in which PPIs induce reconstitution of fluorescent proteins (FPs) that are capable of exhibiting single-molecule fluctuations suitable for stochastic optical fluctuation imaging (SOFI). Subsequently, spatial maps of these interactions can be resolved in super-resolution in living cells. Using this strategy, termed reconstituted fluorescence-based SOFI (refSOFI), we investigated the interaction between the endoplasmic reticulum (ER) Ca(2+) sensor STIM1 and the pore-forming channel subunit ORAI1, a crucial process in store-operated Ca(2+) entry (SOCE). Stimulating SOCE does not appear to change the size of existing STIM1/ORAI1 interaction puncta at the ER-plasma membrane junctions, but results in an apparent increase in the number of interaction puncta.

Expression-Enhanced Fluorescent Proteins Based on Enhanced Green Fluorescent Protein for Super-resolution Microscopy.

"Smart fluorophores", such as reversibly switchable fluorescent proteins, are crucial for advanced fluorescence imaging. However, only a limited number of such labels is available, and many display reduced biological performance compared to more classical variants. We present the development of robustly photoswitchable variants of enhanced green fluorescent protein (EGFP), named rsGreens, that display up to 30-fold higher fluorescence in E. coli colonies grown at 37 °C and more than 4-fold higher fluorescence when expressed in HEK293T cells compared to their ancestor protein rsEGFP. This enhancement is not due to an intrinsic increase in the fluorescence brightness of the probes, but rather due to enhanced expression levels that allow many more probe molecules to be functional at any given time. We developed rsGreens displaying a range of photoswitching kinetics and show how these can be used for multimodal diffraction-unlimited fluorescence imaging such as pcSOFI and RESOLFT, achieving a spatial resolution of ∼70 nm. By determining the first ever crystal structures of a negative reversibly switchable FP derived from Aequorea victoria in both the "on"- and "off"-conformation we were able to confirm the presence of a cis-trans isomerization and provide further insights into the mechanisms underlying the photochromism. Our work demonstrates that genetically encoded "smart fluorophores" can be readily optimized for biological performance and provides a practical strategy for developing maturation- and stability-enhanced photochromic fluorescent proteins.