Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis.

Animal models have proven integral to broadening our understanding of complex cardiac diseases but have been hampered by significant species-dependent differences in cellular physiology. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have shown great promise in the modelling of cardiac diseases despite limitations in functional and structural maturity. 3D stem cell-derived cardiac models represent a step towards mimicking the intricate microenvironment present in the heart as an in vitro model. Incorporation of non-myocyte cell types, such as cardiac fibroblasts, into engineered heart tissue models (EHTs) can help better recapitulate the cell-to-cell and cell-to-matrix interactions present in the human myocardium. Integration of human-induced pluripotent stem cell-derived cardiac fibroblasts (hiPSC-CFs) and hiPSC-CM into EHT models enables the generation of a genetically homogeneous modelling system capable of exploring the abstruse structural and electrophysiological interplay present in cardiac pathophysiology. Furthermore, the construction of more physiologically relevant 3D cardiac models offers great potential in the replacement of animals in heart disease research. Here we describe efficient and reproducible protocols for the differentiation of hiPSC-CMs and hiPSC-CFs and their subsequent assimilation into EHTs. The resultant EHT consists of longitudinally arranged iPSC-CMs, incorporated alongside hiPSC-CFs. EHTs with both hiPSC-CMs and hiPSC-CFs exhibit slower beating frequencies and enhanced contractile force compared to those composed of hiPSC-CMs alone. The modified protocol may help better characterise the interplay between different cell types in the myocardium and their contribution to structural remodelling and cardiac fibrosis.

AbstractThe mammalian plasma membrane is known to contain domains with varying lipid composition and biophysical properties. However, studying these membrane lipid domains presents challenges due to their predicted morphological similarity to the bulk membrane and their scale being below the classical resolution limit of optical microscopy. To address this, we combine the solvatochromic probe di-4-ANEPPDHQ, which reports on its biophysical environment through changes in its fluorescence emission, with spectrally resolved single-molecule localisation microscopy. The resulting data comprises nanometre-precision localisation coordinates and a generalised polarisation value related to the probe’s environment – a marked point pattern. We introduce quantification algorithms based on topological data analysis (PLASMA) to detect and map nano-domains in this marked data, demonstrating their effectiveness in both artificial membranes and live cells. By leveraging environmentally sensitive fluorophores, multi-modal single molecule localisation microscopy, and advanced analysis methods, we achieve nanometre scale mapping of membrane properties and assess changes in response to external perturbation with methyl-β-cyclodextrin. This integrated methodology represents an integrated toolset for investigating marked point pattern data at nanometre spatial scales.

Determining the label to target ratio, also known as the degree of labeling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labeling is beneficial for fluorescence microscopy in general. Yet robust, versatile and easy-to-use tools for measuring cell-specific labeling efficiencies are not available. Here we present a DOL determination technique named protein-tag DOL (ProDOL), which enables fast quantification and optimization of protein-tag labeling. With ProDOL various factors affecting labeling efficiency, including substrate type, incubation time and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how human immunodeficiency virus-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adapter protein SLP-76 in signaling microclusters. ProDOL proved to be a versatile and robust tool for labeling calibration, enabling determination of labeling efficiencies, optimization of strategies and quantification of protein stoichiometry. Protein-tag degree of labeling (ProDOL) is a versatile reference-based approach for experimentally determining the degree of target labeling for improved protein counting and quantification and for optimizing labeling protocols in fixed and live cells.

Determining the label to target ratio, also known as degree of labelling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labelling is beneficial for fluorescence microscopy in general. Yet, robust, versatile, and easy-to-use tools for measuring cell-specific labelling efficiencies are not available. This study presents a novel DOL determination technique named Protein-tag DOL (ProDOL), which enables fast DOL measurements and optimisation of protein-tag labelling. With ProDOL various factors affecting labelling efficiency, including substrate type, incubation time, and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how HIV-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adaptor protein SLP-76 in signalling microclusters. ProDOL proved to be a versatile and robust tool for labelling calibration, enabling determination of labelling efficiencies, optimisation of strategies, and quantification of protein stoichiometry.

The counting of discrete photobleaching steps in fluorescence microscopy is ideally suited to study protein complex stoichiometry in situ. The counting range of photobleaching step analysis has been significantly improved with more-sophisticated algorithms for step detection, albeit at an increasing computational cost and with the necessity for high-quality data. Here, we address concerns regarding robustness, automation, and experimental validation, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labeling strategies with respect to their molecular brightness, photostability, and photoblinking. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we validate the developed methods with experimental data acquired on DNA origami labeled with defined fluorophore numbers, demonstrating counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis by counting labeled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated manner.

AbstractThe composition of cellular structures on the nanoscale is a key determinant of macroscopic functions in cell biology and beyond. Different fluorescence single-molecule techniques have proven ideally suited for measuring protein copy numbers of cellular structures in intact biological samples. Of these, photobleaching step analysis poses minimal demands on the microscope and its counting range has significantly improved with more sophisticated algorithms for step detection, albeit at an increasing computational cost. Here, we present a comprehensive framework for photobleaching step analysis, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labelling strategies with respect to their molecular brightness and photostability. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we benchmark the framework with experimental data acquired on DNA origami labeled with defined fluorophore numbers to demonstrate counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis for robust protein counting by counting labelled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated fashion.

Fluorogenic probes for bioorthogonal labeling chemistry are highly beneficial to reduce background signal in fluorescence microscopy imaging. 1,2,4,5-Tetrazines are known substrates for the bioorthogonal inverse electron demand Diels-Alder reaction (DAinv) and tetrazine substituted fluorophores can exhibit fluorogenic properties. Herein, we report the synthesis of a palette of novel fluorogenic tetrazine dyes derived from widely-used fluorophores that cover the entire emission range from green to far-red. We demonstrate the power of the new fluorogenic probes in fixed and live cell labeling experiments and present the first example of intracellular live cell protein imaging using tetrazine-based probes under no-wash conditions.

Fluorogenic probes for bioorthogonal labeling chemistry are highly beneficial to reduce background signal in fluorescence microscopy imaging.