Contribution of autofluorescence from intracellular proteins in multiphoton fluorescence lifetime imaging

The promise and peril of comparing fluorescence lifetime in biology revealed by simulations

Signaling dynamics are crucial in biological systems, and biosensor-based real-time imaging has revolutionized their analysis. Fluorescence lifetime imaging microscopy (FLIM) excels over the widely used fluorescence intensity imaging by allowing the measurement of absolute signal levels, independent of sensor concentration. This capability enables the comparison of signaling dynamics across different animals, body regions, and timeframes. However, FLIM's advantage can be compromised by factors like autofluorescence in biological experiments. To address this, we introduce FLiSimBA, a flexible computational framework for realistic F luorescence Li fetime Sim ulation for B iological A pplications. Through simulations, we analyze the signal-to-noise ratios of fluorescence lifetime data, determining measurement uncertainty and providing necessary error bars for lifetime measurements. Furthermore, we challenge the belief that fluorescence lifetime is unaffected by sensor expression and establish quantitative limits to this insensitivity in biological applications. Additionally, we propose innovations, notably multiplexed dynamic imaging that combines fluorescence intensity and lifetime measurements. This innovation can transform the number of signals that can be simultaneously monitored, thereby enabling a systems approach in studying signaling dynamics. Thus, by incorporating diverse factors into our simulation framework, we uncover surprises, identify limitations, and propose advancements for fluorescence lifetime imaging in biology. This quantitative framework supports rigorous experimental design, facilitates accurate data interpretation, and paves the way for technological advancements in fluorescence lifetime imaging.

iSERS: from nanotag design to protein assays and ex vivo imaging

Proteins are an eminently important class of ubiquitous biomacromolecules with diverse biological functions, and numerous techniques for their detection, quantification, and localisation have been developed. Many of these methods exploit the selectivity arising from molecular recognition of proteins/antigens by immunoglobulins. The combination of surface-enhanced Raman scattering (SERS) with such "immuno"-techniques to immuno-SERS (iSERS) is the central topic of this review, which is focused on colloidal SERS nanotags, i.e., molecularly functionalised noble metal nanoparticles conjugated to antibodies, for their use in protein assays and ex vivo imaging. After contrasting the fundamental differences between label-free SERS and iSERS, including a balanced description of the advantages and drawbacks of the latter, we describe the usual workflow of iSERS experiments. Milestones in the development of the iSERS technology are summarised from a historical perspective. By highlighting selected examples from the literature, we illustrate the conceptual progress that has been achieved in the fields of iSERS-based protein assays and ex vivo imaging. Finally, we attempt to predict what is necessary to fully exploit the transformative potential of the iSERS technology by stimulating the transition from research in academic labs into applications for the benefit of our society.

Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding

Organoid models have been used to address important questions in developmental and cancer biology, tissue repair, advanced modelling of disease and therapies, among other bioengineering applications. Such 3D microenvironmental models can investigate the regulation of cell metabolism, and provide key insights into the mechanisms at the basis of cell growth, differentiation, communication, interactions with the environment and cell death. Their accessibility and complexity, based on 3D spatial and temporal heterogeneity, make organoids suitable for the application of novel, dynamic imaging microscopy methods, such as fluorescence lifetime imaging microscopy (FLIM) and related decay time-assessing readouts. Several biomarkers and assays have been proposed to study cell metabolism by FLIM in various organoid models. Herein, we present an expert-opinion discussion on the principles of FLIM and PLIM, instrumentation and data collection and analysis protocols, and general and emerging biosensor-based approaches, to highlight the pioneering work being performed in this field.

Quantitative multiphoton imaging of cell metabolism, stromal fibers, and keratinization enables label-free discrimination of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) features atypical clinical manifestations and a low 5-year survival rate (< 5% in many developing countries where most of the disease occurs). Precise ESCC detection and grading toward timely and effective intervention are therefore crucial. In this study, we propose a multidimensional, slicing-free, and label-free histopathological evaluation method based on multispectral multiphoton fluorescence lifetime imaging microscopy (MM-FLIM) for precise ESCC identification. To assess the feasibility of this method, comparative imaging on fresh human biopsy specimens of different ESCC grades is performed. By constructing fluorescence spectrum- and lifetime-coded images, ESCC-induced morphological variations are unveiled. Further quantification of cell metabolism and stromal fibers reveals potential indicators for ESCC detection and grading. The specific identification of keratin pearls provides additional support for the early detection of ESCC. These findings demonstrate the viability of using MM-FLIM and the series of derived indicators for histopathological evaluation of ESCC. As there is an increasing interest in developing multiphoton endoscopes and multiphoton FLIM systems for clinical use, the proposed method would probably allow noninvasive, label-free, and multidimensional histological detection and grading of ESCC in the future.