Biological imaging, combined with molecular insights into genes and proteins, holds immense promise for deepening our understanding of complex cellular systems and accelerating the development of predictive, personalized therapies for human health. To fully realize this potential at scale-and harness the power of AI/ML to extract novel biological insights and therapeutic interventions-it is necessary to transition from siloed datasets to globally shared, rigorously annotated, and computationally ready image data. This demands systematic harmonization of multidimensional bioimaging data, where interoperable formats, and standardized context-rich annotation, quality controls, and analytical pipelines transform scattered observations into a coherent knowledge base ripe for computational mining. Only this machine-actionable aggregation can provide the substrate for AI/ML to extract mechanistic insights into fundamental biological mechanisms, novel diagnostic biomarkers and intervention targets. Enabling seamless image data sharing in the life sciences requires addressing two key areas. The first is outlined in an accompanying publication, Enabling Global Image Data Sharing in the Life Sciences, which focuses on the publicly available repositories needed to share digital array data 1. This White Paper details a comprehensive set of requirements for integrated image data and metadata management - from acquisition through dissemination - ensuring the contextual information necessary for assessing quality, interpreting scientific validity, and enabling meaningful reuse remains intrinsically linked to the data throughout its lifecycle. Critically, it recognizes that generating harmonized, well-annotated publicly available corpora of FAIR bioimage data requires these datasets to be "FAIR-from-the-start" - an objective that can only be achieved by enabling experimental scientists to manage, organize, and analyze their data according to community standards from the very first experiment. Building on recent progress made by the bioimaging field towards establishing shared practices for bioimaging Quality Control (QC) and metadata capture, we present actionable recommendations to advance these efforts through embedding researcher-friendly integrated software infrastructure directly into pre-publication workflows, thus transforming disorganized data capture into structured, shareable resources ready for aggregation and reuse. Our ultimate goal is to expand the use of streamlined tools and practices thus transforming how researchers capture, annotate, analyze and eventually publish bioimaging data thus laying the foundation for a new era of data-driven discovery.

Spectral imaging is a fluorescence microscopy technique with several applications, including imaging of environment-sensitive probes, spectral unmixing and identification of fluorescent species. In confocal microscopes not equipped with a spectral detection unit, spectral images can be obtained using the lambda scan mode of the microscope, namely the sequential acquisition of images using a tunable emission filter or other dispersive optical elements. Unfortunately, the lambda scan mode has poor temporal resolution, is a photon-wasting technique, and is not ideal for the spectral imaging of live samples. Here, we describe a spectral imaging method that can be implemented on commercial confocal microscopes not equipped with a spectral detector. The method is based on simultaneous image acquisition in 4 contiguous spectral channels and spectral phasor analysis. We demonstrate that this method can be easily implemented on a Leica confocal laser scanning microscope, with better photon efficiency and temporal resolution than the lambda scan mode. We perform a 4-channel (4 C) spectral phasor analysis of live cells stained with the environment-sensitive ACDAN and Nile Red dyes. We can distinguish changes in spectral emission in the order of 5 nm between different subcellular compartments. We show that 4 C-spectral phasor can be used to decompose the Nile Red signal into 2 components and perform 3-color imaging in combination with a DNA dye in live organoids. Finally, we show that the 4 C-spectral phasor can be also used to unmix the signal of fluorescent proteins with overlapping emission spectra such as mEmerald and EYFP.

Mycobacteria, including pathogens like Mycobacterium tuberculosis, exhibit unique growth patterns and cell envelope structures that challenge our understanding of bacterial physiology. This study sheds light on FhaA, a conserved protein in Mycobacteriales, revealing its pivotal role in coordinating cell envelope biogenesis and asymmetric growth. The elucidation of the FhaA interactome in living mycobacterial cells reveals its participation in the protein network orchestrating cell envelope biogenesis and cell elongation/division. By manipulating FhaA levels, we uncovered its influence on cell morphology, cell envelope organization, and the localization of peptidoglycan biosynthesis machinery. Notably, fhaA deletion disrupted the characteristic asymmetric growth of mycobacteria, highlighting its importance in maintaining this distinctive feature. Our findings position FhaA as a key regulator in a complex protein network, orchestrating the asymmetric distribution and activity of cell envelope biosynthetic machinery. This work not only advances our understanding of mycobacterial growth mechanisms but also identifies FhaA as a potential target for future studies on cell envelope biogenesis and bacterial growth regulation. These insights into the fundamental biology of mycobacteria may pave the way for novel approaches to combat mycobacterial infections addressing the ongoing challenge of diseases like tuberculosis in global health. IMPORTANCE Mycobacterium tuberculosis, the bacterium responsible for tuberculosis, remains a global health concern. Unlike most well-studied model bacilli, mycobacteria possess a distinctive and complex cell envelope, as well as an asymmetric polar growth mode. However, the proteins and mechanisms that drive cell asymmetric elongation in these bacteria are still not well understood. This study sheds light on the role of the protein FhaA in this process. Our findings demonstrate that FhaA localizes at the septum and asymmetrically to the poles, with a preference for the fast-growing pole. Furthermore, we showed that FhaA is essential for population heterogeneity and asymmetric polar elongation and plays a role in the precise subcellular localization of the cell wall biosynthesis machinery. Mycobacterial asymmetric elongation results in a physiologically heterogeneous bacterial population which is important for pathogenicity and response to antibiotics, stressing the relevance of identifying new factors involved in these still poorly characterized processes.

Fluorescence is one of the most widely used techniques in biological sciences. Its exceptional sensitivity and versatility make it a tool of first choice for quantitative studies in biophysics. The concept of phasors, originally introduced by Charles Steinmetz in the late 19th century for analyzing alternating current circuits, has since found applications across diverse disciplines, including fluorescence spectroscopy. The main idea behind fluorescence phasors was posited by Gregorio Weber in 1981. By analyzing the complementary nature of pulse and phase fluorometry data, he shows that two magnitudes -denoted as G and S- derived from the frequency-domain fluorescence measurements correspond to the real and imaginary part of the Fourier transform of the fluorescence intensity in the time domain. This review provides a historical perspective on how the concept of phasors originates and how it integrates into fluorescence spectroscopy. We discuss their fundamental algebraic properties, which enable intuitive model-free analysis of fluorescence data despite the complexity of the underlying phenomena. Some applications in biophysics illustrate the power of this approach in studying diverse phenomena, including protein folding, protein interactions, phase transitions in lipid mixtures and formation of high-order structures in nucleic acids.

Neospora caninum is known to manipulate host cell organelles and recruit lipids for its survival. However, the impact of this lipid redistribution on host cell membranes remains poorly understood. This study used LAURDAN fluorescence, hyperspectral imaging, and phasor plot analysis to investigate how N. caninum modifies membrane order in Vero cells. The results revealed a significant decrease in host cell plasma and internal membrane order upon infection, suggesting that cholesterol is redistributed from the host plasma membrane to the parasitophorous vacuoles. To mimic cholesterol depletion, uninfected cells were treated with methyl-β-cyclodextrin (MBCD), which increased membrane fluidity. Conversely, replenishing infected cells with cholesterol-loaded MBCD restored membrane fluidity to levels lower than control cells, indicating cholesterol enrichment. These findings provide novel insights into how N. caninum modulates host cell membrane dynamics through lipid manipulation, potentially aiding its intracellular survival.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique offering profound insights into a broad spectrum of biological processes such as metabolic imaging, protein–protein interactions and live-cell intracellular dynamics. The future of FLIM appears promising, with continuous technological advancements for time-resolved measurements pushing the boundaries for spatiotemporal information. However, the growth of the FLIM community has been slower, owing to the requirement for specialized training and technology. This Primer aims to address this gap by providing a comprehensive overview of FLIM principles, methods and analysis. We discuss various methods for measuring fluorescence lifetimes, including time-tagging and phase-modulation shift methods, along with their implementations and setup variations. Additionally, we explore different avenues for data analysis, with a specific focus on the phasor approach and its crucial considerations. Furthermore, we present a range of applications demonstrating versatility and usability of FLIM. Limitations and optimization strategies are also discussed, covering methodological constraints, equipment limitations and potential errors, along with their solutions. By sharing our expertise, we aim to expand FLIM to broader audiences while reinforcing concepts within the FLIM community. This Primer seeks to inspire bioimaging researchers to fully embrace FLIM, thereby advancing our understanding of complex biological systems. Fluorescence lifetime imaging microscopy can offer insights into biological processes such as metabolic imaging, protein–protein interactions and live-cell intracellular dynamics. In this Primer, Torrado et al. discuss methods for measuring fluorescence lifetimes, including time-tagging and phase-modulation shift methods, along with fluorescence lifetime imaging microscopy setup variations.

In September 2023, the two largest bioimaging networks in the Americas, Latin America Bioimaging (LABI) and BioImaging North America (BINA), came together during a 1-week meeting in Mexico. This meeting provided opportunities for participants to interact closely with decision-makers from imaging core facilities across the Americas. The meeting was held in a hybrid format and attended in-person by imaging scientists from across the Americas, including Canada, the United States, Mexico, Colombia, Peru, Argentina, Chile, Brazil and Uruguay. The aims of the meeting were to discuss progress achieved over the past year, to foster networking and collaborative efforts among members of both communities, to bring together key members of the international imaging community to promote the exchange of experience and expertise, to engage with industry partners, and to establish future directions within each individual network, as well as common goals. This meeting report summarises the discussions exchanged, the achievements shared, and the goals set during the LABIxBINA2023: Bioimaging across the Americas meeting.

Melanoma diagnosis typically involves a dermatopathologist examining hematoxylin and eosin (H&E) slides under a microscope to search for specific features. Unfortunately, no single molecular marker can reliably differentiate melanoma from benign lesions such as nevi. We explored the use of autofluorescence molecules within tissues to help identify melanoma by providing molecular fingerprints indicative of degenerated melanocytes. Using UV excitation and a commercial spectral confocal microscope, the study acquired label-free hyperspectral imaging (HSI) data from whole-slice samples and employed spectral phasor analysis to investigate autofluorescence patterns in melanoma compared to intradermal nevi.

Membrane wetting by biomolecular condensates recently emerged as an important phenomenon in cell biology, playing a key role in diverse processes across different organisms. By performing a systematic analysis of the interaction of protein and polymer condensates with giant unilamellar vesicles as model membranes, we have previously demonstrated that these interactions can lead to remodeling processes, governed by the interplay of adhesion, membrane elasticity, and interfacial tension. Here, we show that condensate wetting can promote the stabilization of damaged membranes, uncovering a new mechanism for biomolecular condensates in cell physiology.

CUTie2 is a FRET-based cGMP biosensor tested so far only in cells. To expand its use to multicellular organisms we generated two transgenic Drosophila melanogaster strains that express the biosensor in a tissue-dependent manner. CUTie2 expression and subcellular localization was verified by confocal microscopy. The performance of CUTie2 was analyzed on dissected larval brains by hyperspectral microscopy and flow cytometry. Both approaches confirmed its responsivity, and the latter showed a rapid and reversible change in the fluorescence of the FRET acceptor upon cGMP treatment. This validated reporter system may prove valuable for studying cGMP signaling at organismal level.

IntroductionMelanoma diagnosis traditionally relies on microscopic examination of hematoxylin and eosin (H&E) slides by dermatopathologists to search for specific architectural and cytological features. Unfortunately, no single molecular marker exists to reliably differentiate melanoma from benign lesions such as nevi. This study explored the potential of autofluorescent molecules within tissues to provide molecular fingerprints indicative of degenerated melanocytes in melanoma.MethodsUsing hyperspectral imaging (HSI) and spectral phasor analysis, we investigated autofluorescence patterns in melanoma compared to intradermal nevi. Using UV excitation and a commercial spectral confocal microscope, we acquired label-free HSI data from the whole-slice samples. ResultsOur findings revealed distinct spectral phasor distributions between melanoma and intradermal nevi, with melanoma displaying a broader phasor phase distribution, signifying a more heterogeneous autofluorescence pattern. Notably, longer wavelengths associated with larger phases correlated with regions identified as melanoma by expert dermatopathologists using H&E staining. Quantitative analysis of phase and modulation histograms within the phasor clusters of five melanomas (with Breslow thicknesses ranging from 0.5 mm to 6 mm) and five intradermal nevi consistently highlighted differences between the two groups. We further demonstrated the potential for the discrimination of several melanocytic lesions using center-of-mass comparisons of phase and modulation variables. Remarkably, modulation versus phase center of mass comparisons revealed strong statistical significance among the groups. Additionally, we identified the molecular endogenous markers responsible for tissue autofluorescence, including collagen, elastin, NADH, FAD, and melanin. In melanoma, autofluorescence is characterized by a higher phase contribution, indicating an increase in FAD and melanin in melanocyte nests. In contrast, NADH, elastin, and collagen dominate the autofluorescence of the nevus.DiscussionThis work underscores the potential of autofluorescence and HSI-phasor analysis as valuable tools for quantifying tissue molecular fingerprints, thereby supporting more effective and quantitative melanoma diagnosis.

Membrane wetting by biomolecular condensates recently emerged as a key phenomenon in cell biology, playing an important role in a diverse range of processes across different organisms. However, an understanding of the molecular mechanisms behind condensate formation and interaction with lipid membranes is still missing. To study this, we exploited the properties of the dyes ACDAN and LAURDAN as nano-environmental sensors in combination with phasor analysis of hyperspectral and lifetime imaging microscopy. Using glycinin as a model condensate-forming protein and giant vesicles as model membranes, we obtained vital information on the process of condensate formation and membrane wetting. Our results reveal that glycinin condensates display differences in water dynamics when changing the salinity of the medium as a consequence of rearrangements in the secondary structure of the protein. Remarkably, analysis of membrane-condensates interaction with protein as well as polymer condensates indicated a correlation between increased wetting affinity and enhanced lipid packing. This is demonstrated by a decrease in the dipolar relaxation of water across all membrane-condensate systems, suggesting a general mechanism to tune membrane packing by condensate wetting.

Hyperspectral imaging (HSI) is a paramount technique in biomedical science, however, unmixing and quantification of each spectral component is a challenging task. Traditional unmixing relies on algorithms that need spectroscopic parameters from the fluorescent species in the sample. The phasor-based multi-harmonic unmixing method requires only the empirical measurement of the pure species to compute the pixel-wise photon fraction of every spectral component. Using simulations, we demonstrate the feasibility of the approach for up to 5 components and explore the use of adding a 6th unknown component representing autofluorescence. The simulations show that the method can be successfully used in typical confocal imaging experiments (with pixel photon counts between 101and 103). As a proof of concept, we tested the method in living cells, using 5 common commercial dyes for organelle labeling and we easily and accurately separate them. Finally, we challenged the method by introducing a solvatochromic probe, 6-Dodecanoyl-N,N-dimethyl-2-naphthylamine (LAURDAN), intended to measure membrane dynamics on specific subcellular membrane-bound organelles by taking advantage of the linear combination between the organelle probes and LAURDAN. We succeeded in monitoring the membrane order in the Golgi apparatus, Mitochondria, and plasma membrane in the samein-vivocell and quantitatively comparing them. The phasor-based multi-harmonic unmixing method can help expand the outreach of HSI and democratize its use by the community for it does not require specialized knowledge.

I share my opinions on the benefits of and bottlenecks for hyperspectral and time-resolved imaging. I also discuss current and future perspectives for analyzing these types of data using the phasor approach.

Acridine Orange (AO) has rich photophysics that has been exploited to study its interaction with RNA and DNA. Traditionally AO was used to stain cells differentiating nucleus and cytoplasm due to the differences in DNA and RNA differential composition. AO cell labeling shows complex behavior depending on several parameters, such as concentration, pH, etc. Such complex photophysics will benefit from a model-free analysis such as the spectral phasor (SP) for hyperspectral imaging. The SP linear combination and reciprocity principles allow us to understand better the AO spectral shift associated with its exploration of the different molecular environments in cells. Using this approach, we identified the SP fingerprints for RNA and DNA for in vitro experiments, which remain invariant for fixed and live cells. However, the SP analysis of the AO fluorescence from live cells shows the occurrence of a third spectral component at 640 nm. The linear properties of the SP analysis enable quantification of the AO bound to RNA, DNA, and a third component. By co-labeling with AO and LysoTracker, we associated part of these subcellular structures with acidic compartments. Nonetheless, we could differentiate AO self-interactions from its binding to RNA within cytoplasmic compartments by use of the SP analysis. This work establishes the use of SP for hyperspectral imaging of AO for the first time, expanding our knowledge of its complex photophysics and promoting further application for in vivo cell imaging.