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Time-resolved live-cell imaging using widefield microscopy is instrumental in quantitative microbiology research. It allows researchers to track and measure the size, shape, and content of individual microbial cells over time. However, the small size of microbial cells poses a significant challenge in interpreting image data, as their dimensions approache that of the microscope's depth of field, and they begin to experience significant diffraction effects. As a result, 2D widefield images of microbial cells contain projected 3D information, blurred by the 3D point spread function. In this study, we employed simulations and targeted experiments to investigate the impact of diffraction and projection on our ability to quantify the size and content of microbial cells from 2D microscopic images. This study points to some new and often unconsidered artefacts resulting from the interplay of projection and diffraction effects, within the context of quantitative microbiology. These artefacts introduce substantial errors and biases in size, fluorescence quantification, and even single-molecule counting, making the elimination of these errors a complex task. Awareness of these artefacts is crucial for designing strategies to accurately interpret micrographs of microbes. To address this, we present new experimental designs and machine learning-based analysis methods that account for these effects, resulting in accurate quantification of microbiological processes.

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Cellular longevity is regulated by both genetic and environmental factors. However, the interactions of these factors in the context of aging remain largely unclear. Here, we formulate a mathematical model for dynamic glucose modulation of a core gene circuit in yeast aging, which not only guided the design of pro-longevity interventions but also revealed the theoretical principles underlying these interventions. We introduce the dynamical systems theory to capture two general means for promoting longevity-the creation of a stable fixed point in the "healthy" state of the cell and the "dynamic stabilization" of the system around this healthy state through environmental oscillations. Guided by the model, we investigate how both of these can be experimentally realized by dynamically modulating environmental glucose levels. The results establish a paradigm for theoretically analyzing the trajectories and perturbations of aging that can be generalized to aging processes in diverse cell types and organisms.

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Most mammalian cells have molecular circadian clocks that generate widespread rhythms in transcript and protein abundance. While circadian clocks are robust to fluctuations in the cellular environment, little is known about the mechanisms by which the circadian period compensates for fluctuating metabolic states. Here, we exploit the heterogeneity of single cells both in circadian period and a metabolic parameter-protein stability-to study their interdependence without the need for genetic manipulation. We generated cells expressing key circadian proteins (CRYPTOCHROME1/2 (CRY1/2) and PERIOD1/2 (PER1/2)) as endogenous fusions with fluorescent proteins and simultaneously monitored circadian rhythms and degradation in thousands of single cells. We found that the circadian period compensates for fluctuations in the turnover rates of circadian repressor proteins and uncovered possible mechanisms using a mathematical model. In addition, the stabilities of the repressor proteins are circadian phase dependent and correlate with the circadian period in a phase-dependent manner, in contrast to the prevailing model.

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Molecular phosphorescence in the second near-infrared window (NIR-II, 1000-1700 nm) holds promise for deep-tissue optical imaging with high contrast by overcoming background fluorescence interference. However, achieving bright and stable NIR-II molecular phosphorescence suitable for biological applications remains a formidable challenge. Herein, we report a new series of symmetric isocyanorhodium(I) complexes that could form oligomers and exhibit bright, long-lived (7-8 µs) phosphorescence in aqueous solution via metallophilic interaction. Ligand substituents with enhanced dispersion attraction and electron-donating properties were explored to extend excitation/emission wavelengths and enhanced stability. Further binding the oligomers with fetal bovine serum (FBS) resulted in NIR-II molecular phosphorescence with high quantum yields (up to 3.93 %) and long-term stability in biological environments, enabling in vivo tracking of single-macrophage dynamics and high-contrast time-resolved imaging. These results pave the way for the development of highly-efficient NIR-II molecular phosphorescence for biomedical applications.

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We present a powerful method for direct mRNA detection based on ligation-based recognition and in situ amplification, capable of single-cell imaging mRNA at single-nucleotide and single-molecule resolution. Attributed to the use of Splint R ligase that can ligate padlock probe with RNA as target template, this method can efficiently detect mRNA in the absence of reverse transcription. This method enables spatial localization and correlation analysis of gene expression in single cells, which helps us to elucidate gene function and regulatory mechanisms.

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The presence and accumulation of both, plastics and antibiotics in soils may lead to the colonization, selection, and propagation of soil bacteria with certain metabolic traits, e.g., antibiotic resistance, in the plastisphere. However, the impact of plastic-antibiotic tandem on the soil ecosystem functioning, particularly on microbial function and metabolism remains currently unexplored. Herein, we investigated the competence of soil bacteria to colonize plastics and degrade 13C-labeled sulfamethoxazole (SMX). Using single-cell imaging, isotope tracers, soil respiration and SMX mineralization bulk measurements we show that microbial colonization of polyethylene (PE) and polystyrene (PS) surfaces takes place within the first 30 days of incubation. Morphologically diverse microorganisms were colonizing both plastic types, with a slight preference for PE substrate. CARD-FISH bacterial cell counts on PE and PS surfaces formed under SMX amendment ranged from 5.36 × 103 to 2.06 × 104, and 2.06 × 103 to 3.43 × 103 hybridized cells mm-2, respectively. Nano-scale Secondary Ion Mass Spectrometry measurements show that 13C enrichment was highest at 130 days with values up to 1.29 atom%, similar to those of the 13CO2 pool (up to 1.26 atom%, or 22.55 ‰). Independent Mann-Whitney U test showed a significant difference between the control plastisphere samples incubated without SMX and those in 13C-SMX incubations (P < 0.001). Our results provide direct evidence demonstrating, at single-cell level, the capacity of bacterial colonizers of plastics to assimilate 13C-SMX from contaminated soils. These findings expand our knowledge on the role of soil-seeded plastisphere microbiota in the ecological functioning of soils impacted by anthropogenic stressors.

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Latent HIV-1 reservoirs are a major obstacle to the eradication of HIV-1. Several cure strategies have been proposed to eliminate latent reservoirs. One of the key strategies involves the reactivation of latent HIV-1 from cells using latency-reversing agents. However, currently it is unclear whether any of the latency-reversing agents are able to completely reactivate HIV-1 provirus transcription in all latent cells. An understanding of the reactivation of HIV-1 provirus at single-cell single-molecule level is necessary to fully comprehend the reactivation of HIV-1 in the reservoirs. Furthermore, since reactivable viruses in the pool of latent reservoirs are rare, combining single-cell imaging techniques with the ability to visualize a large number of reactivated single cells that express both viral RNA and proteins in a pool of uninfected and non-reactivated cells will provide unprecedented information about cell-to-cell variability in reactivation. Here, we describe the single-cell single-molecule RNA-FISH (smRNA-FISH) method to visualize HIV-1 gag RNA combined with the immunofluorescence (IF) method to detect Gag protein to characterize the reactivated cells. This method allows the visualization of subcellular localization of RNA and proteins before and after reactivation and facilitates absolute quantitation of the number of transcripts per cell using FISH-quant. In addition, we describe a high-speed and high-resolution scanning (HSHRS) fluorescence microscopy imaging method to visualize rare and reactivated cells in a pool of non-reactivated cells with high efficiency.

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Candida albicans is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of C. albicans to reversibly change morphology and to grow as yeast, pseudohyphae, or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help eradicate C. albicans infections.While numerous studies investigated gene expression changes occurring during C. albicans morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single-molecule fluorescent in situ hybridization (smFISH) protocol for C. albicans, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae, or hyphal cells. We quantified the expression of two mRNAs, a cell cycle-controlled mRNA (CLB2) and a transcription factor (EFG1), which show expression changes in the different morphological cell types and nutrient conditions. In this protocol, we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell segmentation, and mRNA spot analysis. Raw data is provided with the protocol to favor reproducibility. This approach could benefit the molecular characterization of C. albicans and other filamentous fungi, pathogenic or nonpathogenic.

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The CDK4/6 inhibitor palbociclib blocks cell cycle progression in Estrogen receptor-positive, human epidermal growth factor 2 receptor-negative (ER+/HER2-) breast tumor cells. Despite the drug's success in improving patient outcomes, a small percentage of tumor cells continues to divide in the presence of palbociclib-a phenomenon we refer to as fractional resistance. It is critical to understand the cellular mechanisms underlying fractional resistance because the precise percentage of resistant cells in patient tissue is a strong predictor of clinical outcomes. Here, we hypothesize that fractional resistance arises from cell-to-cell differences in core cell cycle regulators that allow a subset of cells to escape CDK4/6 inhibitor therapy. We used multiplex, single-cell imaging to identify fractionally resistant cells in both cultured and primary breast tumor samples resected from patients. Resistant cells showed premature accumulation of multiple G1 regulators including E2F1, retinoblastoma protein, and CDK2, as well as enhanced sensitivity to pharmacological inhibition of CDK2 activity. Using trajectory inference approaches, we show how plasticity among cell cycle regulators gives rise to alternate cell cycle "paths" that allow individual tumor cells to escape palbociclib treatment. Understanding drivers of cell cycle plasticity, and how to eliminate resistant cell cycle paths, could lead to improved cancer therapies targeting fractionally resistant cells to improve patient outcomes.

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Investigating cell-cycle progression has been challenging due to the complex interconnectivity of regulatory processes and inherent cell-to-cell heterogeneity, which often require synchronization procedures. However, recent advancements in cell-cycle sensors and single-cell imaging techniques have turned this heterogeneity into an advantage for investigating the molecular mechanisms underlying diverse responses. This has led to significant progress in our understanding of cell-cycle regulation. In this paper, we present a comprehensive live single-cell imaging workflow that leverages cutting-edge live-cell sensors. These advanced single-cell imaging procedures provide promising opportunities for elucidating the molecular mechanisms underpinnings of heterogeneous responses in cell-cycle progression.

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Hydrogels, three-dimensional hydrophilic polymeric networks with high water retaining capacity, have gained prominence in wound management and drug delivery due to their tunability, softness, permeability, and biocompatibility. Electron-beam polymerized poly(ethylene glycol) diacrylate (PEGDA) hydrogels are particularly useful for phototherapies such as antimicrobial photodynamic therapy (aPDT) due to their excellent optical properties. This work takes advantage of the transparency of PEGDA hydrogels to investigate bacterial responses to aPDT at the single-cell level, in real-time and in situ. The photosensitizer methylene blue (MB) was loaded in PEGDA hydrogels by using two methods: reversible loading and irreversible immobilization within the 3D polymer network. MB release kinetics and singlet oxygen generation were studied, revealing the distinct behaviors of both hydrogels. Real-time imaging of Escherichia coli was conducted during aPDT in both hydrogel types, using the Min protein system to report changes in bacterial physiology. Min oscillation patterns provided mechanistic insights into bacterial photoinactivation, revealing a dependence on the hydrogel preparation method. This difference was attributed to the mobility of MB within the hydrogel, affecting its direct interaction with bacterial membranes. These findings shed light on the complex interplay between hydrogel properties and the bacterial response during aPDT, offering valuable insights for the development of antibacterial wound dressing materials. The study demonstrates the capability of real-time, single-cell fluorescence microscopy to unravel dynamic bacterial behaviors in the intricate environment of hydrogel surfaces during aPDT.

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BACKGROUND: The immune system has evolved to detect foreign antigens and deliver coordinated responses, while minimizing "friendly fire." Until recently, studies investigating the behavior of immune cells were limited to static in vitro measurements. Although static measurements allow for real-time imaging, results are often difficult to translate to an in vivo setting. Multiphoton microscopy is an emerging method to capture spatial information on subcellular events and characterize the local microenvironment. Previous studies have shown that multiphoton microscopy can monitor changes in single-cell macrophage heterogeneity during differentiation. Therefore, there is a need to use multiphoton microscopy to monitor molecular interactions during immunological activities like phagocytosis. Here we investigate the correlation between phagocytic function and changes in endogenous optical reporters during phagocytosis. METHODS: In vitro autofluorescence imaging of nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) was used to detect metabolic changes in macrophages during phagocytosis. More specifically, optical redox ratio, mean NADH fluorescence lifetime and ratio of free to protein-bound NADH were used to quantify changes in metabolism. RESULTS: Results show that IFN-γ (M1) macrophages showed decreased optical redox ratios and mean NADH lifetime while phagocytosing immunogenic cancer cells compared to metastatic cells. To validate phagocytic function, a fluorescence microscopy-based protocol using a pH-sensitive fluorescent probe was used. Results indicate that M0 and M1 macrophages show similar trends in phagocytic potential. CONCLUSION: Overall, this work demonstrates that in vitro multiphoton imaging can be used to longitudinally track changes in phagocytosis and endogenous metabolic cofactors.

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Autophagy is a highly conserved, intracellular recycling process by which cytoplasmic contents are degraded in the lysosome. This process occurs at a low level constitutively; however, it is induced robustly in response to stressors, in particular, starvation of critical nutrients such as amino acids and glucose. That said, the relative contribution of these inputs is ambiguous and many starvation medias are poorly defined or devoid of multiple nutrients. Here, we sought to generate a quantitative catalog of autophagy across multiple stages and in single, living cells under normal growth conditions as well as in media starved specifically of amino acids or glucose. We found that autophagy is induced by starvation of amino acids, but not glucose, in U2OS cells, and that MTORC1-mediated ULK1 regulation and autophagy are tightly linked to amino acid levels. While autophagy is engaged immediately during amino acid starvation, a heightened response occurs during a period marked by transcriptional upregulation of autophagy genes during sustained starvation. Finally, we demonstrated that cells immediately return to their initial, low-autophagy state when nutrients are restored, highlighting the dynamic relationship between autophagy and environmental conditions. In addition to sharing our findings here, we provide our data as a high-quality resource for others interested in mathematical modeling or otherwise exploring autophagy in individual cells across a population.

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In the last 2 decades, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) has gained significant prominence as a powerful imaging technique in the field of life sciences. This comprehensive review provides an in-depth overview of recent advancements in ToF-SIMS instrument technology and its applications in metabolomics, lipidomics, and single-cell analysis. We highlight the use of ToF-SIMS imaging for studying lipid distribution, composition, and interactions in cells and tissues, and discuss its application in metabolomics, including the analysis of metabolic pathways. Furthermore, we review recent progress in single-cell analysis using ToF-SIMS, focusing on sample preparation techniques, in situ investigation for subcellular distribution of drugs, and interactions between drug molecules and biological targets. The high spatial resolution and potential for multimodal analysis of ToF-SIMS make it a promising tool for unraveling the complex molecular landscape of biological systems. We also discuss future prospects and potential advancements of ToF-SIMS in the research of life sciences, with the expectation of a significant impact in the field.

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To investigate the role of intracellular Ca2+ signaling in the perception and response mechanisms to light in unicellular microalgae, the genetically encoded ratiometric Ca2+ indicator Yellow Cameleon (YC3.6) was expressed in the model organism for green algae Chlamydomonas reinhardtii, targeted to cytosol, chloroplast, and mitochondria. Through in vivo single-cell confocal microscopy imaging, light-induced Ca2+ signaling was investigated in different conditions and different genotypes, including the photoreceptors mutants phot and acry. A genetically encoded H2 O2 sensor was also adopted to investigate the possible role of H2 O2 formation in light-dependent Ca2+ signaling. Light-dependent Ca2+ response was observed in Chlamydomonas reinhardtii cells only in the chloroplast as an organelle-autonomous response, influenced by light intensity and photosynthetic electron transport. The absence of blue and red-light photoreceptor aCRY strongly reduced the light-dependent chloroplast Ca2+ response, while the absence of the blue photoreceptor PHOT had no significant effects. A correlation between high light-induced chloroplast H2 O2 gradients and Ca2+ transients was drawn, supported by H2 O2 -induced chloroplast Ca2+ transients in the dark. In conclusion, different triggers are involved in the light-induced chloroplast Ca2+ signaling as saturation of the photosynthetic electron transport, H2 O2 formation, and aCRY-dependent light perception.

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Min oscillations are a fascinating mechanism used by Escherichia coli to find their middle. Beyond their biological role, they provide a convenient and relatively unexplored method to monitor the effect of sublethal environmental challenges on bacterial physiology in real-time and at the single-cell level. In this review, we discuss the original papers that put forward the idea of using Min oscillations as a reporting tool to monitor the effect of extracellular cationic compounds, including antibiotics. More recent work from our laboratory explores this tool to follow bacterial response to other challenges such as weak mechanical interactions with nanomaterials or photodynamic treatment. We discuss the physiological meaning of the changes in Min oscillation period, likely related to membrane potential dynamics, as well as the benefits and limitations of using oscillations as a reporter in fluorescence microscopy. Overall, Min oscillations are a useful addition to the fluorescence microscopy toolbox in order to visualize stress responses in E. coli, and have the potential to provide full mechanistic understanding of the events that lead to bacterial cell death in different contexts.

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Accurately predicting cellular activities of proteins based on their primary amino acid sequences would greatly improve our understanding of the proteome. In this paper, we present CELL-E, a text-to-image transformer model that generates 2D probability density images describing the spatial distribution of proteins within cells. Given an amino acid sequence and a reference image for cell or nucleus morphology, CELL-E predicts a more refined representation of protein localization, as opposed to previous in silico methods that rely on pre-defined, discrete class annotations of protein localization to subcellular compartments.

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Mass spectrometry imaging (MSI) is a sensitive, specific, label-free imaging analysis technique that can simultaneously obtain the spatial distribution, relative content, and structural information of hundreds of biomolecules in cells and tissues, such as lipids, small drug molecules, peptides, proteins, and other compounds. The study of molecular mapping of single cells can reveal major scientific issues such as the activity pattern of living organisms, disease pathogenesis, drug-targeted therapy, and cellular heterogeneity. Applying MSI technology to the molecular mapping of single cells can provide new insights and ideas for the study of single-cell metabolomics. This review aims to provide an informative resource for those in the MSI community who are interested in single-cell imaging. Particularly, we discuss advances in imaging schemes and sample preparation, instrumentation improvements, data processing and analysis, and 3D MSI over the past few years that have allowed MSI to emerge as a powerful technique in the molecular imaging of single cells. Also, we highlight some of the most cutting-edge studies in single-cell MSI, demonstrating the future potential of single-cell MSI. Visualizing molecular distribution at the single-cell or even sub-cellular level can provide us with richer cell information, which strongly contributes to advancing research fields such as biomedicine, life sciences, pharmacodynamic testing, and metabolomics. At the end of the review, we summarize the current development of single-cell MSI technology and look into the future of this technology.

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Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology platforms can provide distributions of cellular signal intensity (CSI) levels of biomolecules across the entire cell populations of interest within the sampled tumor tissue. However, the heterogeneity of CSI levels is usually ignored, and the simple mean signal intensity value is considered a cancer biomarker. Here we consider the entire distribution of CSI expression levels of a given biomolecule in the cancer cell population as a predictor of clinical outcome. The proposed quantile index (QI) biomarker is defined as the weighted average of CSI distribution quantiles in individual tumors. The weight for each quantile is determined by fitting a functional regression model for a clinical outcome. That is, the weights are optimized so that the resulting QI has the highest power to predict a relevant clinical outcome. The proposed QI biomarkers were derived for proteins expressed in cancer cells of malignant breast tumors and demonstrated improved prognostic value compared with the standard mean signal intensity predictors. The R package Qindex implementing QI biomarkers has been developed. The proposed approach is not limited to immunohistochemistry data and can be based on any cell-level expressions of proteins or nucleic acids.

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Numerous studies have linked a wide range of diseases including respiratory illnesses to harmful particulate matter (PM) emissions indoors and outdoors, such as incense PM and industrial PM. Because of their ability to penetrate the lower respiratory tract and the circulatory system, fine particles with diameters of 2.5 µm or less (PM2.5) are believed to be more hazardous than larger PMs. Despite the enormous number of studies focusing on the intracellular processes associated with PM2.5 exposure, there have been limited reports studying the biophysical properties of cell membranes, such as nanoscale morphological changes induced by PM2.5. Our study assesses the membrane topographical and structural effects of PM2.5 from incense PM2.5 exposure in real time on A549 lung carcinoma epithelial cells and SH-SY5Y neuroblastoma cells that had been fixed to preclude adaptive cell responses. The size distribution and mechanical properties of the PM2.5 sample were characterized with atomic force microscopy (AFM). Nanoscale morphological monitoring of the cell membranes utilizing scanning ion conductance microscopy (SICM) indicated statistically significant increasing membrane roughness at A549 cells at half an hour of exposure and visible damage at 4 h of exposure. In contrast, no significant increase in roughness was observed on SH-SY5Y cells after half an hour of PM2.5 exposure, although continued exposure to PM2.5 for up to 4 h affected an expansion of lesions already present before exposure commenced. These findings suggest that A549 cell membranes are more susceptible to structural damage by PM2.5 compared to SH-SY5Y cell membranes, corroborating more enhanced susceptibility of airway epithelial cells to exposure to PM2.5 than neuronal cells.

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