Protein and lipid mass concentration measurement in tissues by stimulated Raman scattering microscopy

GPX4-dependent ferroptosis sensitivity is a fitness trade-off for cell enlargement

Despite wide variation, each cell type has an optimal size. Maintaining optimal size is essential for cellular fitness and function but the biological basis for this remains elusive. Here, we performed fitness analysis involving genome-wide CRISPR-Cas9 knockout data from tens of human cell lines and identified that cell size influences the essentiality of genes related to mitochondria and membrane repair. These genes also included glutathione peroxidase 4 (GPX4), which safeguards membranes from oxidative damage and prevents ferroptosis-iron-dependent death. Growth beyond normal size, with or without cell-cycle arrest, increased lipid peroxidation, resulting in a ferroptosis-sensitive state. Proteomic analysis revealed cell-cycle-independent superscaling of endoplasmic reticulum, accumulation of iron, and lipidome remodeling. Even slight increases from normal cell size sensitized proliferating cells to ferroptosis as evidenced by deep-learning-based single-cell analysis. Thus, lipid peroxidation may be a fitness trade-off that constrains cell enlargement and contributes to the establishment of an optimal cell size.

Advanced vibrational microscopes for life science

Providing molecular fingerprint information, vibrational spectroscopic imaging opens a new window to decipher the function of biomolecules in living systems. While classic vibrational microscopes based on spontaneous Raman scattering or mid-infrared absorption offer rich insights into sample composition, they have very small cross sections or poor spatial resolution. Nonlinear vibrational microscopy, based on coherent Raman scattering or optical photothermal detection of vibrational absorption, overcomes these barriers and enables high-speed and high-sensitivity imaging of chemical bonds in live cells and tissues. Here, we introduce various modalities, including their principles, strengths, weaknesses and data mining methods to the life sciences community. We further provide a guide for prospective users and an outlook on future technological advances.

Raman analysis of lipids in cells: Current applications and future prospects

Lipids play an important role in the regulation of cell life processes. Although there are various lipid detection methods, Raman spectroscopy, a non-invasive technique, provides the detailed chemical composition of lipid profiles without a complex sample preparation procedure and possesses greater potential in basic biology, clinical diagnosis and disease therapy. In this review, we summarized the characteristics and advantages of Raman-based techniques and their primary contribution to illustrating cellular lipid metabolism.

Imaging lipid rafts reveals the principle of ApoE4-induced Aβ upregulation in human neurons

Lipid rafts in plasma membranes are thought to provide a platform for regulating signaling pathways by increasing the expression or proximity of proteins in the same pathway. Despite this understanding, the absence of direct, simultaneous observations of lipid rafts and their affiliated proteins has hindered a comprehensive assessment of their roles across various biological contexts. Amyloid-β (Aβ), a hallmark of Alzheimer's disease (AD), is generated from the sequential cleavage of amyloid precursor proteins (APPs) by β- and γ-secretases, primarily within endosomes after APP endocytosis by canonical clathrin-mediated endocytosis in neurons. In this study, we developed a protocol for imaging APP on lipid rafts using time-of-flight secondary ion mass spectrometry (ToF-SIMS) and found that astrocyte ApoE4 contributes to an increase in APP localization on lipid rafts, subsequently elevating Aβ42 synthesis in a clathrin-independent manner in neurons.

Active cell proliferation contributes to the enlargement of the nascent nucleus pulposus

BACKGROUND

The notochord is an embryonic organ involved in forming and patterning the spinal column. The mechanism by which the notochord transforms from a continuous rod to a segmented structure excluded from the vertebrae and residing solely as the nucleus pulposus within the intervertebral disc is understudied. The current model of notochordal segmentation suggests that swelling through formation and maturation of the vertebrate cartilage squeezes the notochord cells from the vertebra.

RESULTS

Analysis of Collagen 10, a marker for hypertrophic differentiation, as well as evaluation of changes in cell density, reveal that the expansion of the vertebral precursor cells occurs after notochord segmentation has already taken place. We find that the bulk of the nucleus pulposus is derived from accelerated proliferation within the nucleus pulposus itself. In a model of cell proliferation, the increased proliferation at the nucleus pulposus importantly contributes to expand the nucleus pulposus area.

CONCLUSIONS

Our data is consistent with the hypothesis that notochord cell proliferation contributes to the enlargement of the nucleus pulposus before the vertebra undergo hypertrophy.

Raman Spectroscopy in Cellular and Tissue Aging Research

The establishment of various molecular, physiological, and genetic markers for cellular senescence and aging-associated conditions has progressed the aging study. To identify such markers, a combination of optical, proteomic-, and sequencing-based tools is primarily used, often accompanying extrinsic labels. Yet, the tools for clinical detection at the molecular, cellular, and tissue levels are still lacking which profoundly hinders advancements in the specific detection and timely prevention of aging-related diseases and pathologies. Raman spectroscopy, with its capability for rapid, label-free, and non-invasive analysis of molecular compositions and alterations in aging cells and tissues, holds considerable promise for in vivo applications. In this review, we present recent advancements in the application of Raman spectroscopy to the study of aging in cells and tissues. We explore the use of Raman spectroscopy and related techniques for detecting cellular aging and senescence, focusing on the molecular alterations that accompany these processes. Subsequently, we provide a review of the application of Raman spectroscopy in identifying aging-related changes in various molecules within tissues and organs.

To Acquire or Not to Acquire: Evaluating Compressive Sensing for Raman Spectroscopy in Biology

Raman spectroscopy has revolutionized the field of chemical biology by providing detailed chemical and compositional information with minimal sample preparation. Despite its advantages, the technique suffers from low throughput due to the weak Raman effect, necessitating long acquisition times and expensive equipment. This limitation is particularly acute in time-sensitive applications like bioprocess monitoring and dynamic studies. Compressive sensing offers a promising solution by reducing the burden on measurement hardware, lowering costs, and decreasing measurement times. It allows for the collection of sparse data, which can be computationally reconstructed later. This paper explores the practical application of compressive sensing in spontaneous Raman spectroscopy across various biological samples. We demonstrate its benefits in scenarios requiring portable hardware, rapid acquisition, and minimal storage, such as skin hydration prediction and cellular studies involving drug molecules. Our findings highlight the potential of compressive sensing to overcome traditional limitations of Raman spectroscopy, paving the way for broader adoption in biological research and clinical diagnostics.

Mapping cellular stress and lipid dysregulation in Alzheimer-related progressive neurodegeneration using label-free Raman microscopy

Aβ plaques are a main feature of Alzheimer's disease, and pathological alterations especially in their microenvironment have recently come into focus. However, a holistic imaging approach unveiling these changes and their biochemical nature is still lacking. In this context, we leverage confocal Raman microscopy as unbiased tool for non-destructive, label-free differentiation of progressive biomolecular changes in the Aβ plaque microenvironment in brain tissue of a murine model of cerebral amyloidosis. By developing a detailed approach, overcoming many challenges of chemical imaging, we identify spatially-resolved molecular signatures of disease-associated structures. Specifically, our study reveals nuclear condensation, indicating cellular degeneration, and increased levels of cytochrome c, showing mitochondrial dysfunction, in the vicinity of Aβ plaques. Further, we observe severe accumulation of especially unsaturated lipids. Thus, our study contributes to a comprehensive understanding of disease progression in the Aβ plaque microenvironment, underscoring the prospective of Raman imaging in neurodegenerative disorder research.

Membrane potential mediates the cellular response to mechanical pressure

Mechanical forces have been shown to influence cellular decisions to grow, die, or differentiate, through largely mysterious mechanisms. Separately, changes in resting membrane potential have been observed in development, differentiation, regeneration, and cancer. We now demonstrate that membrane potential is the central mediator of cellular response to mechanical pressure. We show that mechanical forces acting on the cell change cellular biomass density, which in turn alters membrane potential. Membrane potential then regulates cell number density in epithelia by controlling cell growth, proliferation, and cell elimination. Mechanistically, we show that changes in membrane potential control signaling through the Hippo and MAPK pathways, and potentially other signaling pathways that originate at the cell membrane. While many molecular interactions are known to affect Hippo signaling, the upstream signal that activates the canonical Hippo pathway at the membrane has previously been elusive. Our results establish membrane potential as a central regulator of growth and tissue homeostasis.

Probing Electrostatic and Hydrophobic Associative Interactions in Cells

Weak nonspecific interactions between biomacromolecules determine the cytoplasmic organization. Despite their importance, it is challenging to determine these interactions in the intracellular dense and heterogeneous mixture of biomacromolecules. Here, we develop a method to indicate electrostatic and hydrophobic associative interactions and map these interactions. The method relies on a genetically encoded probe containing a sensing peptide and a circularly permuted green fluorescent protein that provides a ratiometric readout. Inside bacterial and mammalian cells, we see that the cytoplasmic components interact strongly with cationic and hydrophobic probes but not with neutral hydrophilic probes, which remain inert. The Escherichia coli cytoplasm interacts strongly with highly negatively charged hydrophilic probes, but the HEK293T cytoplasm does not. These associative interactions are modulated by ATP depletion. Hence, the nonspecific associative interaction profile in cells is condition- and species-dependent.

Label-free long-term measurements of adipocyte differentiation from patient-driven fibroblasts and quantitative analyses of in situ lipid droplet generation

The visualization and tracking of adipocytes and their lipid droplets (LDs) during differentiation are pivotal in developmental biology and regenerative medicine studies. Traditional staining or labeling methods, however, pose significant challenges due to their labor-intensive sample preparation, potential disruption of intrinsic cellular physiology, and limited observation timeframe. This study introduces a novel method for long-term visualization and quantification of biophysical parameters of LDs in unlabeled adipocytes, utilizing the refractive index (RI) distributions of LDs and cells. We employ low-coherence holotomography (HT) to systematically investigate and quantitatively analyze the 42-day redifferentiation process of fat cells into adipocytes. This technique yields three-dimensional, high-resolution refractive tomograms of adipocytes, enabling precise segmentation of LDs based on their elevated RI values. Subsequent automated analysis quantifies the mean concentration, volume, projected area, and dry mass of individual LDs, revealing a gradual increase corresponding with adipocyte maturation. Our findings demonstrate that HT is a potent tool for non-invasively monitoring live adipocyte differentiation and analyzing LD accumulation. This study, therefore, offers valuable insights into adipogenesis and lipid research, establishing HT and image-based analysis as a promising approach in these fields.

Eukaryotic cell size regulation and its implications for cellular function and dysfunction

Depending on cell type, environmental inputs, and disease, the cells in the human body can have widely different sizes. In recent years, it has become clear that cell size is a major regulator of cell function. However, we are only beginning to understand how the optimization of cell function determines a given cell's optimal size. Here, we review currently known size control strategies of eukaryotic cells and the intricate link of cell size to intracellular biomolecular scaling, organelle homeostasis, and cell cycle progression. We detail the cell size-dependent regulation of early development and the impact of cell size on cell differentiation. Given the importance of cell size for normal cellular physiology, cell size control must account for changing environmental conditions. We describe how cells sense environmental stimuli, such as nutrient availability, and accordingly adapt their size by regulating cell growth and cell cycle progression. Moreover, we discuss the correlation of pathological states with misregulation of cell size and how for a long time this was considered a downstream consequence of cellular dysfunction. We review newer studies that reveal a reversed causality, with misregulated cell size leading to pathophysiological phenotypes such as senescence and aging. In summary, we highlight the important roles of cell size in cellular function and dysfunction, which could have major implications for both diagnostics and treatment in the clinic.

Benchtop IR Imaging of Live Cells: Monitoring the Total Mass of Biomolecules in Single Cells

Absolute quantity imaging of biomolecules on a single cell level is critical for measurement assurance in biosciences and bioindustries. While infrared (IR) transmission microscopy is a powerful label-free imaging modality capable of chemical quantification, its applicability to hydrated biological samples remains challenging due to the strong IR absorption by water. Traditional IR imaging of hydrated cells relies on powerful light sources, such as synchrotrons, to mitigate the light absorption by water. However, we overcome this challenge by applying a solvent absorption compensation (SAC) technique to a home-built benchtop IR microscope based on an external-cavity quantum cascade laser. SAC-IR microscopy adjusts the incident light using a pair of polarizers to precompensate the IR absorption by water while retaining the full dynamic range. Integrating the IR absorbance over a cell yields the total mass of biomolecules per cell. We monitor the total mass of the biomolecules of live fibroblast cells over 12 h, demonstrating promise for advancing our understanding of the biomolecular processes occurring in live cells on the single-cell level.

Sub-Nanogram Resolution Measurement of Inertial Mass and Density Using Magnetic-Field-Guided Bubble Microthruster

Artificial micro/nanomotors using active particles hold vast potential in applications such as drug delivery and microfabrication. However, upgrading them to micro/nanorobots capable of performing precise tasks with sophisticated functions remains challenging. Bubble microthruster (BMT) is introduced, a variation of the bubble-driven microrobot, which focuses the energy from a collapsing microbubble to create an inertial impact on nearby target microparticles. Utilizing ultra-high-speed imaging, the microparticle mass and density is determined with sub-nanogram resolution based on the relaxation time characterizing the microparticle's transient response. Master curves of the BMT method are shown to be dependent on the viscosity of the solution. The BMT, controlled by a gamepad with magnetic-field guidance, precisely manipulates target microparticles, including bioparticles. Validation involves measuring the polystyrene microparticle mass and hollow glass microsphere density, and assessing the mouse embryo mass densities. The BMT technique presents a promising chip-free, real-time, highly maneuverable strategy that integrates bubble microrobot-based manipulation with precise bioparticle mass and density detection, which can facilitate microscale bioparticle characterizations such as embryo growth monitoring.

Robust trigger wave speed in Xenopus cytoplasmic extracts

Self-regenerating trigger waves can spread rapidly through the crowded cytoplasm without diminishing in amplitude or speed, providing consistent, reliable, long-range communication. The macromolecular concentration of the cytoplasm varies in response to physiological and environmental fluctuations, raising the question of how or if trigger waves can robustly operate in the face of such fluctuations. Using Xenopus extracts, we find that mitotic and apoptotic trigger wave speeds are remarkably invariant. We derive a model that accounts for this robustness and for the eventual slowing at extremely high and low cytoplasmic concentrations. The model implies that the positive and negative effects of cytoplasmic concentration (increased reactant concentration vs. increased viscosity) are nearly precisely balanced. Accordingly, artificially maintaining a constant cytoplasmic viscosity during dilution abrogates this robustness. The robustness in trigger wave speeds may contribute to the reliability of the extremely rapid embryonic cell cycle.

Estimation of the mass density of biological matter from refractive index measurements

The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms. One of the basic biophysical properties is the mass density (MD). It affects the dynamics in sub-cellular compartments and plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge, as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for assumptions about the biochemical composition of the sample and respective RI measurements. To this aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations and Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well-characterized complex mixtures given by bovine milk and intralipid emulsion and employ it to estimate the MD of living zebrafish (Danio rerio) larvae trunk tissue. Our results illustrate the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

Too big not to fail: emerging evidence for size-induced senescence

Cellular senescence refers to a permanent and stable state of cell cycle exit. This process plays an important role in many cellular functions, including tumor suppression. It was first noted that senescence is associated with increased cell size in the early 1960s; however, how this contributes to permanent cell cycle exit was poorly understood until recently. In this review, we discuss new findings that identify increased cell size as not only a consequence but also a cause of permanent cell cycle exit. We highlight recent insights into how increased cell size alters normal cellular physiology and creates homeostatic imbalances that contribute to senescence induction. Finally, we focus on the potential clinical implications of these findings in the context of cell cycle arrest-causing cancer therapeutics and speculate on how tumor cell size changes may impact outcomes in patients treated with these drugs.

Protecting Proteins from Desiccation Stress Using Molecular Glasses and Gels

Faced with desiccation stress, many organisms deploy strategies to maintain the integrity of their cellular components. Amorphous glassy media composed of small molecular solutes or protein gels present general strategies for protecting against drying. We review these strategies and the proposed molecular mechanisms to explain protein protection in a vitreous matrix under conditions of low hydration. We also describe efforts to exploit similar strategies in technological applications for protecting proteins in dry or highly desiccated states. Finally, we outline open questions and possibilities for future explorations.

Measuring single-cell density with high throughput enables dynamic profiling of immune cell and drug response from patient samples

Cell density, the ratio of cell mass to volume, is an indicator of molecular crowding and therefore a fundamental determinant of cell state and function. However, existing density measurements lack the precision or throughput to quantify subtle differences in cell states, particularly in primary samples. Here we present an approach for measuring the density of 30,000 single cells per hour with a precision of 0.03% (0.0003 g/mL) by integrating fluorescence exclusion microscopy with a suspended microchannel resonator. Applying this approach to human lymphocytes, we discovered that cell density and its variation decrease as cells transition from quiescence to a proliferative state, suggesting that the level of molecular crowding decreases and becomes more regulated upon entry into the cell cycle. Using a pancreatic cancer patient-derived xenograft model, we found that the ex vivo density response of primary tumor cells to drug treatment can predict in vivo tumor growth response. Our method reveals unexpected behavior in molecular crowding during cell state transitions and suggests density as a new biomarker for functional precision medicine.

Nanoplastics Penetrate Human Bronchial Smooth Muscle and Small Airway Epithelial Cells and Affect Mitochondrial Metabolism

Micro- and nanoplastic particles, including common forms like polyethylene and polystyrene, have been identified as relevant pollutants, potentially causing health problems in living organisms. The mechanisms at the cellular level largely remain to be elucidated. This study aims to visualize nanoplastics in bronchial smooth muscle (BSMC) and small airway epithelial cells (SAEC), and to assess the impact on mitochondrial metabolism. Healthy and asthmatic human BSMC and SAEC in vitro cultures were stimulated with polystyrene nanoplastics (PS-NPs) of 25 or 50 nm size, for 1 or 24 h. Live cell, label-free imaging by holotomography microscopy and mitochondrial respiration and glycolysis assessment were performed. Furthermore, 25 and 50 nm NPs were shown to penetrate SAEC, along with healthy and diseased BSMC, and they impaired bioenergetics and induce mitochondrial dysfunction compared to cells not treated with NPs, including changes in oxygen consumption rate and extracellular acidification rate. NPs pose a serious threat to human health by penetrating airway tissues and cells, and affecting both oxidative and glycolytic metabolism.

Recent advances in label-free imaging and quantification techniques for the study of lipid droplets in cells

Lipid droplets (LDs), once considered mere storage depots for lipids, have gained recognition for their intricate roles in cellular processes, including metabolism, membrane trafficking, and disease states like obesity and cancer. This review explores label-free imaging techniques' applications in LD research. We discuss holotomography and vibrational spectroscopic microscopy, emphasizing their potential for studying LDs without molecular labels, and we highlight the growing integration of artificial intelligence. Clinical applications in disease diagnosis and therapy are also considered.

Temporally optimized and spectrally shaped hyperspectral coherent anti-Stokes Raman scattering microscopy

Coherent anti-Stokes Raman scattering (CARS) microscopy offers label-free chemical contrasts based on molecular vibrations. Hyperspectral CARS (HS-CARS) microscopy enables comprehensive microscale chemical characterization of biological samples. Various HS-CARS methods have been developed with individual advantages and disadvantages. We present what we believe to be a new temporally optimized and spectrally shaped (TOSS) HS-CARS method to overcome the limitations of existing techniques by providing precise control of the spatial and temporal profiles of the excitation beams for efficient and accurate measurements. This method uniquely uses Fourier transform pulse shaping based on a two-dimensional spatial light modulator to control the phase and amplitude of the excitation beams. TOSS-HS-CARS achieves fast, stable, and flexible acquisition, minimizes photodamage, and is highly adaptable to a multimodal multiphoton imaging system.

Photoswitchable polyynes for multiplexed stimulated Raman scattering microscopy with reversible light control

Optical imaging with photo-controllable probes has greatly advanced biological research. With superb chemical specificity of vibrational spectroscopy, stimulated Raman scattering (SRS) microscopy is particularly promising for super-multiplexed optical imaging with rich chemical information. Functional SRS imaging in response to light has been recently demonstrated, but multiplexed SRS imaging with reversible photocontrol remains unaccomplished. Here, we create a multiplexing palette of photoswitchable polyynes with 16 Raman frequencies by coupling asymmetric diarylethene with super-multiplexed Carbow (Carbow-switch). Through optimization of both electronic and vibrational spectroscopy, Carbow-switch displays excellent photoswitching properties under visible light control and SRS response with large frequency change and signal enhancement. Reversible and spatial-selective multiplexed SRS imaging of different organelles are demonstrated in living cells. We further achieve photo-selective time-lapse imaging of organelle dynamics during oxidative stress and protein phase separation. The development of Carbow-switch for photoswitchable SRS microscopy will open up new avenues to study complex interactions and dynamics in living cells with high spatiotemporal precision and multiplexing capability.

Viscosity-dependent control of protein synthesis and degradation

It has been proposed that the concentration of proteins in the cytoplasm maximizes the speed of important biochemical reactions. Here we have used Xenopus egg extracts, which can be diluted or concentrated to yield a range of cytoplasmic protein concentrations, to test the effect of cytoplasmic concentration on mRNA translation and protein degradation. We find that protein synthesis rates are maximal in ~1x cytoplasm, whereas protein degradation continues to rise to a higher optimal concentration of ~1.8x. We show that this difference in optima can be attributed to a greater sensitivity of translation to cytoplasmic viscosity. The different concentration optima could produce a negative feedback homeostatic system, where increasing the cytoplasmic protein concentration above the 1x physiological level increases the viscosity of the cytoplasm, which selectively inhibits translation and drives the system back toward the 1x set point.

Macromolecular Crowding, Phase Separation, and Homeostasis in the Orchestration of Bacterial Cellular Functions

Macromolecular crowding affects the activity of proteins and functional macromolecular complexes in all cells, including bacteria. Crowding, together with physicochemical parameters such as pH, ionic strength, and the energy status, influences the structure of the cytoplasm and thereby indirectly macromolecular function. Notably, crowding also promotes the formation of biomolecular condensates by phase separation, initially identified in eukaryotic cells but more recently discovered to play key functions in bacteria. Bacterial cells require a variety of mechanisms to maintain physicochemical homeostasis, in particular in environments with fluctuating conditions, and the formation of biomolecular condensates is emerging as one such mechanism. In this work, we connect physicochemical homeostasis and macromolecular crowding with the formation and function of biomolecular condensates in the bacterial cell and compare the supramolecular structures found in bacteria with those of eukaryotic cells. We focus on the effects of crowding and phase separation on the control of bacterial chromosome replication, segregation, and cell division, and we discuss the contribution of biomolecular condensates to bacterial cell fitness and adaptation to environmental stress.

Multi-molecular hyperspectral PRM-SRS microscopy

Lipids play crucial roles in many biological processes. Mapping spatial distributions and examining the metabolic dynamics of different lipid subtypes in cells and tissues are critical to better understanding their roles in aging and diseases. Commonly used imaging methods (such as mass spectrometry-based, fluorescence labeling, conventional optical imaging) can disrupt the native environment of cells/tissues, have limited spatial or spectral resolution, or cannot distinguish different lipid subtypes. Here we present a hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. Using this platform, we visualize and identify high density lipoprotein particles in human kidney, a high cholesterol to phosphatidylethanolamine ratio inside granule cells of mouse hippocampus, and subcellular distributions of sphingosine and cardiolipin in human brain. Our PRM-SRS displays unique advantages of enhanced chemical specificity, subcellular resolution, and fast data processing in distinguishing lipid subtypes in different organs and species.

Fast histological assessment of adipose tissue inflammation by label-free mid-infrared optoacoustic microscopy

Conventional histology, as well as immunohistochemistry or immunofluorescence, enables the study of morphological and phenotypical changes during tissue inflammation with single-cell accuracy. However, although highly specific, such techniques require multiple time-consuming steps to apply exogenous labels, which might result in morphological deviations from native tissue structures. Unlike these techniques, mid-infrared (mid-IR) microspectroscopy is a label-free optical imaging method that retrieves endogenous biomolecular contrast without altering the native composition of the samples. Nevertheless, due to the strong optical absorption of water in biological tissues, conventional mid-IR microspectroscopy has been limited to dried thin (5-10 µm) tissue preparations and, thus, it also requires time-consuming steps-comparable to conventional imaging techniques. Here, as a step towards label-free analytical histology of unprocessed tissues, we applied mid-IR optoacoustic microscopy (MiROM) to retrieve intrinsic molecular contrast by vibrational excitation and, simultaneously, to overcome water-tissue opacity of conventional mid-IR imaging in thick (mm range) tissues. In this proof-of-concept study, we demonstrated application of MiROM for the fast, label-free, non-destructive assessment of the hallmarks of inflammation in excised white adipose tissue; i.e., formation of crown-like structures and changes in adipocyte morphology.

Unraveling Molecular Composition in Biological Samples-Systematic Evaluation of Statistical Methods for the Analysis of Hyperspectral Raman Data

Recently, confocal Raman microscopy has gained popularity in biomedical research for studying tissues in healthy and diseased state due to its ability to acquire chemically selective data in a noninvasive approach. However, biological samples, such as brain tissue, are inherently difficult to analyze due to the superposition of molecules in the Raman spectra and low variation of spectral features within the sample. The analysis is further impeded by pathological hallmarks, for example beta-amyloid (Aβ) plaques in Alzheimer's disease, which are often solely characterized by subtle shifts in the respective Raman peaks. To unravel the underlying molecular information, convoluted statistical procedures are inevitable. Unfortunately, such statistical methods are often inadequately described, and most natural scientists lack knowledge of their appropriate use, causing unreproducible results and stagnation in the application of hyperspectral Raman imaging. Therefore, we have set out to provide a comprehensive guide to address these challenges with the example of a complex hyperspectral data set of brain tissue samples with Aβ plaques. Our study encompasses established as well as novel statistical methods, including univariate analysis, principal component analysis, cluster analysis, spectral unmixing, and 2D correlation spectroscopy, and critically compares the outcomes of each analysis. Moreover, we transparently demonstrate the effect of preprocessing decisions like denoising and scaling techniques, providing valuable insights into implications of spectral quality for data evaluation. Thereby, this study provides a comprehensive evaluation of analysis approaches for complex hyperspectral Raman data, laying out a blueprint for elucidating meaningful information from biological samples in chemical imaging.

Genome homeostasis defects drive enlarged cells into senescence

Cellular senescence refers to an irreversible state of cell-cycle arrest and plays important roles in aging and cancer biology. Because senescence is associated with increased cell size, we used reversible cell-cycle arrests combined with growth rate modulation to study how excessive growth affects proliferation. We find that enlarged cells upregulate p21, which limits cell-cycle progression. Cells that re-enter the cell cycle encounter replication stress that is well tolerated in physiologically sized cells but causes severe DNA damage in enlarged cells, ultimately resulting in mitotic failure and permanent cell-cycle withdrawal. We demonstrate that enlarged cells fail to recruit 53BP1 and other non-homologous end joining (NHEJ) machinery to DNA damage sites and fail to robustly initiate DNA damage-dependent p53 signaling, rendering them highly sensitive to genotoxic stress. We propose that an impaired DNA damage response primes enlarged cells for persistent replication-acquired damage, ultimately leading to cell division failure and permanent cell-cycle exit.

In-situ quantification of lipids in live cells through imaging approaches

Lipids are important molecules that are widely distributed within the cell, and they play a crucial role in several biological processes such as cell membrane formation, signaling, cell motility and division. Monitoring the spatiotemporal dynamics of cellular lipids in real-time and quantifying their concentrations in situ is crucial since the local concentration of lipids initiates various signaling pathways that regulate cellular processes. In this review, we first introduced the historical background of lipid quantification methods. We then delve into the current state of the art of in situ lipid quantification, including the establishment and utility of fluorescence imaging techniques based on sensors of lipid-binding domains labeled with organic dyes or fluorescent proteins, and Raman and magnetic resonance imaging (MRI) techniques that do not require lipid labeling. Next, we highlighted the biological applications of live-cell lipid quantification techniques in the study of in situ lipid distribution, lipid transformation, and lipid-mediated signaling pathways. Finally, we discussed the technical challenges and prospects for the development of lipid quantification in live cells, with the aim of promoting the development of in situ lipid quantification in live cells, which may have a profound impact on the biological and medical fields.

Label-Free High-Resolution Photothermal Optical Infrared Spectroscopy for Spatiotemporal Chemical Analysis in Fresh, Hydrated Living Tissues and Embryos

Label-free chemical imaging of living and functioning systems is the holy grail of biochemical research. However, existing techniques often require extensive sample preparation to remove interfering molecules such as water, rendering many molecular imaging techniques unsuitable for in situ structural studies. Here, we examined freshly extracted tissue biopsies and living small vertebrates at submicrometer resolution using optical photothermal infrared (O-PTIR) microspectroscopy and demonstrated the following major advances: (1) O-PTIR can be used for submicrometer structural analysis of unprocessed, fully hydrated tissue biopsies extracted from diverse organs, including living brain and lung tissues. (2) O-PTIR imaging can be performed on living organisms, such as salamander embryos, without compromising their further development. (3) Using O-PTIR, we tracked the structural changes of amyloids in functioning brain tissues over time, observing the appearance of newly formed amyloids for the first time. (4) Amyloid structures appeared altered following standard fixation and dehydration procedures. Thus, we demonstrate that O-PTIR enables time-resolved submicrometer in situ investigation of chemical and structural changes in diverse biomolecules in their native conditions, representing a technological breakthrough for in situ molecular imaging of biological samples.

Quantitative Raman chemical imaging of intracellular drug-membrane aggregates and small molecule drug precipitates in cytoplasmic organelles

Raman confocal microscopes have been used to visualize the distribution of small molecule drugs within different subcellular compartments. This visualization allows the discovery, characterization, and detailed analysis of the molecular transport phenomena underpinning the Volume of Distribution - a key parameter governing the systemic pharmacokinetics of small molecule drugs. In the specific case of lipophilic small molecules with large Volumes of Distribution, chemical imaging studies using Raman confocal microscopes have revealed how weakly basic, poorly soluble drug molecules can accumulate inside cells by forming stable, supramolecular complexes in association with cytoplasmic membranes or by precipitating out within organelles. To study the self-assembly and function of the resulting intracellular drug inclusions, Raman chemical imaging methods have been developed to measure and map the mass, concentration, and ionization state of drug molecules at a microscopic, subcellular level. Beyond the field of drug delivery, Raman chemical imaging techniques relevant to the study of microscopic drug precipitates and drug-lipid complexes which form inside cells are also being developed by researchers with seemingly unrelated scientific interests. Highlighting advances in data acquisition, calibration methods, and computational data management and analysis tools, this review will cover a decade of technological developments that enable the conversion of spectral signals obtained from Raman confocal microscopes into new discoveries and information about previously unknown, concentrative drug transport pathways driven by soluble-to-insoluble phase transitions occurring within the cytoplasmic organelles of eukaryotic cells.

New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory

Aging is the slowest process in a living organism. During this process, mortality rate increases exponentially due to the accumulation of damage at the cellular level. Cellular senescence is a well-established hallmark of aging, as well as a promising target for preventing aging and age-related diseases. However, mapping the senescent cells in tissues is extremely challenging, as their low abundance, lack of specific markers, and variability arise from heterogeneity. Hence, methodologies for identifying or predicting the development of senescent cells are necessary for achieving healthy aging. A new wave of bioinformatic methodologies based on mathematics/physics theories have been proposed to be applied to aging biology, which is altering the way we approach our understand of aging. Here, we discuss the dynamical network biomarkers (DNB) theory, which allows for the prediction of state transition in complex systems such as living organisms, as well as usage of Raman spectroscopy that offers a non-invasive and label-free imaging, and provide a perspective on potential applications for the study of aging.

Noninvasive morpho-molecular imaging reveals early therapy-induced senescence in human cancer cells

Anticancer therapy screening in vitro identifies additional treatments and improves clinical outcomes. Systematically, although most tested cells respond to cues with apoptosis, an appreciable portion enters a senescent state, a critical condition potentially driving tumor resistance and relapse. Conventional screening protocols would strongly benefit from prompt identification and monitoring of therapy-induced senescent (TIS) cells in their native form. We combined complementary all-optical, label-free, and quantitative microscopy techniques, based on coherent Raman scattering, multiphoton absorption, and interferometry, to explore the early onset and progression of this phenotype, which has been understudied in unperturbed conditions. We identified TIS manifestations as early as 24 hours following treatment, consisting of substantial mitochondrial rearrangement and increase of volume and dry mass, followed by accumulation of lipid vesicles starting at 72 hours. This work holds the potential to affect anticancer treatment research, by offering a label-free, rapid, and accurate method to identify initial TIS in tumor cells.

Broadband tunable Raman fiber laser with monochromatic pump

Raman fiber laser (RFL) has been widely adopted in astronomy, optical sensing, imaging, and communication due to its unique advantages of flexible wavelength and broadband gain spectrum. Conventional RFLs are generally based on silica fiber. Here, we demonstrate that the phosphosilicate fiber has a broader Raman gain spectrum as compared to the common silica fiber, making it a better choice for broadband Raman conversion. By using the phosphosilicate fiber as gain medium, we propose and build a tunable RFL, and compare its operation bandwidth with a silica fiber-based RFL. The silica fiber-based RFL can operate within the Raman shift range of 4.9 THz (9.8-14.7 THz), whereas in the phosphosilicate fiber-based RFL, efficient lasing is achieved over the Raman shift range of 13.7 THz (3.5-17.2 THz). The operation bandwidths of the two RFLs are also calculated theoretically. The simulation results agree well with experimental data, where the operation bandwidth of the phosphosilicate fiber-based RFL is more than twice of that of the silica fiber-based RFL. This work reveals the phosphosilicate fiber's unique advantage in broadband Raman conversion, which has great potential in increasing the reach and capacity of optical communication systems.

Hybrid machine-learning framework for volumetric segmentation and quantification of vacuoles in individual yeast cells using holotomography

The precise, quantitative evaluation of intracellular organelles in three-dimensional (3D) imaging data poses a significant challenge due to the inherent constraints of traditional microscopy techniques, the requirements of the use of exogenous labeling agents, and existing computational methods. To counter these challenges, we present a hybrid machine-learning framework exploiting correlative imaging of 3D quantitative phase imaging with 3D fluorescence imaging of labeled cells. The algorithm, which synergistically integrates a random-forest classifier with a deep neural network, is trained using the correlative imaging data set, and the trained network is then applied to 3D quantitative phase imaging of cell data. We applied this method to live budding yeast cells. The results revealed precise segmentation of vacuoles inside individual yeast cells, and also provided quantitative evaluations of biophysical parameters, including volumes, concentration, and dry masses of automatically segmented vacuoles.

Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity

Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral stimulated Raman scattering (hSRS) imaging in the carbon-hydrogen (C-H) window and sparsity-driven hyperspectral image decomposition, we demonstrate a high-content hSRS (h2SRS) imaging approach that enables the simultaneous mapping of five major biomolecules, including proteins, carbohydrates, fatty acids, cholesterol, and nucleic acids at the single-cell level. h2SRS imaging of brain and pancreatic cancer cells under chemotherapy revealed acute and adapted chemotherapy-induced metabolic reprogramming and the unique metabolic features of chemoresistance. Our approach is expected to facilitate the discovery of therapeutic targets to combat chemoresistance. This study illustrates a high-content, label-free chemical imaging approach that measures metabolic profiles at the single-cell level and warrants further research on cellular metabolism.

Label-free mid-infrared photothermal live-cell imaging beyond video rate

Advancement in mid-infrared (MIR) technology has led to promising biomedical applications of MIR spectroscopy, such as liquid biopsy or breath diagnosis. On the contrary, MIR microscopy has been rarely used for live biological samples in an aqueous environment due to the lack of spatial resolution and the large water absorption background. Recently, mid-infrared photothermal (MIP) imaging has proven to be applicable to 2D and 3D single-cell imaging with high spatial resolution inherited from visible light. However, the maximum measurement rate has been limited to several frames s^-1, limiting its range of use. Here, we develop a significantly improved wide-field MIP quantitative phase microscope with two orders-of-magnitude higher signal-to-noise ratio than previous MIP imaging techniques and demonstrate live-cell imaging beyond video rate. We first derive optimal system design by numerically simulating thermal conduction following the photothermal effect. Then, we develop the designed system with a homemade nanosecond MIR optical parametric oscillator and a high full-well-capacity image sensor. Our high-speed and high-spatial-resolution MIR microscope has great potential to become a new tool for life science, in particular for live-cell analysis.

Deep ensemble learning and transfer learning methods for classification of senescent cells from nonlinear optical microscopy images

The success of chemotherapy and radiotherapy anti-cancer treatments can result in tumor suppression or senescence induction. Senescence was previously considered a favorable therapeutic outcome, until recent advancements in oncology research evidenced senescence as one of the culprits of cancer recurrence. Its detection requires multiple assays, and nonlinear optical (NLO) microscopy provides a solution for fast, non-invasive, and label-free detection of therapy-induced senescent cells. Here, we develop several deep learning architectures to perform binary classification between senescent and proliferating human cancer cells using NLO microscopy images and we compare their performances. As a result of our work, we demonstrate that the most performing approach is the one based on an ensemble classifier, that uses seven different pre-trained classification networks, taken from literature, with the addition of fully connected layers on top of their architectures. This approach achieves a classification accuracy of over 90%, showing the possibility of building an automatic, unbiased senescent cells image classifier starting from multimodal NLO microscopy data. Our results open the way to a deeper investigation of senescence classification via deep learning techniques with a potential application in clinical diagnosis.

Analytical Techniques for Single-Cell Biochemical Assays of Lipids

Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.

Polyploidy in Xenopus lowers metabolic rate by decreasing total cell surface area

Although polyploidization is frequent in development, cancer, and evolution, impacts on animal metabolism are poorly understood. In Xenopus frogs, the number of genome copies (ploidy) varies across species and can be manipulated within a species. Here, we show that triploid tadpoles contain fewer, larger cells than diploids and consume oxygen at a lower rate. Drug treatments revealed that the major processes accounting for tadpole energy expenditure include cell proliferation, biosynthesis, and maintenance of plasma membrane potential. While inhibiting cell proliferation did not abolish the oxygen consumption difference between diploids and triploids, treatments that altered cellular biosynthesis or electrical potential did. Combining these results with a simple mathematical framework, we propose that the decrease in total cell surface area lowered production and activity of plasma membrane components including the Na+/K+ ATPase, reducing energy consumption in triploids. Comparison of Xenopus species that evolved through polyploidization revealed that metabolic differences emerged during development when cell size scaled with genome size. Thus, ploidy affects metabolism by altering the cell surface area to volume ratio in a multicellular organism.

Protein homeostasis from diffusion-dependent control of protein synthesis and degradation

It has been proposed that the concentration of proteins in the cytoplasm maximizes the speed of important biochemical reactions. Here we have used the Xenopus extract system, which can be diluted or concentrated to yield a range of cytoplasmic protein concentrations, to test the effect of cytoplasmic concentration on mRNA translation and protein degradation. We found that protein synthesis rates are maximal in ~1x cytoplasm, whereas protein degradation continues to rise to an optimal concentration of ~1.8x. This can be attributed to the greater sensitivity of translation to cytoplasmic viscosity, perhaps because it involves unusually large macromolecular complexes like polyribosomes. The different concentration optima sets up a negative feedback homeostatic system, where increasing the cytoplasmic protein concentration above the 1x physiological level increases the viscosity of the cytoplasm, which selectively inhibits translation and drives the system back toward the 1x set point.

Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging

Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRamanomics, to qualify RSI as a tissue phantom calibrated tool for quantitative spatial chemotyping of major classes of biomolecules. Next, we apply qRamanomics to fixed 3D liver organoids generated from stem-cell-derived or primary hepatocytes to assess specimen variation and maturity. We then demonstrate the utility of qRamanomics for identifying biomolecular response signatures from a panel of liver-altering drugs, probing drug-induced compositional changes in 3D organoids followed by in situ monitoring of drug metabolism and accumulation. Quantitative chemometric phenotyping constitutes an important step in developing quantitative label-free interrogation of 3D biological specimens.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

Simultaneous Dual-Band Hyperspectral Stimulated Raman Scattering Microscopy with Femtosecond Optical Parametric Oscillators

Stimulated Raman scattering (SRS) microscopy is a label-free quantitative optical technique for imaging molecular distributions in cells and tissues by probing their intrinsic vibrational frequencies. Despite its usefulness, existing SRS imaging techniques have limited spectral coverage due to either a wavelength tuning constraint or narrow spectral bandwidth. High-wavenumber SRS imaging is commonly used to map lipid and protein distribution in biological cells and visualize cell morphology. However, to detect small molecules or Raman tags, imaging in the fingerprint region or "silent" region, respectively, is often required. For many applications, it is desirable to collect SRS images in two Raman spectral regions simultaneously for visualizing the distribution of specific molecules in cellular compartments or providing accurate ratiometric analysis. In this work, we present an SRS microscopy system using three beams generated by a femtosecond oscillator to acquire hyperspectral SRS image stacks in two arbitrary vibrational frequency bands, between 650-3280 cm-1, simultaneously. We demonstrate potential biomedical applications of the system in investigating fatty acid metabolism, cellular drug uptake and accumulation, and lipid unsaturation level in tissues. We also show that the dual-band hyperspectral SRS imaging system can be adapted for the broadband fingerprint region hyperspectral imaging (1100-1800 cm-1) by simply adding a modulator.

Optical trapping with holographically structured light for single-cell studies

A groundbreaking work in 1970 by Arthur Ashkin paved the way for developing various optical trapping techniques. Optical tweezers have become an established method for the manipulation of biological objects, due to their noninvasiveness and precise controllability. Recent innovations are accelerating and now enable single-cell manipulation through holographic light structuring. In this review, we provide an overview of recent advances in optical tweezer techniques for studies at the individual cell level. Our review focuses on holographic optical tweezers that utilize active spatial light modulators to noninvasively manipulate live cells. The versatility of the technology has led to valuable integrations with microscopy, microfluidics, and biotechnological techniques for various single-cell studies. We aim to recapitulate the basic principles of holographic optical tweezers, highlight trends in their biophysical applications, and discuss challenges and future prospects.

Optical diffraction tomography and image reconstruction to measure host cell alterations caused by divergent Plasmodium species

Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium. Understanding the biological features of various parasite forms is important for the optical diagnosis and defining pathological states, which are often constrained by the lack of ambient visualization approaches. Here, we employ a label-free tomographic technique to visualize the host red blood cell (RBC) remodeling process and quantify changes in biochemical properties arising from parasitization. Through this, we provide a quantitative body of information pertaining to the influence of host cell environment on growth, survival, and replication of P. falciparum and P. vivax in their respective host cells: mature erythrocytes and young reticulocytes. These exquisite three-dimensional measurements of infected red cells demonstrats the potential of evolving 3D imaging to advance our understanding of Plasmodium biology and host-parasite interactions.