Raman fingerprints as promising markers of cellular senescence and aging

Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis

Human and animal health rely on balancing cell division and cell death to maintain normal homeostasis. This process is accomplished by regulated cell death (RCD), whose imbalance can lead to disease. Currently, the most frequently used method for analyzing RCD is fluorescence microscopy. This method has limitations and potential side effects due to the presence of fluorescent labels. Furthermore, fluorescence often lacks specificity and may have side effects. In the quest to overcome such difficulties, label-free approaches have come into focus.Here, Raman microscopy in combination with machine learning is used to investigate RCDs, where biochemical molecular "fingerprints" are investigated with a focus on the vibrations of atoms in molecules. Three different and unique RCD types with different genetic and biochemical machinery, namely, ferroptosis is studied in comparison with apoptosis, and necroptosis in the murine fibroblast line L929sAhFas. Interestingly, during ferroptosis, a decrease in the wavenumber at 939 cm-1 was observed, which is associated with a potential reduction in the expression of collagen - a compound essential in multiple diseases. Data analysis was performed by machine learning (ML), here SVMs, where the model utilizing the spectra directly into a support vector machine (SVM) outperforms other SVM strategies correctly predicting 73% of all spectra. Other methods: PCA-SVM (principal component analysis-SVM), peak fitting-AUC-SVM (area under the curve) and peak fitting-spectral reconstruction-SVM rendered prediction accuracies of ~52%, ~43%, and 61%, respectively. Peak fitting has the additional benefit of enabling the biological interpretation of Raman scattering peaks by using the area under the curve, although at a loss of general accuracy. The potential of Raman microscopy in biology, in combination with machine learning pipelines, can be applied to a broader field of cell biology, not limited to regulated cell death.

The construction of an inflammation classification model for HDPCs applied in guiding pulpotomy based on single-cell Raman spectroscopy

The immune defense and the repair function of the pulp tissue serve as the biological foundation of pulpotomy. The precise evaluation of the pulp inflammation extent and determining its reversibility are essential for the success of pulpotomy. The objective of this study was to classify the molecular-level of dental pulp cell physiology and inflammatory state based on the biochemical changes obtained by single-cell Raman spectroscopy. Firstly, we differentiated the growth of HDPCs (human dental pulp cells) under physiological states by employing Raman spectroscopy with multivariate statistical analysis. Raman spectroscopy reflected the biochemical changes at different growth phases, including the lag phase, log phase, and stationary phase. Secondly, we evaluated the optimal concentration and duration of Porphyromonas gingivalis lipopolysaccharide (P.g.LPS) stimulation to establish a six-level inflammation classification model of HDPCs. Thirdly, we performed label-free characterization of biological component changes in cells of different inflammation grades by Raman spectroscopy. As a result, the differences of peaks in the region 600-1800 cm-1 demonstrated the biochemical molecular alterations in the different inflammation grades of HDPCs. As inflammation progresses in steps, protein peaks increased first and then decreased, while lipid and nucleic acid peaks gradually decreased compared to unstimulated cells. However, when the inflammatory stimulation reached grade V, the changes in the biological properties were characterized by a recovery in protein and lipid content, and a decrease in nucleic acid content. We then established the diagnostic model using the Raman spectra of HDPCs in physiological and inflammatory states, which had a prediction accuracy of 100 % and 97.4 %, respectively. Finally, we determined the reversibility threshold of HDPCs at different grades of inflammation. We observed that the inflammation of grade I and II cells had potential reversibility and could be attempted to be retained. In conclusion, Raman spectroscopy combined with multivariate statistical analysis has potential possibility to effectively distinguish the degree of inflammation in the dental pulp, thus providing new tools and perspectives on pulpotomy in clinical practice.

Coherent Raman microscopy visualizes ongoing cellular senescence through amide I peak shifts originating from β sheets in disordered nucleolar proteins

Cellular senescence occurs through the accumulation of many kinds of stresses. Senescent cells in tissues also cause various age-related disorders. Therefore, detecting them without labeling is beneficial for medical research and developing diagnostic methods. However, existing biomarkers have limitations of requiring fixation and labeling, or their molecular backgrounds are uncertain. Coherent anti-Stokes Raman scattering (CARS) spectroscopic imaging is a novel option because it can assess and visualize molecular structures based on their molecular fingerprint. Here, we present a new label-free method to visualize cellular senescence using CARS imaging in nucleoli. We found the peak of the nucleolar amide I band shifted to a higher wavenumber in binuclear senescent cells, which reflects changes in the protein secondary structure from predominant α-helices to β-sheets originating from amyloid-like aggregates. Following this, we developed a procedure that can visualize the senescent cells by providing the ratios and subtractions of these two components. We also confirmed that the procedure can visualize nucleolar aggregates due to unfolded/misfolded proteins produced by proteasome inhibition. Finally, we found that this method can help visualize the nucleolar defects in naïve cells even before binucleation. Thus, our method is beneficial to evaluate ongoing cellular senescence through label-free imaging of nucleolar defects.

Enhancing Bone Infection Diagnosis with Raman Handheld Spectroscopy: Pathogen Discrimination and Diagnostic Potential

Osteomyelitis is a bone disease caused by bacteria that can damage bone. Raman handheld spectroscopy has emerged as a promising diagnostic tool for detecting bone infection and can be used intraoperatively during surgical procedures. This study involved 120 bone samples from 40 patients, with 80 samples infected with either Staphylococcus aureus or Staphylococcus epidermidis. Raman handheld spectroscopy demonstrated successful differentiation between healthy and infected bone samples and between the two types of bacterial pathogens. Raman handheld spectroscopy appears to be a promising diagnostic tool in bone infection and holds the potential to overcome many of the shortcomings of traditional diagnostic procedures. Further research, however, is required to confirm its diagnostic capabilities and consider other factors, such as the limit of pathogen detection and optimal calibration standards.

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.

Sub-Cellular Dynamic Analysis of BGC823 Cells after Treatment with the Multi-Component Drug CKI Using Raman Spectroscopy

Multi-component drugs (MCDs) can induce various cellular changes covering multiple levels, from molecular and subcellular structure to cell morphology. A "non-invasive" method for comprehensively detecting the dynamic changes of cellular fine structure and chemical components on the subcellular level is highly desirable for MCD studies. In this study, the subcellular dynamic processes of gastric cancer BGC823 cells after treatment with a multi-component drug, Compound Kushen Injection (CKI), were investigated using a homemade, high-resolution, confocal Raman spectroscopy (RS) device combined with bright-field imaging. The Raman spectra of the nucleus, cytoplasm and intracellular vesicles (0.4-1 μm) were collected simultaneously for each cell treated with CKI at different times and doses. The RS measurements showed that CKI decreased the DNA signatures, which the drug is known to inhibit. Meanwhile, the CKI-induced subcellular dynamic changes in the appearance of numerous intracellular vesicles and the deconstruction of cytoplasm components were observed and discussed. The results demonstrated that high-resolution subcellular micro-Raman spectroscopy has potential for detecting fine cellular dynamic variation induced by drugs and the screening of MCDs in cancer therapy.

Cellular senescence in cancer: from mechanisms to detection

Senescence refers to a cellular state featuring a stable cell-cycle arrest triggered in response to stress. This response also involves other distinct morphological and intracellular changes including alterations in gene expression and epigenetic modifications, elevated macromolecular damage, metabolism deregulation and a complex pro-inflammatory secretory phenotype. The initial demonstration of oncogene-induced senescence in vitro established senescence as an important tumour-suppressive mechanism, in addition to apoptosis. Senescence not only halts the proliferation of premalignant cells but also facilitates the clearance of affected cells through immunosurveillance. Failure to clear senescent cells owing to deficient immunosurveillance may, however, lead to a state of chronic inflammation that nurtures a pro-tumorigenic microenvironment favouring cancer initiation, migration and metastasis. In addition, senescence is a response to post-therapy genotoxic stress. Therefore, tracking the emergence of senescent cells becomes pivotal to detect potential pro-tumorigenic events. Current protocols for the in vivo detection of senescence require the analysis of fixed or deep-frozen tissues, despite a significant clinical need for real-time bioimaging methods. Accuracy and efficiency of senescence detection are further hampered by a lack of universal and more specific senescence biomarkers. Recently, in an attempt to overcome these hurdles, an assortment of detection tools has been developed. These strategies all have significant potential for clinical utilisation and include flow cytometry combined with histo- or cytochemical approaches, nanoparticle-based targeted delivery of imaging contrast agents, OFF-ON fluorescent senoprobes, positron emission tomography senoprobes and analysis of circulating SASP factors, extracellular vesicles and cell-free nucleic acids isolated from plasma. Here, we highlight the occurrence of senescence in neoplasia and advanced tumours, assess the impact of senescence on tumorigenesis and discuss how the ongoing development of senescence detection tools might improve early detection of multiple cancers and response to therapy in the near future.

Raman spectroscopy assisted biochemical evaluation of L929 fibroblast cells on differentially crosslinked gelatin hydrogels

Biochemical evaluation of cell-matrix interaction using conventional labelling techniques often possesses limitations due to dye entrapment. In contrast, Raman spectroscopy guided approach offers label-free determination of cell-matrix biochemistry. Herein, gelatin (Gel) matrices modified with 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide/ N-Hydroxysuccinimide (EDC/NHS) and glutaraldehyde (GTA) was used as standards for comparative evaluation. Raman spectroscopy was deployed as a label-free approach to investigate interaction of cells with Gel hydrogels. Raman-based approach assisted in evaluation of cell-matrix interactions by identifying key biomolecular signatures retrospecting the fact that L929 fibroblast cells portrayed excellent growth and proliferation kinetics in crosslinked Gel as compared to its bare counterpart. EDC crosslinked hydrogels exhibited superior cell proliferation than its GTA counterparts. Cell proliferation on differentially crosslinked gel was also confirmed using standard MTT Assay and Rhodamine-DAPI staining thus corroborating the fact that Raman spectroscopy can be deployed as a superior label-free alternative towards real-time determination of cell proliferation and growth.

Faces of cellular senescence in skin aging

The skin is comprised of different cell types with different proliferative capacities. Skin aging occurs with chronological age and upon exposure to extrinsic factors such as photodamage. During aging, senescent cells accumulate in different compartments of the human skin, leading to impaired skin physiology. Diverse skin cell types may respond differently to senescence-inducing stimuli and it is not clear how this results in aging-associated skin phenotypes and pathologies. This review aims to examine and provide an overview of current evidence of cellular senescence in the skin. We will focus on cellular characteristics and behaviour of different skin cell types undergoing senescence in the epidermis and dermis, with a particular focus on the complex interplay between mitochondrial dysfunction, autophagy and DNA damage pathways. We will also examine how the dermis and epidermis cope with the accumulation of DNA damage during aging.

A guide to assessing cellular senescence in vitro and in vivo

Cellular senescence is a physiological mechanism whereby a proliferating cell undergoes a stable cell cycle arrest upon damage or stress and elicits a secretory phenotype. This highly dynamic and regulated cellular state plays beneficial roles in physiology, such as during embryonic development and wound healing, but it can also result in antagonistic effects in age-related pathologies, degenerative disorders, ageing and cancer. In an effort to better identify this complex state, and given that a universal marker has yet to be identified, a general set of hallmarks describing senescence has been established. However, as the senescent programme becomes more defined, further complexities, including phenotype heterogeneity, have emerged. This significantly complicates the recognition and evaluation of cellular senescence, especially within complex tissues and living organisms. To address these challenges, substantial efforts are currently being made towards the discovery of novel and more specific biomarkers, optimized combinatorial strategies and the development of emerging detection techniques. Here, we compile such advances and present a multifactorial guide to identify and assess cellular senescence in cell cultures, tissues and living organisms. The reliable assessment and identification of senescence is not only crucial for better understanding its underlying biology, but also imperative for the development of diagnostic and therapeutic strategies aimed at targeting senescence in the clinic.

Heterochronic parabiosis regulates the extent of cellular senescence in multiple tissues

An increase in the burden of senescent cells in tissues with age contributes to driving aging and the onset of age-related diseases. Genetic and pharmacologic elimination of senescent cells extends both health span and life span in mouse models. Heterochronic parabiosis in mice has been used to identify bloodborne, circulating pro- and anti-geronic factors able to drive or slow aging, respectively. However, whether factors in the circulation also regulate senescence is unknown. Here, we measured the expression of senescence and senescence-associated secretory phenotype (SASP) markers in multiple tissues from 4- to 18-month-old male mice that were either isochronically or heterochronically paired for 2 months. In heterochronic parabionts, the age-dependent increase in senescence and SASP marker expression was reduced in old mice exposed to a young environment, while senescence markers were concurrently increased in young heterochronic parabionts. These findings were supported by geropathology analysis using the Geropathology Grading Platform that showed a trend toward reduced hepatic lesions in old heterochronic parabionts. In summary, these results demonstrate that senescence is regulated in part by circulating geronic factors and suggest that one of the possible mediators of the rejuvenating effects with heterochronic parabiosis is through the reduction of the senescent cell burden.

Negligible senescence in naked mole rats may be a consequence of well-maintained splicing regulation

Naked mole-rats (NMRs) have amongst the longest lifespans relative to body size of any known, non-volant mammalian species. They also display an enhanced stress resistance phenotype, negligible senescence and very rarely are they burdened with chronic age-related diseases. Alternative splicing (AS) dysregulation is emerging as a potential driver of senescence and ageing. We hypothesised that the expression of splicing factors, important regulators of patterns of AS, may differ in NMRs when compared to other species with relatively shorter lifespans. We designed assays specific to NMR splicing regulatory factors and also to a panel of pre-selected brain-expressed genes known to demonstrate senescence-related alterations in AS in other species, and measured age-related changes in the transcript expression levels of these using embryonic and neonatal developmental stages through to extreme old age in NMR brain samples. We also compared splicing factor expression in both young mouse and NMR spleen and brain samples. Both NMR tissues showed approximately double the expression levels observed in tissues from similarly sized mice. Furthermore, contrary to observations in other species, following a brief period of labile expression in early life stages, adult NMR splicing factors and patterns of AS for functionally relevant brain genes remained remarkably stable for at least two decades. These findings are consistent with a model whereby the conservation of splicing regulation and stable patterns of AS may contribute to better molecular stress responses and the avoidance of senescence in NMRs, contributing to their exceptional lifespan and prolonged healthspan.