Direct visualization of de novo lipogenesis in single living cells

Seeing is Believing: Developing Multimodal Metabolic Insights at the Molecular Level

This outlook explores how two different molecular imaging approaches might be combined to gain insight into dynamic, subcellular metabolic processes. Specifically, we discuss how matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and stimulated Raman scattering (SRS) microscopy, which have significantly pushed the boundaries of imaging metabolic and metabolomic analyses in their own right, could be combined to create comprehensive molecular images. We first briefly summarize the recent advances for each technique. We then explore how one might overcome the inherent limitations of each individual method, by envisioning orthogonal and interchangeable workflows. Additionally, we delve into the potential benefits of adopting a complementary approach that combines both MSI and SRS spectro-microscopy for informing on specific chemical structures through functional-group-specific targets. Ultimately, by integrating the strengths of both imaging modalities, researchers can achieve a more comprehensive understanding of biological and chemical systems, enabling precise metabolic investigations. This synergistic approach holds substantial promise to expand our toolkit for studying metabolites in complex environments.

Discovery and Mechanistic Studies of Dual-Target Hits for Carbonic Anhydrase IX and VEGFR-2 as Potential Agents for Solid Tumors: X-ray, In Vitro, In Vivo, and In Silico Investigations of Coumarin-Based Thiazoles

A dual-targeting approach is predicted to yield better cancer therapy outcomes. Consequently, a series of coumarin-based thiazoles (5a-h, 6, and 7a-e) were designed and constructed as potential carbonic anhydrase (CA) and VEGFR-2 suppressors. The inhibitory actions of the target compounds were assessed against CA isoforms IX and VEGFR-2. The assay results showed that coumarin-based thiazoles 5a, 5d, and 5e can effectively inhibit both targets. 5a, 5d, and 5e cytotoxic effects were tested on pancreatic, breast, and prostate cancer cells (PANC1, MCF7, and PC3). Further mechanistic investigation disclosed the ability of 5e to interrupt the PANC1 cell progression in the S stage by triggering the apoptotic cascade, as seen by increased levels of caspases 3, 9, and BAX, alongside the Bcl-2 decline. Moreover, the in vivo efficacy of compound 5e as an antitumor agent was evaluated. Also, molecular docking and dynamics displayed distinctive interactions between 5e and CA IX and VEGFR-2 binding pockets.

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.

Dysregulation of cellular membrane homeostasis as a crucial modulator of cancer risk

Cellular membranes serve as an epicentre combining extracellular and cytosolic components with membranous effectors, which together support numerous fundamental cellular signalling pathways that mediate biological responses. To execute their functions, membrane proteins, lipids and carbohydrates arrange, in a highly coordinated manner, into well-defined assemblies displaying diverse biological and biophysical characteristics that modulate several signalling events. The loss of membrane homeostasis can trigger oncogenic signalling. More recently, it has been documented that select membrane active dietaries (MADs) can reshape biological membranes and subsequently decrease cancer risk. In this review, we emphasize the significance of membrane domain structure, organization and their signalling functionalities as well as how loss of membrane homeostasis can steer aberrant signalling. Moreover, we describe in detail the complexities associated with the examination of these membrane domains and their association with cancer. Finally, we summarize the current literature on MADs and their effects on cellular membranes, including various mechanisms of dietary chemoprevention/interception and the functional links between nutritional bioactives, membrane homeostasis and cancer biology.

Oleic acid differentially affects lipid droplet storage of de novo synthesized lipids in hepatocytes and adipocytes

Lipogenesis is a vital but often dysregulated metabolic pathway. Here we use optical photothermal infrared imaging to quantify lipogenesis rates of isotopically labelled oleic acid and glucose concomitantly in live cells. In hepatocytes, but not adipocytes, we find that oleic acid feeding at 60 μM increases the number and size of lipid droplets (LDs) while simultaneously inhibiting storage of de novo synthesized lipids in LDs. Our results demonstrate alternate regulation of lipogenesis between cell types.

Advances in Nanodelivery Systems Based on Metabolism Reprogramming Strategies for Enhanced Tumor Therapy

Tumor development and metastasis are closely related to the complexity of the metabolism network. Recently, metabolism reprogramming strategies have attracted much attention in tumor metabolism therapy. Although there is preliminary success of metabolism therapy agents, their therapeutic effects have been restricted by the effective reaching of the tumor sites of drugs. Nanodelivery systems with unique physical properties and elaborate designs can specifically deliver to the tumors. In this review, we first summarize the research progress of nanodelivery systems based on tumor metabolism reprogramming strategies to enhance therapies by depleting glucose, inhibiting glycolysis, depleting lactic acid, inhibiting lipid metabolism, depleting glutamine and glutathione, and disrupting metal metabolisms combined with other therapies, including chemotherapy, radiotherapy, photodynamic therapy, etc. We further discuss in detail the advantages of nanodelivery systems based on tumor metabolism reprogramming strategies for tumor therapy. As well as the opportunities and challenges for integrating nanodelivery systems into tumor metabolism therapy, we analyze the outlook for these emerging areas. This review is expected to improve our understanding of modulating tumor metabolisms for enhanced therapy.

Raman microscopy reveals how cell inflammation activates glucose and lipid metabolism

Metabolism of endothelial cells (ECs) depends on the availability of the energy substrates. Since the endothelium is the first line of defence against inflammation in the cardiovascular system and its dysfunction can lead to the development of cardiovascular diseases, it is important to understand how glucose metabolism changes during inflammation. In this work, glucose uptake was studied in human microvascular endothelial cells (HMEC-1) in high glucose (HG), and additionally in an inflammatory state, using Raman imaging. HG state was induced by incubation of ECs with a deuterated glucose analogue, while the EC inflammation was caused by TNF-α pre-treatment. Spontaneous and stimulated Raman scattering spectroscopy provided comprehensive information on biochemical changes, including lipids and the extent of unsaturation induced by excess glucose in ECs., induced by excess glucose in ECs. In this work, we indicated spectroscopic markers of metabolic changes in ECs as a strong increase in the ratio of the intensity of lipids / (proteins + lipids) bands and an increase in the level of lipid unsaturation and mitochondrial changes. Inflamed ECs treated with HG, revealed enhanced glucose uptake, and intensified lipid production i.a. of unsaturated lipids. Additionally, increased cytochrome c signal in the mitochondrial region indicated higher mitochondrial activity and biogenesis. Raman spectroscopy is a powerful method for determining the metabolic markers of ED which will better inform understanding of disease onset, development, and treatment.

Label-free spatially maintained measurements of metabolic phenotypes in cells

Metabolic reprogramming at a cellular level contributes to many diseases including cancer, yet few assays are capable of measuring metabolic pathway usage by individual cells within living samples. Here, autofluorescence lifetime imaging is combined with single-cell segmentation and machine-learning models to predict the metabolic pathway usage of cancer cells. The metabolic activities of MCF7 breast cancer cells and HepG2 liver cancer cells were controlled by growing the cells in culture media with specific substrates and metabolic inhibitors. Fluorescence lifetime images of two endogenous metabolic coenzymes, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), were acquired by a multi-photon fluorescence lifetime microscope and analyzed at the cellular level. Quantitative changes of NADH and FAD lifetime components were observed for cells using glycolysis, oxidative phosphorylation, and glutaminolysis. Conventional machine learning models trained with the autofluorescence features classified cells as dependent on glycolytic or oxidative metabolism with 90%-92% accuracy. Furthermore, adapting convolutional neural networks to predict cancer cell metabolic perturbations from the autofluorescence lifetime images provided improved performance, 95% accuracy, over traditional models trained via extracted features. Additionally, the model trained with the lifetime features of cancer cells could be transferred to autofluorescence lifetime images of T cells, with a prediction that 80% of activated T cells were glycolytic, and 97% of quiescent T cells were oxidative. In summary, autofluorescence lifetime imaging combined with machine learning models can detect metabolic perturbations between glycolysis and oxidative metabolism of living samples at a cellular level, providing a label-free technology to study cellular metabolism and metabolic heterogeneity.

Stimulated Raman photothermal microscopy toward ultrasensitive chemical imaging

Stimulated Raman scattering (SRS) microscopy has shown enormous potential in revealing molecular structures, dynamics, and couplings in complex systems. However, the sensitivity of SRS is fundamentally limited to the millimolar level due to shot noise and the small modulation depth. To overcome this barrier, we revisit SRS from the perspective of energy deposition. The SRS process pumps molecules to their vibrationally excited states. The subsequent relaxation heats up the surroundings and induces refractive index changes. By probing the refractive index changes with a laser beam, we introduce stimulated Raman photothermal (SRP) microscopy, where a >500-fold boost of modulation depth is achieved. The versatile applications of SRP microscopy on viral particles, cells, and tissues are demonstrated. SRP microscopy opens a way to perform vibrational spectroscopic imaging with ultrahigh sensitivity.

Oleic acid differentially affects de novo lipogenesis in adipocytes and hepatocytes

Lipogenesis is a vital but often dysregulated metabolic pathway. We report super-resolution multiplexed vibrational imaging of lipogenesis rates and pathways using isotopically labelled oleic acid and glucose as probes in live adipocytes and hepatocytes. These findings suggest oleic acid inhibits de novo lipogenesis (DNL), but not total lipogenesis, in hepatocytes. No significant effect is seen in adipocytes. These differential effects may be due to alternate regulation of DNL between cell types and could help explain the complicated role oleic acid plays in metabolism.

Accelerating Cancer Histopathology Workflows with Chemical Imaging and Machine Learning

Histopathology has remained a cornerstone for biomedical tissue assessment for over a century, with a resource-intensive workflow involving biopsy or excision, gross examination, sampling, tissue processing to snap frozen or formalin-fixed paraffin-embedded blocks, sectioning, staining, optical imaging, and microscopic assessment. Emerging chemical imaging approaches, including stimulated Raman scattering (SRS) microscopy, can directly measure inherent molecular composition in tissue (thereby dispensing with the need for tissue processing, sectioning, and using dyes) and can use artificial intelligence (AI) algorithms to provide high-quality images. Here we show the integration of SRS microscopy in a pathology workflow to rapidly record chemical information from minimally processed fresh-frozen prostate tissue. Instead of using thin sections, we record data from intact thick tissues and use optical sectioning to generate images from multiple planes. We use a deep learning–based processing pipeline to generate virtual hematoxylin and eosin images. Next, we extend the computational method to generate archival-quality images in minutes, which are equivalent to those obtained from hours/days-long formalin-fixed, paraffin-embedded processing. We assessed the quality of images from the perspective of enabling pathologists to make decisions, demonstrating that the virtual stained image quality was diagnostically useful and the interpathologist agreement on prostate cancer grade was not impacted. Finally, because this method does not wash away lipids and small molecules, we assessed the utility of lipid chemical composition in determining grade. Together, the combination of chemical imaging and AI provides novel capabilities for rapid assessments in pathology by reducing the complexity and burden of current workflows.

SIGNIFICANCE

Archival-quality (formalin-fixed paraffin-embedded), thin-section diagnostic images are obtained from thick-cut, fresh-frozen prostate tissues without dyes or stains to expedite cancer histopathology by combining SRS microscopy and machine learning.

Stimulated Raman Photothermal Microscopy towards Ultrasensitive Chemical Imaging

Stimulated Raman scattering (SRS) microscopy has shown enormous potential in revealing molecular structures, dynamics and coupling in a complex system. However, the bond-detection sensitivity of SRS microscopy is fundamentally limited to milli-molar level due to the shot noise and the small modulation depth in either pump or Stokes beam4. Here, to overcome this barrier, we revisit SRS from the perspective of energy deposition. The SRS process pumps molecules to their vibrational excited states. The thereafter relaxation heats up the surrounding and induces a change in refractive index. By probing the refractive index change with a continuous wave beam, we introduce stimulated Raman photothermal (SRP) microscopy, where a >500-fold boost of modulation depth is achieved on dimethyl sulfide with conserved average power. Versatile applications of SRP microscopy on viral particles, cells, and tissues are demonstrated. With much improved signal to noise ratio compared to SRS, SRP microscopy opens a new way to perform vibrational spectroscopic imaging with ultrahigh sensitivity and minimal water absorption.

Coherent Raman scattering microscopy of lipid droplets in cells and tissues

Lipid droplets (LDs) play a key role as the hub for lipid metabolism to maintain cellular metabolic homeostasis. Understanding the functions and changes of LDs in different pathological conditions is crucial for identifying new markers for diagnosis and discovering new targets for treatment. In recent years, coherent Raman scattering (CRS) microscopy has been popularized for the imaging and quantification of LDs in live cells. Compared to spontaneous Raman scattering microscopy, CRS microscopy offers a much higher imaging speed while maintaining similar chemical information. Due to the high lipid density, LDs usually have strong CRS signals and therefore are the most widely studied organelle in the CRS field. In this review, we discuss recent achievements using CRS to study the quantity, distribution, composition, and dynamics of LDs in various systems.

Lipid Polyunsaturated Fatty Acid Chains in Mouse Kidneys Were Increased within 5 min of a Single High Dose Whole Body Irradiation

To understand the ultra-early reaction of normal organ lipids during irradiation, we investigated the response of lipids, including polyunsaturated fatty acid (PUFA) chains, which are particularly susceptible to damage by ROS, in mice's kidneys, lungs, brains, and livers within 5 min of single high-dose irradiation. In this study, we set up three groups of C56BL/6 male mice and conducted whole-body irradiation with 0 Gy, 10 Gy, and 20 Gy single doses. Kidney, lung, brain, and liver tissues were collected within 5 min of irradiation. PUFA-targeted and whole lipidomic analyses were conducted using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results showed that PUFA chains of kidney phosphatidylcholine (PC), phosphatidylethanolamine (PE), and triacylglycerol (TG) significantly increased within 5 min of 10 Gy and 20 Gy irradiation. The main components of increased PUFA chains in PC and PE were C18:2, C20:4, and C22:6, and in TG the main component was C18:2. The kidney lipidomes also showed significant changes from the perspective of lipid species, mainly dominated by an increase in PC, PE, TG, and signal lipids, while lipidomes of the lung, brain, and liver were slightly changed. Our results revealed that acute PUFA chains increase and other lipidomic changes in the kidney upon whole-body irradiation within 5 min of irradiation. The significantly increased lipids also showed a consistent preference for possessing PUFA chains. The lipidomic changes varied from organ to organ, which indicates that the response upon irradiation within a short time is tissue-specific.

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.

Cancer metabolic features allow discrimination of tumor from white blood cells by label-free multimodal optical imaging

Circulating tumor cells (CTCs) are tumor cells that have penetrated the circulatory system preserving tumor properties and heterogeneity. Detection and characterization of CTCs has high potential clinical values and many technologies have been developed for CTC identification. These approaches remain challenged by the extraordinary rarity of CTCs and the difficulty of efficiently distinguishing cancer from the much larger number of white blood cells in the bloodstream. Consequently, there is still a need for efficient and rapid methods to capture the broad spectrum of tumor cells circulating in the blood. Herein, we exploit the peculiarities of cancer metabolism for discriminating cancer from WBCs. Using deuterated glucose and Raman microscopy we show that a) the known ability of cancer cells to take up glucose at greatly increased rates compared to non-cancer cells results in the lipid generation and accumulation into lipid droplets and, b) by contrast, leukocytes do not appear to generate visible LDs. The difference in LD abundance is such that it provides a reliable parameter for distinguishing cancer from blood cells. For LD sensitive detections in a cell at rates suitable for screening purposes, we test a polarization-sensitive digital holographic imaging (PSDHI) technique that detects the birefringent properties of the LDs. By using polarization-sensitive digital holographic imaging, cancer cells (prostate cancer, PC3 and hepatocarcinoma cells, HepG2) can be rapidly discriminated from leukocytes with reliability close to 100%. The combined Raman and PSDHI microscopy platform lays the foundations for the future development of a new label-free, simple and universally applicable cancer cells' isolation method.

Importance of lactate dehydrogenase (LDH) and monocarboxylate transporters (MCTs) in cancer cells

Background

In most regions, cancer ranks the second most frequent cause of death following cardiovascular disorders.

Aim

In this article, we review the various aspects of glycolysis with a focus on types of MCTs and the importance of lactate in cancer cells.

Results and Discussion

Metabolic changes are one of the first and most important alterations in cancer cells. Cancer cells use different pathways to survive, energy generation, growth, and proliferation compared to normal cells. The increase in glycolysis, which produces substances such as lactate and pyruvate, has an important role in metastases and invasion of cancer cells. Two important cellular proteins that play a role in the production and transport of lactate include lactate dehydrogenase and monocarboxylate transporters (MCTs). These molecules by their various isoforms and different tissue distribution help to escape the immune system and expansion of cancer cells under different conditions.

Untargeted metabolomics characterization of the resectable pancreatic ductal adenocarcinoma

Background

Diagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to the lack of specific symptoms and screening methods. Only less than 10% of PDAC patients are candidates for surgery at the time of diagnosis. Thus, there is a great global unmet need for valuable biomarkers that could improve the opportunity to detect PDAC at the resectable stage. This study aimed to develop a potential biomarker model for the detection of resectable PDAC by tissue and serum metabolomics.

Methods

Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS) was performed for metabolome quantification in 98 serum samples (49 PDAC patients and 49 healthy controls (HCs)) and 20 pairs of matched pancreatic cancer tissues (PCTs) and adjacent noncancerous tissues (ANTs) from PDAC patients. Univariate and multivariate analyses were used to profile the differential metabolites between PDAC and HC.

Results

A total of 12 differential metabolites were present in both serum and tissue samples of PDAC. Among them, a total of eight differential metabolites showed the same expressional levels, including four upregulated and four downregulated metabolites. Finally, a panel of three metabolites including 16-hydroxypalmitic acid, phenylalanine, and norleucine was constructed by logistic regression analysis. Notably, the panel was capable of distinguishing resectable PDAC from HC with an AUC value of 0.942. Additionally, a multimarker model based on the 3-metabolites-based panel and CA19-9 showed a better performance than the metabolites panel or CA19-9 alone (AUC: 0.968 vs. 0.942, 0.850).

Conclusions

Taken together, the resectable early-stage PDAC has unique metabolic features in serum and tissue samples. The defined panel of three metabolites has the potential value for early screening of PDAC at the resectable stage.

Acetyl-CoA regulates lipid metabolism and histone acetylation modification in cancer

Acetyl-CoA, as an important molecule, not only participates in multiple intracellular metabolic reactions, but also affects the post-translational modification of proteins, playing a key role in the metabolic activity and epigenetic inheritance of cells. Cancer cells require extensive lipid metabolism to fuel for their growth, while also require histone acetylation modifications to increase the expression of cancer-promoting genes. As a raw material for de novo lipid synthesis and histone acetylation, acetyl-CoA has a major impact on lipid metabolism and histone acetylation in cancer. More importantly, in cancer, acetyl-CoA connects lipid metabolism with histone acetylation, forming a more complex regulatory mechanism that influences cancer growth, proliferation, metastasis.

Raman Spectroscopy for Chemical Biology Research

In chemical biology research, various fluorescent probes have been developed and used to visualize target proteins or molecules in living cells and tissues, yet there are limitations to this technology, such as the limited number of colors that can be detected simultaneously. Recently, Raman spectroscopy has been applied in chemical biology to overcome such limitations. Raman spectroscopy detects the molecular vibrations reflecting the structures and chemical conditions of molecules in a sample and was originally used to directly visualize the chemical responses of endogenous molecules. However, our initial research to develop "Raman tags" opens a new avenue for the application of Raman spectroscopy in chemical biology. In this Perspective, we first introduce the label-free Raman imaging of biomolecules, illustrating the biological applications of Raman spectroscopy. Next, we highlight the application of Raman imaging of small molecules using Raman tags for chemical biology research. Finally, we discuss the development and potential of Raman probes, which represent the next-generation probes in chemical biology.

Advances in measuring cancer cell metabolism with subcellular resolution

Characterizing metabolism in cancer is crucial for understanding tumor biology and for developing potential therapies. Although most metabolic investigations analyze averaged metabolite levels from all cell compartments, subcellular metabolomics can provide more detailed insight into the biochemical processes associated with the disease. Methodological limitations have historically prevented the wider application of subcellular metabolomics in cancer research. Recently, however, ways to distinguish and identify metabolic pathways within organelles have been developed, including state-of-the-art methods to monitor metabolism in situ (such as mass spectrometry-based imaging, Raman spectroscopy and fluorescence microscopy), to isolate key organelles via new approaches and to use tailored isotope-tracing strategies. Herein, we examine the advantages and limitations of these developments and look to the future of this field of research.

Metabolic reprogramming from glycolysis to fatty acid uptake and beta-oxidation in platinum-resistant cancer cells

Increased glycolysis is considered as a hallmark of cancer. Yet, cancer cell metabolic reprograming during therapeutic resistance development is under-studied. Here, through high-throughput stimulated Raman scattering imaging and single cell analysis, we find that cisplatin-resistant cells exhibit increased fatty acids (FA) uptake, accompanied by decreased glucose uptake and lipogenesis, indicating reprogramming from glucose to FA dependent anabolic and energy metabolism. A metabolic index incorporating glucose derived anabolism and FA uptake correlates linearly to the level of cisplatin resistance in ovarian cancer (OC) cell lines and primary cells. The increased FA uptake facilitates cancer cell survival under cisplatin-induced oxidative stress by enhancing beta-oxidation. Consequently, blocking beta-oxidation by a small molecule inhibitor combined with cisplatin or carboplatin synergistically suppresses OC proliferation in vitro and growth of patient-derived xenografts in vivo. Collectively, these findings support a rapid detection method of cisplatin-resistance at single cell level and a strategy for treating cisplatin-resistant tumors.

Bringing Vibrational Imaging to Chemical Biology with Molecular Probes

As an emerging optical imaging modality, stimulated Raman scattering (SRS) microscopy provides invaluable opportunities for chemical biology studies using its rich chemical information. Through rapid progress over the past decade, the development of Raman probes harnessing the chemical biology toolbox has proven to play a key role in advancing SRS microscopy and expanding biological applications. In this perspective, we first discuss the development of biorthogonal SRS imaging using small tagging of triple bonds or isotopes and highlight their unique advantages for metabolic pathway analysis and microbiology investigations. Potential opportunities for chemical biology studies integrating small tagging with SRS imaging are also proposed. We next summarize the current designs of highly sensitive and super-multiplexed SRS probes, as well as provide future directions and considerations for next-generation functional probe design. These rationally designed SRS probes are envisioned to bridge the gap between SRS microscopy and chemical biology research and should benefit their mutual development.

SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level

One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.

Label-Free Imaging of Lipid Droplets in Prostate Cells Using Stimulated Raman Scattering Microscopy and Multivariate Analysis

Hyperspectral stimulated Raman scattering (SRS) microscopy is a powerful imaging modality for the analysis of biological systems. Here, we report the application of k-means cluster analysis (KMCA) of multi-wavelength SRS images in the high-wavenumber region of the Raman spectrum as a robust and reliable method for the segmentation of cellular organelles based on the intrinsic SRS spectrum. KMCA has been applied to the study of the endogenous lipid biochemistry of prostate cancer and prostate healthy cell models, while the corresponding SRS spectrum of the lipid droplet (LD) cluster enabled direct comparison of their composition. The application of KMCA in visualizing the LD content of prostate cell models following the inhibition of de novo lipid synthesis (DNL) using the acetyl-coA carboxylase inhibitor, 5-(tetradecyloxy)-2-furoic acid (TOFA), is demonstrated. This method identified a reliance of prostate cancer cell models upon DNL for metabolic requirements, with a significant reduction in the cellular LD content after treatment with TOFA, which was not observed in normal prostate cell models. SRS imaging combined with KMCA is a robust method for investigating drug–cell interactions in a label-free manner.

Quantitative Stimulated Raman Scattering Microscopy: Promises and Pitfalls

Since its first demonstration, stimulated Raman scattering (SRS) microscopy has become a powerful chemical imaging tool that shows promise in numerous biological and biomedical applications. The spectroscopic capability of SRS enables identification and tracking of specific molecules or classes of molecules, often without labeling. SRS microscopy also has the hallmark advantage of signal strength that is directly proportional to molecular concentration, allowing for in situ quantitative analysis of chemical composition of heterogeneous samples with submicron spatial resolution and subminute temporal resolution. However, it is important to recognize that quantification through SRS microscopy requires assumptions regarding both system and sample. Such assumptions are often taken axiomatically, which may lead to erroneous conclusions without proper validation. In this review, we focus on the tacitly accepted, yet complex, quantitative aspect of SRS microscopy. We discuss the various approaches to quantitative analysis, examples of such approaches, challenges in different systems, and potential solutions. Through our examination of published literature, we conclude that a scrupulous approach to experimental design can further expand the powerful and incisive quantitative capabilities of SRS microscopy.

Targeting lipid metabolism in the treatment of ovarian cancer

Cancer cells undergo alterations in lipid metabolism to support their high energy needs, tumorigenesis and evade an anti-tumor immune response. Alterations in fatty acid production are controlled by multiple enzymes, chiefly Acetyl CoA Carboxylase, ATP-Citrate Lyase, Fatty Acid Synthase, and Stearoyl CoA Desaturase 1. Ovarian cancer (OC) is a common gynecological malignancy with a high rate of aggressive carcinoma progression and drug resistance. The accumulation of unsaturated fatty acids in ovarian cancer supports cell growth, increased cancer cell migration, and worse patient outcomes. Ovarian cancer cells also expand their lipid stores via increased uptake of lipids using fatty acid translocases, fatty acid-binding proteins, and low-density lipoprotein receptors. Furthermore, increased lipogenesis and lipid uptake promote chemotherapy resistance and dampen the adaptive immune response needed to eliminate tumors. In this review, we discuss the role of lipid synthesis and metabolism in driving tumorigenesis and drug resistance in ovarian cancer conferring poor prognosis and outcomes in patients. We also cover some aspects of how lipids fuel ovarian cancer stem cells, and how these metabolic alterations in intracellular lipid content could potentially serve as biomarkers of ovarian cancer.

Decreased expression of miR-195 mediated by hypermethylation promotes osteosarcoma

Osteosarcoma (OS) is the most common type of primary malignant bone tumor. The early lung metastasis of osteosarcoma is one of the main factors of poor prognosis. Therefore, searching for new targets and new mechanisms of osteosarcoma metastasis is essential for the prevention and treatment of osteosarcoma. Our previous studies suggested that fatty acid synthase (FASN) was an oncogene and promoted osteosarcoma. In addition, it is reported that the expression of miR-195 was negatively correlated with osteosarcoma. Aberrant DNA methylation can reversely regulate the expression of miRNAs. However, whether miR-195 could target FASN in osteosarcoma and whether ectopic DNA methylation is the upstream regulatory mechanism of miR-195 in metastasis of osteosarcoma are not fully studied. The expressions were detected by qPCR and western blot, and methylation level was determined by methylation-specific PCR. Luciferase reporter assay, MTT, wound healing, and Transwell assay were used. We found that the expression of miR-195 was low in osteosarcoma. The methylation of miR-195 was high. miR-195 targeted and decreased the expression of FASN. In osteosarcoma, miR-195 inhibited cell proliferation, cell migration, and invasion. The methylation of miR-195 was related to decreased miR-195, it might promote osteosarcoma.

Probing Methionine Uptake in Live Cells by Deuterium Labeling and Stimulated Raman Scattering

The small biomolecule methionine (Met) is a fundamental amino acid required for a vast range of biological processes such as protein synthesis, cancer metabolism, and epigenetics. However, it is still difficult to visualize the subcellular distribution of small biomolecules including Met in a minimally invasive manner. Here, we demonstrate stimulated Raman scattering (SRS) imaging of cellular uptake of deuterated methionine (d₈-Met) in live HeLa cells by way of comparison to the previously used alkyne-labeled Met analogue─homopropargylglycine (Hpg). We show that the solutions of d₈-Met and Hpg have similar SRS signal intensities. Furthermore, by careful image analysis with background subtraction, we succeed in the SRS imaging of cellular uptake of d₈-Met with a much greater signal intensity than Hpg, possibly reflecting the increased and minimally invasive uptake kinetics of d₈-Met compared with Hpg. We anticipate that d₈-Met and other deuterated biomolecules will be useful for investigating metabolic processes with subcellular resolution.

Metabolic response to radiation therapy in cancer

Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms. Studying radiation-induced metabolic changes will lead to a better understanding of radiation response mechanisms as well as the identification of new therapeutic targets, but there are few robust studies characterizing the metabolic changes induced by radiation therapy in cancer. In this review, we will highlight studies that provide information on the metabolic changes induced by radiation and oxidative stress in cancer cells and the associated underlying mechanisms.

Metabolic manipulation of the tumour immune microenvironment

In the past few years, the evolution of immunotherapy has resulted in a shift in cancer treatment models. However, with immunosuppressive effects of the tumour microenvironment continue to limit advances in tumour immunotherapy. The tumour microenvironment induces metabolic reprogramming in cancer cells, which results in competition for nutrients between tumour cells and host immunocytes. Metabolic and waste products originating in tumour cells can influence the activation and effector properties of immunocytes in numerous ways and ultimately promote the survival and propagation of tumour cells. In this paper, we discuss metabolic reprogramming in tumour cells and the influence of metabolite byproducts on the immune microenvironment, providing novel insights into tumour immunotherapy.

Investigation of insulin resistance through a multiorgan microfluidic organ-on-chip

The development of hepatic insulin resistance (IR) is a critical factor in developing type 2 diabetes (T2D), where insulin fails to inhibit hepatic glucose production but retains its capacity to promote hepatic lipogenesis. Improving insulin sensitivity can be effective in preventing and treating T2D. However, selective control of glucose and lipid synthesis has been difficult. It is known that excess white adipose tissue is detrimental to insulin sensitivity, whereas brown adipose tissue transplantation can restore it in diabetic mice. However, challenges remain in our understanding of liver-adipose communication because the confounding effects of hypothalamic regulation of metabolic function cannot be ruled out in previous studies. There is a lack of in vitro models that use primary cells to study cellular-crosstalk under insulin resistant conditions. Building upon our previous work on the microfluidic primary liver and adipose organ-on-chips, we report for the first time the development of integrated insulin resistant liver-adipose (white and brown) organ-on-chip. The design of the microfluidic device was carried out using computational fluid dynamics; the experimental studies were conducted by carrying out detailed biochemical analysis RNA-seq analysis on both cell types. Further, we tested the hypothesis that brown adipocytes regulated both hepatic insulin sensitivity and lipogenesis. Our results show effective co-modulation of hepatic glucose and lipid synthesis through a platform for identifying potential therapeutics for IR and diabetes.

Probing the Biogenesis of Polysaccharide Granules in Algal Cells at Sub-Organellar Resolution via Raman Microscopy with Stable Isotope Labeling

Phototrophs assimilate CO₂ into organic compounds that accumulate in storage organelles. Elucidation of the carbon dynamics of storage organelles could enhance the production efficiency of valuable compounds and facilitate the screening of strains with high photosynthetic activity. To comprehensively elucidate the carbon dynamics of these organelles, the intraorganellar distribution of the carbon atoms that accumulate at specific time periods should be probed. In this study, the biosynthesis of polysaccharides in storage organelles was spatiotemporally probed via stimulated Raman scattering (SRS) microscopy using a stable isotope (¹³C) as the tracking probe. Paramylon granules (a storage organelle of β-1,3-glucan) accumulated in a unicellular photosynthetic alga, Euglena gracilis, were investigated as a model organelle. The carbon source of the culture medium was switched from NaH¹²CO₃ to NaH¹³CO₃ during the production of the paramylon granules; this resulted in the distribution of the ¹²C and ¹³C constituents in the granules, so that the biosynthetic process could be tracked. Taking advantage of high-resolution SRS imaging and label switching, the localization of the ¹²C and ¹³C constituents inside a single paramylon granule could be visualized in three dimensions, thus revealing the growth process of paramylon granules. We propose that this method can be used for comprehensive elucidation of the dynamic activities of storage organelles.

A UHPLC-Mass Spectrometry View of Human Melanocytic Cells Uncovers Potential Lipid Biomarkers of Melanoma

Melanoma is the deadliest form of skin cancer due to its ability to colonize distant sites and initiate metastasis. Although these processes largely depend on the lipid-based cell membrane scaffold, our understanding of the melanoma lipid phenotype lags behind most other aspects of this tumor cell. Here, we examined a panel of normal human epidermal and nevus melanocytes and primary and metastatic melanoma cell lines to determine whether distinctive cell-intrinsic lipidomes can discern non-neoplastic from neoplastic melanocytes and define their metastatic potential. Lipidome profiles were obtained by UHPLC-ESI mass-spectrometry, and differences in the signatures were analyzed by multivariate statistical analyses. Significant and highly specific changes in more than 30 lipid species were annotated in the initiation of melanoma, whereas less numerous changes were associated with melanoma progression and the non-malignant transformation of nevus melanocytes. Notably, the "malignancy lipid signature" features marked drops in pivotal membrane lipids, like sphingomyelins, and aberrant elevation of ether-type lipids and phosphatidylglycerol and phosphatidylinositol variants, suggesting a previously undefined remodeling of sphingolipid and glycerophospholipid metabolism. Besides broadening the molecular definition of this neoplasm, the different lipid profiles identified may help improve the clinical diagnosis/prognosis and facilitate therapeutic interventions for cutaneous melanoma.

Advancing Raman spectroscopy from research to clinic: Translational potential and challenges

Raman spectroscopy has emerged as a non-invasive and versatile diagnostic technique due to its ability to provide molecule-specific information with ultrahigh sensitivity at near-physiological conditions. Despite exhibiting substantial potential, its translation from optical bench to clinical settings has been impacted by associated limitations. This perspective discusses recent clinical and biomedical applications of Raman spectroscopy and technological advancements that provide valuable insights and encouragement for resolving some of the most challenging hurdles.

Lipid Droplet Accumulation Independently Predicts Poor Clinical Prognosis in High-Grade Serous Ovarian Carcinoma

Simple Summary

High-grade serous carcinoma (HGSOC) is the most aggressive subtype of ovarian cancer and accounts for the vast majority of advanced stage cases. Intracellular accumulation of lipids as lipid droplets has been recognized as one of the characteristics of cancers and implicated in poor prognosis of several cancers, such as human melanomas. Here, we investigated the relationship between prognosis and lipid accumulation in HGSOC, and found that enhanced lipid accumulation in HGSOC tissues significantly correlated with poor prognosis. In cell-based assays with human ovarian cancer cells, we provide evidence that aerobic glycolysis, which is one of the characteristic metabolic abnormalities in cancer, induced lipid accumulation within cancer cells and targeting the lipid accumulation could suppress cancer cell proliferation. Thus, our results propose abnormal lipid accumulation as a negative indicator of HGSOC prognosis and a novel therapeutic target.

Abstract

High-grade serous ovarian carcinoma (HGSOC) is an epithelial cancer that accounts for most ovarian cancer deaths. Metabolic abnormalities such as extensive aerobic glycolysis and aberrant lipid metabolism are well-known characteristics of cancer cells. Indeed, accumulation of lipid droplets (LDs) in certain types of malignant tumors has been known for more than 50 years. Here, we investigated the correlation between LD accumulation and clinical prognosis. In 96 HGSOC patients, we found that high expression of the LD marker adipophilin was associated with poor progression-free and overall survival (p = 0.0022 and p = 0.014, respectively). OVCAR-3 ovarian carcinoma cells accumulated LDs in a glucose-dependent manner, which suggested the involvement of aerobic glycolysis and subsequently enhanced lipogenesis, with a result being LD accumulation. The acyl-CoA: cholesterol acyltransferase 1 inhibitor K604 and the hydroxymethylglutaryl-CoA reductase inhibitor pitavastatin blocked LD accumulation in OVCAR-3 cells and reduced phosphorylation of the survival-related kinases Akt and ERK1/2, both of which have been implicated in malignancy. Our cell-based assays thus suggested that enhanced aerobic glycolysis resulted in LD accumulation and activation of survival-related kinases. Overall, our results support the idea that cancers with lipogenic phenotypes are associated with poor clinical prognosis, and we suggest that adipophilin may serve as an independent indicator of a poor prognosis in HGSOC.

Multimodal Metabolic Imaging Reveals Pigment Reduction and Lipid Accumulation in Metastatic Melanoma

Objective and Impact Statement. Molecular signatures are needed for early diagnosis and improved treatment of metastatic melanoma. By high-resolution multimodal chemical imaging of human melanoma samples, we identify a metabolic reprogramming from pigmentation to lipid droplet (LD) accumulation in metastatic melanoma. Introduction. Metabolic plasticity promotes cancer survival and metastasis, which promises to serve as a prognostic marker and/or therapeutic target. However, identifying metabolic alterations has been challenged by difficulties in mapping localized metabolites with high spatial resolution. Methods. We developed a multimodal stimulated Raman scattering and pump-probe imaging platform. By time-domain measurement and phasor analysis, our platform allows simultaneous mapping of lipids and pigments at a subcellular level. Furthermore, we identify the sources of these metabolic signatures by tracking deuterium metabolites at a subcellular level. By validation with mass spectrometry, a specific fatty acid desaturase pathway was identified. Results. We identified metabolic reprogramming from a pigment-containing phenotype in low-grade melanoma to an LD-rich phenotype in metastatic melanoma. The LDs contain high levels of cholesteryl ester and unsaturated fatty acids. Elevated fatty acid uptake, but not de novo lipogenesis, contributes to the LD-rich phenotype. Monounsaturated sapienate, mediated by FADS2, is identified as an essential fatty acid that promotes cancer migration. Blocking such metabolic signatures effectively suppresses the migration capacity both in vitro and in vivo. Conclusion. By multimodal spectroscopic imaging and lipidomic analysis, the current study reveals lipid accumulation, mediated by fatty acid uptake, as a metabolic signature that can be harnessed for early diagnosis and improved treatment of metastatic melanoma.

Airy light-sheet Raman imaging

Light-sheet fluorescence microscopy has greatly improved the speed and overall photostability of optically sectioning cellular and multi-cellular specimens. Similar gains have also been conferred by light-sheet Raman imaging; these schemes, however, rely on diffraction limited Gaussian beams that hinder the uniformity and size of the imaging field-of-view, and, as such, the resulting throughput rates. Here, we demonstrate that a digitally scanned Airy beam increases the Raman imaging throughput rates by more than an order of magnitude than conventional diffraction-limited beams. Overall, this, spectrometer-less, approach enabled 3D imaging of microparticles with high contrast and 1 µm axial resolution at 300 msec integration times per plane and orders of magnitude lower irradiation density than coherent Raman imaging schemes. We detail the apparatus and its performance, as well as its compatibility with fluorescence light-sheet and quantitative-phase imaging towards rapid and low phototoxicity multimodal imaging.

Raman Stable Isotope Probing of Bacteria in Visible and Deep UV-Ranges

Raman stable isotope probing (Raman-SIP) is an excellent technique that can be used to access the overall metabolism of microorganisms. Recent studies have mainly used an excitation wavelength in the visible range to characterize isotopically labeled bacteria. In this work, we used UV resonance Raman spectroscopy (UVRR) to evaluate the spectral red-shifts caused by the uptake of isotopes (¹³C, ¹⁵N, ²H(D) and ¹⁸O) in E. coli cells. Moreover, we present a new approach based on the extraction of labeled DNA in combination with UVRR to identify metabolically active cells. The proof-of-principle study on E. coli revealed heterogeneities in the Raman features of both the bacterial cells and the extracted DNA after labeling with ¹³C, ¹⁵N, and D. The wavelength of choice for studying ¹⁸O- and deuterium-labeled cells is 532 nm is, while ¹³C-labeled cells can be investigated with visible and deep UV wavelengths. However, ¹⁵N-labeled cells are best studied at the excitation wavelength of 244 nm since nucleic acids are in resonance at this wavelength. These results highlight the potential of the presented approach to identify active bacterial cells. This work can serve as a basis for the development of new techniques for the rapid and efficient detection of active bacteria cells without the need for a cultivation step.

Looking for a perfect match: multimodal combinations of Raman spectroscopy for biomedical applications

Raman spectroscopy has shown very promising results in medical diagnostics by providing label-free and highly specific molecular information of pathological tissue ex vivo and in vivo. Nevertheless, the high specificity of Raman spectroscopy comes at a price, i.e., low acquisition rate, no direct access to depth information, and limited sampling areas. However, a similar case regarding advantages and disadvantages can also be made for other highly regarded optical modalities, such as optical coherence tomography, autofluorescence imaging and fluorescence spectroscopy, fluorescence lifetime microscopy, second-harmonic generation, and others. While in these modalities the acquisition speed is significantly higher, they have no or only limited molecular specificity and are only sensitive to a small group of molecules. It can be safely stated that a single modality provides only a limited view on a specific aspect of a biological specimen and cannot assess the entire complexity of a sample. To solve this issue, multimodal optical systems, which combine different optical modalities tailored to a particular need, become more and more common in translational research and will be indispensable diagnostic tools in clinical pathology in the near future. These systems can assess different and partially complementary aspects of a sample and provide a distinct set of independent biomarkers. Here, we want to give an overview on the development of multimodal systems that use RS in combination with other optical modalities to improve the diagnostic performance.

Coherent Raman scattering microscopy for chemical imaging of biological systems

Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.

Coherent Raman scattering microscopy: capable solution in search of a larger audience

SIGNIFICANCE

Coherent Raman scattering (CRS) microscopy is an optical imaging technique with capabilities that could benefit a broad range of biomedical research studies.

AIM

We reflect on the birth, rapid rise, and inescapable growing pains of the technique and look back on nearly four decades of developments to examine where the CRS imaging approach might be headed in the next decade to come.

APPROACH

We provide a brief historical account of CRS microscopy, followed by a discussion of the challenges to disseminate the technique to a larger audience. We then highlight recent progress in expanding the capabilities of the CRS microscope and assess its current appeal as a practical imaging tool.

RESULTS

New developments in Raman tagging have improved the specificity and sensitivity of the CRS technique. In addition, technical advances have led to CRS microscopes that can capture hyperspectral data cubes at practical acquisition times. These improvements have broadened the application space of the technique.

CONCLUSION

The technical performance of the CRS microscope has improved dramatically since its inception, but these advances have not yet translated into a substantial user base beyond a strong core of enthusiasts. Nonetheless, new developments are poised to move the unique capabilities of the technique into the hands of more users.

Long Noncoding RNA CTD-2245E15.3 Promotes Anabolic Enzymes ACC1 and PC to Support Non-Small Cell Lung Cancer Growth

Long noncoding RNAs (lncRNA) have been shown to play critical regulatory roles in the onset and progression of human cancers. However, the functions of a large proportion of lncRNAs are still unexplored. Here we describe a novel lncRNA, CTD-2245E15.3, that promotes lung tumorigenesis by regulating the anabolic enzymes acetyl-CoA carboxylase 1 (ACC1, encoded by the ACACA gene) and pyruvate carboxylase (PC). Differentially expressed lncRNAs between non-small cell lung cancer (NSCLC) and paired adjacent nontumor tissues were identified by a microarray and validated using quantitative real-time polymerase chain reaction. CTD-2245E15.3 was significantly upregulated in NSCLC and was mainly located in the cytoplasm. Knockdown of CTD-2245E15.3 by specific antisense oligonucleotides suppressed cell growth in vitro and in vivo, largely due to cell-cycle arrest and induction of apoptosis. Overexpression of CTD-2245E15.3 in an orthotopic model of lung cancer led to a significant increase in total tumor burden. CTD-2245E15.3 exerted its oncogenic function by binding ACC1 and PC, which are key anabolic factors for biomolecule synthesis in rapidly proliferating tumor cells. Knockdown of CTD-2245E15.3 increased phosphorylation of ACC1 at an inhibitory site for enzymatic activity and promoted PC degradation via ubiquitination. Supplements of palmitate or oxaloacetate, products of ACC1 and PC, alleviated the suppression of cell growth caused by loss of CTD-2245E15.3. These findings reveal the important role of CTD-2245E15.3 as an oncogenic lncRNA in the anabolic process for tumor growth. SIGNIFICANCE: These findings demonstrate a novel lncRNA CTD-2245E15.3 that binds and positively regulates anabolic enzymes ACC1 and PC to promote tumor growth. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/13/3509/F1.large.jpg.

Ultrasensitive Vibrational Imaging of Retinoids by Visible Preresonance Stimulated Raman Scattering Microscopy

High-sensitivity chemical imaging offers a window to decipher the molecular orchestra inside a living system. Based on vibrational fingerprint signatures, coherent Raman scattering microscopy provides a label-free approach to map biomolecules and drug molecules inside a cell. Yet, by near-infrared (NIR) pulse excitation, the sensitivity is limited to millimolar concentration for endogenous biomolecules. Here, the imaging sensitivity of stimulated Raman scattering (SRS) is significantly boosted for retinoid molecules to 34 micromolar via electronic preresonance in the visible wavelength regime. Retinoids play critical roles in development, immunity, stem cell differentiation, and lipid metabolism. By visible preresonance SRS (VP-SRS) imaging, retinoid distribution in single embryonic neurons and mouse brain tissues is mapped, retinoid storage in chemoresistant pancreatic and ovarian cancers is revealed, and retinoids stored in protein network and lipid droplets of Caenorahbditis elegans are identified. These results demonstrate VP-SRS microscopy as an ultrasensitive label-free chemical imaging tool and collectively open new opportunities of understanding the function of retinoids in biological systems.

Unveiling Cancer Metabolism through Spontaneous and Coherent Raman Spectroscopy and Stable Isotope Probing

Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.

Recent Development of Rapid Antimicrobial Susceptibility Testing Methods through Metabolic Profiling of Bacteria

Due to the inappropriate use and overuse of antibiotics, the emergence and spread of antibiotic-resistant bacteria are increasing and have become a major threat to human health. A key factor in the treatment of bacterial infections and slowing down the emergence of antibiotic resistance is to perform antimicrobial susceptibility testing (AST) of infecting bacteria rapidly to prescribe appropriate drugs and reduce the use of broad-spectrum antibiotics. Current phenotypic AST methods based on the detection of bacterial growth are generally reliable but are too slow. There is an urgent need for new methods that can perform AST rapidly. Bacterial metabolism is a fast process, as bacterial cells double about every 20 to 30 min for fast-growing species. Moreover, bacterial metabolism has shown to be related to drug resistance, so a comparison of differences in microbial metabolic processes in the presence or absence of antimicrobials provides an alternative approach to traditional culture for faster AST. In this review, we summarize recent developments in rapid AST methods through metabolic profiling of bacteria under antibiotic treatment.

Multicolour chemical imaging of plant tissues with hyperspectral stimulated Raman scattering microscopy

Recent development of stimulated Raman scattering (SRS) microscopy allows for label-free biological imaging with chemical specificity based on molecular-vibrational signatures. In particular, hyperspectral SRS imaging can acquire a molecular-vibrational spectrum at each pixel, allowing us not only to investigate the spectral difference of various biological molecules but also to discriminate different constituents based on their spectral difference. However, the number of constituents discriminated in previous label-free SRS imaging was limited to four because of the subtleness of spectral difference. Here, we report hyperspectral SRS imaging of plant tissues including leaves of Camellia japonica, roots of Arabidopsis thaliana, and thalli of a liverwort Marchantia polymorpha L. We show that SRS can discriminate as many as six components in Marchantia polymorpha L. without labeling. Our results demonstrate the effectiveness of hyperspectral SRS imaging as a tool for label-free multicolour imaging analysis of various biomolecules in plant tissues.