Detection of Metabolic Changes Induced via Drug Treatments in Live Cancer Cells and Tissue Using Raman Imaging Microscopy

The patatin-like protein PlpD forms structurally dynamic homodimers in the Pseudomonas aeruginosa outer membrane

Members of the Omp85 superfamily of outer membrane proteins (OMPs) found in Gram-negative bacteria, mitochondria and chloroplasts are characterized by a distinctive 16-stranded β-barrel transmembrane domain and at least one periplasmic POTRA domain. All previously studied Omp85 proteins promote critical OMP assembly and/or protein translocation reactions. Pseudomonas aeruginosa PlpD is the prototype of an Omp85 protein family that contains an N-terminal patatin-like (PL) domain that is thought to be translocated across the OM by a C-terminal β-barrel domain. Challenging the current dogma, we find that the PlpD PL-domain resides exclusively in the periplasm and, unlike previously studied Omp85 proteins, PlpD forms a homodimer. Remarkably, the PL-domain contains a segment that exhibits unprecedented dynamicity by undergoing transient strand-swapping with the neighboring β-barrel domain. Our results show that the Omp85 superfamily is more structurally diverse than currently believed and suggest that the Omp85 scaffold was utilized during evolution to generate novel functions.

Resolving Challenges in Detection and Quantification of D-2-hydroxyglutarate and L-2-hydroxyglutarate via LC/MS

D-2-Hydroxyglutarate and L-2-Hydroxyglutarate (D-2HG/L-2HG) are typically metabolites of non-specific enzymatic reactions that are kept in check by the housekeeping enzymes, D-2HG /L-2HG dehydrogenase (D-2HGDH/L-2HGDH). In certain disease states, such as D-2HG or L-2HG aciduria and cancers, accumulation of these biomarkers interferes with oxoglutarate-dependent enzymes that regulate bioenergetic metabolism, histone methylation, post-translational modification, protein expression and others. D-2HG has a complex role in tumorigenesis that drives metabolomics investigations. Meanwhile, L-2HG is produced by non-specific action of malate dehydrogenase and lactate dehydrogenase under acidic or hypoxic environments. Characterization of divergent effects of D-2HG/L-2HG on the activity of specific enzymes in diseased metabolism depends on their accurate quantification via mass spectrometry. Despite advancements in high-resolution quadrupole time-of-flight mass spectrometry (HR-QTOF-MS), challenges are typically encountered when attempting to resolve of isobaric and isomeric metabolites such as D-2HG/L-2HG for quantitative analysis. Herein, available D-2HG/L-2HG derivatization and liquid chromatography (LC) MS quantification methods were examined. The outcome led to the development of a robust, high-throughput HR-QTOF-LC/MS approach that permits concomitant quantification of the D-2HG and L-2HG enantiomers with the benefit to quantify the dysregulation of other intermediates within interconnecting pathways. Calibration curve was obtained over the linear range of 0.8-104 nmol/mL with r 2 ≥ 0.995 for each enantiomer. The LC/MS-based assay had an overall precision with intra-day CV % ≤ 8.0 and inter-day CV % ≤ 6.3 across the quality control level for commercial standard and pooled biological samples; relative error % ≤ 2.7 for accuracy; and resolution, R s = 1.6 between 2HG enantiomers (m/z 147.030), D-2HG and L-2HG (at retention time of 5.82 min and 4.75 min, respectively) following chiral derivatization with diacetyl-L-tartaric anhydride (DATAN). Our methodology was applied to disease relevant samples to illustrate the implications of proper enantioselective quantification of both D-2HG and L-2HG. The stability of the method allows scaling to large cohorts of clinical samples in the future.

Monitoring Metabolic Changes in Response to Chemotherapies in Cancer with Raman Spectroscopy and Metabolomics

Resistance to clinical therapies remains a major barrier in cancer management. There is a critical need for rapid and highly sensitive diagnostic tools that enable early prediction of treatment response to allow accurate clinical decisions. Here, Raman spectroscopy was employed to monitor changes in key metabolites as early predictors of response in KRAS-mutant colorectal cancer (CRC) cells, HCT116, treated with chemotherapies. We show at the single cell level that HCT116 is resistant to cetuximab (CTX), the first-line treatment in CRC, but this resistance can be overcome with pre-sensitization of cells with oxaliplatin (OX). In combination treatment of CTX + OX, sequential delivery of OX followed by CTX rather than simultaneous administration of drugs was observed to be critical for effective therapy. Our results demonstrated that metabolic changes are well aligned to cellular mechanical changes where Young's modulus decreased after effective treatment, indicating that both changes in mechanical properties and metabolism in cells are likely responsible for cancer proliferation. Raman findings were verified with mass spectrometry (MS) metabolomics, and both platforms showed changes in lipids, nucleic acids, and amino acids as predictors of resistance/response. Finally, key metabolic pathways enriched were identified when cells are resistant to CTX but downregulated with effective treatment. This study highlights that drug-induced metabolic changes both at the single cell level (Raman) and ensemble level (MS) have the potential to identify mechanisms of response to clinical cancer therapies.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Quantitative Assessment of Low-Dose Photodynamic Therapy Effects on Diabetic Wound Healing Using Raman Spectroscopy

One of challenges that faces diabetes is the wound healing process. The delayed diabetic wound healing is caused by a complicated molecular mechanism involving numerous physiological variables. Low-dose photodynamic therapy (LDPDT) provides excellent results in rejuvenation and wound healing. In this study, the LDPDT effect on diabetic wounds in mice was studied using two photosensitizers, 5-aminolevulinic acid and methylene blue, and two laser dose expositions of 1 J/cm² and 4 J/cm² by Raman spectroscopy (RS). The latter was used as a noninvasive method, providing specific information about tissue state based on the fundamental vibrational modes of its molecular components. RS allows high spatial resolution acquisition of biochemical and structural information through the generation of point spectra or spectral images. An approach to in vivo quantitative assessment of diabetic wound healing state was developed. This approach is based on an application of the principal component analysis combined with the Mahalanobis metrics to skin Raman spectra, in particular, intensities of the amide I and CH₂ bands.

Medical Imaging Technology and Imaging Agents

Medical imaging is a technology that studies the interaction between human body and irradiations of X-ray, ultrasound, magnetic field, etc. and represents anatomical structures of human organs/tissues with the implication of irradiation attenuation in the form of grayscales. With these medical images, detailed information on health status and disease diagnosis may be judged by clinical physicians to determine an appropriate therapy approach. This chapter will give a systematic introduction on the modalities, classifications, basic principles, and biomedical applications of traditional medical imaging along with the types, construction, and major features of the corresponding contrast agents or imaging probes.

Label-Free Optical Spectroscopy for Early Detection of Oral Cancer

Oral cancer is the 16th most common cancer worldwide. It commonly arises from painless white or red plaques within the oral cavity. Clinical outcome is highly related to the stage when diagnosed. However, early diagnosis is complex owing to the impracticality of biopsying every potentially premalignant intraoral lesion. Therefore, there is a need to develop a non-invasive cost-effective diagnostic technique to differentiate non-malignant and early-stage malignant lesions. Optical spectroscopy may provide an appropriate solution to facilitate early detection of these lesions. It has many advantages over traditional approaches including cost, speed, objectivity, sensitivity, painlessness, and ease-of use in clinical setting for real-time diagnosis. This review consists of a comprehensive overview of optical spectroscopy for oral cancer diagnosis, epidemiology, and recent improvements in this field for diagnostic purposes. It summarizes major developments in label-free optical spectroscopy, including Raman, fluorescence, and diffuse reflectance spectroscopy during recent years. Among the wide range of optical techniques available, we chose these three for this review because they have the ability to provide biochemical information and show great potential for real-time deep-tissue point-based in vivo analysis. This review also highlights the importance of saliva-based potential biomarkers for non-invasive early-stage diagnosis. It concludes with the discussion on the scope of development and future demands from a clinical point of view.

Targeting the Sphingolipid Rheostat in Gliomas

Gliomas are highly aggressive cancer types that are in urgent need of novel drugs and targeted therapies. Treatment protocols have not improved in over a decade, and glioma patient survival remains among the worst of all cancer types. As a result, cancer metabolism research has served as an innovative approach to identifying novel glioma targets and improving our understanding of brain tumors. Recent research has uncovered a unique metabolic vulnerability in the sphingolipid pathways of gliomas that possess the IDH1 mutation. Sphingolipids are a family of lipid signaling molecules that play a variety of second messenger functions in cellular regulation. The two primary metabolites, sphingosine-1-phosphate (S1P) and ceramide, maintain a rheostat balance and play opposing roles in cell survival and proliferation. Altering the rheostat such that the pro-apoptotic signaling of the ceramides outweighs the pro-survival S1P signaling in glioma cells diminishes the hallmarks of cancer and enhances tumor cell death. Throughout this review, we discuss the sphingolipid pathway and identify the enzymes that can be most effectively targeted to alter the sphingolipid rheostat and enhance apoptosis in gliomas. We discuss each pathway’s steps based on their site of occurrence in the organelles and postulate novel targets that can effectively exploit this vulnerability.

Glioblastoma Metabolomics-In Vitro Studies

In 2016, the WHO introduced new guidelines for the diagnosis of brain gliomas based on new genomic markers. The addition of these new markers to the pre-existing diagnostic methods provided a new level of precision for the diagnosis of glioma and the prediction of treatment effectiveness. Yet, despite this new classification tool, glioblastoma (GBM), a grade IV glioma, continues to have one of the highest mortality rates among central nervous system tumors. Metabolomics is a particularly promising tool for the analysis of GBM tumors and potential methods of treating them, as it is the only "omics" approach that is capable of providing a metabolic signature of a tumor's phenotype. With careful experimental design, cell cultures can be a useful matrix in GBM metabolomics, as they ensure stable conditions and, under proper conditions, are capable of capturing different tumor phenotypes. This paper reviews in vitro metabolomic profiling studies of high-grade gliomas, with a particular focus on sample-preparation techniques, crucial metabolites identified, cell culture conditions, in vitro-in vivo extrapolation, and pharmacometabolomics. Ultimately, this review aims to elucidate potential future directions for in vitro GBM metabolomics.

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.

Novel diagnostic and therapeutic techniques reveal changed metabolic profiles in recurrent focal segmental glomerulosclerosis

Idiopathic forms of Focal Segmental Glomerulosclerosis (FSGS) are caused by circulating permeability factors, which can lead to early recurrence of FSGS and kidney failure after kidney transplantation. In the past three decades, many research endeavors were undertaken to identify these unknown factors. Even though some potential candidates have been recently discussed in the literature, "the" actual factor remains elusive. Therefore, there is an increased demand in FSGS research for the use of novel technologies that allow us to study FSGS from a yet unexplored angle. Here, we report the successful treatment of recurrent FSGS in a patient after living-related kidney transplantation by removal of circulating factors with CytoSorb apheresis. Interestingly, the classical published circulating factors were all in normal range in this patient but early disease recurrence in the transplant kidney and immediate response to CytoSorb apheresis were still suggestive for pathogenic circulating factors. To proof the functional effects of the patient's serum on podocytes and the glomerular filtration barrier we used a podocyte cell culture model and a proteinuria model in zebrafish to detect pathogenic effects on the podocytes actin cytoskeleton inducing a functional phenotype and podocyte effacement. We then performed Raman spectroscopy in the < 50 kDa serum fraction, on cultured podocytes treated with the FSGS serum and in kidney biopsies of the same patient at the time of transplantation and at the time of disease recurrence. The analysis revealed changes in podocyte metabolome induced by the FSGS serum as well as in focal glomerular and parietal epithelial cell regions in the FSGS biopsy. Several altered Raman spectra were identified in the fractionated serum and metabolome analysis by mass spectrometry detected lipid profiles in the FSGS serum, which were supported by disturbances in the Raman spectra. Our novel innovative analysis reveals changed lipid metabolome profiles associated with idiopathic FSGS that might reflect a new subtype of the disease.

Metabolic Landscape of a Genetically Engineered Mouse Model of IDH1 Mutant Glioma

Understanding the metabolic reprogramming of aggressive brain tumors has potential applications for therapeutics as well as imaging biomarkers. However, little is known about the nutrient requirements of isocitrate dehydrogenase 1 (IDH1) mutant gliomas. The IDH1 mutation involves the acquisition of a neomorphic enzymatic activity which generates D-2-hydroxyglutarate from α-ketoglutarate. In order to gain insight into the metabolism of these malignant brain tumors, we conducted metabolic profiling of the orthotopic tumor and the contralateral regions for the mouse model of IDH1 mutant glioma; as well as to examine the utilization of glucose and glutamine in supplying major metabolic pathways such as glycolysis and tricarboxylic acid (TCA). We also revealed that the main substrate of 2-hydroxyglutarate is glutamine in this model, and how this re-routing impairs its utilization in the TCA. Our 13C tracing analysis, along with hyperpolarized magnetic resonance experiments, revealed an active glycolytic pathway similar in both regions (tumor and contralateral) of the brain. Therefore, we describe the reprogramming of the central carbon metabolism associated with the IDH1 mutation in a genetically engineered mouse model which reflects the tumor biology encountered in glioma patients.