Targeted metabolic analysis of nucleotides and identification of biomarkers associated with cancer in cultured cell models

Advancements in Adenine Nucleotides Extraction and Quantification from a Single Drop of Human Blood

Adenine nucleotides (ANs)-adenosine 5'-triphosphate (ATP), adenosine 5'-diphosphate (ADP), and adenosine 5'-monophosphate (AMP)-are essential for energy transfer and the supply of countless processes within cellular metabolism. Their concentrations can be expressed as adenylate energy charge (AEC), a measure of cellular metabolic energy that directly correlates with the homeostasis of the organism. AEC index has broad diagnostic potential, as reduced ATP levels are associated to various conditions, such as inflammatory diseases, metabolic disorders, and cancer. We introduce a novel methodology for rapid isolation, purification, and quantification of ANs from a single drop of capillary blood. Of all the stationary phases tested, activated carbon proved to be the most efficient for the purification of adenine nucleotides, using an automated micro-solid phase extraction (µ-SPE) platform. An optimized µ-SPE method, coupled with RP-HPLC and a run time of 30 min, provides a reliable analytical framework for adenine nucleotide analysis of diverse biological samples. AN concentrations measured in capillary blood samples were 1393.1 µM, 254.8 µM, and 76.9 µM for ATP, ADP, and AMP molecules aligning with values reported in the literature. Overall, this study presents a streamlined and precise approach for analyzing ANs from microliters of blood, offering promising applications in clinical diagnostics.

Inactivation of guanylate kinase in Bacillus sp. TL7-3 cultivated under an optimized ratio of carbon and nitrogen sources influenced GTP regeneration capability and sporulation

Bacillus sp. TL7-3 has potential as a dietary supplement to promote human and animal health. It produces spores that can survive in harsh environments. Thus, when supplemented with nutrients, these spores can withstand the acidic pH of the stomach and resume vegetative development in the gut when exposed to growth-promoting conditions. Spores are formed as a cellular defense mechanism when a culture experiences stress and process optimization to achieve high spore production in a typical batch process remains challenging. Existing literature on the manipulation of gene expression and enzyme activity during batch cultivation is limited. Studies on the growth patterns, morphological changes, and relevant gene expression have aided in enhancing spore production. The present study used the response surface methodology for medium optimization. The model suggested that yeast extract and NH4Cl were significant factors controlling spore production. A comparison between the high weight ratio of carbon and nitrogen (C:N) substrates (8.57:1) in the optimized and basal media (0.52:1) showed an 8.76-fold increase in the final spore concentration. The expression of major genes, including codY, spo0A, kinA, and spo0F, involved in the sporulation was compared when cultivating Bacillus sp. TL7-3 in media with varying C:N ratios. At high C:N ratios, spo0A, kinA, and spo0F were upregulated, whereas codY was downregulated. This led to decreased guanylate kinase activity, resulting in a low guanosine triphosphate concentration and inactivation of CodY, thereby reducing the repression of spo0A and CodY-repressed genes and stimulating sporulation.

High-fidelity ATP imaging via an isothermal cascade catalytic amplifier

Artificial catalytic DNA circuits that can identify, transduce and amplify the biomolecule of interest have supplemented a powerful toolkit for visualizing various biomolecules in cancer cells. However, the non-specific response in normal tissues and the low abundance of analytes hamper their extensive biosensing and biomedicine applications. Herein, by combining tumor-responsive MnO2 nanoparticles with a specific stimuli-activated cascade DNA amplifier, we propose a multiply guaranteed and amplified ATP-sensing platform via the successive cancer-selective probe exposure and stimulation procedures. Initially, the GSH-degradable MnO2 nanocarrier, acting as a tumor-activating module, ensures the accurate delivery of the cascade DNA amplifier into GSH-rich cancer cells and simultaneously provides adequate Mn2+ cofactors for facilitating the DNAzyme biocatalysis. Then, the released cascade amplifier, acting as an ATP-monitoring module, fulfills the precise and sensitive analysis of low-abundance ATP in cancer cells where the catalyzed hairpin assembly (CHA) is integrated with the DNAzyme biocatalyst for higher signal gain. Additionally, the cascade catalytic amplifier achieved tumor-specific activated photodynamic therapy (PDT) after integrating an activatable photosensitizer into the system. This homogeneous cascade catalytic aptasensing circuit can detect low-abundance endogenous ATP of cancer cells, due to its intrinsically rich recognition repertoire and avalanche-mimicking hierarchical acceleration, thus demonstrating broad prospects for analyzing clinically important biomolecules and the associated physiological processes.

Stable Isotope Tracing Uncovers Reduced γ/β-ATP Turnover and Metabolic Flux Through Mitochondrial-Linked Phosphotransfer Circuits in Aggressive Breast Cancer Cells

Changes in dynamics of ATP γ- and β-phosphoryl turnover and metabolic flux through phosphotransfer pathways in cancer cells are still unknown. Using ¹⁸O phosphometabolite tagging technology, we have discovered phosphotransfer dynamics in three breast cancer cell lines: MCF7 (non-aggressive), MDA-MB-231 (aggressive), and MCF10A (control). Contrary to high intracellular ATP levels, the ¹⁸O labeling method revealed a decreased γ- and β-ATP turnover in both breast cancer cells, compared to control. Lower β-ATP[¹⁸O] turnover indicates decreased adenylate kinase (AK) flux. Aggressive cancer cells had also reduced fluxes through hexokinase (HK) G-6-P[¹⁸O], creatine kinase (CK) [CrP[¹⁸O], and mitochondrial G-3-P[¹⁸O] substrate shuttle. Decreased CK metabolic flux was linked to the downregulation of mitochondrial MTCK1A in breast cancer cells. Despite the decreased overall phosphoryl flux, overexpression of HK2, AK2, and AK6 isoforms within cell compartments could promote aggressive breast cancer growth.

NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome

Follicular lymphoma (FL) is a cancer of B-cells, representing the second most common type of non-Hodgkin lymphoma and typically diagnosed at advanced stage in older adults. In contrast to the wide range of available molecular genetic data, limited data relating the metabolomic features of follicular lymphoma are known. Metabolomics is a promising analytical approach employing metabolites (molecules < 1 kDa in size) as potential biomarkers in cancer research. In this pilot study, we performed proton nuclear magnetic resonance spectroscopy (¹H-NMR) on 29 cases of FL and 11 control patient specimens. The resulting spectra were assessed by both unsupervised and supervised statistical methods. We report significantly discriminant metabolomic models of common metabolites distinguishing FL from control tissues. Within our FL case series, we also report discriminant metabolomic signatures predictive of progression-free survival.

Moderate molecular recognitions on ZnO m-plane and their selective capture/release of bio-related phosphoric acids

Herein, we explore the hidden molecular recognition abilities of ZnO nanowires uniformly grown on the inner surface of an open tubular fused silica capillary via liquid chromatography. Chromatographic evaluation revealed that ZnO nanowires showed a stronger intermolecular interaction with phenylphosphoric acid than any other monosubstituted benzene. Furthermore, ZnO nanowires specifically recognized the phosphate groups present in nucleotides even in the aqueous mobile phase, and the intermolecular interaction increased with the number of phosphate groups. This discrimination of phosphate groups in nucleotides was unique to the rich (101̄0) m-plane of ZnO nanowires with a moderate hydrophilicity and negative charge. The discrimination could be evidenced by the changes in the infrared bands of the phosphate groups on nucleotides on ZnO nanowires. Finally, as an application of the molecular recognition, nucleotides were separated by the number of phosphate groups, utilizing optimized gradient elution on ZnO nanowire column. Thus, the present results elucidate the unique and versatile molecular selectivity of well-known ZnO nanostructures for the capture and separation of biomolecules.

Bovine milk exosomes attenuate the alteration of purine metabolism and energy status in IEC-6 cells induced by hydrogen peroxide

Evidence suggests that dietary depletion of bovine milk exosomes and their cargos causes a loss of circulating microRNAs and a series of health problems. The aim of the current study was to determine whether bovine milk exosomes affect purine nucleotide metabolism and energy metabolism in oxidatively stressed intestinal crypt epithelial cells (IEC-6). Cells were pretreated with exosomes, followed by H₂O₂ to induce oxidative stress. Reactive oxidative species (ROS) levels, purine nucleotides, purine metabolic key enzyme activities, cell energy status, and AMPK protein expression were analysed. Exosome pretreatment reduced ROS level and the activities of adenosine deaminase and xanthine oxidase induced by H₂O₂ in cells. Total adenine nucleotides and energy charge were increased with exosome pretreatment, while the AMPK phosphorylation level was downregulated. The results indicated that bovine milk exosomes could attenuate purine nucleotide catabolism and improve energy status in oxidatively stressed IEC-6 cells and exerted protective effects against oxidative stress.

Monitoring of dynamic ATP level changes by oligomycin-modulated ATP synthase inhibition in SW480 cancer cells using fluorescent "On-Off" switching DNA aptamer

Adenosine triphosphate (ATP) is the main energy source in cells and an important biomolecule participating in cellular reactions in living organisms. Since the ATP level changes dynamically reflecting the development of a debilitating disease or carcinogenesis, we have focused in this work on monitoring of the oligomycin (OMC)-modulated ATP synthase inhibition using a fluorescent-switching DNA aptamer designed for the detection of ATP (Apt(ATP)), as the model for studies of dynamic ATP level variation. The behavior of the ATP aptamer has been characterized using fluorescence spectroscopy. The Intramolecular fluorescence resonance energy transfer (iFRET) operates in the proposed aptamer from the FAM dye moiety to guanines of the aptamer G-quadruplex when the target ATP is present and binds to the aptamer changing its conformation. The iFRET process enables the detection of ATP down to the limit of detection, LOD = 17 μM, without resorting to any extra chemi-amplification schemes. The selectivity coefficients for relevant interferent triphosphates (UTP, GTP, and CTP) are low for the same concentration as that of ATP. We have demonstrated an efficient transfection of intact cells and OMC-treated SW480 colon cancer cells with Apt(ATP), using microscopic imaging, iFRET measurements, and cell viability testing with MTT method. The applicability of the switching DNA aptamer for the analysis of real samples, obtained by lysis of SW480 cells, was also tested. The proposed Apt(ATP) may be considered as a viable candidate for utilization in measurements of dynamic ATP level modulation in cells in different stages of cancer development and testing of new drugs in pharmacological studies.

Discovery and Validation of Clinical Biomarkers of Cancer: A Review Combining Metabolomics and Proteomics

Early detection and diagnosis of cancer can allow timely medical intervention, which greatly improves chances of survival and enhances quality of life. Biomarkers play an important role in assisting clinicians and health care providers in cancer diagnosis and treatment follow-up. In spite of years of research and the discovery of thousands of candidate cancer biomarkers, only a few have transitioned to routine usage in the clinic. This review highlights advances in proteomics technologies that have enabled high rates of discovery of candidate cancer biomarkers and evaluates integration with other omics technologies to improve their progress through to validation and clinical translation. Furthermore, it gauges the role of metabolomics technology in cancer biomarker research and assesses it as a complementary tool in aiding cancer biomarker discovery and validation.

Involvement of the uridine cytidine kinase 2 enzyme in cancer cell death: A molecular crosstalk between the enzyme and cellular apoptosis induction

Apoptosis is a series of molecular signalling regulating normal cellular growth and development. Cells resistance to apoptosis, however, leads to uncontrolled proliferation. Research involving cancer cell death is one of the most important targeted areas in the discovery of novel anticancer therapy. There are several biochemical pathways that are liked towards cancer cell death of which, uridine-cytidine kinase 2 (UCK2) was recently linked to cell apoptosis induction. UCK2 is responsible for the phosphorylation of uridine and cytidine to their corresponding monophosphate in a salvage pathway of pyrimidine nucleotides biosynthesis. Cytotoxic ribonucleoside analogues that target UCK2 enzyme activity are currently being investigated in clinical trials useful for cancer treatment. Whilst findings have clearly shown that these antimetabolites inhibit cancer development in clinical settings, they have yet to establish linking cytotoxic nucleoside analogues to cancer cell death. In this present review, we propose the probable molecular crosstalk involving UCK2 protein and cancer cell death through cell cycle arrest and triggering of apoptosis involving proteins, MDM2 and the subsequent activation of p53.

Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases

In the past decade, advances in liquid chromatography-mass spectrometry (LC-MS) have revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply, researchers are now primed to uncover key metabolites and their associations with diseases. The employment of untargeted metabolomics has led to new biomarker discoveries and a better mechanistic understanding of diseases with applications in precision medicine. However, many major pertinent challenges remain. First, compound identification has been poor, and left an overwhelming number of unidentified peaks. Second, partial, incomplete metabolomes persist due to factors such as limitations in mass spectrometry data acquisition speeds, wide-range of metabolites concentrations, and cellular/tissue/temporal-specific expression changes that confound our understanding of metabolite perturbations. Third, to contextualize metabolites in pathways and biology is difficult because many metabolites partake in multiple pathways, have yet to be described species specificity, or possess unannotated or more-complex functions that are not easily characterized through metabolomics analyses. From a translational perspective, information related to novel metabolite biomarkers, metabolic pathways, and drug targets might be sparser than they should be. Thankfully, significant progress has been made and novel solutions are emerging, achieved through sustained academic and industrial community efforts in terms of hardware, computational, and experimental approaches. Given the rapidly growing utility of metabolomics, this review will offer new perspectives, increase awareness of the major challenges in LC-MS metabolomics that will significantly benefit the metabolomics community and also the broader the biomedical community metabolomics aspire to serve.

LC-MS based cell metabolic profiling of tumor cells: a new predictive method for research on the mechanism of action of anticancer candidates

In the process of anticancer drug development, research on the mechanism of action remains a major obstacle. In the present study, a cell metabolic profiling based discriminatory model was designed to give general direction on anticancer candidate mechanisms. Firstly, ultra-performance liquid chromatography in tandem with high-definition mass spectrometry was applied to obtain a comprehensive metabolic view of 12 human tumor cells. Secondly, multivariate data analysis was used to assess the metabolites' variations, and 42 metabolites were identified as the main contributors to the discrimination of different groups. Then a metabolite-based prediction model was constructed for the first time and verified by cross validation (R 2 = 0.909 and Q 2 = 0.869) and a permutation test (R 2 = 0.0871 and Q 2 = -0.4360). To validate if the model can be applied for mechanism prediction, 4 independent sample sets were used to train the model and the data dots of different drugs were located in different regions. Finally, the model was applied to predict the anticancer mechanism of two natural compounds and the results were consistent with several other studies. Overall, this is the first experimental evidence which reveals that a metabolic profiling based prediction model has good performance in anticancer mechanism research, and thus it may be a new method for rapid mechanism screening.

MIP-Based Sensors: Promising New Tools for Cancer Biomarker Determination

Detecting cancer disease at an early stage is one of the most important issues for increasing the survival rate of patients. Cancer biomarker detection helps to provide a diagnosis before the disease becomes incurable in later stages. Biomarkers can also be used to evaluate the progression of therapies and surgery treatments. In recent years, molecularly imprinted polymer (MIP) based sensors have been intensely investigated as promising analytical devices in several fields, including clinical analysis, offering desired portability, fast response, specificity, and low cost. The aim of this review is to provide readers with an overview on recent important achievements in MIP-based sensors coupled to various transducers (e.g., electrochemical, optical, and piezoelectric) for the determination of cancer biomarkers by selected publications from 2012 to 2016.

CdTe amplification nanoplatforms capped with thioglycolic acid for electrochemical aptasensing of ultra-traces of ATP

A "signal off" voltammetric aptasensor was developed for the sensitive and selective detection of ultra-low levels of adenosine triphosphate (ATP). For this purpose, a new strategy based on the principle of recognition-induced switching of aptamers from DNA/DNA duplex to DNA/target complex was designed using thioglycolic acid (TGA)-capped CdTe quantum dots (QDs) as the signal amplifying nano-platforms. Owing to the small size, high surface-to-volume ratio and good conductivity, quantum dots were immobilized on the electrode surface for signal amplification. In this work, methylene blue (MB) adsorbed to DNA was used as a sensitive redox reporter. The intensity of voltammetric signal of MB was found to decrease linearly upon ATP addition over a concentration range of 0.1nM to 1.6μM with a correlation coefficient of 0.9924. Under optimized conditions, the aptasensor was able to selectively detect ATP with a limit of detection of 45pM at 3σ. The results also demonstrated that the QDs-based amplification strategy could be feasible for ATP assay and presented a potential universal method for other small biomolecular aptasensors.

Love Acoustic Wave-Based Devices and Molecularly-Imprinted Polymers as Versatile Sensors for Electronic Nose or Tongue for Cancer Monitoring

Cancer is a leading cause of death worldwide and actual analytical techniques are restrictive in detecting it. Thus, there is still a challenge, as well as a need, for the development of quantitative non-invasive tools for the diagnosis of cancers and the follow-up care of patients. We introduce first the overall interest of electronic nose or tongue for such application of microsensors arrays with data processing in complex media, either gas (e.g., Volatile Organic Compounds or VOCs as biomarkers in breath) or liquid (e.g., modified nucleosides as urinary biomarkers). Then this is illustrated with a versatile acoustic wave transducer, functionalized with molecularly-imprinted polymers (MIP) synthesized for adenosine-5'-monophosphate (AMP) as a model for nucleosides. The device including the thin film coating is described, then static measurements with scanning electron microscopy (SEM) and electrical characterization after each step of the sensitive MIP process (deposit, removal of AMP template, capture of AMP target) demonstrate the thin film functionality. Dynamic measurements with a microfluidic setup and four targets are presented afterwards. They show a sensitivity of 5 Hz·ppm(-1) of the non-optimized microsensor for AMP detection, with a specificity of three times compared to PMPA, and almost nil sensitivity to 3'AMP and CMP, in accordance with previously published results on bulk MIP.

In Silico Discovery of Potential Uridine-Cytidine Kinase 2 Inhibitors from the Rhizome of Alpinia mutica

Uridine-cytidine kinase 2 is implicated in uncontrolled proliferation of abnormal cells and it is a hallmark of cancer, therefore, there is need for effective inhibitors of this key enzyme. In this study, we employed the used of in silico studies to find effective UCK2 inhibitors of natural origin using bioinformatics tools. An in vitro kinase assay was established by measuring the amount of ADP production in the presence of ATP and 5-fluorouridine as a substrate. Molecular docking studies revealed an interesting ligand interaction with the UCK2 protein for both flavokawain B and alpinetin. Both compounds were found to reduce ADP production, possibly by inhibiting UCK2 activity in vitro. In conclusion, we have identified flavokawain B and alpinetin as potential natural UCK2 inhibitors as determined by their interactions with UCK2 protein using in silico molecular docking studies. This can provide information to identify lead candidates for further drug design and development.

Effects of antibiotic antitumor drugs on nucleotide levels in cultured tumor cells: an exploratory method to distinguish the mechanisms of antitumor drug action based on targeted metabolomics

Nucleotide pools in mammalian cells change due to the influence of antitumor drugs, which may help in evaluating the drug effect and understanding the mechanism of drug action. In this study, an ion-pair RP-HPLC method was used for a simple, sensitive and simultaneous determination of the levels of 12 nucleotides in mammalian cells treated with antibiotic antitumor drugs (daunorubicin, epirubicin and dactinomycin D). Through the use of this targeted metabolomics approach to find potential biomarkers, UTP and ATP were verified to be the most appropriate biomarkers. Moreover, a holistic statistical approach was put forward to develop a model which could distinguish 4 categories of drugs with different mechanisms of action. This model can be further validated by evaluating drugs with different mechanisms of action. This targeted metabolomics study may provide a novel approach to predict the mechanism of action of antitumor drugs.