Systematic Proteome Profiling of Maternal Plasma for Development of Preeclampsia Biomarkers.

BACKGROUND: Preeclampsia (PE) is a hypertensive disorder of pregnancy with various clinical symptoms. However, traditional markers for the disease including high blood pressure and proteinuria are poor indicators of the related adverse outcomes. Here, we performed systematic proteome profiling of plasma samples obtained from pregnant women with PE to identify clinically effective diagnostic biomarkers. METHODS: Proteome profiling was performed using TMT-based liquid chromatography-mass spectrometry (LC-MS/MS) followed by subsequent verification by multiple reaction monitoring (MRM) analysis on normal and PE maternal plasma samples. Functional annotations of differentially expressed proteins (DEPs) in PE were predicted using bioinformatic tools. The diagnostic accuracies of the biomarkers for PE were estimated according to the area under the receiver operating characteristics curve (AUC). RESULTS: A total of 1,307 proteins were identified, and 870 proteins of them were quantified from plasma samples. Significant differences were evident in 138 DEPs, including 71 upregulated DEPs and 67 downregulated DEPs in the PE group, compared with those in the control group. Up-regulated proteins were significantly associated with biological processes including platelet degranulation, proteolysis, lipoprotein metabolism, and cholesterol efflux. Biological processes including blood coagulation and acute-phase response were enriched for down-regulated proteins. Of these, 40 proteins were subsequently validated in an independent cohort of 26 PE patients and 29 healthy controls. APOM, LCN2, and QSOX1 showed high diagnostic accuracies for PE detection (AUC > 0.9 and P < 0.001, for all) as validated by MRM and ELISA. CONCLUSIONS: Our data demonstrate that three plasma biomarkers, identified by systematic proteomic profiling, present a possibility for the assessment of PE, independent of the clinical characteristics of pregnant women.

Galectin-3-Binding Protein Inhibits Extracellular Heparan 6-O-Endosulfatase Sulf-2.

Human extracellular 6-O-endosulfatases Sulf-1 and Sulf-2 are the only enzymes that post-synthetically alter the 6-O sulfation of heparan sulfate proteoglycans (HSPG), which regulates interactions of HSPG with many proteins. Oncogenicity of Sulf-2 in different cancers has been documented, and we have shown that Sulf-2 is associated with poor survival outcomes in head and neck squamous cell carcinoma (HNSCC). Despite its importance, limited information is available on direct protein-protein interactions of the Sulf-2 protein in the tumor microenvironment. In this study, we used monoclonal antibody (mAb) affinity purification and mass spectrometry to identify galectin-3-binding protein (LG3BP) as a highly specific binding partner of Sulf-2 in the conditioned media of HNSCC cell lines. We validated their direct interaction in vitro using recombinant proteins and have shown that the chondroitin sulfate (CS) covalently bound to the Sulf-2 influences the binding to LG3BP. We confirmed the importance of the CS chain for the interaction by generating a mutant Sulf-2 protein that lacks the CS. Importantly, we have shown that the LG3BP inhibits Sulf-2 activity in vitro in a concentration-dependent manner. As a consequence, the addition of LG3BP to a spheroid cell culture inhibited the invasion of the HNSCC cells into Matrigel. Thus, Sulf-2 interaction with LG3BP may regulate the physiological activity of the Sulf-2 enzyme as well as its activity in the tumor microenvironment.

Identification of a rare [Gγ(Aγδß)0] -thalassemia using tandem mass spectrometry.

Thalassemias are a group of inherited monogenic disorders characterized by defects in the synthesis of one or more of the globin chain subunits of the hemoglobin tetramer. Delta-beta (δß-) thalassemia has large deletions in the ß globin gene cluster involving δ- and ß-globin genes, leading to absent or reduced synthesis of both δ- and ß-globin chains. Here, we used direct globin-chain analysis using tandem mass spectrometry for the diagnosis of δß-thalassemia. Two cases from unrelated families were recruited for the study based on clinical and hematological evaluation. Peptides obtained after trypsin digestion of proteins extracted from red blood cell pellets from two affected individuals and their parents were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Mass spectrometric analysis revealed a severe reduction in δ, ß, and Aγ globin proteins with increased Gγ globin protein in the affected individuals. The diagnosis of Gγ(Aγδß)0 -thalassemia in the homozygous state in the affected individuals and in the heterozygous state in the parents was made from our results. The diagnosis was confirmed at the genetic level using multiplex ligation-dependent probe amplification (MLPA). Our findings demonstrate the utility of direct globin protein quantitation using LC-MS/MS to quantify individual globin proteins reflecting changes in globin production. This approach can be utilized for accurate and timely diagnosis of hemoglobinopathies, including rare variants, where existing diagnostic methods provide inconclusive results.

Quantitative proteomics investigating the intrinsic adaptation mechanism of Aeromonas hydrophila to streptomycin.

Aeromonas hydrophila, a prevalent pathogen in the aquaculture industry, poses significant challenges due to its drug-resistant strains. Moreover, residues of antibiotics like streptomycin, extensively employed in aquaculture settings, drive selective bacterial evolution, leading to the progressive development of resistance to this agent. However, the underlying mechanism of its intrinsic adaptation to antibiotics remains elusive. Here, we employed a quantitative proteomics approach to investigate the differences in protein expression between A. hydrophila under streptomycin (SM) stress and nonstress conditions. Notably, bioinformatics analysis unveiled the potential involvement of metal pathways, including metal cluster binding, iron-sulfur cluster binding, and transition metal ion binding, in influencing A. hydrophila's resistance to SM. Furthermore, we evaluated the sensitivity of eight gene deletion strains related to streptomycin and observed the potential roles of petA and AHA_4705 in SM resistance. Collectively, our findings enhance the understanding of A. hydrophila's response behavior to streptomycin stress and shed light on its intrinsic adaptation mechanism.

Dysregulated proteome and N-glycoproteome in ALG1-deficient fibroblasts.

Asparagine-linked glycosylation 1 protein is a ß-1,4-mannosyltransferase, is encoded by the ALG1 gene, which catalyzes the first step of mannosylation in N-glycosylation. Pathogenic variants in ALG1 cause a rare autosomal recessive disorder termed as ALG1-CDG. We performed a quantitative proteomics and N-glycoproteomics study in fibroblasts derived from patients with one homozygous and two compound heterozygous pathogenic variants in ALG1. Several proteins that exhibited significant upregulation included insulin-like growth factor II and pleckstrin, whereas hyaluronan and proteoglycan link protein 1 was downregulated. These proteins are crucial for cell growth, survival and differentiation. Additionally, we observed a decrease in the expression of mitochondrial proteins and an increase in autophagy-related proteins, suggesting mitochondrial and cellular stress. N-glycoproteomics revealed the reduction in high-mannose and complex/hybrid glycopeptides derived from numerous proteins in patients explaining that defect in ALG1 has broad effects on glycosylation. Further, we detected an increase in several short oligosaccharides, including chitobiose (HexNAc2) trisaccharides (Hex-HexNAc2) and novel tetrasaccharides (NeuAc-Hex-HexNAc2) derived from essential proteins including LAMP1, CD44 and integrin. These changes in glycosylation were observed in all patients irrespective of their gene variants. Overall, our findings not only provide novel molecular insights into understanding ALG1-CDG but also offer short oligosaccharide-bearing peptides as potential biomarkers.

Integrative Analyses Reveal the Correlation Between the Airway Microbiome and Host Metabolism in Severe Community-acquired Pneumonia.

Community-acquired pneumonia (CAP) is a significant global health concern, responsible for high mortality and morbidity. Recent research has revealed a potential link between disordered microbiome and metabolism in pneumonia, although the precise relationship between these factors and severe CAP remains unclear. To address this knowledge gap, we conducted a comprehensive analysis utilizing 16S sequencing and LC-MS/MS metabolomics data to characterize the microbial profile in sputum and metabolic profile in serum in patients with severe community-acquired pneumonia (sCAP). Our analysis identified 13 genera through LEfSe analysis and 15 metabolites meeting specific criteria (P < 0.05, VIP ≥ 2, and |Log2(FC)| ≥ 2). The findings of this study demonstrate the presence of altered coordination between the microbiome of the lower respiratory tract and host metabolism in patients with sCAP. The observed concentration trends of specific metabolites across different disease stages further support the potential involvement of the serum metabolism in the development of sCAP. These correlations between the airway microbiome and host metabolism in sCAP patients have important implications for optimizing early diagnosis and developing individualized therapeutic strategies.

Use of Proteomics for Dietary Reconstruction: A Case Study Using Animal Teeth from Ancient Mesopotamia.

This research examines animal teeth from Early Dynastic (2900-2350 BCE) Mesopotamia (Southern Iraq) to assess animal management practices and identify consumption patterns in animal diets. The objective to answer larger questions about food management and environmental resilience in ancient early complex societies in the Near East was achieved by the use of mass spectrometry-based proteomics for dietary reconstruction. Dietary MS, a revolutionary new methodology applying proteomics techniques to archeological sample sets to reconstruct ancient animal diet. A developed protein extraction technique followed by liquid chromatography tandem mass spectrometry allowed for the identification of the specific plant species consumed in order to highlight variable herd management strategies, resource optimization, for each taxon over time. It also provided information about overall health and indications of disease. This is the first study to apply a full suite of analyses to the region and provides the foundations of a necessary long-term view of human interaction within an environment, through both time and space.

Unveiling Endogenous Serum Peptides as Potential Biomarkers for Hepatocellular Carcinoma in Patients with Liver Cirrhosis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, mainly associated with liver cirrhosis. Current diagnostic methods for HCC have limited sensitivity and specificity, highlighting the need for improved early detection and intervention. In this study, we used a comprehensive approach involving endogenous peptidome along with bioinformatics analysis to identify and evaluate potential biomarkers for HCC. Serum samples from 40 subjects, comprising 20 HCC cases and 20 patients with liver cirrhosis (CIRR), were analyzed. Among 2568 endogenous peptides, 67 showed significant differential expression between the HCC vs CIRR. Further analysis revealed three endogenous peptides (VMHEALHNHYTQKSLSLSPG, NRFTQKSLSLSPG, and SARQSTLDKEL) that showed far better performance compared to AFP in terms of area under the receiver operating characteristic curve (AUC), showcasing their potential as biomarkers for HCC. Additionally, endogenous peptide IAVEWESNGQPENNYKT that belongs to the precursor protein Immunoglobulin heavy constant gamma 4 was detected in 100% of the HCC group and completely absent in the CIRR group, suggesting a promising diagnostic biomarker. Gene ontology and pathway analysis revealed the potential involvement of these dysregulated peptides in HCC. These findings provide valuable insights into the molecular basis of HCC and may contribute to the development of improved diagnostic methods and therapeutic targets for HCC.

O-Glycome Profiling of Breast Cancer Cell Lines to Understand Breast Cancer Brain Metastasis.

Breast cancer is the second leading cause of cancer-related death among women and a major source of brain metastases. Despite the increasing incidence of brain metastasis from breast cancer, the underlying mechanisms remain poorly understood. Altered glycosylation is known to play a role in various diseases including cancer metastasis. However, profiling studies of O-glycans and their isomers in breast cancer brain metastasis (BCBM) are scarce. This study analyzed the expression of O-glycans and their isomers in human breast cancer cell lines (MDA-MB-231, MDA-MB-361, HTB131, and HTB22), a brain cancer cell line (CRL-1620), and a brain metastatic breast cancer cell line (MDA-MB-231BR) using nanoLC-MS/MS, identifying 27 O-glycan compositions. We observed significant upregulation in the expression of HexNAc1Hex1NeuAc2 and HexNAc2Hex3, whereas the expression of HexNAc1Hex1NeuAc1 was downregulated in MDA-MB-231BR compared to other cell lines. In our isomeric analysis, we observed notable alterations in the isomeric forms of the O-glycan structure HexNAc1Hex1NeuAc1 in a comparison of different cell lines. Our analysis of O-glycans and their isomers in cancer cells demonstrated that changes in their distribution can be related to the metastatic process. We believe that our investigation will contribute to an enhanced comprehension of the significance of O-glycans and their isomers in BCBM.

IsoForma: An R Package for Quantifying and Visualizing Positional Isomers in Top-Down LC-MS/MS Data.

Proteoforms, the different forms of a protein with sequence variations including post-translational modifications (PTMs), execute vital functions in biological systems, such as cell signaling and epigenetic regulation. Advances in top-down mass spectrometry (MS) technology have permitted the direct characterization of intact proteoforms and their exact number of modification sites, allowing for the relative quantification of positional isomers (PI). Protein positional isomers refer to a set of proteoforms with identical total mass and set of modifications, but varying PTM site combinations. The relative abundance of PI can be estimated by matching proteoform-specific fragment ions to top-down tandem MS (MS2) data to localize and quantify modifications. However, the current approaches heavily rely on manual annotation. Here, we present IsoForma, an open-source R package for the relative quantification of PI within a single tool. Benchmarking IsoForma's performance against two existing workflows produced comparable results and improvements in speed. Overall, IsoForma provides a streamlined process for quantifying PI, reduces the analysis time, and offers an essential framework for developing customized proteoform analysis workflows. The software is open source and available at https://github.com/EMSL-Computing/isoforma-lib.

Low-Invasive Sampling Method with Tape-Disc Sampling for the Taxonomic Identification of Archeological and Paleontological Bones by Proteomics.

Collagen from paleontological bones is an important organic material for isotopic measurement, radiocarbon analysis, and paleoproteomic analysis to provide information on diet, dating, taxonomy, and phylogeny. Current paleoproteomic methods are destructive and require from a few milligrams to several tens of milligrams of bone for analysis. In many cultures, bones are raw materials for artifacts that are conserved in museums, which hampers damage to these precious objects during sampling. Here, we describe a low-invasive sampling method that identifies collagen, taxonomy, and post-translational modifications from Holocene and Upper Pleistocene bones dated to 130,000 and 150 BC using dermatological skin tape discs for sampling. The sampled bone micropowders were digested following our highly optimized enhanced filter-aided sample preparation protocol and then analyzed by MALDI FTICR MS and LC-MS/MS for identifying the genus taxa of the bones. We show that this low-invasive sampling does not deteriorate the bones and achieves results similar to those obtained by more destructive sampling. Moreover, this sampling method can be carried out at archeological sites or in museums.

Multispecies Benchmark Analysis for LC-MS/MS Validation and Performance Evaluation in Bottom-Up Proteomics.

We present an instrument-independent benchmark procedure and software (LFQ_bout) for the validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. The procedure enables a back-to-back comparison of common and emerging workflows, e.g., diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary and inadequately documented settings or black-box data processing algorithms. It enhances the overall performance and quantification accuracy by recognizing and reporting common quantification errors.

ARID3C Acts as a Regulator of Monocyte-to-Macrophage Differentiation Interacting with NPM1.

ARID3C is a protein located on human chromosome 9 and expressed at low levels in various organs, yet its biological function has not been elucidated. In this study, we investigated both the cellular localization and function of ARID3C. Employing a combination of LC-MS/MS and deep learning techniques, we identified NPM1 as a binding partner for ARID3C's nuclear shuttling. ARID3C was found to predominantly localize with the nucleus, where it functioned as a transcription factor for genes STAT3, STAT1, and JUNB, thereby facilitating monocyte-to-macrophage differentiation. The precise binding sites between ARID3C and NPM1 were predicted by AlphaFold2. Mutating this binding site prevented ARID3C from interacting with NPM1, resulting in its retention in the cytoplasm instead of translocation to the nucleus. Consequently, ARID3C lost its ability to bind to the promoters of target genes, leading to a loss of monocyte-to-macrophage differentiation. Collectively, our findings indicate that ARID3C forms a complex with NPM1 to translocate to the nucleus, acting as a transcription factor that promotes the expression of the genes involved in monocyte-to-macrophage differentiation.

Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry.

Proteins usually execute their biological functions through interactions with other proteins and by forming macromolecular complexes, but global profiling of protein complexes directly from human tissue samples has been limited. In this study, we utilized cofractionation mass spectrometry (CF-MS) to map protein complexes within the postmortem human brain with experimental replicates. First, we used concatenated anion and cation Ion Exchange Chromatography (IEX) to separate native protein complexes in 192 fractions and then proceeded with Data-Independent Acquisition (DIA) mass spectrometry to analyze the proteins in each fraction, quantifying a total of 4,804 proteins with 3,260 overlapping in both replicates. We improved the DIA's quantitative accuracy by implementing a constant amount of bovine serum albumin (BSA) in each fraction as an internal standard. Next, advanced computational pipelines, which integrate both a database-based complex analysis and an unbiased protein-protein interaction (PPI) search, were applied to identify protein complexes and construct protein-protein interaction networks in the human brain. Our study led to the identification of 486 protein complexes and 10054 binary protein-protein interactions, which represents the first global profiling of human brain PPIs using CF-MS. Overall, this study offers a resource and tool for a wide range of human brain research, including the identification of disease-specific protein complexes in the future.

Harnessing the power of proteomics in precision diabetes medicine.

Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.

ACSF2 and lysine lactylation contribute to renal tubule injury in diabetes.

AIMS: Lactate accumulation is reported to be a biomarker for diabetic nephropathy progression. Lactate drives lysine lactylation, a newly discovered post-translational modification that is involved in the pathogenesis of cancers and metabolic and inflammatory disease. Here, we aimed to determine whether lysine lactylation is involved in the pathogenesis of diabetic nephropathy. METHODS: Renal biopsy samples from individuals with diabetic nephropathy (n=22) and control samples from individuals without diabetes and kidney disease (n=9) were obtained from the First Affiliated Hospital of Zhengzhou University for immunohistochemical staining. In addition, we carried out global lactylome profiling of kidney tissues from db/m and db/db mice using LC-MS/MS. Furthermore, we assessed the role of lysine lactylation and acyl-CoA synthetase family member 2 (ACSF2) in mitochondrial function in human proximal tubular epithelial cells (HK-2). RESULTS: The expression level of lysine lactylation was significantly increased in the kidneys of individuals with diabetes as well as in kidneys from db/db mice. Integrative lactylome analysis of the kidneys of db/db and db/m mice identified 165 upregulated proteins and 17 downregulated proteins, with an increase in 356 lysine lactylation sites and a decrease in 22 lysine lactylation sites decreased. Subcellular localisation analysis revealed that most lactylated proteins were found in the mitochondria (115 proteins, 269 sites). We further found that lactylation of the K182 site in ACSF2 contributes to mitochondrial dysfunction. Finally, the expression of ACSF2 was notably increased in the kidneys of db/db mice and individuals with diabetic nephropathy. CONCLUSIONS: Our study strongly suggests that lysine lactylation and ACSF2 are mediators of mitochondrial dysfunction and may contribute to the progression of diabetic nephropathy. DATA AVAILABILITY: The LC-MS/MS proteomics data have been deposited in the ProteomeXchange Consortium database ( https://proteomecentral.proteomexchange.org ) via the iProX partner repository with the dataset identifier PXD050070.

Proteomic analysis and protein structure prediction of Shigella phage Sfk20 based on a comparative study using structure prediction approaches.

Bacteriophages are the natural predators of bacteria and are available abundantly everywhere in nature. Lytic phages can specifically infect their bacterial host (through attachment to the receptor) and use their host replication machinery to replicate rapidly, a feature that enables them to kill a disease-causing bacteria. Hence, phage attachment to the host bacteria is the first important step of the infection process. It is reported in this study that the receptor could be an LPS which is responsible for the attachment of the Sfk20 phage to its host (Shigella flexneri 2a). Phage Sfk20 bacteriolytic activity was examined for preliminary optimization of phage titer. The phage Sfk20 viability at different saline conditions was conducted. The LC-MS/MS technique used here for detecting and identifying 40 Sfk20 phage proteins helped us to get an initial understanding of the structural landscape of phage Sfk20. From the identified proteins, six structurally significant proteins were selected for structure prediction using two neural network systems: AlphaFold2 and ESMFold, and one homology modeling software: Phyre2. Later the performance of these modeling systems was compared using various metrics. We conclude from the available and generated information that AlphaFold2 and Phyre2 perform better than ESMFold for predicting Sfk20 phage protein structures.

Phosphoproteomic analysis reveals distinctive responses in Mangrovibacter phragmatis under high-salinity condition.

We conducted a thorough genome-wide investigation of protein phosphorylation in the halotolerant bacterium Mangrovibacter phragmitis (MPH) ASIOC01, using the Fe-IMAC enrichment method combined with tandem mass spectrometry under low- and high-salinity conditions. The phosphoproteome comprises 86 unique phosphorylated proteins, crucially involving pathways such as glycolysis/gluconeogenesis, the citrate cycle, chaperones, ribosomal proteins, and cell division. This study represents the first and most extensive investigation to-date comparing the bacterial phosphoproteome under different osmotic conditions using a gel-free approach. We identified 45 unique phosphoproteins in MPH cultured in media containing 1 % NaCl, and 33 exclusive phosphoproteins in MPH cultured in media containing 5 % NaCl. Eight phosphoproteins were detected in both growth conditions. Analysis of high-confidence phosphosites reveals that phosphorylation predominantly occurs on serine residues (52.3 %), followed by threonine (35.1 %) and tyrosine (12.6 %) residues. Interestingly, 34 % of the phosphopeptides display multiple phosphosites. Currently, prokaryotic phosphorylation site prediction platforms like MPSite and NetPhosBac 1.0 demonstrate an average prediction accuracy of only 21 % when applied to our dataset. Fourteen phosphoproteins did not yield matches when compared against dbPSP 2.0 (database of Phosphorylation Sites in Prokaryotes), indicating that these proteins may be novel phosphoproteins. These unique proteins undergoing phosphorylation under high salinity growth conditions potentially enhance their adaptive capabilities to environmental challenges.

Quantifying carboxymethyl lysine and carboxyethyl lysine in human plasma: clinical insights into aging research using liquid chromatography-tandem mass spectrometry.

OBJECTIVE: The objective of this study was to establish a methodology for determining carboxymethyl lysine (CML) and carboxyethyl lysine (CEL) concentrations in human plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The test results were also used for clinical aging research. METHODS: Human plasma samples were incubated with aqueous perfluorovaleric acid (NFPA), succeeded by precipitation utilizing trichloroacetic acid, hydrolysis facilitated by hydrochloric acid, nitrogen drying, and ultimate re-dissolution utilizing NFPA, followed by filtration. Cotinine-D3 was added as an internal standard. The separation was performed on an Agela Venusil ASB C18 column (50 mm × 4.6 mm, 5 µm) with a 5 mmol/L NFPA and acetonitrile/water of 60:40 (v/v) containing 0.15% formic acid. The multiple reaction monitoring mode was used for detecting CML, CEL, and cotinine-D3, with ion pairs m/z 205.2 > 84.1 (for quantitative) and m/z 205.2 > m/z 130.0 for CML, m/z 219.1 > 84.1 (for quantitative) and m/z 219.1 > m/z 130.1 for CEL, and m/z 180.1 > 80.1 for cotinine-D3, respectively. RESULTS: The separation of CML and CEL was accomplished within a total analysis time of 6 minutes. The retention times of CML, CEL, and cotinine-D3 were 3.43 minutes, 3.46 minutes, and 4.50 minutes, respectively. The assay exhibited linearity in the concentration range of 0.025-1.500 µmol/L, with a lower limit of quantification of 0.025 µmol/L for both compounds. The relative standard deviations of intra-day and inter-day were both below 9%, and the relative errors were both within the range of ±4%. The average recoveries were 94.24% for CML and 97.89% for CEL. CONCLUSION: The results indicate that the developed methodology is fast, highly sensitive, highly specific, reproducible, and suitable for the rapid detection of CML and CEL in clinical human plasma samples. The outcomes of the clinical research project on aging underscored the important indicative significance of these two indicators for research on human aging.

Altitudinal variation of dragon fruit metabolite profiles as revealed by UPLC-MS/MS-based widely targeted metabolomics analysis.

BACKGROUND: Geographical factors affect the nutritional, therapeutic and commercial values of fruits. Dragon fruit (Hylocereus spp) is a popular fruit in Asia and a potential functional food with diverse pharmacological attributes. Although it is produced in various localities, the information related to the altitudinal variation of dragon fruit nutrients and active compounds is scarce. Hence, this study aimed to investigate the variations in metabolite profiles of H. polyrhizus (variety Jindu1) fruit pulps from three different altitudes of China, including Wangmo (WM, 650 m), Luodian (LD, 420 m), and Zhenning (ZN, 356 m). Jindu1 is the main cultivated pitaya variety in Guizhou province, China. RESULTS: The LC-MS (liquid chromatography-mass spectroscopy)-based widely targeted metabolic profiling identified 645 metabolites, of which flavonoids (22.64%), lipids (13.80%), phenolic acids (12.40%), amino acids and derivatives (10.39%), alkaloids (8.84%), and organic acids (8.37%) were dominant. Multivariate analyses unveiled that the metabolite profiles of the fruit differed regarding the altitude. Fruits from WM (highest altitude) were prime in quality, with higher levels of flavonoids, alkaloids, nucleotides and derivatives, amino acids and derivatives, and vitamins. Fruits from LD and ZN had the highest relative content of phenolic acids and terpenoids, respectively. We identified 69 significantly differentially accumulated metabolites across the pulps of the fruits from the three locations. KEGG analysis revealed that flavone and flavonol biosynthesis and isoflavonoid biosynthesis were the most differentially regulated. It was noteworthy that most active flavonoid compounds exhibited an increasing accumulation pattern along with the increase in altitude. Vitexin and isovitexin were the major differentially accumulated flavonoids. Furthermore, we identified two potential metabolic biomarkers (vitexin and kaempferol 3-O-[2-O-ß-D-galactose-6-O-a-L-rhamnose]-ß-D-glucoside) to discriminate between dragon fruits from different geographical origins. CONCLUSION: Our findings provide insights into metabolic changes in dragon fruits grown at different altitudes. Furthermore, they show that growing pitaya at high altitudes can produce fruit with higher levels of bioactive compounds, particularly flavonoids.