Insights into the seasonal characteristics of single particle aerosols in Chengdu based on SPAMS.

To investigate the seasonal characteristics in air pollution in Chengdu, a single particle aerosol mass spectrometry was used to continuously observe atmospheric fine particulate matter during one-month periods in summer and winter, respectively. The results showed that, apart from O3, the concentrations of other pollutants (CO, NO2, SO2, PM2.5 and PM10) were significantly higher in winter than in summer. All single particle aerosols were divided into seven categories: biomass burning (BB), coal combustion (CC), Dust, vehicle emission (VE), K mixed with nitrate (K-NO3), K mixed with sulfate and nitrate (K-SN), and K mixed with sulfate (K-SO4) particles. The highest contributions in both seasons were VE particles (24%). The higher contributions of K-SO4 (16%) and K-NO3 (10%) particles occurred in summer and winter, respectively, as a result of their different formation mechanisms. S-containing (K-SO4 and K-SN), VE, and BB particles caused the evolution of pollution in both seasons, and they can be considered as targets for future pollution reduction. The mixing of primary sources particles (VE, Dust, CC, and BB) with secondary components was stronger in winter than in summer. In summer, as pollution worsens, the mixing of primary sources particles with 62 [NO3]- weakened, but the mixing with 97 [HSO4]- increased. However, in winter, the mixing state of particles did not exhibit an obvious evolution rules. The potential source areas in summer were mainly distributed in the southern region of Sichuan, while in winter, besides the southern region, the contribution of the western region cannot be ignored.

A dopant-assisted iodide-adduct chemical ionization time-of-flight mass spectrometer based on VUV lamp photoionization for atmospheric low-molecular-weight organic acids analysis.

Formic and acetic acids are the most abundant gaseous organic acids and play the key role in the atmospheric chemistry. In iodine-adduct chemical ionization mass spectrometry (CIMS), the low utilization efficiency of methyl iodide and humidity interference are two major issues of the vacuum ultraviolet (VUV) lamp initiated CIMS for on-line gaseous formic and acetic acids analysis. In this work, we present a new CIMS based on VUV lamp, and the ion-molecular reactor is separated into photoionization and chemical ionization zones by a reducer electrode. Acetone was added to the photoionization zone, and the VUV photoionization acetone provided low-energy electrons for methyl iodide to generate I-, and the addition of acetone reduced the amount of methyl iodide by 2/3. In the chemical ionization zone, a headspace vial containing ultrapure water was added for humidity calibration, and the vial changes the sensitivity as a function of humidity from ambiguity to well linear correlation (R2 > 0.95). With humidity calibration, the CIMS can quantitatively measure formic and acetic acids in the humidity range of 0%-88% RH. In this mode, limits of detection of 10 and 50 pptv are obtained for formic and acetic acids, respectively. And the relative standard deviation (RSD) of quantitation stability for 6 days were less than 10.5%. This CIMS was successfully used to determine the formic and acetic acids in the underground parking and ambient environment of the Shandong University campus (Qingdao, China). In addition, we developed a simple model based formic acid concentration to assess vehicular emissions.

Application of Proteomics Technology Based on LC-MS Combined with Western Blotting and Co-IP in Antiviral Innate Immunity.

As an interferon-stimulating factor protein, STING plays a role in the response and downstream liaison in antiviral natural immunity. Upon viral invasion, the immediate response of STING protein leads to a series of changes in downstream proteins, which ultimately leads to an antiviral immune response in the form of proinflammatory cytokines and type I interferons, thus triggering an innate immune response, an adaptive immune response in vivo, and long-term protection of the host. In the field of antiviral natural immunity, it is particularly important to rigorously and sequentially probe the dynamic changes in the antiviral natural immunity connector protein STING caused by the entire anti-inflammatory and anti-pathway mechanism and the differences in upstream and downstream proteins. Traditionally, proteomics technology has been validated by detecting proteins in a 2D platform, for which it is difficult to sensitively identify changes in the nature and abundance of target proteins. With the development of mass spectrometry (MS) technology, MS-based proteomics has made important contributions to characterizing the dynamic changes in the natural immune proteome induced by viral infections. MS analytical techniques have several advantages, such as high throughput, rapidity, sensitivity, accuracy, and automation. The most common techniques for detecting complex proteomes are liquid chromatography (LC) and mass spectrometry (MS). LC-MS (Liquid Chromatography-Mass Spectrometry), which combines the physical separation capability of LC and the mass analysis capability of MS, is a powerful technique mainly used for analyzing the proteome of cells, tissues, and body fluids. To explore the combination of traditional proteomics techniques such as Western blotting, Co-IP (co-Immunoprecipitation), and the latest LC-MS methods to probe the anti-inflammatory pathway and the differential changes in upstream and downstream proteins induced by the antiviral natural immune junction protein STING.

Identifying an Abnormal Phosphorylated Adaptor by Viral Kinase Using Mass Spectrometry.

Mass spectrometers are widely used to identify protein phosphorylation sites. The process usually involves selective isolation of phosphoproteins and subsequent fragmentation to identify both the peptide sequence and phosphorylation site. Immunoprecipitation could capture and purify the protein of interest, greatly reducing sample complexity before submitting it for mass spectrometry analysis. This chapter describes a method to identify an abnormal phosphorylated site of the adaptor protein by a viral kinase through immunoprecipitation followed by LC-MS/MS.

Investigation of Protein Lysine Acetylation in Antiviral Innate Immunity.

Protein lysine acetylation involved in the antiviral innate immunity contributes to the regulation of antiviral inflammation responses, including type 1 interferon production and interferon-stimulated gene expression. Thus, investigation of acetylated antiviral proteins is vital for the complete understanding of inflammatory responses to viral infections. Immunoprecipitation (IP) assay with anti-targeted-protein antibody or with acetyl-lysine affinity beads followed by immunoblot provides a classical way to determine the potential modified protein in the antiviral innate pathways, whereas mass spectrometry can be utilized to identify the accurate acetylation lysine residues or explore the acetyl-proteomics. We demonstrate here comprehensive methods of protein lysine acetylation determination in virus-infected macrophages and embryonic fibroblast cells or proteins-overexpressed HEK 293 T cells in the context of antiviral innate immunity.

Degradation of gaseous hydrocarbons in aerated stirred bioreactors inoculated with Rhodococcus erythropolis: Effect of the carbon source and SIFT-MS method development.

The study of microbial hydrocarbons removal is of great importance for the development of future bioremediation strategies. In this study, we evaluated the removal of a gaseous mixture containing toluene, m-xylene, ethylbenzene, cyclohexane, butane, pentane, hexane and heptane in aerated stirred bioreactors inoculated with Rhodococcus erythropolis and operated under non-sterile conditions. For the real-time measurement of hydrocarbons, a novel systematic approach was implemented using Selected-Ion Flow Tube Mass Spectrometry (SIFT-MS). The effect of the carbon source (∼9.5 ppmv) on (i) the bioreactors' performance (BR1: dosed with only cyclohexane as a single hydrocarbon versus BR2: dosed with a mixture of the 8 hydrocarbons) and (ii) the evolution of microbial communities over time were investigated. The results showed that cyclohexane reached a maximum removal efficiency (RE) of 53% ± 4% in BR1. In BR2, almost complete removal of toluene, m-xylene and ethylbenzene, being the most water-soluble and easy-to-degrade carbon sources, was observed. REs below 32% were obtained for the remaining compounds. By exposing the microbial consortium to only the five most recalcitrant hydrocarbons, REs between 45% ± 5% and 98% ± 1% were reached. In addition, we observed that airborne microorganisms populated the bioreactors and that the type of carbon source influenced the microbial communities developed. The abundance of species belonging to the genus Rhodococcus was below 10% in all bioreactors at the end of the experiments. This work provides fundamental insights to understand the complex behavior of gaseous hydrocarbon mixtures in bioreactors, along with a systematic approach for the development of SIFT-MS methods.

Exploring the diversity of dissolved organic matter (DOM) properties and sources in different functional areas of a typical macrophyte - derived lake combined with optical spectroscopy and FT-ICR MS analysis.

Lake Baiyangdian is one of China's largest macrophyte - derived lakes, facing severe challenges related to water quality maintenance and eutrophication prevention. Dissolved organic matter (DOM) was a huge carbon pool and its abundance, property, and transformation played important roles in the biogeochemical cycle and energy flow in lake ecosystems. In this study, Lake Baiyangdian was divided into four distinct areas: Unartificial Area (UA), Village Area (VA), Tourism Area (TA), and Breeding Area (BA). We examined the diversity of DOM properties and sources across these functional areas. Our findings reveal that DOM in this lake is predominantly composed of protein - like substances, as determined by excitation - emission matrix and parallel factor analysis (EEM - PARAFAC). Notably, the exogenous tyrosine-like component C1 showed a stronger presence in VA and BA compared to UA and TA. Ultrahigh - resolution mass spectrometry (FT - ICR MS) unveiled a similar DOM molecular composition pattern across different functional areas due to the high relative abundances of lignan compounds, suggesting that macrophytes significantly influence the material structure of DOM. DOM properties exhibited specific associations with water quality indicators in various functional areas, as indicated by the Mantel test. The connections between DOM properties and NO3N and NH3N were more pronounced in VA and BA than in UA and TA. Our results underscore the viability of using DOM as an indicator for more precise and scientific water quality management.

Validation of two LCHRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose.

Untargeted metabolomics by LCHRMS is a powerful tool to enhance our knowledge of pathophysiological processes. Whereas validation of a bioanalytical method is customary in most analytical chemistry fields, it is rarely performed for untargeted metabolomics. This study aimed to establish and validate an analytical platform for a long-term, clinical metabolomics study. Sample preparation was performed with an automated liquid handler and four analytical methods were developed and evaluated. The validation study spanned three batches with twelve runs using individual serum samples and various quality control samples. Data was acquired with untargeted acquisition and only metabolites identified at level 1 were evaluated. Validation parameters were set to evaluate key performance metrics relevant for the intended application: reproducibility, repeatability, stability, and identification selectivity, emphasizing dataset intrinsic variance. Concordance of semi-quantitative results between methods was evaluated to identify potential bias. Spearman rank correlation coefficients (rs) were calculated from individual serum samples. Of the four methods tested, two were selected for validation. A total of 47 and 55 metabolites (RPLC-ESI+- and HILIC-ESI--HRMS, respectively) met specified validation criteria. Quality assurance involved system suitability testing, sample release, run release, and batch release. The median repeatability and within-run reproducibility as coefficient of variation% for metabolites that passed validation on RPLC-ESI+- and HILIC-ESI--HRMS were 4.5 and 4.6, and 1.5 and 3.8, respectively. Metabolites that passed validation on RPLC-ESI+-HRMS had a median D-ratio of 1.91, and 89 % showed good signal intensity after ten-fold dilution. The corresponding numbers for metabolites with the HILIC-ESI--HRMS method was 1.45 and 45 %, respectively. The rs median ({range}) for metabolites that passed validation on RPLC-ESI+- was 0.93 (N = 9 {0.69-0.98}) and on HILIC-ESI--HRMS was 0.93 (N = 22 {0.55-1.00}). The validated methods proved fit-for-purpose and the laboratory thus demonstrated its capability to produce reliable results for a large-scale, untargeted metabolomics study. This validation not only bolsters the reliability of the assays but also significantly enhances the impact and credibility of the hypotheses generated from the studies. Therefore, this validation study serves as a benchmark in the documentation of untargeted metabolomics, potentially guiding future endeavors in the field.

Characterization and identification of the wide-polarity multicomponents from Prunella vulgaris by offline two-dimensional liquid chromatography and hydrophilic interaction chromatography coupled to ion mobility-quadrupole time-of-flight mass spectrometry.

Metabolites identification is crucial to develop functional foods or perform quality control. Prunella vulgaris (Xia-Ku-Cao) is a medicinal and edible plant used as the herbal medicine or main additive in functional beverage. However, current analytical strategies can only on-line characterize tens of compounds, restricted by insufficient chromatographic resolution and low coverage of the mass spectrometric scan methods. This work was designed to characterize the wide-polarity components from the ear of P. vulgaris. The total extract was fractionated by semi-preparative high-performance liquid chromatography into the retained medium-polarity fraction and unretained polar fraction, which were further analyzed by offline two-dimensional liquid chromatography (2D-LC) and hydrophilic interaction chromatography, respectively. Data-independent high-definition MSE of the Vion™ ion mobility time-of-flight mass spectrometer was utilized enabling the high-coverage acquisition of collision-induced dissociation-MS2 data. The offline 2D-LC, configuring the XBridge Amide and HSS T3 columns, gave high orthogonality (0.81) and effective peak capacity (1555). Automatic peak annotation facilitated by the UNIFI™ bioinformatics platform and comparison with 62 reference compounds achieved the efficient and more reliable structural elucidation. We could characterize 255 compounds from P. vulgaris, with numerous phenylpropanoid phenolic acids and triterpenoid O-glycosides newly reported. Especially, collision cross section (CCS) prediction and targeted isolation of three compounds assisted in the identification of 39 groups of isomers. Additionally, 17 hydrophilic compounds, involving oligosaccharides and organic acids, were characterized from the unretained polar fraction. Conclusively, the in-depth metabolites identification of P. vulgaris was accomplished, and the results can benefit the development and better quality control of this valuable plant.

Proteomic Analysis of Aqueous Humor in Central Retinal Artery Occlusion: Unveiling Novel Insights Into Disease Pathophysiology.

Purpose: Central retinal artery occlusion (CRAO) is an ocular emergency that results from acute blockage of the blood supply to the retina and leads to a sudden vision loss. Other forms of ischemic retinopathies include diabetic retinopathy (DR), which involves chronic retinal ischemia and remains the leading cause of blindness in working-age adults. This study is the first to conduct a proteomic analysis of aqueous humor (AH) from patients with CRAO with a comparative analysis using vitreous humor (VH) samples from patients with DR. Methods: AH samples were collected from 10 patients with CRAO undergoing paracentesis and 10 controls undergoing cataract surgery. VH samples were collected from 10 patients with DR and 10 non-diabetic controls undergoing pars plana vitrectomy (PPV). Samples were analyzed using mass spectrometry. Results: Compared with controls, AH levels of 36 differentially expressed proteins (DEPs) were identified in patients with CRAO. Qiagen Ingenuity Pathway Analysis (IPA) revealed 11 proteins linked to ophthalmic diseases. Notably, enolase 2, a glycolysis enzyme isoform primarily expressed in neurons, was upregulated, suggesting neuronal injury and enzyme release. Additionally, clusterin, a protective glycoprotein, was downregulated. ELISA was conducted to confirm proteomics data. VH samples from patients with DR exhibited changes in a distinct set of proteins, including ones previously reported in the literature. Conclusions: The study provides novel insights into CRAO pathophysiology with multiple hits identified. Proteomic results differed between DR and CRAO studies, likely due to the different pathophysiology and disease duration. Translational Relevance: This is the first proteomic analysis of CRAO AH, with the potential to identify future therapeutic targets.

Identification of active ingredients in Naomaitai capsules using high-resolution mass spectrometry unite molecular network analysis and prediction of their action mechanisms.

RATIONALE: Although Naomaitai capsule (NMC) is widely used in clinical practice and has a good curative effect for cerebral infarction, its material basis and mechanism of action remain unclear. METHODS: In this study, ultra-high-performance liquid chromatography (UHPLC) coupled with quadrupole Orbitrap MS technology was used to analyse the in vivo and in vitro components of NMC, and the Global Natural Products Social Molecular Networking website was used to further analyse the components of NMC. Next, systems biology approaches were employed to investigate the mechanism of action of NMC. Finally, molecular docking technology was used to verify the network pharmacological results. RESULTS: In total, 177 compounds were identified in vitro, including 65 terpenoids, 62 flavonoids, 25 organic acids and 11 quinones. 64 compounds were identified in the blood of mice, and the main active components included ginkgolide C, ginkgolide A, ligustilide, tanshinone IIB, olmelin, emodin and puerarin. The main targets in vivo included TP53, SRC, STAT3, PIK3CA and PIK3R1. CONCLUSIONS: In conclusion, this study has revealed that NMC acts on multiple targets in the body through various active components, exerting synergistic effects in the treatment of CI. Its mechanism of action may involve inhibiting neuronal apoptosis, oxidative stress and inflammatory responses as well as reducing cerebral vascular permeability and promoting cerebral vascular regeneration.

Plasma proteomics and lipidomics facilitate elucidation of the link between Alzheimer's disease development and vessel wall fragility.

Proximity Extension Assay (PEA) and mass spectrometry (MS) methodologies were utilized for the proteomic and lipidomic characterization of plasma specimens from patients who developed Alzheimer's disease. Proteomics was performed by both PEA and Liquid Chromatography (LC)/MS in this study, but all the more because LC/MS generally tends to be biased towards proteins with high expression and high variability, generating hypotheses proved challenging. Consequently, attempt was made to interpret the results from the PEA data. There were 150 significantly variable proteins and 68 lipids among 1000 proteins and 400 lipids. Pathway analysis was performed for both total and variable proteins measured to reduce bias, and it appeared that vascular fragility was related to AD. Furthermore, a multitude of lipid-associated proteins exhibited statistical changes. In certain instances, the function of individual proteins affected the factors associated with them, whereas others demonstrated trends contrary to anticipated outcomes. These trends seem indicative of diverse feedback mechanisms that provide homeostatic equilibrium. The degree of unsaturation of fatty acids, correlated with cardiovascular risk, warrants specific attention. Certain bile acids exhibited the potential to cause vascular endothelial damage. Contemplating these discoveries in tandem with previously documented phenomena, subtle shifts in homeostatic functions seem to be linked to the fragility of vascular endothelial cells. This is evidenced by the slow and chronic evolution of Alzheimer's disease from preclinical stages to its manifestation.

An automated and high-throughput data processing workflow for PFAS identification in biota by direct infusion ultra-high resolution mass spectrometry.

The increasing recognition of the health impacts from human exposure to per- and polyfluorinated alkyl substances (PFAS) has surged the need for sophisticated analytical techniques and advanced data analyses, especially for assessing exposure by food of animal origin. Despite the existence of nearly 15,000 PFAS listed in the CompTox chemicals dashboard by the US Environmental Protection Agency, conventional monitoring and suspect screening methods often fall short, covering only a fraction of these substances. This study introduces an innovative automated data processing workflow, named PFlow, for identifying PFAS in environmental samples using direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). PFlow's validation on a bream liver sample, representative of low-concentration biota, involves data pre-processing, annotation of PFAS based on their precursor masses, and verification through isotopologues. Notably, PFlow annotated 17 PFAS absent in the comprehensive targeted approach and tentatively identified an additional 53 compounds, thereby demonstrating its efficiency in enhancing PFAS detection coverage. From an initial dataset of 30,332 distinct m/z values, PFlow thoroughly narrowed down the candidates to 84 potential PFAS compounds, utilizing precise mass measurements and chemical logic criteria, underscoring its potential in advancing our understanding of PFAS prevalence and of human exposure.

Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer.

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.

Native metabolomics for mass spectrometry-based siderophore discovery.

Microorganisms, plants, and animals alike have specialized acquisition pathways for obtaining metals, with microorganisms and plants biosynthesizing and secreting small molecule natural products called siderophores and metallophores with high affinities and specificities for iron or other non-iron metals, respectively. This chapter details a novel approach to discovering metal-binding molecules, including siderophores and metallophores, from complex samples ranging from microbial supernatants to biological tissue to environmental samples. This approach, called Native Metabolomics, is a mass spectrometry method in which pH adjustment and metal infusion post-liquid chromatography are interfaced with ion identity molecular networking (IIMN). This rule-based data analysis workflow that enables the identification of metal-binding species based on defined mass (m/z) offsets with the same chromatographic profiles and retention times. Ion identity molecular networking connects compounds that are structurally similar by their fragmentation pattern and species that are ion adducts of the same compound by chromatographic shape correlations. This approach has previously revealed new insights into metal binding metabolites, including that yersiniabactin can act as a biological zincophore (in addition to its known role as a siderophore), that the recently elucidated lepotchelin natural products are cyanobacterial metallophores, and that antioxidants in traditional medicine bind iron. Native metabolomics can be conducted on any liquid chromatography-mass spectrometry system to explore the binding of any metal or multiple metals simultaneously, underscoring the potential for this method to become an essential strategy for elucidating biological metal-binding molecules.

Linking biosynthetic genes to natural products using inverse stable isotopic labeling (InverSIL).

The sequencing of microbial genomes has far outpaced their functional annotation. Stable isotopic labeling can be used to link biosynthetic genes with their natural products; however, the availability of the required isotopically substituted precursors can limit the accessibility of this approach. Here, we describe a method for using inverse stable isotopic labeling (InverSIL) to link biosynthetic genes with their natural products. With InverSIL, a microbe is grown on an isotopically substituted medium to create a fully substituted culture, and subsequently, the incorporation of precursors of natural isotopic abundance can be tracked by mass spectrometry. This eliminates issues with isotopically substituted precursor availability. We demonstrate the utility of this approach by linking a luxI-type acyl-homoserine lactone synthase gene in a bacterium that grows on methanol with its quorum sensing signal products. In the future, InverSIL can also be used to link biosynthetic gene clusters hypothesized to produce siderophores with their natural products.

Identification potential biomarkers for diagnosis, and progress of breast cancer by using high-pressure photon ionization time-of-flight mass spectrometry.

BACKGROUND: In this study, exhaled breath testing has been considered a promising method for the detection and monitoring of breast cancer (BC). METHODS: A high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform was used to detect volatile organic compounds (VOCs) in breath samples. Then, machine learning (ML) models were constructed on VOCs for the diagnosis of BC and its progression monitoring. Ultimately, 1981 women with useable breath samples were included in the study, of whom 937 (47.3 %) had been diagnosed with BC. VOC panels were used for ML model construction for BC detection and progression monitoring. RESULTS: On the blinded testing cohort, this VOC-based model successfully differentiated patients with and without BC with sensitivity, specificity, and area under receiver operator characteristic curve (AUC) values of 85.9 %, 90.4 %, and 0.946. The corresponding AUC values when differentiating between patients with and without lymph node metastasis (LNM) or between patients with tumor-node-metastasis (TNM) stage 0/I/II or III/IV disease were 0.840 and 0.708, respectively. While developed VOC-based models exhibited poor performance when attempting to differentiate between patients based on pathological patterns (Ductal carcinoma in situ (DCIS) vs Invasive BC (IBC)) or molecular subtypes (Luminal vs Human epidermal growth factor receptor 2 (HER2+) vs Triple-negative BC (TNBC)) of BC. CONCLUSION: Collectively, the HPPI-TOFMS-based breathomics approaches may offer value for the detection and progression monitoring of BC. Additional research is necessary to explore the fundamental mechanisms of the identified VOCs.

Proteomics and metabolomics analyses of urine for investigation of gallstone disease in a high-altitude area.

BACKGROUND: The incidence of gallstones is high in Qinghai Province. However, the molecular mechanisms underlying the development of gallstones remain unclear. METHODS: In this study, we collected urine samples from 30 patients with gallstones and 30 healthy controls. The urine samples were analysed using multi-omics platforms. Proteomics analysis was conducted using data-independent acquisition, whereas metabolomics analysis was performed using liquid chromatography-mass spectrometry (LC-MS). RESULTS: Among the patients with gallstones, we identified 49 down-regulated and 185 up-regulated differentially expressed proteins as well as 195 up-regulated and 189 down-regulated differentially expressed metabolites. Six pathways were significantly enriched: glycosaminoglycan degradation, arginine and proline metabolism, histidine metabolism, pantothenate and coenzyme A biosynthesis, drug metabolism-other enzymes, and the pentose phosphate pathway. Notably, 10 differentially expressed proteins and metabolites showed excellent predictive performance and were selected as potential biomarkers. CONCLUSION: The findings of our metabolomics and proteomics analyses provide new insights into novel biomarkers for patients with cholelithiasis in high-altitude areas.

Reverse Chromatin Immunoprecipitation (R-ChIP).

DNA-protein interactions play fundamental roles in diverse biological functions. The gene-centered method is used to identify the upstream regulators of defined genes. In this study, we developed a novel method for capturing the proteins that bind to certain chromatin fragments or DNA sequences, which is called reverse chromatin immunoprecipitation (R-ChIP). This technology uses a set of specific DNA probes labeled with biotin to isolate chromatin or DNA fragments, and the DNA-associated proteins are then analyzed using mass spectrometry. This method can capture DNA-associated proteins with sufficient quantity and purity for identification.

Standardizing Protein Corona Characterization in Nanomedicine: A Multicenter Study to Enhance Reproducibility and Data Homogeneity.

We recently revealed significant variability in protein corona characterization across various proteomics facilities, indicating that data sets are not comparable between independent studies. This heterogeneity mainly arises from differences in sample preparation protocols, mass spectrometry workflows, and raw data processing. To address this issue, we developed standardized protocols and unified sample preparation workflows, distributing uniform protein corona digests to several top-performing proteomics centers from our previous study. We also examined the influence of using similar mass spectrometry instruments on data homogeneity and standardized database search parameters and data processing workflows. Our findings reveal a remarkable stepwise improvement in protein corona data uniformity, increasing overlaps in protein identification from 11% to 40% across facilities using similar instruments and through a uniform database search. We identify the key parameters behind data heterogeneity and provide recommendations for designing experiments. Our findings should significantly advance the robustness of protein corona analysis for diagnostic and therapeutics applications.