Biofluorescence imaging-guided spatial metabolic tracing: In vivo tracking of metabolic activity in circulating tumor cell-mediated multi-organ metastases.

Circulating tumor cells (CTC) are considered metastatic precursors that are shed from the primary or metastatic deposits and navigate the bloodstream before undergoing extravasation to establish distant metastases. Metabolic reprogramming appears to be a hallmark of metastatic progression, yet current methods for evaluating metabolic heterogeneity within organ-specific metastases in vivo are limited. To overcome this challenge, we present Biofluorescence Imaging-Guided Spatial Metabolic Tracing (BIGSMT), a novel approach integrating in vivo biofluorescence imaging, stable isotope tracing, stain-free laser capture microdissection, and liquid chromatography-mass spectrometry. This innovative technology obviates the need for staining or intricate sample preparation, mitigating metabolite loss, and substantially enhances detection sensitivity and accuracy through chemical derivatization of polar metabolites in central carbon pathways. Application of BIGSMT to a preclinical CTC-mediated metastasis mouse model revealed significant heterogeneity in the in vivo carbon flux from glucose into glycolysis and the tricarboxylic acid (TCA) cycle across distinct metastatic sites. Our analysis indicates that carbon predominantly enters the TCA cycle through the enzymatic reaction catalyzed by pyruvate dehydrogenase. Thus, our spatially resolved BIGSMT technology provides fresh insights into the metabolic heterogeneity and evolution during melanoma CTC-mediated metastatic progression and points to novel therapeutic opportunities.

Simultaneous analysis of DL-Amino acids in foods and beverages using a highly sensitive chiral resolution labeling reagent.

Amino acids with various functions are abundant in living organisms and foods. Recent advances in analytical technology show that trace amounts of D-amino acids exist in living organisms and foods. In addition, studies show that these amino acids are involved in various physiological functions that differ from those of L-amino acids. Thus, a technique for analyzing DL-amino acids is required. However, the simultaneous separation and highly sensitive detection of DL-amino acids are complicated; therefore, highly sensitive analytical methods that can rapidly separate and identify compounds are required. We previously developed our original chiral resolution labeling reagents for the separation and highly sensitive detection of DL-amino acids. Here, we developed a simple method for the rapid separation and highly sensitive detection of DL-amino acids in various foods and beverages by liquid chromatography-mass spectrometry (LC-MS) using an octadecyl (C18) column after labeling with 1-fluoro-2,4-dinitrophenyl-5-D-leucine-N,N-dimethylethylenediamineamide (D-FDLDA; enantiomeric excess > 99.9 %). In addition, we synthesized a stable isotope (13C6)-labeled D-FDLDA (13C6-D-FDLDA) and established an analytical method that can accurately identify the peak of each DL-amino acid. MS sensitivity of DL-amino acids labeled with our labeling reagent was higher than that of conventional labeling reagents (Marfey's reagents). The labeling reagent was neither desorbed from each DL-amino acid nor degraded for at least 1 week at 4 °C. Furthermore, we determined the DL-amino acid contents in foods and beverages using the proposed method, and differences in the total amino acid content and D/L ratio in each food and beverage were observed.

Metabolomics 2023 workshop report: moving toward consensus on best QA/QC practices in LC-MS-based untargeted metabolomics.

INTRODUCTION: During the Metabolomics 2023 conference, the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) presented a QA/QC workshop for LC-MS-based untargeted metabolomics. OBJECTIVES: The Best Practices Working Group disseminated recent findings from community forums and discussed aspects to include in a living guidance document. METHODS: Presentations focused on reference materials, data quality review, metabolite identification/annotation and quality assurance. RESULTS: Live polling results and follow-up discussions offered a broad international perspective on QA/QC practices. CONCLUSIONS: Community input gathered from this workshop series is being used to shape the living guidance document, a continually evolving QA/QC best practices resource for metabolomics researchers.

A Microdissection Protocol for Proteogenomic Analysis of Histological Sections to Advance Drug Development.

Combining proteogenomics with laser capture microdissection (LCM) in cancer research offers a targeted way to explore the intricate interactions between tumor cells and the different microenvironment components. This is especially important for immuno-oncology (IO) research where improvements in the predictability of IO-based drugs are sorely needed, and depends on a better understanding of the spatial relationships involving the tumor, blood supply, and immune cell interactions, in the context of their associated microenvironments. LCM is used to isolate and obtain distinct histological cell types, which may be routinely performed on complex and heterogeneous solid tumor specimens. Once cells have been captured, nucleic acids and proteins may be extracted for in-depth multimodality molecular profiling assays. Optimizing the minute tissue quantities from LCM captured cells is challenging. Following the isolation of nucleic acids, RNA-seq may be performed for gene expression and DNA sequencing performed for the discovery and analysis of actionable mutations, copy number variation, methylation profiles, etc. However, there remains a need for highly sensitive proteomic methods targeting small-sized samples. A significant part of this protocol is an enhanced liquid chromatography mass spectrometry (LC-MS) analysis of micro-scale and/or nano-scale tissue sections. This is achieved with a silver-stained one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) approach developed for LC-MS analysis of fresh-frozen tissue specimens obtained via LCM. Included is a detailed in-gel digestion method adjusted and specifically designed to maximize the proteome coverage from amount-limited LCM samples to better facilitate in-depth molecular profiling. Described is a proteogenomic approach leveraged from microdissected fresh frozen tissue. The protocols may also be applicable to other types of specimens having limited nucleic acids, protein quantity, and/or sample volume.

Elevated homocysteine is negatively correlated with plasma cystathionine ß-synthase activity in givosiran-treated patients.

Givosiran is a subcutaneously administered, liver-targeted RNA interference (RNAi) therapeutic that has been approved for treating acute hepatic porphyria (AHP). Elevation in plasma homocysteine (hyperhomocysteinemia) has been reported in AHP patients, and treatment with givosiran has been reported to further increase homocysteine levels in some patients. The mechanism of homocysteine elevation during givosiran treatment is unknown, but has been hypothesized to be mediated by a reduction in activity of cystathionine ß-synthase (CBS), which uses homocysteine as a substrate. A liquid chromatography-tandem mass spectrometry-based assay was adapted to measure circulating CBS activity. Using plasma collected from the Phase III ENVISION study, CBS activity was measured to directly evaluate whether it is associated with elevated homocysteine levels in givosiran-treated patients. CBS activity was reduced following givosiran treatment and both homocysteine and methionine levels were inversely correlated with CBS activity. Following administration of a supplement containing vitamin B6, a cofactor for CBS, in four patients during the trial, plasma CBS activity was found to increase, mirroring a corresponding decrease in homocysteine levels. These results support the hypothesis that elevated homocysteine levels following givosiran treatment result from a reduction of CBS activity and that vitamin B6 supplementation lowers homocysteine levels by increasing CBS activity.

A ng/L Level LC-MS Method Using Membrane SPE as Sampling Technology: Determination of Nine Halobenzoquinones in Potable Water.

A promising method was established for the determination of nine halobenzoquinones (HBQs) in potable water by membrane solid-phase extraction (MSPE) pretreatment and the liquid chromatography-mass spectrometry (LC-MS) method. A 500 mL water sample was taken for enrichment by the SDB-RPS membrane, which was previously activated by methanol and ultrapure water. The sample was eluted with methanol and re-dissolved with the initial mobile phase after nitrogen blowing. Then, it was detected in negative ion mode using the working curve, and HBQs were quantified by the external standard method. The linearity was satisfactory in the concentration range of 4-1000 ng/L, with correlation coefficients of 0.9963~0.9994. The recoveries were 73.5~126.6% at three spiked levels, with relative standard deviations (RSDs) of 6.8~15.5%. The limits of detection (LOD, S/N = 3) values were 0.1~0.7 ng/L. The results demonstrate that the MSPE-LC-MS method is reliable, rapid, and sensitive for the simultaneous analysis of nine HBPs in potable water.

Lipidomics random forest algorithm of seminal plasma is a promising method for enhancing the diagnosis of necrozoospermia.

BACKGROUND: Despite the clear clinical diagnostic criteria for necrozoospermia in andrology, the fundamental mechanisms underlying it remain elusive. This study aims to profile the lipid composition in seminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia. It also evaluates the efficacy of a lipidomics-based random forest algorithm model in identifying necrozoospermia. METHODS: Seminal plasma samples were collected from patients diagnosed with necrozoospermia (n = 28) and normozoospermia (n = 28). Liquid chromatography-mass spectrometry (LC-MS) was used to perform lipidomic analysis and identify the underlying biomarkers. A lipid functional enrichment analysis was conducted using the LION lipid ontology database. The top 100 differentially significant lipids were subjected to lipid biomarker examination through random forest machine learning model. RESULTS: Lipidomic analysis identified 46 lipid classes comprising 1267 lipid metabolites in seminal plasma. The top five enriched lipid functions as follows: fatty acid (FA) with ≤ 18 carbons, FA with 16-18 carbons, monounsaturated FA, FA with 18 carbons, and FA with 16 carbons. The top 100 differentially significant lipids were subjected to machine learning analysis and identified 20 feature lipids. The random forest model identified lipids with an area under the curve > 0.8, including LPE(20:4) and TG(4:0_14:1_16:0). CONCLUSIONS: LPE(20:4) and TG(4:0_14:1_16:0), were identified as differential lipids for necrozoospermia. Seminal plasma lipidomic analysis could provide valuable biochemical information for the diagnosis of necrozoospermia, and its combination with conventional sperm analysis may improve the accuracy and reliability of the diagnosis.

Predictive analysis of breast cancer response to neoadjuvant chemotherapy through plasma metabolomics.

PURPOSE: Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to neoadjuvant chemotherapy in breast cancer patients utilizing a metabolomic approach. METHODS: Plasma samples were obtained from 87 breast cancer patients undergoing neoadjuvant chemotherapy at our facility, collected both before the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles. RESULTS: Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second neoadjuvant chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points. CONCLUSION: The application of plasma metabolomics, utilizing CE-MS and LC-MS, may serve as a tool for predicting the efficacy of neoadjuvant chemotherapy in breast cancer in the future after all necessary validations have been completed.

Identification of Acyl-Protein Thioesterase-1 as a Polysorbate-Degrading Host Cell Protein in a Monoclonal Antibody Formulation Using Activity-Based Protein Profiling.

Polysorbate (PS) degradation in monoclonal antibody (mAb) formulations poses a significant challenge in the biopharmaceutical industry. PS maintains protein stability during drug product's shelf life but is vulnerable to breakdown by low-abundance residual host cell proteins (HCPs), particularly hydrolytic enzymes such as lipases and esterases. In this study, we used activity-based protein profiling (ABPP) coupled with mass spectrometry to identify acyl-protein thioesterase-1 (APT-1) as a polysorbate-degrading HCP in one case of mAb formulation with stability problems. We validated the role of APT1 by matching the polysorbate degradation fingerprint in the mAb formulation with that of a recombinant APT1 protein. Furthermore, we found an agreement between APT1 levels and PS degradation rates in the mAb formulation, and we successfully halted PS degradation using APT1-specific inhibitors ML348 and ML211. APT1 was found to co-purify with a specific mAb via hitchhiking mechanism. Our work provides a streamlined approach to identifying critical HCPs in PS degradation, supporting quality-by-design principles in pharmaceutical development.

Identification and Characterization of Rotigotine Degradation Products by HPLC Coupled DAD and CAD Detectors and HRMS Through Q-Orbitrap and Electrospray Ionization.

Rotigotine (RTG) is a dopamine agonist used in the treatment of Parkinson's disease. As it is susceptible to oxidation, stability studies must be carefully designed for the identification and characterization of all possible degradation products. Here, RTG degradation was evaluated according to the International Conference on Harmonization guidelines under various stress conditions, including acidic and basic hydrolysis, oxidative, metallic, photolytic, and thermal conditions. Additionally, more severe stress conditions were applied to induce RTG degradation. Significant degradation was only observed under oxidative and photolytic conditions. The samples were analyzed by high performance liquid chromatography coupled to photodiode array detectors, charged aerosol, and high-resolution mass spectrometry. Chromatographic analyses revealed the presence of eight substances related to RTG, four of which were already described and were qualified impurities (impurities B, C, K and E) and four new degradation products (DP-1 - DP-4), whose structures were characterized by high-resolution mass spectrometry through Q-Orbitrap and electrospray ionization. In the stress testing of the active pharmaceutical ingredient in solid form, significant RTG degradation was observed in the presence of the oxidative matrix. The results corroborate the literature that confirm the high susceptibility of RTG to oxidation and the importance of using different detectors to detect degradation products in forced degradation studies.

Enhancing drug development and clinical studies with patient-centric sampling using microsampling techniques: Opportunities, challenges, and insights into liquid chromatography-mass spectrometry strategies.

Microsampling has revolutionized pharmaceutical drug development and clinical research by reducing sample volume requirements, allowing sample collection at home or nontraditional sites, minimizing animal and patient burden, and enabling more flexible study designs. This perspective paper discusses the transformative impact of microsampling and patient-centric sampling (PCS) techniques, emphasizing their advantages in drug development and clinical trials. We highlight the integration of liquid chromatography-mass spectrometry (LC-MS) strategies for analyzing PCS samples, focusing on our research experience and a review of current literatures. The paper reviews commercially available PCS devices, their regulatory status, and their application in clinical trials, underscoring the benefits of PCS in expanding patient enrollment diversity and improving study designs. We also address the operational challenges of implementing PCS, including the need for bridging studies to ensure data comparability between traditional and microsampling methods, and the analytical challenges posed by PCS samples. The paper proposes future directions for PCS, including the development of global regulatory standards, technological advancements to enhance user experience, the increased concern of sustainability and patient data privacy, and the integration of PCS with other technologies for improved performance in drug development and clinical studies. By advancing microsampling and PCS techniques, we aim to foster patient-centric approaches in pharmaceutical sciences, ultimately enhancing patient care and treatment efficacy.

Changes in the Serum Metabolome in an Inflammatory Model of Osteoarthritis in Rats.

Osteoarthritis (OA) is a pathology of great impact worldwide. Its physiopathology is not completely known, and it is usually diagnosed by imaging techniques performed at advanced stages of the disease. The aim of this study was to evaluate early serum metabolome changes and identify the main metabolites involved in an inflammatory OA animal model. This study was performed on thirty rats. OA was induced in all animals by intra-articular injection of monoiodoacetate into the knee joint. Blood samples were taken from all animals and analyzed by mass spectrometry before OA induction and 28, 56, and 84 days following induction. Histological evaluation confirmed OA in all samples. The results of this study allow the identification of several changes in 18 metabolites over time, including organic acids, benzenoids, heterocyclic compounds, and lipids after 28 days, organic acids after 56 days, and lipid classes after 84 days. We conclude that OA induces serological changes in the serum metabolome, which could serve as potential biomarkers. However, it was not possible to establish a relationship between the identified metabolites and the time at which the samples were taken. Therefore, these findings should be confirmed in future OA studies.

Simultaneous determination of sulfonamides, trimethoprim, amoxicillin and tylosin in medicated feed by high performance liquid chromatography with mass spectrometry.

Introduction: The article presents a rapid and simple analytical procedure for determination of four sulfonamides (sulfadiazine, sulfamerazine, sulfamethazine and sulfamethoxazole), trimethoprim, tylosin and amoxicillin in animal medicated feed. Material and Methods: Eighteen medicated feed samples were analysed for active substances. The analytical protocol used a mixture of acetonitrile and 0.05 M phosphoric buffer, pH 4.5 for the extraction of seven antibacterial substances. After extraction, the samples were diluted in Milli-Q water and analysed by liquid chromatography with mass spectrometry. The developed procedure was subjected to validation in terms of linearity, selectivity, limits of quantification and determination, repeatability, reproducibility and uncertainty. Results: The validation of the method was carried out in accordance with the criteria set out in Commission Implementing Regulation (EU) 2021/808 and ICH guidelines. This method provided average recoveries of 90.8 to 104.5% with coefficients of variation for repeatability and reproducibility in the ranges of 3.2-6.9% and 5.2-8.3%, respectively for all analysed antibacterial substances. The limit of detection and limit of quantification for all seven analytes ranged from 5.4 mg/kg to 48.3 mg/kg and from 10.4 mg/kg to 119.3 mg/kg, respectively. The uncertainty of the method depending on the compound varied from 14.0% to 24.0%. The validated method was successfully applied to the 18 medicated feeds. Conclusion: The developed method can be successfully used to routinely control the content and homogeneity of seven antibacterial substances in medicated feed.

[Alignment method for metabolite chromatographic peaks using an N-acyl glycine retention index system].

Peak alignment is a crucial data-processing step in untargeted metabolomics analysis that aims to integrate metabolite data from multiple liquid chromatography-mass spectrometry (LC-MS) batches for enhanced comparability and reliability. However, slight variations in the chromatographic separation conditions can result in retention time (RT) shifts between consecutive analyses, adversely affecting peak alignment accuracy. In this study, we present a retention index (RI)-based chromatographic peak-shift correction (CPSC) strategy to address RT shifts and align chromatographic peaks for metabolomics studies. A series of N-acyl glycine homologues (C2-C23) was synthesized as calibrants, and an LC RI system was established. This system effectively corrected RT shifts arising from variations in flow rate, gradient elution, instrument systems, and chromatographic columns. Leveraging the RI system, we successfully adjusted the RT of raw data to mitigate RT shifts and then implemented the Joint Aligner algorithm for peak alignment. We assessed the accuracy of the RI-based CPSC strategy using pooled human fecal samples as a test model. Notably, the application of the RI-based CPSC strategy to a long-term dataset spanning 157 d as an illustration revealed a significant enhancement in peak alignment accuracy from 15.5% to 80.9%, indicating its ability to substantially improve peak-alignment precision in multibatch LC-MS analyses.

Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics.

BACKGROUND: Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities. AIM OF REVIEW: A present goal of the Best Practices WG is to develop a working strategy, or roadmap, that guides the actions of practitioners and progress in the field. The framework in which mQACC operates promotes the harmonization and dissemination of current best QA/QC practice guidance and encourages widespread adoption of these essential QA/QC activities for liquid chromatography-mass spectrometry. KEY SCIENTIFIC CONCEPTS OF REVIEW: Community engagement and QA/QC information gathering activities have been occurring through conference workshops, virtual and in-person interactive forum discussions, and community surveys. Seven principal QC stages prioritized by internal discussions of the Best Practices WG have received participant input, feedback and discussion. We outline these stages, each involving a multitude of activities, as the framework for identifying QA/QC best practices. The ultimate planned product of these endeavors is a "living guidance" document of current QA/QC best practices for untargeted metabolomics that will grow and change with the evolution of the field.

Cover Crop Root Exudates Impact Soil Microbiome Functional Trajectories in Agricultural Soils.

Background: Cover cropping is an agricultural practice that uses secondary crops to support the growth of primary crops through various mechanisms including erosion control, weed suppression, nutrient management, and enhanced biodiversity. Cover crops may elicit some of these ecosystem services through chemical interactions with the soil microbiome via root exudation, or the release of plant metabolites from roots. Phytohormones are one metabolite type exuded by plants that activate the rhizosphere microbiome, yet managing this chemical interaction remains an untapped mechanism for optimizing plant-soil microbiome interactions. Currently, there is limited understanding on the diversity of cover crop phytohormone root exudation patterns and how these chemical messages selectively enrich specific microbial taxa and functionalities in agricultural soils. Results: Here, we link variability in cover crop root exudate composition to changes in soil microbiome functionality. Exudate chemical profiles from 4 cover crop species (Sorghum bicolor, Vicia villosa, Brassica napus, and Secale cereal) were used as the chemical inputs to decipher microbial responses. These distinct exudate profiles, along with a no exudate control, were amended to agricultural soil microcosms with microbial responses tracked over time using metabolomes and genome-resolved metatranscriptomes. Our findings illustrated microbial metabolic patterns were unique in response to cover crop exudate inputs over time, particularly by sorghum and cereal rye amended microcosms where we identify novel microbial members (at the genera and family level) who produced IAA and GA4 over time. We also identify broad changes in microbial nitrogen cycling in response chemical inputs. Conclusions: We highlight that root exudate amendments alter microbial community function and phytohormone metabolisms, particularly in response to root exudates isolated from cereal rye and sorghum plants. Additionally, we constructed a soil microbial genomic catalog of microorganisms responding to commonly used cover crops, a public resource for agriculturally-relevant microbes. Many of our exudate-stimulated microorganisms are representatives from poorly characterized or novel taxa, highlighting the yet to be discovered metabolic reservoir harbored in agricultural soils. Our findings emphasize the tractability of high-resolution multiomics approaches to investigate processes relevant for agricultural soils, opening the possibility of targeting specific soil biogeochemical outcomes through biological precision agricultural practices that use cover crops and the microbiome as levers for enhanced crop production.

Assessment of the proteome profile of decellularized human amniotic membrane and its biocompatibility with umbilical cord-derived mesenchymal stem cells.

Extracellular matrix-based bio-scaffolds are useful for tissue engineering as they retain the unique structural, mechanical, and physiological microenvironment of the tissue thus facilitating cellular attachment and matrix activities. However, considering its potential, a comprehensive understanding of the protein profile remains elusive. Herein, we evaluate the impact of decellularization on the human amniotic membrane (hAM) based on its proteome profile, physicochemical features, as well as the attachment, viability, and proliferation of umbilical cord-derived mesenchymal stem cells (hUC-MSC). Proteome profiles of decellularized hAM (D-hAM) were compared with hAM, and gene ontology (GO) enrichment analysis was performed. Proteomic data revealed that D-hAM retained a total of 249 proteins, predominantly comprised of extracellular matrix proteins including collagens (collagen I, collagen IV, collagen VI, collagen VII, and collagen XII), proteoglycans (biglycan, decorin, lumican, mimecan, and versican), glycoproteins (dermatopontin, fibrinogen, fibrillin, laminin, and vitronectin), and growth factors including transforming growth factor beta (TGF-ß) and fibroblast growth factor (FGF) while eliminated most of the intracellular proteins. Scanning electron microscopy was used to analyze the epithelial and basal surfaces of D-hAM. The D-hAM displayed variability in fibril morphology and porosity as compared with hAM, showing loosely packed collagen fibers and prominent large pore areas on the basal side of D-hAM. Both sides of D-hAM supported the growth and proliferation of hUC-MSC. Comparative investigations, however, demonstrated that the basal side of D-hAM displayed higher hUC-MSC proliferation than the epithelial side. These findings highlight the importance of understanding the micro-environmental differences between the two sides of D-hAM while optimizing cell-based therapeutic applications.

Investigating pH Effects on Enzymes Catalyzing Polysorbate Degradation by Activity-Based Protein Profiling.

Host cell proteins (HCPs) are process-related impurities that can negatively impact the quality of biotherapeutics. Some HCPs possess enzymatic activity and can affect the active pharmaceutical ingredient (API) or excipients such as polysorbates (PS). PSs are a class of non-ionic surfactants commonly used as excipients in biotherapeutics to enhance the stability of APIs. The enzyme activity of certain HCPs can result in the degradation of PSs, leading to particle formation and decreased shelf life of biotherapeutics. Identifying and characterizing these HCPs is therefore crucial. This study employed the Activity-Based Protein Profiling (ABPP) technique to investigate the effect of pH on the activity of HCPs that have the potential to degrade polysorbates. Two probes were utilized: the commercially available fluorophosphonate (FP)-Desthiobiotin probe and a probe based on the antiobesity drug, Orlistat. Over 50 HCPs were identified, showing a strong dependence on pH-milieu regarding their enzyme activity. These findings underscore the importance of accounting for pH variations in the ABPP method and other investigations of HCP activity. Notably, the Orlistat-based probe (OBP) enabled us to investigate the enzymatic activity of a wider range of HCPs, emphasizing the advantage of using more than one probe for ABPP. Finally, this study led to the discovery of previously unreported active enzymes, including three HCPs from the carboxylesterase enzyme family.

A comparative study of plasma and dried blood spot metabolomics and its application to diabetes mellitus.

Metabolomics has become a promising method for understanding pathological mechanisms. Plasma (PLS) is the most common sample type used for metabolomics studies, and dried blood spot (DBS) sampling has been regarded as a good strategy due to its unique characteristics. However, how results obtained from DBS can be correlated to results obtained from PLS remains unclear. To bridge the results and to investigate the feasibility of using DBS to study metabolomics, we performed a comparative study using 64 paired PLS and DBS samples. The number of features extracted from the two different sample types was investigated. The concentration correlations of the identified metabolites between the DBS and PLS were individually studied. Approximately 47 % showed a strong correlation, 19 % showed a moderate correlation, and 34 % showed a low or even negligible correlation. Finally, we applied both PLS- and DBS-based metabolomics to explore the dysregulated metabolites in diabetes mellitus (DM) patients. Thirty-two non-DM subjects and 32 DM patients were enrolled, and 2 significant metabolites were found in both PLS and DBS samples. In summary, detailed correlation information between PLS and DBS metabolites was first explored in this study, and it is anticipated that these results could facilitate future applications in DBS-based metabolomics.

Serum Stabilities and Antiviral Activities of Chemically Modified Peptides Against Dengue Serotypes 1-4.

Dengue presents a major public health concern in over 100 countries due to the absence of an effective vaccine and antiviral therapy against all four dengue virus (DENV) serotypes. Several antiviral peptides were previously reported to inhibit at least three or all four DENV serotypes. Chemical modifications such as d-amino acid substitutions, polyethylene glycol (PEG)ylation, and cyclization could be applied to peptides to improve their biological activities and stability in serum. The PEGylated peptide 3 (PEG-P3) was identified to be the most promising antiviral candidate as it demonstrated good inhibitory effects against all four DENV serotypes during the pre- and post-infection stages, Based on the RP-HPLC and LC/MS analysis, peptide 4 was identified to be more stable in human serum than peptide 3, with 78.9 % and 41.6 % of the peptides remaining after 72 h of incubation in human serum, respectively. Both peptides were also able to retain their antiviral activities against specific DENV serotypes after 72 h incubation in human serum. PEG-P3 was found to be more stable than the unmodified peptide 3 with 89.4 % of PEG-P3 remaining in the human serum after 72 h of incubation. PEG-P3 was able to retain its inhibitory effects against DENV-1 to 4 after 72 h of incubation in human serum. This study provided insights into the antiviral activities and stabilities of the unmodified and chemically modified peptides in human serum.