Connecting chemical exposome to human health using high-resolution mass spectrometry-based biomonitoring: Recent advances and future perspectives.

Compared with the rapid advances in genomics leading to broad understanding of human disease, the linkage between chemical exposome and diseases is still under investigation. High-resolution mass spectrometry (HRMS) is expected to accelerate the process via relatively accurate and precise biomonitoring of human exposome. This review covers recent advancements in biomonitoring of exposed environmental chemicals (chemical exposome) using HRMS described in the 124 articles that resulted from a systematic literature search on Medline and Web of Science databases. The analytical strategic aspects, including the selection of specimens, sample preparation, instrumentation, untargeted versus targeted analysis, and workflows for MS-based biomonitoring to explore the environmental chemical space of human exposome, are deliberated. Applications of HRMS in human exposome investigation are presented by biomonitoring (1) exposed chemical compounds and their biotransformation products; (2) DNA/protein adducts; and (3) endogenous compound perturbations. Challenges and future perspectives are also discussed.

Characterizing the D-Amino Acid Position in Peptide Epimers by Using Higher-Energy Collisional Dissociation Tandem Mass Spectrometry: A Case Study of Liraglutide.

D-amino acid-containing peptides (DAACPs) occur in biological and artificial environments. Since the importance of DAACPs has been recognized, various mass spectrometry-based analytical approaches have been developed. However, the capability of higher-energy collisional dissociation (HCD) fragmentation to characterize DAACP sites has not been evaluated. In this study, we compared the normalized spectra intensity under different conditions of HCD and used liraglutide along with its DAACPs as examples. Our results indicated that the difference in the intensity of y ions between DAACPs and all-L liraglutide could not only distinguish them but also localize the sites of D-amino acids in the DAACPs. Our data demonstrate the potential of using HCD for the site characterization of DAACPs, which may have great impact in biological studies and peptide drug development.

Identification of Xenobiotic Biotransformation Products Using Mass Spectrometry-Based Metabolomics Integrated with a Structural Elucidation Strategy by Assembling Fragment Signatures.

The identification of xenobiotic biotransformation products is crucial for delineating toxicity and carcinogenicity that might be caused by xenobiotic exposures and for establishing monitoring systems for public health. However, the lack of available reference standards and spectral data leads to the generation of multiple candidate structures during identification and reduces the confidence in identification. Here, a UHPLC-HRMS-based metabolomics strategy integrated with a metabolite structure elucidation approach, namely, FragAssembler, was proposed to reduce the number of false-positive structure candidates. biotransformation product candidates were filtered by mass defect filtering (MDF) and multiple-group comparison. FragAssembler assembled fragment signatures from the MS/MS spectra and generated the modified moieties corresponding to the identified biotransformation products. The feasibility of this approach was demonstrated by the three biotransformation products of di(2-ethylhexyl)phthalate (DEHP). Comprehensive identification was carried out, and 24 and 13 biotransformation products of two xenobiotics, DEHP and 4'-Methoxy-α-pyrrolidinopentiophenone (4-MeO-α-PVP), were annotated, respectively. The number of 4-MeO-α-PVP biotransformation product candidates in the FragAssembler calculation results was approximately 2.1 times lower than that generated by BioTransformer 3.0. Our study indicates that the proposed approach has great potential for efficiently and reliably identifying xenobiotic biotransformation products, which is attributed to the fact that FragAssembler eliminates false-positive reactions and chemical structures and distinguishes modified moieties on isomeric biotransformation products. The FragAssembler software and associated tutorial are freely available at https://cosbi.ee.ncku.edu.tw/FragAssembler/ and the source code can be found at https://github.com/YuanChihChen/FragAssembler.

Discovering Hair Biomarkers of Alzheimer's Disease Using High Resolution Mass Spectrometry-Based Untargeted Metabolomics.

Hair may be a potential biospecimen to discover biomarkers for Alzheimer's disease (AD) since it reflects the integral metabolic profiles of body burden over several months. Here, we described the AD biomarker discovery in the hair using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach. A total of 24 patients with AD and 24 age- and sex-matched cognitively healthy controls were recruited. The hair samples were collected 0.1-cm away from the scalp and further cut into 3-cm segments. Hair metabolites were extracted by ultrasonication with methanol/phosphate-buffered saline 50/50 (v/v) for 4 h. A total of 25 discriminatory chemicals in hair between the patients with AD and controls were discovered and identified. The AUC value achieved 0.85 (95% CI: 0.72~0.97) in patients with very mild AD compared to healthy controls using a composite panel of the 9 biomarker candidates, indicating high potential for the initiation or promotion phase of AD dementia in the early stage. A metabolic panel combined with the nine metabolites may be used as biomarkers for the early detection of AD. The hair metabolome can be used to reveal metabolic perturbations for biomarker discovery. Investigating perturbations of the metabolites will offer insight into the pathogenesis of AD.

Investigation of New Psychoactive Substances (NPS), Other Illicit Drugs, and Drug-Related Compounds in a Taiwanese Wastewater Sample Using High-Resolution Mass-Spectrometry-Based Targeted and Suspect Screening.

The proliferation of new psychoactive substances (NPSs) in recent years has posed a significant challenge to public health. Traditional monitoring methods have proven insufficient in tracking these constantly evolving substances, leading to the development of alternative approaches such as wastewater-based epidemiology (WBE). The present study aims to utilize high-resolution mass spectrometry (HRMS)-based targeted and suspect screening to profile NPS, other illicit drugs, and drug-related compounds in a Taiwanese wastewater sample. For the targeted analysis, 8 out 18 standards of illicit drugs have been identified. The suspect screening approach based on approximately 3600 substances in the SWGDRUG library can further identify 92 compounds, including opiate analgesics, synthetic cathinones, phenylalkylamines derivatives, phenethylamine derivatives, tryptamine derivatives, steroids, and ephedrine-related compounds. Additionally, the presence of 5-methoxy-2-aminoindane (MEAI) in the wastewater indicates that drug dealers have recently sold this potential NPS to evade drug regulations. This study firstly reports the HRMS-based comprehensive profile of NPS, other illicit drugs, and drug-related compounds in Taiwan, which could be applied as biomarkers for estimating the consumption of drugs.

Post-Deconvolution MS/MS Spectra Extraction with Data-Independent Acquisition for Comprehensive Profiling of Urinary Glucuronide-Conjugated Metabolome.

Conjugation reactions are of critical significance in human metabolism. Identification of these conjugated metabolites is still challenging. Here, we propose a strategy, post-deconvolution MS/MS spectra extraction with data-independent acquisition (PDMS2E-DIA), to comprehensively profile the glucuronide-conjugated metabolome. PDMS2E-DIA enables the identification of conjugated and unconjugated metabolite pairs through neutral loss filtering combined with a significant change in abundance after the deconjugation reaction. Purified DIA MS/MS spectra were constructed by extracting MS/MS fragments shared between spectra derived from conjugated and unconjugated metabolites. The feasibility of this approach was first demonstrated by the identification of two glucuronide-conjugated metabolite standards spiked in urine samples. For human urine samples, 479 features were structurally annotated as potential glucuronide-conjugated metabolites, resulting in the identification of 211 metabolites. Fragment peaks derived from interferents were found to be removed by PDMS2E-DIA, which increased about 6 times the number of identified urine metabolites compared with those calculated from raw DIA deconvoluted MS/MS spectra. This approach was found to have great potential for identifying glucuronide-conjugated metabolites, as well as other kinds of chemical conjugations.

Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition.

The proteins of extracellular vesicles (EVs) that originate from tumors reflect the producer cells' proteomes and can be detected in biological fluids. Thus, EVs provide proteomic signatures that are of great interest for screening and predictive cancer diagnostics. By applying targeted mass spectrometry with stable isotope-labeled peptide standards, we assessed the levels of 28 EV-associated proteins, including the conventional exosome markers CD9, CD63, CD81, CD82, and HSPA8, in vesicles derived from the lung cancer cell lines NCI-H23 and A549. Furthermore, we evaluated the detectability of these proteins and their abundance in plasma samples from 34 lung cancer patients and 23 healthy volunteers. The abundance of TLN1, TUBA4A, HSPA8, ITGB3, TSG101, and PACSIN2 in the plasma of lung cancer patients was measured using targeted mass spectrometry and compared to that in plasma from healthy volunteers. The most diagnostically potent markers were TLN1 (AUC, 0.95), TUBA4A (AUC, 0.91), and HSPA8 (AUC, 0.88). The obtained EV proteomic signature allowed us to distinguish between the lung adenocarcinoma and squamous cell carcinoma histological types. The proteomic cargo of the extracellular vesicles represents a promising source of potential biomarkers.

Assessing the Similarity between Random Copolymer Drug Glatiramer Acetate by Using LC-MS Data Coupling with Hypothesis Testing.

The full characterization of nonbiological complex drugs (NBCDs) is not possible, but analytical approaches are of urgent need to evaluate the similarity between different lots and compare with their follow-up versions. Here, we propose a hypothesis testing-based approach to assess the similarity/difference between random amino acid copolymer drugs using liquid chromatography mass spectrometry (LC-MS) analysis. Two glatiramer acetate (GA) drugs, commercially available Copaxone and in-house synthesized SPT, and a negative control were digested by Lys-C and followed by HILIC-MS analysis. After retention time alignment and feature identification, 1627 features matched to m/z values in an elemental composition database were considered as derived from active drug ingredients. A hypothesis testing approach, the sum of squared deviations test, was developed to process high-dimensional data derived from LC-MS spectra. The feasibility of this approach was first demonstrated by testing 5 versus 5 lots of Copaxone and Copaxone versus SPT, which suggested a significant similarity by obtaining the estimated 95th percentile of the distribution of the estimator (ρ̂(95%)) at 0.0056 (p-value = 0.0026) and 0.0026 (p-value < 0.0001), respectively. In contrast, the ρ̂ was 0.036 (p-value = 1.00), while comparing Copaxone and the negative control, implying a lack of similarity. We further synthesized nine stable isotope-labeled peptides to validate the proposed amino acid sequences in the database, demonstrating the correctness in sequence identification. The quantitation variations in our analytical procedures were determined to be 6.8-7.7%. This approach was found to have a great potential for evaluating the similarity between generic NBCDs and listed reference drugs, as well as to monitor the lot-to-lot variation.

Secretomic Analysis of Host-Pathogen Interactions Reveals That Elongation Factor-Tu Is a Potential Adherence Factor of Helicobacter pylori during Pathogenesis.

The secreted proteins of bacteria are usually accompanied by virulence factors, which can cause inflammation and damage host cells. Identifying the secretomes arising from the interactions of bacteria and host cells could therefore increase understanding of the mechanisms during initial pathogenesis. The present study used a host-pathogen coculture system of Helicobacter pylori and monocytes (THP-1 cells) to investigate the secreted proteins associated with initial H. pylori pathogenesis. The secreted proteins from the conditioned media from H. pylori, THP-1 cells, and the coculture were collected and analyzed using SDS-PAGE and LC-MS/MS. Results indicated the presence of 15 overexpressed bands in the coculture. Thirty-one proteins were identified-11 were derived from THP-1 cells and 20 were derived from H. pylori. A potential adherence factor from H. pylori, elongation factor-Tu (EF-Tu), was selected for investigation of its biological function. Results from confocal microscopic and flow cytometric analyses indicated the contribution of EF-Tu to the binding ability of H. pylori in THP-1. The data demonstrated that fluorescence of EF-Tu on THP-1 cells increased after the addition of the H. pylori-conditioned medium. This study reports a novel secretory adherence factor in H. pylori, EF-Tu, and further elucidates mechanisms of H. pylori adaptation for host-pathogen interaction during pathogenesis.

Qualification and Verification of Serological Biomarker Candidates for Lung Adenocarcinoma by Targeted Mass Spectrometry.

Lung cancer is the leading cause of cancer mortality worldwide. Although many biomarkers have been identified for lung cancer, their low specificity and sensitivity present an urgent need for the identification of more candidate biomarkers. In this study, we conducted MRM-based targeted analysis to evaluate the potential utility of a list of candidate proteins for lung cancer diagnosis. A total of 1249 transitions of 420 peptides representing 102 candidate proteins from our previous study and the literature were first screened by MRM analysis in pooled plasma samples, resulting in 78 proteins remaining in the list. Relative quantification of these 78 proteins was further performed in 60 individual plasma samples from lung adenocarcinoma patients in stages I-III and matched healthy control subjects. Ultimately, nine proteins were found to be able to distinguish patients from controls. Further combinations of five, three, and two candidate marker proteins improved the sensitivity to discriminate patients from controls and resulted in a merged AUC value of nearly 1.00 in stages I-III patients versus controls. Our results highlighted several possible markers for lung adenocarcinoma, and the proposed protein panels require further validation in a larger cohort to evaluate their potential use in clinical applications or development of therapeutics.

Down-regulation of TIMP-1 inhibits cell migration, invasion, and metastatic colonization in lung adenocarcinoma.

Tissue inhibitor metalloproteinase-1 (TIMP-1) is clinically associated with a poor prognosis for various cancers, but the roles of TIMP-1 in lung cancer metastasis are controversial. Our previous secretomic study revealed that TIMP-1 is highly abundant in high invasiveness cells of lung adenocarcinoma. In the current study, TIMP-1 abundances in primary lung adenocarcinoma tissues, as revealed by immunohistochemistry, are significantly higher in patients with lymph invasion and distant metastasis than in those without. Receiver operating characteristic curve analyses suggest 73.7 and 86.2 % accuracy to separate patients with lymph node and distant metastasis and those without, respectively. Moreover, we demonstrate that the expression level of TIMP-1 positively associates with cell mobility, invasiveness, and metastatic colonization. Most notably, the novel mechanism in which TIMP-1 facilitates metastatic colonization through the mediation of pericellular polyFN1 assembly was revealed. In summary, this study presents novel functions of TIMP-1 in promoting cancer metastasis and suggests TIMP-1 is a potential tissue biomarker for lymph invasion and distant metastasis of lung adenocarcinoma.

Optimization of titanium dioxide and immunoaffinity-based enrichment procedures for tyrosine phosphopeptide using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Tyrosine phosphorylation is an important regulator of signaling in cellular pathways, and dysregulated tyrosine phosphorylation causes several diseases. Mass spectrometry has revealed the importance of global phosphoproteomic characterization. Analysis of tyrosine phosphorylation by studying the mass-spectrometry (MS)-determined phosphoproteome remains difficult because of the relatively low abundance of tyrosine phosphoproteins. To effectively evaluate tyrosine-phosphopeptide enrichment and reduce ion suppression from non-phosphorylated peptides in MS analysis, three trypsin-digested BSA peptides and 14 standard phosphopeptides, including six tyrosine phosphopeptides, four serine phosphopeptides, and four threonine phosphopeptides, were subjected to titanium dioxide immunoaffinity-based enrichment and also to combined enrichment using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and liquid chromatography-mass spectrometry (LC-MS) analyses. The enrichment factors were evaluated to determine the efficiency of each enrichment procedure. Comparison of five optimized enrichment methods, including TiO2-based immunoaffinity purification in Tris and MOPS buffer systems, TiO2-immunoaffinity enrichment, and immunoaffinity-TiO2 enrichment for total tyrosine, serine and threonine phosphopeptides, revealed that the order of the enrichment factors for total tyrosine phosphopeptides is: (i) immunoaffinity-TiO2 (enrichment factor = 38,244), (ii) TiO2-immunoaffinity (enrichment factor = 24,987), (iii) TiO2 micro-column (enrichment factor = 10,305), (iv) immunoaffinity in Tris buffer system (enrichment factor = 1450), and (v) immunoaffinity in the MOPS buffer system (enrichment factor = 32). These results reveal that an alternative enrichment scheme before use of a TiO2 micro-column, using immunoaffinity 4G10 and PY99 antibody enrichment under optimized conditions, can provide greater selectivity for tyrosine-phosphopeptide enrichment.

Prenatal exposure to phthalate ester and pubertal development in a birth cohort in central Taiwan: a 12-year follow-up study.

Phthalate esters are widely used plasticizers that are present in many daily used products. Although some of their reproductive effects have been reported, pubertal development effects from prenatal exposure to phthalates awaits further investigations. A population based birth cohort was established (N=437 at baseline) with maternal exposure to phthalates assessed in urine collected at the third trimester of pregnancy in 2001 and 2002. Their 133 children with prenatal phthalates exposure were followed up for the outcomes of pubertal development by sequential physical examinations at eight and 11 years old in 2009 and 2012. Urinary concentrations of major phthalate metabolites (i.e., mono-2-ethylhexyl phthalate [MEHP], mono-(2-ethyl-5-hydroxyhexyl) phthalate [MEHHP], mono-(2-ethyl-5-oxohexyl) phthalate [MEOHP], mono-butyl phthalate [MBP], mono-benzyl phthalate [MBzP], monomethyl phthalate [MMP], and mono-ethyl phthalate [MEP]) were determined using liquid chromatography linked to tandem mass spectrometry. The reproductive development measurements included bone age (for both genders), testicle size (for boys), uterus size, and ovarian volume (for girls). We reported results of 133 children with complete data by applying generalized estimating equations for the repeated continuous outcomes. After controlling for Tanner stage, we detected a significant association between reduced uterus size and increasing phthalate exposure in the 2(nd) tertile relative to the 1st tertile of creatinine-corrected MEHP (B=-0.40; 95% C.I.: -0.73, -0.07, relative to the 1st tertile) and total DEHP (B=-0.39, 95% C.I.:-0.66, -0.01 for the 2nd tertile and B=0.34, 95% C.I.: -0.67, -0.01 for the 3rd tertile, relative to the 1st tertile) with a linear trend among girls. MBzP was also found negatively associated with bone age/chronological age ratio (B=-0.07, 95% CI: -0.13, -0.01 for the 3rd tertile, relative to the 1st tertile) with a linear trend for girls. We found no evidence of an association between phthalate exposure and ovarian volume or testicle size. This analysis suggests phthalate exposure may affect specific pubertal development characteristics in human beings. Further studies with larger sample sizes and longer follow-up period are warranted.

Phylodynamic analysis of the canine distemper virus hemagglutinin gene.

BACKGROUND: Canine distemper (CD) is one of the most contagious and lethal viral diseases in dogs. Despite the widespread use of vaccines, the prevalence of the CD virus (CDV) has increased at an alarming rate in recent years. In this phylodynamic study, we investigated the spatiotemporal modes of dispersal, viral demographic trends, and effectiveness of vaccines for CDV. A total of 188 full-length CDV hemagglutinin (H) gene sequences dataset were subjected to recombination analysis, including seven from modified live vaccine (MLV) strains and 12 from Taiwan specimens. After excluding the MLV strains and potential recombinant strains, alignments of 176 of 188 previous CDV strains were further used to analyze phylodynamic characteristics, and evidence of selection, and co-evolution. RESULTS: The CDV genotype consisted of MLV-associated genotypes such as America-1 and Rockborn-like strains, which were characterized by long terminal branches and no distinct geographical patterns among lineages. In contrast, wild-type isolates clustered into lineages with a spatiotemporal structure and short terminal branches. Co-circulation and extensive diversification were simultaneously observed. The sequence variation signature was shaped by both geographic diversity and host tropism. Codon 506 was identified as a multi-epistatic interacting in the H protein. CONCLUSIONS: The topological signature revealed in this study suggests different epidemic scenarios. For example, a ladder-like backbone is a hallmark of directional selection, and cladogenesis at long terminal branches indicates the emergence of a surviving lineage. The stable effective viral population of CDV indicate the effectiveness of vaccines currently used to control the virus.

Activation of the ubiquitin proteasome pathway by silk fibroin modified chitosan nanoparticles in hepatic cancer cells.

Silk fibroin (SF) is a protein with bulky hydrophobic domains and can be easily purified as sericin-free silk-based biomaterial. Silk fibroin modified chitosan nanoparticle (SF-CSNP), a biocompatible material, has been widely used as a potential drug delivery system. Our current investigation studied the bio-effects of the SF-CSNP uptake by liver cells. In this experiment, the characterizations of SF-CSNPs were measured by particle size analysis and protein assay. The average size of the SF-CSNP was 311.9 ± 10.7 nm, and the average zeta potential was +13.33 ± 0.3 mV. The SF coating on the SF-CSNP was 6.27 ± 0.17 µg/mL. Moreover, using proteomic approaches, several proteins involved in the ubiquitin proteasome pathway were identified by analysis of differential protein expressions of HepG2 cell uptake the SF-CSNP. Our experimental results have demonstrated that the SF-CSNP may be involved in liver cancer cell survival and proliferation.

iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation.

BACKGROUND: Comprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle in mass spectrometry-based proteomic analysis. To provide a solution, an alternative analytic strategy to confidently identify phosphorylated peptides by using the alkaline phosphatase (AP) treatment combined with high-resolution mass spectrometry was provided. While the process is applicable, the key integration along the pipeline was mostly done by tedious manual work. RESULTS: We developed a software toolkit, iPhos, to facilitate and streamline the work-flow of AP-assisted phosphoproteome characterization. The iPhos tookit includes one assister and three modules. The iPhos Peak Extraction Assister automates the batch mode peak extraction for multiple liquid chromatography mass spectrometry (LC-MS) runs. iPhos Module-1 can process the peak lists extracted from the LC-MS analyses derived from the original and dephosphorylated samples to mine out potential phosphorylated peptide signals based on mass shift caused by the loss of some multiples of phosphate groups. And iPhos Module-2 provides customized inclusion lists with peak retention time windows for subsequent targeted LC-MS/MS experiments. Finally, iPhos Module-3 facilitates to link the peptide identifications from protein search engines to the quantification results from pattern-based label-free quantification tools. We further demonstrated the utility of the iPhos toolkit on the data of human metastatic lung cancer cells (CL1-5). CONCLUSIONS: In the comparison study of the control group of CL1-5 cell lysates and the treatment group of dasatinib-treated CL1-5 cell lysates, we demonstrated the applicability of the iPhos toolkit and reported the experimental results based on the iPhos-facilitated phosphoproteome investigation. And further, we also compared the strategy with pure DDA-based LC-MS/MS phosphoproteome investigation. The results of iPhos-facilitated targeted LC-MS/MS analysis convey more thorough and confident phosphopeptide identification than the results of pure DDA-based analysis.

Secretome analysis using a hollow fiber culture system for cancer biomarker discovery.

Secreted proteins, collectively referred to as the secretome, were suggested as valuable biomarkers in disease diagnosis and prognosis. However, some secreted proteins from cell cultures are difficult to detect because of their intrinsically low abundance; they are frequently masked by the released proteins from lysed cells and the substantial amounts of serum proteins used in culture medium. The hollow fiber culture (HFC) system is a commercially available system composed of small fibers sealed in a cartridge shell; cells grow on the outside of the fiber. Recently, because this system can help cells grow at a high density, it has been developed and applied in a novel analytical platform for cell secretome collection in cancer biomarker discovery. This article focuses on the advantages of the HFC system, including the effectiveness of the system for collection of secretomes, and reviews the process of cell secretome collection by the HFC system and proteomic approaches to discover cancer biomarkers. The HFC system not only provides a high-density three-dimensional (3D) cell culture system to mimic tumor growth conditions in vivo but can also accommodate numerous cells in a small volume, allowing secreted proteins to be accumulated and concentrated. In addition, cell lysis rates can be greatly reduced, decreasing the amount of contamination by abundant cytosolic proteins from lysed cells. Therefore, the HFC system is useful for preparing a wide range of proteins from cell secretomes and provides an effective method for collecting higher amounts of secreted proteins from cancer cells. This article is part of a Special Issue entitled: An Updated Secretome.

Secretomic analysis identifies alpha-1 antitrypsin (A1AT) as a required protein in cancer cell migration, invasion, and pericellular fibronectin assembly for facilitating lung colonization of lung adenocarcinoma cells.

Metastasis is a major obstacle that must be overcome for the successful treatment of lung cancer. Proteins secreted by cancer cells may facilitate the progression of metastasis, particularly within the phases of migration and invasion. To discover metastasis-promoting secretory proteins within cancer cells, we used the label-free quantitative proteomics approach and compared the secretomes from the lung adenocarcinoma cell lines CL1-0 and CL1-5, which exhibit low and high metastatic properties, respectively. By employing quantitative analyses, we identified 660 proteins, 68 of which were considered to be expressed at different levels between the two cell lines. High levels of A1AT were secreted by CL1-5, and the roles of A1AT in the influence of lung adenocarcinoma metastasis were investigated. Molecular and pathological confirmation demonstrated that altered expression of A1AT correlates with the metastatic potential of lung adenocarcinoma. The migration and invasion properties of CL1-5 cells were significantly diminished by reducing the expression and secretion of their A1AT proteins. Conversely, the migration and invasion properties of CL1-0 cells were significantly increased through the overexpression and secretion of A1AT proteins. Furthermore, the assembly levels of the metastasis-promoting pericellular fibronectin (FN1), which facilitates colonization of lung capillary endothelia by adhering to the cell surface receptor dipeptidyl peptidase IV (DPP IV), were higher on the surfaces of suspended CL1-5 cells than on those of the CL1-0 cells. This discovery reflects previous findings in breast cancer. In line with this finding, FN1 assembly and the lung colonization of suspended CL1-5 cells were inhibited when endogenous A1AT protein was knocked down using siRNA. The major thrust of this study is to demonstrate the effects of coupling the label-free proteomics strategy with the secretomes of cancer cells that differentially exhibit invasive and metastatic properties. This provides a new opportunity for the effective identification of metastasis-associated proteins that are secreted by cancer cells and promote experimental metastasis.

Deep eutectic solvents as sustainable extraction media for extraction of polysaccharides from natural sources: Status, challenges and prospects.

Deep eutectic solvents (DES) emerge as promising alternatives to conventional solvents, offering outstanding extraction capabilities, low toxicity, eco-friendliness, straightforward synthesis procedures, broad applicability, and impressive recyclability. DES are synthesized by combining two or more components through various synthesis procedures, such as heat-assisted mixing/stirring, grinding, freeze drying, and evaporation. Polysaccharides, as abundant natural materials, are highly valued for their biocompatibility, biodegradability, and sustainability. These versatile biopolymers can be derived from various natural sources such as plants, algae, animals, or microorganisms using diverse extraction techniques. This review explores the synthesis procedures of DES, their physicochemical properties, characterization analysis, and their application in polysaccharide extraction. The extraction optimization strategies, parameters affecting DES-based polysaccharide extraction, and separation mechanisms are comprehensively discussed. Additionally, this review provides insights into recently developed molecular guides for DES screening and the utilization of artificial neural networks for optimizing DES-based extraction processes. DES serve as excellent extraction media for polysaccharides from different sources, preserving their functional features. They are utilized both as extraction solvents and as supporting media to enhance the extraction abilities of other solvents. Continued research aims to improve DES-based extraction methods and achieve selective, energy-efficient processes to meet the demands of this expanding field.

Utilizing fish wastewater in aquaponic systems to enhance anti-inflammatory and antioxidant bioactive compounds in Sarcodia suae.

Aquaculture wastewater, rich in organic nutrients, is an essential environmental factor. When applied to seaweed cultivation systems, this wastewater holds the potential to notably increase the growth rate and carbon capture of Sarcodia suae. Sarcodia suae has the potential to be a healthy food due to its various biological activities; however, its chemical composition has yet to be completely defined. In this study, we applied a UHPLC-HRMS-based foodomics strategy to determine and classify possible bioactive metabolites in S. suae. From pooled seaweed samples (S. suae cultured in filtered running, FR, aquaponic recirculation, AR systems), we identified 179 and 146 compounds in POS and NEG modes, respectively. These compounds were then classified based on their structures using the Classyfire classification. Results show that S. suae in AR exhibited higher growth performance, and ten upregulated metabolites were determined. We also validated the anti-inflammatory and antioxidative bioactivities of some selected compounds. Our study provided important insights into the potential use of fish wastewater in aquaponic systems to profile and produce bioactive compounds in S. suae comprehensively. This has significant implications for the development of sustainable food and the promotion of environmental health.