Integrating MALDI-TOF Mass Spectrometry with Machine Learning Techniques for Rapid Antimicrobial Resistance Screening of Foodborne Bacterial Pathogens.

Although MALDI-TOF mass spectrometry (MS) is considered as the gold standard for rapid and cost-effective identification of microorganisms in routine laboratory practices, its capability for antimicrobial resistance (AMR) detection has received limited focus. Nevertheless, recent studies explored the predictive performance of MALDI-TOF MS for detecting AMR in clinical pathogens when machine learning techniques are applied. This chapter describes a routine MALDI-TOF MS workflow for the rapid screening of AMR in foodborne pathogens, with Campylobacter spp. as a study model.

Metabolomics analysis reveals a protective effect of hydroxycitric acid on calcium oxalate-induced kidney injury.

Objectives: Prior research has indicated that hydroxycitric acid (HCA) can impede the formation of calcium oxalate (CaOx) crystals, yet the specific mechanisms underlying its therapeutic effects remain unclear. In this study, we delved into the protective effects of HCA against glyoxylate-induced renal stones in rats and sought to elucidate the underlying metabolic pathways. Materials and Methods: Forty rats were randomly assigned to five groups: control group, model group, L-HCA-treated group, M-HCA-treated group, and H-HCA-treated group. Von Kossa staining was conducted on renal sections, and blood urea nitrogen and serum creatinine were determined by biochemical analysis. Meanwhile, body weight and urine volume were also measured. We subjected urine samples from the rats to analysis using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Next, we employed a metabolomic approach to scrutinize the metabolic profiles of each group. Results: HCA significantly reduced blood urea nitrogen and serum creatinine, and increased body weight and urine volume. It also reduced CaOx crystal deposition. A total of 24 metabolites, exhibiting a significant reversal pattern following HCA administration, were identified as urine biomarkers indicative of HCA's preventive effects against CaOx crystal-induced renal injury. These metabolites are primarily associated with glycine, serine, and threonine metabolism; phenylalanine metabolism; tricarboxylic acid cycle; taurine and hypotaurine metabolism; and tryptophan metabolism. Conclusion: It was demonstrated that HCA has a protective effect against CaOx crystal-induced kidney injury in rats by modulating various metabolic pathways. Additionally, results suggest that HCA holds promise as a potential clinical therapeutic drug for both the prevention and treatment of renal stones.

Anti-liver tumor ingredient exploration and validation of Elephantopus tomentosus Linn. by combining in silico and in vitro experiments.

Elephantopus tomentosus (ET) Linn. was reported to be an anti-tumor plant. However, the chemical composition of ET and its anti-tumor compounds and potential mechanisms still unclear. In this paper, UPLC-Q-TOF-MS/MS was firstly used to identified the ingredients in ET and UPLC was used to determine the main compounds of ET. Network pharmacology was applied to predict the potential mechanisms of anti-liver cancer. Anti-tumor nuclear activate compounds and targets of ET were obtained and the anti-liver cancer effect was validated on HepG2. Finally, Molecule docking, RT-qPCR, and western blotting were used for verification of the relationship between nuclear activate compounds and nuclear targets and the potential anti-cancer mechanisms. The result showed that 42 compounds were identified in ET, which consisted of sesquiterpene lactones, flavonoids, and phenylpropanoid compounds. Scabertopin (ST), chlorogenic acid, Isochlorogenic acid B, Isochlorogenic acid A and Isochlorogenic acid C were identified as main compounds and were determined as 0.426%, 0.457%, 0.159%, 0.701%, and 0.103% respectively. 24 compounds showed high pharmacokinetics and good drug-likeness. 520 overlapping targets of the ET compounds and liver cancer were collected. The targets were used for KEGG and GO analysis. GO enrichment analysis suggested that the targets of 24 active compound closed related to promote apoptosis, inhibit proliferation, and regulate oxidative levels. KEGG enrichment analysis suggested that pathway in cancer was enriched most and p38 MAPK/p53 signaling pathway, which closely related to promoting apoptosis and inhibiting proliferation. Compounds-targets analysis based on the parameter of Betweenness, Closeness, Information, Eigenvector, Degree, and component content indicated that ST was the nucleus anti-tumor active compound of ET. HepG2 was first used to validated the anti-tumor effect of ST and the result showed that ST significantly inhibited HepG2 proliferation with a low IC50 less than 5 µM. Nucleus active compound targets, including TP53, CASP3, BCL2, EGFR, TNF-a, IL-1ß, and IL-6 were enriched based on degree value of PPI analysis. Molecule docking suggested that ST showed a good combination to TGFBR1 with the combination energy less than - 5 kcal/mol. RT-qPCR result also suggested that ST significantly medicated the mRNA expression level of TP53, CASP3, BCL2, EGFR, TNF-a, IL-1ß, and IL-6. Protein expression of p-p38/p38 and p-p53/p53 notable increased by ST treatment. In conclude, combining with UPLC-Q-TOF-MS/MS qualitative analysis, UPLC quantitative analysis, network pharmacology analysis, molecule docking, and in vitro experiments on HepG2, we suggest that ST is an anti-tumor ingredient of ET, which may target to TGFBR1 and promote apoptosis and inhibited proliferation of HepG2 by activating p38 MAPK/p53 signaling pathway. ST can be regarded as a quality marker of ET.

Identification of N-linked glycans recognized by WGA in saliva from patients with non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-related deaths. Saliva diagnosis is an essential approach for clinical applications owing to its noninvasive and material-rich features. The purpose of this study was to investigate differences in wheat germ agglutinin (WGA)-based recognition of salivary protein N-linked glycan profiles to distinguish non-small cell lung cancer (NSCLC) patients from controls. We used WGA-magnetic particle conjugates to isolate glycoproteins in the pooled saliva of healthy volunteers (HV, n = 35), patients with benign pulmonary disease (BPD, n = 35), lung adenocarcinoma (ADC, n = 35), and squamous cell carcinoma (SCC, n = 35), following to release the N-linked glycans from the isolated proteins with PNGase F, and further identified and annotated the released glycans by MALDI-TOF/TOF-MS, respectively. The results showed that 34, 35, 39, and 44 N-glycans recognized by WGA were identified and annotated from pooled saliva samples of HV, BPD, ADC, and SCC, respectively. Furthermore, the proportion of N-glycans recognized by WGA in BPD (81.2 %), ADC (90.1 %), and SCC (88.7 %), increased compared to HV (71.9 %). Two N-glycan peaks (m/z 2286.799, and 3399.211) specifically recognized by WGA were present only in NSCLC. These findings suggest that altered salivary glycopatterns such as sialic acids and GlcNAc containing N-glycans recognized by WGA might serve as potential personalized biomarkers for the diagnosis of NSCLC patients.

Evidence for the occurrence of Acinetobacter faecalis in cattle feces and its emended description.

This study provides an emended description of Acinetobacter faecalis, a species previously described based on a single isolate (YIM 103518T) from elephant feces in China. Our emended description is based on 15 novel isolates conspecific with the A. faecalis type strain, obtained from eight cattle farms in the Czech Republic. The A. faecalis strains have relatively small genomes (≈2.5-2.7 Mbp), with a GC content of 36.3-36.7 mol%. Core genome-based phylogenetic analysis showed that the 15 strains, together with the type strain of A. faecalis, form a distinct and internally coherent phylogroup within the genus. Pairwise genomic ANIb values for the 16 A. faecalis strains were 97.32-99.04 %, while ANIb values between the genomes of the 16 strains and those of the other Acinetobacter spp. were ≤ 86.2 %. Analysis of whole-cell MALDI-TOF mass spectra supported the distinctness and cohesiveness of the taxon. The A. faecalis strains could be differentiated from the other validly named Acinetobacter spp. by the absence of hemolytic activity along with their ability to grow at 37 °C and on L-aspartate, ethanol, and L-glutamate but not at 41 °C or on adipate or 2,3-butanediol. Reduced susceptibility to sulfamethoxazole, trimethoprim and/or streptomycin was shown in eight strains, along with the presence of corresponding antibiotic resistance genes. In conclusion, this study provides a comprehensive description of A. faecalis and demonstrates its occurrence in cattle feces. Though the ecological role of A. faecalis remains unknown, our results show its ability to acquire antibiotic resistance genes, likely as an adaptation to antibiotic selection pressure in livestock farms.

Accurate prediction of antimicrobial resistance and genetic marker of Staphylococcus aureus clinical isolates using MALDI-TOF MS and machine learning - Across DRIAMS and Taiwan database.

BACKGROUND: The use of matrix-assisted laser desorption/ionization-time-of-flight mass spectra (MALDI-TOF MS) with machine learning (ML) has been explored for predicting antimicrobial resistance. This study evaluates the effectiveness of MALDI-TOF MS paired with various ML classifiers and establishes optimal models for predicting antimicrobial resistance and mecA gene existence among Staphylococcus aureus. MATERIALS AND METHODS: The antimicrobial resistance against tier 1 antibiotics and MALDI-TOF MS of S. aureus were analyzed using data from the Database of Resistance against Antimicrobials with MALDI-TOF Mass Spectrometry (DRIAMS) and one medical center (CS database). Five ML classifiers were used to analyze performance metrics. The Shapley value quantified the predictive contribution of individual feature. RESULTS: The LightGBM demonstrated superior performance in predicting antimicrobial resistance for most tier 1 antibiotics among oxacillin-resistant S. aureus (ORSA) than all and oxacillin-susceptible S. aureus (OSSA) in both databases. In DRIAMS, MLP encompassed excellent predictive performance, expressed as accuracy/AUROC/AUPR, for clindamycin (0.74/0.81/0.90), tetracycline (0.86/0.87/0.94), and trimethoprim-sulfamethoxazole (0.95/0.72/0.97). In CS database, Ada and LightGBM retained excellent performance for erythromycin (0.97/0.92/0.86) and tetracycline (0.68/0.79/0.86), respectively. Mass-to-charge ratio (m/z) features of 2,411-2,414 and 2,429-2,432 correlated with clindamycin resistance, while 5,033-5,036 was linked to erythromycin resistance in DRIAMS. In CS database, overlapping features of 2,423-2,426, 4,496-4,499, and 3,764-3,767 simultaneously predicted mecA existence and oxacillin resistance. CONCLUSION: The predictive performance of antimicrobial resistance against S. aureus using MALDI-TOF MS depends on database characteristics and ML algorithm selected. Specific and overlapping MS features are excellent predictive markers for mecA and specific antimicrobial resistance.

The therapeutic effect of Yinqiaosan decoction against influenza A virus infection by regulating T cell receptor signaling pathway.

Background: Yinqiaosan decoction (YQSD), a traditional Chinese medicinal recipe, has been employed to treat influenza in China for approximately 300 years. Objective: Our study aimed to explore the mechanisms of YQSD against influenza via in vivo and in vitro experimental studies. Study design: and methods UHPLC-Q-TOF-MS/MS was utilized to examine the substances of the YQSD. The chemical components of YQSD detected by UHPLC-Q-TOF-MS/MS were used for network pharmacology analysis. The antiviral effect of YQSD in vivo was investigated. The potential mechanisms of YQSD in combating influenza, which were predicted from network pharmacology analysis, were validated in vitro. Results: By use of UHPLC-Q-TOF-MS/MS, 97 compounds were identified from YQSD. Network pharmacology analysis revealed that the therapeutic effect of YQSD against influenza may be associated with the regulation of T cell receptors (TCR) and Phosphoinositide 3-Kinase (PI3K)- protein kinase B (Akt) signaling pathways. Treatment with YQSD significantly prolonged the mean survival time of the mice and reduced lung injury due to the influenza A virus in vivo. It was discovered that YQSD efficiently inhibited the expression of inflammation-related cytokines. Moreover, YQSD has been found to significantly reduce the expression levels of cluster of differentiation 3 (CD3), monocyte chemoattractant protein-1 (MCP-1), and H1N1 virus nucleoprotein (NP), and prevent the decrease of epithelial cadherin (E-cadherin) protein. In addition, YQSD can inhibit the phosphorylation of the zeta chain of T cell receptor-associated protein kinase 70 (ZAP70) and PI3K proteins in vitro. Conclusion: The capacity of YQSD to suppress viral multiplication and inflammatory response by modulating T cell immunity may explain its effect against influenza viral pneumonia, which may involve the regulation of TCR and PI3K signaling pathways.

ENOVAT: the European Network for Optimization of Veterinary Antimicrobial Treatment.

The global antimicrobial resistance crisis has been the driver of several international strategies on antimicrobial stewardship. For their implementation on field level, the veterinary sector encounters several specific challenges and in particular: (i) a shortage of experts in key disciplines related to antimicrobial stewardship, (ii) a lack of evidence-based antimicrobial treatment guidelines, and (iii) inferior diagnostic tests available compared to human medicine. The present white paper describes how the COST Action ENOVAT (the European Network for Optimization of Veterinary Antimicrobial Treatment, CA18217), comprising 332 persons from 51 countries, worked towards solutions to these challenges. Initially, surveys were conducted to explore the present state in Europe in terms of existing antimicrobial use guidelines and microbiology practices performed. Concurrently, various research activities were launched to optimize diagnostics, including development of epidemiological cut-offs, clinical breakpoints and matrix-assisted laser desorption ionization time of flight mass spectrometry interpretive criteria. Also, guidelines drafting groups working towards evidence-based antimicrobial treatment guidelines for six conditions in food-producing and companion animals were established. The processes and outcomes, also in terms of capacity building, are summarized in this white paper where emphasis is placed on sustainability of the activities. Although several ENOVAT initiatives and spin-off projects will continue beyond the Action, we recommend that a new European veterinary research agenda is launched focusing on research and funding leading to long-term impacts on veterinary antimicrobial use.

Antimicrobial resistance is an urgent global public health threat that is amplified by over- and misuse of antimicrobials. As a result of antimicrobial resistance, antibiotics and other antimicrobial medicines become ineffective and infections become difficult or impossible to treat. This goes for human infections, but also for infections in animals. In a recently finished European project called ENOVAT we tried to tackle the problem of antimicrobial resistance in animals. We focused on two topics. First we optimized and harmonized diagnostics of bacterial infections in the laboratory, and second we developed evidence-based treatment guidelines to support veterinary practitioners on how and when to use antibiotics in the best way. Improved diagnostics and new treatment guidelines can help veterinary practitioners to a more sensible antibiotic choice and with that less over- and misuse of antimicrobials. This article summarizes the process and progress of the work done in the ENOVAT project. Emphasis is also put on how the project benefitted from a unique consortium encompassing 332 professionals with diverse backgrounds, from 51 countries.

Uptake and translocation of nanoplastics in mono and dicot vegetables.

The excessive production and use of plastics increase the release of micro- and nanoplastics (MNPs) into the environment. In recent years, research has focused on the occurrence of MNPs in air, soil and water. Nevertheless, there is still a lack of knowledge regarding MNPs in plants. To determine the load, translocation of MNPs and their effects on metabolism, pak choi, tomato, radish and asparagus have been exposed with fluorescent-labelled poly(methyl methacrylate) or polystyrene (PS) MNPs. The entry of nanoparticles (NPs) of various sizes (100-500 nm) and surface modifications (unmodified, COOH or NH2) into plants has been demonstrated using confocal laser scanning microscopy (CLSM). The translocalization from root to shoot and the accumulation of NP in the intercellular spaces were regardless of the surface modification. In addition, metabolomics was used to evaluate metabolic changes induced by MNPs in pak choi. Changes in phenolic compounds, phytohormone derivatives and other classes of compounds known to be triggered by various environmental stresses have been identified. The present study demonstrates the uptake and translocalization of MNPs in edible parts of vegetables and may pose a hazard for humans.

Diversity in gut microbiota among colorectal cancer patients: findings from a case-control study conducted at a Tunisian University Hospital.

PURPOSE: Globally, colorectal cancer (CRC) is among the most prevalent cancers. One distinctive feature of colorectal cancer is its close relationship to the gut microbiota, which is a crucial component of the tumor microenvironment. Over the last ten years, research has demonstrated that colorectal cancer is accompanied with dysbiosis of gut bacteria, fungi, viruses, and Archaea, and that these alterations may be causal. OBJECTIVES: This study aimed to evaluate the disruption of the microorganism composition in the intestine, especially bacteria and to determine their relationship with colorectal cancer. METHODS: An evaluation system for determining colorectal cancer (CRC) risk and prognosis can be established more easily with the help of accurate gut microbiota profiling. Stool samples from 14 CRC patients and 13 controls were collected and the flora relative abundance was measured using targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers: Streptococcus gallolyticus and Enterococcus faecalis. Culture and MALDI-TOF mass spectrometry were coupled to identify the gut microbiota in both colorectal cancer and control groups. RESULTS: Compared with controls, the gut microbiota of CRC patients showed an increase in the abundance of Enterococcus, Fusobacterium and Streptococcus. At the species level, the CRC enriched bacterium including Escherichia coli, Enterococcus faecalis, Fusobacterium nucleatum, Streptococcus gallolyticus, Flavoni fractorplautii and Eggerthella lenta acted as promising biomarkers for early detection of CRC. CONCLUSION: This study highlights the potential of gut microbiota biomarkers as a promising non-invasive tool for the accurate detection and distinction of individuals with CRC.

Comparison of Zybio Kit and saponin in-house method in rapid identification of bacteria from positive blood cultures by EXS2600 matrix-assisted laser desorption ionization time-of-flight mass spectrometry system.

We evaluated the performance of Zybio EXS2600 matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) (Zybio Inc., Chongqing, China) for the identification of bacteria from positive blood culture (BC) bottles using Blood Culture Positive Sample Pretreatment Kit (Zybio Inc., Chongqing, China) in comparison to an in-house saponin method. Following a positive signal by the BACTEC™ FX system, confirmation of identification was achieved using subcultured growing biomass used for MALDI-TOF MS analysis. A total of 94 positive BC bottles with 97 bacterial isolates were analyzed. The overall identification rates at the genus and species levels for the saponin method were 89.7% (87/97) and 74.2% (72/97), respectively. With the Zybio Kit, 88.7% (86/97) and 80.4% (78/97) of microorganisms were correctly identified to the genus and species levels, respectively. The saponin method identified 65.3% (32/49) of Gram-positive bacteria at the species level, whereas the Zybio Kit achieved a higher species-level identification rate of 79.6% (39/49) (p = 0.1153). The saponin method with additional on-plate formic acid extraction showed a significantly higher overall identification rate in comparison to the saponin method without that step for both genus (87.6% [85/97] vs. 70.1% [68/97], p = 0.0029) and species level (70.1% [68/97] vs. 46.4% [45/97], p = 0.0008). Identification rates of Gram-negative bacteria showed a higher identification rate, however, not statistically significant with additional Zybio Kit protocol step on both genus (85.4% [41/48] vs. 81.3% [39/48], p = 0.5858) and species level (77.1% [37/48] vs. 75% [36/48], p = 0.8120). Zybio Kit could offer an advantage in species-level identification, particularly for Gram-positive bacteria. The inclusion of on-plate formic acid extraction in the saponin method notably enhanced identification at both genus and species levels for Gram-positive bacteria. The extended protocol provided by the Zybio Kit could potentially offer an advantage in the identification of Gram-negative bacteria at both genus and species levels. Enhancements to the Zybio EXS2600 MALDI-TOF instrument software database are necessary.

Exploring chemical markers and identifying phenolic markers using a metabolomics strategy and chemometrics to study the different origins of defatted Coix seed.

Coix seed, a prevalent medicinal and food-homologous plant, is extensively consumed in Asia. It has various pharmacological properties, such as anti-inflammatory and anticancer effects. Coix seed oil, as its main component, is widely produced. However, during the industrial production process of Coix seed oil, substantial byproducts are produced, namely, defatted Coix seeds, which are also worth researching. Currently, it remains unclear whether there will be differences in defatted Coix seeds obtained from different geographical locations, with previous studies reporting that phenolic compounds in defatted Coix seeds have a significant utilization value. In this study, firstly, the TPC and TFC of samples collected in three temperature zones were detected. Subsequently, UPLC-Q-TOF/MS was used to analyze the samples, and a metabolomics data processing strategy and chemometric analysis method were established. We have confirmed the presence of flavonoids and phenolic compounds in 30 batches of Coix seed from different temperature zones in China, and concluded that the overall quality of Coix seed from different batches is relatively stable. With the established strategy, 12 characteristic chemical markers were identified, and 5 valuable phenolic chemical markers were selected for distinguishing the origin of Coix seed and evaluating the quality of defatted Coix seed. Among them, proanthocyanidin A2 has the highest content in defatted Coix seed in subtropical regions, while the content of caffeic acid, naringin, rutin, and chlorogenic acid decreases from north to south. The strategy proposed in this study may provide some basis for the quality control and rational use of defatted Coix seeds.

Artificial intelligence decision making tools in food metabolomics: Data fusion unravels synergies within the hazelnut (Corylus avellana L.) metabolome and improves quality prediction.

This study investigates the metabolome of high-quality hazelnuts (Corylus avellana L.) by applying untargeted and targeted metabolome profiling techniques to predict industrial quality. Utilizing comprehensive two-dimensional gas chromatography and liquid chromatography coupled with high-resolution mass spectrometry, the research characterizes the non-volatile (primary and specialized metabolites) and volatile metabolomes. Data fusion techniques, including low-level (LLDF) and mid-level (MLDF), are applied to enhance classification performance. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) reveal that geographical origin and postharvest practices significantly impact the specialized metabolome, while storage conditions and duration influence the volatilome. The study demonstrates that MLDF approaches, particularly supervised MLDF, outperform single-fraction analyses in predictive accuracy. Key findings include the identification of metabolites patterns causally correlated to hazelnut's quality attributes, of them aldehydes, alcohols, terpenes, and phenolic compounds as most informative. The integration of multiple analytical platforms and data fusion methods shows promise in refining quality assessments and optimizing storage and processing conditions for the food industry.

Insight into the compositional variation of volatile and polar compounds of Radix Bupleuri from different processing technologies by GC-MS and UHPLC-Q-TOF/MS metabolomics.

INTRODUCTION: Insight into comparing key active ingredients of Radix Bupleuri (RB) based on different processing technologies is a key step to reveal the material basis of drug efficacy and a challenging task for developing traditional Chinese medicine (TCM). OBJECTIVE: This work aims to establish a comprehensive comparative analysis method of TCM and its processed products, which can be used to analyze the changing trend of active components of RB before and after processing. METHODS: First, RB was processed with rice vinegar, rice wine, and honey. Then, ultra-high-performance liquid chromatography (UHPLC) and gas chromatography (GC) coupled with mass spectrometry (MS) technology as well as multiple statistical analyses were used to comprehensively evaluate the compositional variation of polar and volatile compounds in RB under different processing processes. Meanwhile, in UHPLC-MS, a sequential window acquisition of all theoretical fragment ion spectral and information-dependent acquisition mutual authentication (SIMA) was developed. RESULTS: A total of 30 polar components and 33 volatile components were identified as chemical markers (mainly type II saikosaponins, terpenes, and fatty acid esters). These may be the material basis for giving unique pharmacological activities to RB and its processed products. CONCLUSIONS: These findings provided a solid foundation for the differentiated clinical application of RB, and the SIMA method held great potential for achieving accurate analysis of TCM processing ingredients.

Feature-based molecular networking and MS2LDA analysis for the dereplication of adjacent bis-tetrahydrofuran Annonaceous acetogenins.

INTRODUCTION: Annonaceous acetogenins are a group of natural polyketide compounds possessing notable cytotoxic and antitumor properties. Mass spectrometry (MS) techniques can be used for the structural determination of these compounds, including the location of functional groups along the long alkyl chain. OBJECTIVE: This study aims to develop a convenient liquid chromatography (LC)-MS-based method for the dereplication of acetogenins in plant extracts using a molecular networking approach. METHODOLOGY: The LC-electrospray ionization (ESI)-MS/MS spectra of pure adjacent bis-tetrahydrofuran (THF) acetogenins isolated from Uvaria rufa (Annonaceae) were acquired, along with those of the crude ethyl acetate and hexanes fractions of the plant extract, followed by dereplication and molecular networking analysis using the Global Natural Products Social Molecular Networking (GNPS) platform. RESULTS: A high level of fragmentation of the protonated molecules [M + H]+ was observed at collision energies of 37.5 and 25.0 eV. The application of feature-based molecular networking (FBMN) allowed for distinguishing diastereoisomers based on different retention times in the reversed-phase high-performance liquid chromatography method. The acetogenin possessing one or more additional OH groups on the methyl-terminal chain side of the OH-flanked bis-THF ring unit were grouped separately from those lacking such substructure. Furthermore, the MS2LDA analysis revealed shared Mass2Motifs among acetogenins, confirming the structural relations within the molecular network. CONCLUSIONS: The ESI-MS/MS-based molecular networking method provided an effective strategy for the dereplication of acetogenins in plant extracts. It is anticipated that this molecular networking approach could be extended to other types of acetogenins to facilitate rapid identification of this class of compounds.

Performance of MALDI-TOF MS, real-time PCR, antigen detection, and automated biochemical testing for the identification of Burkholderia pseudomallei.

Burkholderia pseudomallei is the causative agent of melioidosis, a disease highly endemic to Southeast Asia and northern Australia, though the area of endemicity is expanding. Cases may occur in returning travelers or, rarely, from imported contaminated products. Identification of B. pseudomallei is challenging for laboratories that do not see this organism frequently, and misidentifications by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and automated biochemical testing have been reported. The in vitro diagnostic database for use with the Vitek MS has recently been updated to include B. pseudomallei and we aimed to validate the performance for identification in comparison to automated biochemical testing with the Vitek 2 GN card, quantitative real-time polymerase chain reaction (qPCR) targeting the type III secretion system, and capsular polysaccharide antigen detection using a lateral flow immunoassay (LFA). We tested a "derivation" cohort including geographically diverse B. pseudomallei and a range of closely related Burkholderia species, and a prospective "validation" cohort of B. pseudomallei and B. cepacia complex clinical isolates. MALDI-TOF MS had a sensitivity of 1.0 and specificity of 1.0 for the identification and differentiation of B. pseudomallei from related Burkholderia species when a certainty cutoff of 99.9% was used. In contrast, automated biochemical testing for B. pseudomallei identification had a sensitivity of 0.83 and specificity of 0.88. Both qPCR and LFA correctly identified all B. pseudomallei isolates with no false positives. Due to the high level of accuracy, we have now incorporated MALDI-TOF MS into our laboratory's B. pseudomallei identification workflow.IMPORTANCEBurkholderia pseudomallei causes melioidosis, a disease associated with high morbidity and mortality that disproportionately affects rural areas in Southeast Asia and northern Australia. The known area of endemicity is expanding and now includes the continental United States. Laboratory identification can be challenging which may result in missed or delayed diagnoses and poor patient outcomes. In this study, we compared mass spectrometry using an updated spectral database with multiple other methods for B. pseudomallei identification and found mass spectrometry highly accurate. We have therefore incorporated this fast and cost-effective method into our laboratory's workflow for B. pseudomallei identification.

Based on UPLC-Q-TOF/MS and Network Pharmacology to Explore the Mechanism of Qingre Lishi Decoction in the Treatment of Psoriasis.

Background: Psoriasis is an immune-mediated chronic inflammatory disease. Qingre Lishi Decoction (QRLSD) has achieved great clinical effect in the treatment of psoriasis. However, the potential bioactive components and the mechanisms are yet unclear. Aim: To analyze the serum parameters of rats fed with QRLSD, screen out the active components of QRLSD, and explore the potential targets and pathway of QRLSD in the treatment of psoriasis. Materials and Methods: The active components of serum containing QRLSD were analyzed using ultra-high performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS). The targets of QRLSD in the treatment of psoriasis were predicted by network pharmacology and molecular docking. In vitro experiments verified the underlying mechanism. Results: By UPLC-Q-TOF/MS, 15 prototype components and 22 metabolites were identified in serum containing QRLSD. Subsequently, 260 chemical composition targets and 218 psoriasis targets were overlapped to obtain 23 intersection targets, including LGALS3, TNF, F10, DPP4, EGFR, MAPK14, STAT3 and others. TNF, IL-10, GAPDH, STAT3, EGFR, ITGB1, LGALS3 genes were identified as potential drug targets in the PPI network analyzed by CytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that QRLSD may improve psoriasis by regulating immune and inflammatory pathways, the cytokine mediated signal transduction pathways and other signaling pathways. Molecular docking results showed that the main active components of the serum containing QRLSD had higher affinities for TNF and LGALS3. In vitro experiments confirmed that QRLSD may decrease levels of inflammatory cytokines by suppressing the NF-κB signaling pathway activated by TNF-α in human keratinocytes. Conclusion: This study explores the potential compounds, targets and signaling pathways of QRLSD in the treatment of psoriasis, which will help clarify the efficacy and mechanism of QRLSD.

Metabolic profiling of triptophenolide in rat plasma, urine, bile and faeces after intragastric administration.

Triptophenolide, a major diterpenoid extracted from Tripterygium wilfordii Hook. f., has been reported to possess significant anti-tumour, anti-androgen and anti-inflammatory activities. However, the metabolic fate of triptophenolide remains unknown. Therefore, this study focused on the metabolic profiling of triptophenolide in rat plasma, urine, bile and faeces following intragastric administration. An ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry with combination of extracted ion chromatogram strategy based on 71 typical metabolic reactions was established to comprehensively profile the metabolites of triptophenolide. This strategy allowed for the identification of 17 metabolites from the biosamples. Reduction, oxidation, glucuronide conjugation, and hydroxylation were considered as its main metabolic pathways in vivo. The present study will be greatly helpful for the further pharmacological studies on triptophenolide and would provide valuable information for its clinical application.

Integration of MALDI-TOF MS and machine learning to classify enterococci: A comparative analysis of supervised learning algorithms for species prediction.

This research focused on distinguishing distinct matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) spectral signatures of three Enterococcus species. We evaluated and compared the predictive performance of four supervised machine learning algorithms, K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), to accurately classify Enterococcus species. This study involved a comprehensive dataset of 410 strains, generating 1640 individual spectra through on-plate and off-plate protein extraction methods. Although the commercial database correctly identified 76.9% of the strains, machine learning classifiers demonstrated superior performance (accuracy 0.991). In the RF model, top informative peaks played a significant role in the classification. Whole-genome sequencing showed that the most informative peaks are biomarkers connected to proteins, which are essential for understanding bacterial classification and evolution. The integration of MALDI-TOF MS and machine learning provides a rapid and accurate method for identifying Enterococcus species, improving healthcare and food safety.