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.

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.

MALDI versus DESI mass spectrometry imaging of lipids in atherosclerotic plaque.

Mass spectrometry imaging (MSI) is a powerful tool for detecting lipids in tissue sections, with matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) as its key ionization techniques. In this study, we examine how MALDI compares with state-of-the-art DESI ionization in identifying lipids in heterogeneous samples, specifically atherosclerotic plaques. Carotid plaques (n = 4) from patients undergoing endarterectomy were snap-frozen, stored at -80°C, and then sectioned for MSI analysis and H&E staining. Measurements were conducted using a SYNAPT XS mass spectrometer in positive ion mode, employing MALDI with a 2,5-dihydroxybenzoic acid (DHB) matrix and DESI with a methanol: water (98:2) (v/v) solvent. Our comparison covered spectral profiles, sensitivity, and image quality generated by these two techniques. We found that both MALDI and DESI are highly suitable techniques for detecting a wide range of lipids in atherosclerotic plaque sections. DESI-MSI exhibited higher ion counts for most lipid classes than MALDI-MSI and provided sharper images. MALDI detected larger amounts of ceramide and hexosylceramide species, possibly due to its efficient generation of dehydrated ions. In contrast, DESI showed greater peak intensities of cholesteryl ester and triacylglyceride species than MALDI, consistent with reduced fragmentation. These findings establish the relative merits of DESI and MALDI and demonstrate their complementarity as techniques for lipid research in MSI.

A tunable LDI-MS platform assisted by metal-phenolic network-coated AuNPs for sensitive and customized detection of amino acids.

This study introduces a novel approach for the sensitive and accurate detection of small molecule metabolites, employing metal-phenolic network (MPN) functionalized AuNPs as both adsorbent and matrix to enhance laser desorption/ionization mass spectrometry (LDI-MS) performance. The MPN comprising tannic acid (TA) and transition metal ions (Fe3+, Co2+, Ni2+, Cu2+, or Zn2+) was coated on the surface of AuNPs, forming metal-TA network-coated AuNPs (M-TA@AuNPs). The M-TA@AuNPs provided a tunable surface for specific interactions with analytes, displaying distinct enrichment efficacies for different amino acids, especially for Cu-TA@AuNPs exhibiting the highest affinity for histidine (His). Under the optimized condition, the proposed method enabled ultrasensitive detection of His, with good linearity (R2 = 0.9627) in the low-concentration range (50 nM-1 µM) and a limit of detection (LOD) as low as 0.9 nM. Furthermore, the method was successfully applied to detect His from human urine samples, showcasing its practical applications in clinical diagnostics, particularly in the realm of amino acid-based targeted metabolomics.

Molecular Imaging of Human Brain Organoids Using Mass Spectrometry.

Brain organoid models serve as a powerful tool for studying human brain development and function. Mass spectrometry imaging (MSI), a cutting-edge technology, allows us to map the spatial distribution of diverse molecules such as lipids, sugars, amino acids, drugs, and their metabolites within these organoids, all without the need for specific molecular probes. High-quality MSI data hinge on meticulous sample preparation. Fixatives play a pivotal role, but conventional options such as glutaraldehyde, paraformaldehyde, and cryopreserving such as sucrose may inadvertently impact tissue metabolites. Optimal fixation entails flash freezing in liquid nitrogen. However, for small organoids, a more suitable approach involves transitioning the organoids directly from the incubator into a warmed embedding solution, followed by freezing in dry ice-cooled ethanol. Another critical step is the embedding prior to cryosectioning, which also requires materials compatible with MSI, as traditional options can interfere with matrix deposition and ionization. Here, an optimized protocol for high resolution-MALDI-MSI of human brain organoids is presented, encompassing sample preparation, sectioning, and imaging using mass spectrometry. This method showcases the molecular distribution of small metabolites, such as amino acids, with high mass accuracy and sensitivity. As such, coupled with complementary studies of brain organoids, it can assist in illuminating complex processes governing early brain development, metabolic cell fate trajectories, and distinctive metabolite signatures. Furthermore, it provides insights into the precise locations of molecules within the organoid, enriching our understanding of the spatial organization of 3D brain organoid models. As the field continues to advance, a growing number of studies leveraging MSI to delve into brain organoids and complex biological systems is anticipated, thereby deepening the understanding of the metabolic aspects of human brain function and development.

Determination of nut varieties and their detection in festive cookies by MALDI-TOF mass spectrometry.

RATIONALE: Nuts contain a large amount of essential fatty acids, amino acids, and whole range of minerals and vitamins valuable for human health, yet certain risks are associated with their consumption, of which allergic reaction is the most important. Considering the growing number of people suffering from allergies caused by allergens of protein origin, the aim of this work is to find out whether nuts can be distinguished from each other on the basis of contained proteins. METHODS: A total of eleven raw and subsequently heat-treated nuts (almonds, Brazil nuts, cashews, coconuts, hazelnuts, macadamia nuts, peanuts, pecans, pine nuts, pistachios, and walnuts) were analyzed using MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry with the subsequent finding of characteristic m/z values for each analyzed nut. No previous method for protein extraction was used. RESULTS: The characteristic values were used to verify the composition of seven types of festive cookies - six commercial products and one "unknown" cookie, where it was not known in advance, which nut it was made from. CONCLUSIONS: The procedure, together with the found characteristic m/z values, could serve to rapidly identify the plant origin of nut products.

Facile fabrication of the immuno-MALDI-MS chip for the enrichment of abused drug in human urine integrated with MALDI-MS analysis.

BACKGROUND: Drug abuse can result in both physical and mental health issues for individuals, and can also contribute to broader societal problems. The number of drug abuse cases rose to 296 million in 2021. The sample pretreatment methods commonly employed typically require longer processing times and occasionally necessitate derivatization. Furthermore, with the increase in sample sizes, traditional chromatography-mass spectrometry methods for analyzing abused drugs were no longer sufficient to handle such numerous samples. In this study, immuno-MALDI-MS chip were fabricated for specific enrichment of illicit drugs, integrating with the rapid and accurate capabilities of MALDI-MS for high-throughput analysis of drug abuse. RESULTS: The immuno-MALDI-MS chip was successfully prepared by coating an aluminum chip with antibody-conjugated boronic acid-modified gold nanoparticles. Ketamine, a frequently abused illicit drug, served as the proof of concept for this study. The immuno-MALDI-MS chip was employed to selectively enrich ketamine in human urine samples, facilitating direct MALDI-MS analysis with the addition of α-CHCA matrix solution. The challenge of detecting abused drugs, exacerbated by interfering peaks in the low m/z region from salts and small molecules in human urine samples, was successfully overcome. The developed method exhibited a wide linear range of 10-5000 ng/mL with a limit of detection of 3.3 ng/mL for ketamine. Notably, the proposed method enabled high-throughput screening and accurate confirmation of ketamine concentrations in suspects' urine samples within few minutes, requiring a minimal sample volume of 1 µL. The obtained data were in complete agreement with the previous GC/MS analysis. SIGNIFICANCE: A straightforward, cost-effective and sensitive method for the selective enrichment and absolute quantification of abused drugs was developed using a homemade immuno-MALDI-MS chip integrated with MALDI-MS analysis. This method combines the advantages of immunoassay and mass spectrometry, offering both speed and accuracy. The reported method for the quantification of ketamine in human urine offers a practical approach and has the potential to analyze emerging new psychoactive substances in the future.

2-Nitro-4-Carboxyphenylhydrazine and 2,4-Dicarboxylphenylhydrazine as a Pair of Novel Reactive MALDI Matrices for Rapid and Accurate Profiling of N-Glycome in Dual Ion Modes.

N-glycosylation is closely linked to a wide range of biological functions in organisms. Owing to the constriction of awful crystals formed by conventional MALDI matrices and the extremely inferior ionization efficiency of N-glycans, the traditional direct detection of N-glycans by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has been gradually replaced by postderivatization detection using reactive matrices. Nevertheless, the laborious identification of complex spectral peaks remains the major difficulty in N-glycan profiling. Hence, we logically designed and synthesized two novel reactive matrices, 2-nitro-4-carboxylphenylhydrazine (NCPH) and 2,4-dicarboxylphenylhydrazine (DCPH), and separately combined them with the acidic matrix 2,5-dihydroxybenzoic acid (DHB) to constitute two composite matrices with high on-target derivatization efficiency and significant promotion of N-glycan ionization for productive MALDI analysis in dual ion modes. Using both composite matrices, we can actualize MALDI-MS and MS2 mass calibration in dual ion modes by postderivatization detection and fragmentation of dextrans and selectively enhance the ionization effect of oligosaccharides in mixed systems. Quite homogeneous cocrystals can ensure N-glycan quantification with decent linearity and reproducibility. A fixed mass difference derived from the identical N-glycan in two ion modes is available for rapid identification in complex biological samples. Ultimately, the developed strategy was triumphantly employed to identify and quantify the relative content and alteration tendency of peach N-glycans, which can be referable to the latent correlation between N-glycan expression and peach ripening.

Antifungal Susceptibility Testing and Cluster Analysis of Candida auris Strains.

BACKGROUND: Candida auris is an opportunistic pathogen that has become widespread in recent years and shows resistance to multiple drugs. The aim of our study was to determine the antifungal susceptibilities of C. auris isolates, to perform a dendrogram from the mass spectra of strains obtained from matrix-assisted laser desorption ionization-time of flight mass spectrometry in order to evaluate the proteomic similarities of the strains and determine the geographical clade of C. auris strains in this study by the help of Multiplex RT-PCR. METHODS: The samples yielded 58 C. auris isolates. MALDI TOF MS (BioMerieux, France) was used for identification of the isolates and Sensititre Yeast One (Thermoscientific) system was used for antifungal susceptibility testing. Dendrograms of strain's spectra were generated by using the RUO/Saramis (BioMerieux, France) database and evaluated through hierarchical clustering analysis. The selected nine strains were examined at the clade level by using Multiplex RT-PCR. Results The susceptibility profile of the strains revealed resistance to Fluconazole in 84% (MICs ≥ 32) and resistance to Amphotericin B in 60% (MIC ≥ 2). All strains were found to be sensitive to Anidulafungin and Micafungin. The dendrogram of the main spectra of C. auris isolates showed a similarity range of 35 - 100%. The nine strains studied were identified as clade 1 (South Asian). CONCLUSIONS: It was determined that C. auris strains were members of geographical clade 1, and the Amphotericin B resistance was found to be higher than expected. This situation poses a threat to critically ill patients.

A New Activity Assay Method for Diamine Oxidase Based on Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

Copper-containing diamine oxidases are ubiquitous enzymes that participate in many important biological processes. These processes include the regulation of cell growth and division, programmed cell death, and responses to environmental stressors. Natural substrates include, for example, putrescine, spermidine, and histamine. Enzymatic activity is typically assayed using spectrophotometric, electrochemical, or fluorometric methods. The aim of this study was to develop a method for measuring activity using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry based on the intensity ratio of product to product-plus-substrate signals in the reaction mixtures. For this purpose, an enzyme purified to homogeneity from pea (Pisum sativum) seedlings was used. The method employed α-cyano-4-hydroxycinnamic acid as a matrix with the addition of cetrimonium bromide. Product signal intensities with pure compounds were evaluated in the presence of equal substrate amounts to determine intensity correction factors for data processing calculations. The kinetic parameters kcat and Km for the oxidative deamination of selected substrates were determined. These results were compared to parallel measurements using an established spectrophotometric method, which involved a coupled reaction of horseradish peroxidase and guaiacol, and were discussed in the context of data from the literature and the BRENDA database. It was found that the method provides accurate results that are well comparable with parallel spectrophotometry. This method offers advantages such as low sample consumption, rapid serial measurements, and potential applicability in assays where colored substances interfere with spectrophotometry.

Thermal Denaturation of Fresh Frozen Tissue Enhances Mass Spectrometry Detection of Peptides.

Thermal denaturation (TD), known as antigen retrieval, heats tissue samples in a buffered solution to expose protein epitopes. Thermal denaturation of formalin-fixed paraffin-embedded samples enhances on-tissue tryptic digestion, increasing peptide detection using matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS). We investigated the tissue-dependent effects of TD on peptide MALDI IMS and liquid chromatography-tandem mass spectrometry signal in unfixed, frozen human colon, ovary, and pancreas tissue. In a triplicate experiment using time-of-flight, orbitrap, and Fourier-transform ion cyclotron resonance mass spectrometry platforms, we found that TD had a tissue-dependent effect on peptide signal, resulting in a (22.5%) improvement in peptide detection from the colon, a (73.3%) improvement in ovary tissue, and a (96.6%) improvement in pancreas tissue. Biochemical analysis of identified peptides shows that TD facilitates identification of hydrophobic peptides.

Lack of Candida africana in Ugandan pregnant women: results from a pilot study using MALDI-ToF.

BACKGROUND: Candida africana is an emergent variant that has been listed as a new species or variety within the Candida albicans complex since 2001. It has a worldwide intra-albicans complex pooled prevalence of 1.67% and varies between 0 and 8% depending on geographical region. We present the results of a pilot study on its prevalence in Uganda. METHODOLOGY: We conducted a cross-sectional study between March and June 2023. We recruited 4 pregnant women from Mulago Specialized Women and Neonatal Hospital, 102 from Kawempe National Referral Hospital, and 48 from Sebbi Hospital. Vaginal swabs were tested using microscopy, culture and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF). RESULTS: The prevalence of C. africana was zero. Out of the 103 isolates, the majority (81.553%) were identified as Candida albicans, followed by Nakeseomyces glabrata (13.592%) and Pichia kudriavzevii (1.942%). Cyberlindnera jadinii, Candida tropicalis, and Candida parapsilosis each accounted for 0.971% of the isolates. CONCLUSION: The prevalence of C. africana in Uganda is zero. However, large-scale cross-sectional studies, including studies involving the collection of vaginal samples from both urban and rural settings in Uganda and the use of both MALDI-TOF- and PCR-based laboratory methods, are needed to fully describe the public health burden of C. africana infections.

An investigation of scattered light integrating collector technology for rapid blood culture sensitivity testing.

Introduction. Sepsis rates are increasing, with Gram-negative organisms representing a large proportion of bloodstream infections. Rapid antibiotic administration, alongside diagnostic investigations, is required for the effective management of these patients.Gap statement. Current diagnostics take ~48 h for a final report; therefore, rapid diagnostics are required.Aim. This study investigated a novel antibiotic sensitivity method, the scattered light integrating collector (SLIC), combined with a rapid identification method using matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) technology to determine if an accurate identification and susceptibility result can be provided within 4 h of a positive blood culture report.Methodology. A total of 47 blood cultures containing Gram-negative bacteria from 46 patients were processed using the MALDI-TOF Biotyper Sepsityper for identification directly from the blood and the SLIC instrument for susceptibility testing. All organisms were also tested using the current standard workflow used in the host laboratory. Categorical agreement (CA), major errors (MaEs) and very major errors (VMEs) were determined.Results. SLIC produced susceptibility results with a 71.9% CA, 30.6% MaE and 17.5% VME. The median difference in time to the final result was 44.14 (43 : 05-45 : 15) h earlier compared to the current method.Conclusion. We conclude that SLIC was unable to consistently provide sufficiently accurate antibiotic susceptibility results compared to the current standard method.

Repurposing MALDI-TOF MS for effective antibiotic resistance screening in Staphylococcus epidermidis using machine learning.

The emergence of Staphylococcus epidermidis as a significant nosocomial pathogen necessitates advancements in more efficient antimicrobial resistance profiling. However, existing culture-based and PCR-based antimicrobial susceptibility testing methods are far too slow or costly. This study combines machine learning with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to develop predictive models for various antibiotics using a comprehensive dataset containing thousands of S. epidermidis isolates. Optimized machine learning models utilized feature selection and achieved high AUROC scores ranging from 0.80 to 0.95 while maintaining AUPRC scores up to 0.97. Shapley Additive exPlanations were employed to analyze relevant features and assess the significance of corresponding protein biomarkers while also verifying that predictive power was derived from the detection of proteins rather than noise. Antimicrobial resistance models were validated externally to evaluate model performance outside the original data collection site. The approaches and findings in this study demonstrate a significant advancement in rapid, cost-effective antimicrobial resistance profiling, offering a promising solution for improving treatments for nosocomial infections and being potentially applicable to other microbial pathogens in the future.

A new fusion strategy for rapid strain differentiation based on MALDI-TOF MS and Raman spectra.

Typing of bacterial subspecies is urgently needed for the diagnosis and efficient treatment during disease outbreaks. Physicochemical spectroscopy can provide a rapid analysis but its identification accuracy is still far from satisfactory. Herein, a novel feature-extractor-based fusion-assisted machine learning strategy has been developed for high accuracy and rapid strain differentiation using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and Raman spectroscopy. Based on this fusion approach, rapid and reliable identification and analysis can be performed within 24 hours. Validation on a panel of important pathogens comprising Staphylococcus aureus, Klebsiella pneumoniae, Escherichia coli, and Acinetobacter baumannii showed that the identification accuracies of k-nearest neighbors (KNNs), support vector machines (SVMs) and artificial neural networks (ANNs) were 100%. In particular, when benchmarked against a MALDI-TOF MS spectral dataset, the new approach improved the identification accuracy of Acinetobacter baumannii from 87.67% to 100%. This work demonstrates the effectiveness of combining MALDI-TOF MS and Raman spectroscopy fusion data in pathogenic bacterial subtyping.

A novel barcoded nanopore sequencing workflow of high-quality, full-length bacterial 16S amplicons for taxonomic annotation of bacterial isolates and complex microbial communities.

Due to recent improvements, Nanopore sequencing has become a promising method for experiments relying on amplicon sequencing. We describe a flexible workflow to generate and annotate high-quality, full-length 16S rDNA amplicons. We evaluated it for two applications, namely, (i) identification of bacterial isolates and (ii) species-level profiling of microbial communities. We assessed the identification of single bacterial isolates by sequencing, using a set of barcoded full-length 16S rRNA gene primer pairs (pair A), on 47 isolates encompassing multiple genera and compared those results with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based identification. Species-level community profiling was tested with two sets of barcoded full-length 16S primer pairs (A and B) and compared to the results obtained with shotgun Illumina sequencing using 27 stool samples. We developed a Nextflow pipeline to retain high-quality reads and taxonomically annotate them. We found high agreement between our workflow and MALDI-TOF data for isolate identification (positive predictive value = 0.90, Cramér's V = 0.857, and Theil's U = 0.316). For species-level community profiling, we found strong correlations (rs > 0.6) of alpha diversity indices between the two primer sets and Illumina sequencing. At the community level, we found significant but small differences when comparing sequencing techniques. Finally, we found a moderate to strong correlation when comparing the relative abundances of individual species (average rs = 0.6 and 0.533 for primers A and B). Despite identified shortcomings, the proposed workflow enabled accurate identification of single bacterial isolates and prominent features in microbial communities, making it a worthwhile alternative to MALDI-TOF MS and Illumina sequencing.IMPORTANCEA quick, robust, simple, and cost-effective method to identify bacterial isolates and communities in each sample is indispensable in the fields of microbiology and infection biology. Recent technological advances in Oxford Nanopore Technologies sequencing make this technique an attractive option considering the adaptability, portability, and cost-effectiveness of the platform, even with small sequencing batches. Here, we validated a flexible workflow to identify bacterial isolates and characterize bacterial communities using the Oxford Nanopore Technologies sequencing platform combined with the most recent v14 chemistry kits. For bacterial isolates, we compared our nanopore-based approach to matrix-assisted laser desorption ionization-time of flight mass spectrometry-based identification. For species-level profiling of complex bacterial communities, we compared our nanopore-based approach to Illumina shotgun sequencing. For reproducibility purposes, we wrapped the code used to process the sequencing data into a ready-to-use and self-contained Nextflow pipeline.

Aligning Post-Column ESI-MS, MALDI-MS, and Coagulation Bioassay Data of Naja spp., Ophiophagus hannah, and Pseudonaja textillis Venoms Chromatographically to Assess MALDI-MS and ESI-MS Complementarity with Correlation of Bioactive Toxins to Mass Spectrometric Data.

Snakebite is a serious health issue in tropical and subtropical areas of the world and results in various pathologies, such as hemotoxicity, neurotoxicity, and local swelling, blistering, and tissue necrosis around the bite site. These pathologies may ultimately lead to permanent morbidity and may even be fatal. Understanding the chemical and biological properties of individual snake venom toxins is of great importance when developing a newer generation of safer and more effective snakebite treatments. Two main approaches to ionizing toxins prior to mass spectrometry (MS) analysis are electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). In the present study, we investigated the use of both ESI-MS and MALDI-MS as complementary techniques for toxin characterization in venom research. We applied nanofractionation analytics to separate crude elapid venoms using reversed-phase liquid chromatography (RPLC) and high-resolution fractionation of the eluting toxins into 384-well plates, followed by online LC-ESI-MS measurements. To acquire clear comparisons between the two ionization approaches, offline MALDI-MS measurements were performed on the nanofractionated toxins. For comparison to the LC-ESI-MS data, we created so-called MALDI-MS chromatograms of each toxin. We also applied plasma coagulation assaying on 384-well plates with nanofractionated toxins to demonstrate parallel biochemical profiling within the workflow. The plotting of post-column acquired MALDI-MS data as so-called plotted MALDI-MS chromatograms to directly align the MALDI-MS data with ESI-MS extracted ion chromatograms allows the efficient correlation of intact mass toxin results from the two MS-based soft ionization approaches with coagulation bioassay chromatograms. This facilitates the efficient correlation of chromatographic bioassay peaks with the MS data. The correlated toxin masses from ESI-MS and/or MALDI-MS were all around 6-8 or 13-14 kDa, with one mass around 20 kDa. Between 24 and 67% of the toxins were observed with good intensity from both ionization methods, depending on the venom analyzed. All Naja venoms analyzed presented anticoagulation activity, whereas pro-coagulation was only observed for the Pseudonaja textillis venom. The data of MALDI-MS can provide complementary identification and characterization power for toxin research on elapid venoms next to ESI-MS.

Metabolite Profiling of Hydroponic Lettuce Roots Affected by Nutrient Solution Flow: Insights from Comprehensive Analysis Using Widely Targeted Metabolomics and MALDI Mass Spectrometry Imaging Approaches.

Root morphology, an important determinant of nutrient absorption and plant growth, can adapt to various growth environments to promote survival. Solution flow under hydroponic conditions provides a mechanical stimulus, triggering adaptive biological responses, including altered root morphology and enhanced root growth and surface area to facilitate nutrient absorption. To clarify these mechanisms, we applied untargeted metabolomics technology, detecting 1737 substances in lettuce root samples under different flow rates, including 17 common differential metabolites. The abscisic acid metabolic pathway product dihydrophaseic acid and the amino and nucleotide sugar metabolism factor N-acetyl-d-mannosamine suggest that nutrient solution flow rate affects root organic acid and sugar metabolism to regulate root growth. Spatial metabolomics analysis of the most stressed root bases revealed significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways: "biosynthesis of cofactors" and "amino sugar and nucleotide sugar metabolism". Colocalization analysis of pathway metabolites revealed a flow-dependent spatial distribution, with higher flavin mononucleotide, adenosine-5'-diphosphate, hydrogenobyrinic acid, and D-glucosamine 6-phosphate under flow conditions, the latter two showing downstream-side enrichment. In contrast, phosphoenolpyruvate, 1-phospho-alpha-D-galacturonic acid, 3-hydroxyanthranilic acid, and N-acetyl-D-galactosamine were more abundant under no-flow conditions, with the latter two concentrated on the upstream side. As metabolite distribution is associated with function, observing their spatial distribution in the basal roots will provide a more comprehensive understanding of how metabolites influence plant morphology and response to environmental changes than what is currently available in the literature.

Slot Blot- and Electrospray Ionization-Mass Spectrometry/Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry-Based Novel Analysis Methods for the Identification and Quantification of Advanced Glycation End-Products in the Urine.

Proteins, saccharides, and low molecular organic compounds in the blood, urine, and saliva could potentially serve as biomarkers for diseases related to diet, lifestyle, and the use of illegal drugs. Lifestyle-related diseases (LSRDs) such as diabetes mellitus (DM), non-alcoholic steatohepatitis, cardiovascular disease, hypertension, kidney disease, and osteoporosis could develop into life-threatening conditions. Therefore, there is an urgent need to develop biomarkers for their early diagnosis. Advanced glycation end-products (AGEs) are associated with LSRDs and may induce/promote LSRDs. The presence of AGEs in body fluids could represent a biomarker of LSRDs. Urine samples could potentially be used for detecting AGEs, as urine collection is convenient and non-invasive. However, the detection and identification of AGE-modified proteins in the urine could be challenging, as their concentrations in the urine might be extremely low. To address this issue, we propose a new analytical approach. This strategy employs a method previously introduced by us, which combines slot blotting, our unique lysis buffer named Takata's lysis buffer, and a polyvinylidene difluoride membrane, in conjunction with electrospray ionization-mass spectrometry (ESI)/matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). This novel strategy could be used to detect AGE-modified proteins, AGE-modified peptides, and free-type AGEs in urine samples.