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.

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.

Host heterogeneity in humoral bactericidal activity can be complement independent.

Background: Humoral bactericidal activity was first recognized nearly a century ago. However, the extent of inter-individual heterogeneity and the mechanisms underlying such heterogeneity beyond antibody or complement systems have not been well studied. Methods: The plasma bactericidal activity of five healthy volunteers were tested against 30 strains of Gram-negative uropathogens, Klebsiella pneumoniae and Escherichia coli, associated with bloodstream infections. IgG and IgM titers specific to K. pneumoniae strains KP13883 and KPB1 were measured by ELISA, and complement inhibitor was used to measure the contribution of complement-induced killing. Furthermore, MALDI-TOF mass spectrometry was conducted to determine the metabolomic components of plasma with bactericidal properties in 25 healthy individuals using Bayesian inference of Pearson correlation between peak intensity and colony counts of surviving bacteria. Results: Plasma bactericidal activity varied widely between individuals against various bacterial strains. While individual plasma with higher IgM titers specific to K. pneumoniae strain KP13883 showed more efficient killing of the strain, both IgM and IgG titers for K. pneumoniae strain KPB1 did not correlate well with the killing activity. Complement inhibition assays elucidated that the complement-mediated killing was not responsible for the inter-individual heterogeneity in either isolate. Subsequently, using MALDI-TOF mass spectrometry on plasmas of 25 healthy individuals, we identified several small molecules including gangliosides, pediocins, or saponins as candidates that showed negative correlation between peak intensities and colony forming units of the test bacteria. Conclusion: This is the first study to demonstrate the inter-individual heterogeneity of constitutive innate humoral bactericidal function quantitatively and that the heterogeneity can be independent of antibody or the complement system.

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.

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.

Development of a rapid mass spectrometric method for the analysis of ten-eleven translocation enzymes.

In DNA, methylation at the fifth position of cytosine (5mC) by DNA methyltransferases is essential for eukaryotic gene regulation. Methylation patterns are dynamically controlled by epigenetic machinery. Erasure of 5mC by Fe2+ and 2-ketoglutarate (2KG) dependent dioxygenases in the ten-eleven translocation family (TET1-3), plays a key role in nuclear processes. Through the event of active demethylation, TET proteins iteratively oxidize 5mC to 5-hydroxymethyl cytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxycytosine (5caC), each of which has been implicated in numerous diseases when aberrantly generated. A wide range of biochemical assays have been developed to characterize TET activity, many of which require multi-step processing to detect and quantify the 5mC oxidized products. Herein, we describe the development and optimization of a sensitive MALDI mass spectrometry-based technique that directly measures TET activity and eliminates tedious processing steps. Employing optimized assay conditions, we report the steady-state activity of wild type TET2 enzymes to furnish 5hmC, 5fC and 5caC. We next determine IC50 values of several small-molecule inhibitors of TETs. The utility of this assay is further demonstrated by analyzing the activity of V1395A which is an activating mutant of TET2 that primarily generates 5caC. Lastly, we describe the development of a secondary assay that utilizes bisulfite chemistry to further examine the activity of wildtype TET2 and V1395A in a base-resolution manner. The combined results demonstrate that the activity of TET proteins can be gauged, and their products accurately quantified using our methods.

Application of MALDI-TOF mass spectrometry for identification of Nocardia species.

BACKGROUND: Nocardiosis, despite its rarity and underreporting, is significant due to its severe impact, characterized by high morbidity and mortality rates. The development of a precise, reliable, rapid, and straightforward technique for identifying the pathogenic agent in clinical specimens is crucial to reduce fatality rates and facilitate timely antimicrobial treatment. In this study, we aimed to identify Nocardia spp. in clinical isolates, using MALDI-TOF MS as the primary method, with molecular methods as the gold standard. Clinical Nocardia isolates were identified using 16S rRNA/hsp65/gyrB/secA1/rpoB gene sequencing. Identification performance of the Bruker MALDI Biotyper 3.1 (V09.0.0.0_8468) and MBT Compass 4.1 (V11.0.0.0_10833) for Nocardia identification was evaluated. RESULTS: Seventy-six Nocardia isolates were classified into 12 species through gene sequencing. The MALDI Biotyper 3.1 (V09.0.0.0_8468) achieved 100% genus-level accuracy and 84.2% species accuracy (64/76). The MBT Compass 4.1 with the BDAL Database (V11.0.0.0_10833) improved species identification to 98.7% (75/76). The updated database enhanced species level identification with scores > 1.7, increasing from 77.6% (59/76) to 94.7% (72/76), a significant improvement (P = 0.001). The new and simplified extraction increased the proportion of strains identified to the species level with scores > 1.7 from 62.0% (18/29) to 86.2% (25/29) (P = 0.016). An in-house library construction ensured accurate species identification for all isolates. CONCLUSIONS: The Bruker mass spectrometer can accurately identify Nocardia species, albeit with some variations observed between different database versions. The MALDI Biotyper 3.1 (V09.0.0.0_8468) has limitations in identifying Nocardia brasiliensis, with some strains only identifiable to the genus level. MBT Compass 4.1 (V11.0.0.0_10833) effectively addresses this shortfall, improving species identification accuracy to 98.7%, and offering quick and reliable identification of Nocardia. Both database versions incorrectly identified the clinically less common Nocardia sputorum as Nocardia araoensis. For laboratories that have not upgraded their databases and are unable to achieve satisfactory identification results for Nocardia, employing the new and simplified extraction method can provide a degree of improvement in identification outcomes.

[Rapid serotyping of Salmonella based on matrix assisted laser desorption ionization-time of flight mass spectrometry].

Objective: To establish a matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) assay for the identification of common Salmonella serotypes and provide etiology evidence for the early precise treatment of salmonellosis. Methods: A total of 500 strains were collected from different regions and sources and five predominant Salmonella serotypes (Salmonella Typhi, Salmonella Paratyphi A, Salmonella Typhimurium, Salmonella Enteritidis, and Salmonella Indiana) of each strain was identified by agglutination test and whole-genome sequencing. The protein complex of the strains was extracted by using optimized pretreatment method to establish the fingerprint database of peptides for each Salmonella serotype. The new serotyping assays were established by using different modules based on the mass spectra database. Additional 155 strains with specified serotypes and variant sources were used to test and evaluate the accuracy of the new typing assays. Results: Five MALDI-TOF MS databases were established, and two new serotyping assays were established via peptide fingerprint mapping/matching and machine learning of the neuronal convolutional network respectively based on the databases. The results showed that the fingerprint matching approach could quickly identify five common Salmonella serotypes in clinical practice compared with the machine learning method, the accuracy of fingerprint matching assay to identify five Salmonella serotypes reached 100.00% and the serotyping can be conducted within a short time (15-20 minutes) and had a good reproducibility, while the machine learning method could not completely identify these serotypes. Moreover the sensitivity and specificity of fingerprint matching assay were all 100.00% respectively, while they were only 82.23% and 95.81% for machine learning method. Conclusion: The established Salmonella serotyping assay based on MALDI-TOF MS in this study can easily, rapidly and accurately identify different serotypes of Salmonella.

Validation of short culture method for rapid bacterial identification of blood cultures via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

BACKGROUND: Development of rapid bacterial identification from blood cultures has been an area of intense study in diagnostic microbiology. Shortened turnaround time coupled with antimicrobial stewardship interventions have been shown to improve patient outcomes and decrease healthcare-associated costs. OBJECTIVES: We report the validation of a short incubation method for Gram-positive and Gram-negative bacterial identification utilizing MALDI-TOF MS without additional instrumentation, processing or cost compared with current practice. METHODS: Prospective, observational, single-centre study in a quaternary care academic hospital encompassing 376 blood cultures subjected to bacterial identification after short incubation periods of 3-4 and 6-8 h. RESULTS: There was 97.5% species-level identification agreement with tests undertaken after 3-4 h incubation with 83.6% isolates identified, and 99.7% species-level identification agreement after 6-8 h incubation with 96.7% isolates identified. CONCLUSIONS: The short incubation method provides a rapid MALDI-TOF MS bacterial identification method, reducing turnaround time by 10-18 h compared with standard practice without additional cost, processing or instrumentation.

Evolving strategies in microbe identification-a comprehensive review of biochemical, MALDI-TOF MS and molecular testing methods.

Detection and identification of microorganisms are the first steps to guide susceptibility testing and enable clinicians to confirm diseases and guide therapy. The faster the pathogen identification is determined, the quicker the appropriate treatment can be started. In the clinical microbiology laboratory, multiple methodologies can be used to identify organisms, such as traditional biochemical testing or more recent methods like MALDI TOF MS and nucleic acid detection/identification assays. Each of these techniques has advantages and limitations, and clinical laboratories need to determine which methodology is best suited to their particular setting in terms of clinical needs, availability of technical expertise and cost. This article presents a concise review of the history, utilization, advantages and limitations of the main methods used for identifying microorganisms in microbiology laboratories.

Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae.

BACKGROUND: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes. METHODS: Out of 107,721 bacterial samples, 675 specimens of KP with suspected multi-drug resistance were selected. These specimens were collected from a tertiary hospital and four secondary hospitals between 2022 and 2023 to evaluate CZA resistance. We used MALDI-TOF MS and machine learning to develop an AI-CDSS with enhanced speed of resistance detection. RESULTS: Machine learning models, especially light gradient boosting machines (LGBM), exhibited an area under the curve (AUC) of 0.95, indicating high accuracy. The predictive models formed the core of our newly developed AI-CDSS, enabling clinical decisions quicker than traditional methods using culture and antibiotic susceptibility testing by a day. CONCLUSIONS: The study confirms that MALDI-TOF MS, integrated with machine learning, can swiftly detect CZA resistance. Incorporating this insight into an AI-CDSS could transform clinical workflows, giving healthcare professionals immediate, crucial insights for shaping treatment plans. This approach promises to be a template for future anti-resistance strategies, emphasizing the vital importance of advanced diagnostics in enhancing public health outcomes.

Contribution of machine learning for subspecies identification from Mycobacterium abscessus with MALDI-TOF MS in solid and liquid media.

Mycobacterium abscessus (MABS) displays differential subspecies susceptibility to macrolides. Thus, identifying MABS's subspecies (M. abscessus, M. bolletii and M. massiliense) is a clinical necessity for guiding treatment decisions. We aimed to assess the potential of Machine Learning (ML)-based classifiers coupled to Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) MS to identify MABS subspecies. Two spectral databases were created by using 40 confirmed MABS strains. Spectra were obtained by using MALDI-TOF MS from strains cultivated on solid (Columbia Blood Agar, CBA) or liquid (MGIT®) media for 1 to 13 days. Each database was divided into a dataset for ML-based pipeline development and a dataset to assess the performance. An in-house programme was developed to identify discriminant peaks specific to each subspecies. The peak-based approach successfully distinguished M. massiliense from the other subspecies for strains grown on CBA. The ML approach achieved 100% accuracy for subspecies identification on CBA, falling to 77.5% on MGIT®. This study validates the usefulness of ML, in particular the Random Forest algorithm, to discriminate MABS subspecies by MALDI-TOF MS. However, identification in MGIT®, a medium largely used in mycobacteriology laboratories, is not yet reliable and should be a development priority.

A case of human diarrhea caused by Gallibacterium anatis: a case report.

Gallibacterium anatis (G. anatis) is an opportunistic pathogen previously associated with deaths in poultry and is also a pathogen that rarely causes human diseases. G. anatis has only been reported twice as the causative agent of a human disease (both in France). Here, we report a 62-year-old male patient with hypertension and type 2 diabetes who suffered from acute watery diarrhea caused by this bacterium which was identified by MALDI-TOF MS and 16 S rRNA sequencing. Despite human diarrhea caused by G.anatis is rare, with the continuous emergence of multidrug-resistant isolates of G. anatis in recent years, this case report will inform clinicians that G. anatis especially drug-resistant G. anatis may be a possible infectious source of human diarrhea in immune-suppressed populations.

Absolute Quantification of Glutathione Using Top-Hat Optics for IR-MALDESI Mass Spectrometry Imaging.

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) uses an infrared laser to desorb neutral biomolecules with postionization via ESI at atmospheric pressure. The Gaussian profile of the laser with conventional optics results in the heating of adjacent nonablated tissue due to the energy profile being circular. A diffractive optical element (DOE) was incorporated into the optical train to correct for this disadvantage. The DOE produces a top-hat beam profile and square ablation spots, which have uniform energy distributions. Although beneficial to mass spectrometry imaging (MSI), it is unknown how the DOE affects the ability to perform quantitative MSI (qMSI). In this work, we evaluate the performance of the DOE optical train against our conventional optics to define the potential advantages of the top-hat beam profile. Absolute quantification of glutathione (GSH) was achieved by normalizing the analyte of interest to homoglutathione (hGSH), spotting a dilution series of stable isotope labeled glutathione (SIL-GSH), and analyzing by IR-MALDESI MSI with either the conventional optical train or with the DOE incorporated. Statistical comparison indicates that there was no significant difference between the quantification of GSH by the two optical trains as evidenced by similar calibration curves. Results support that both optical trains can be used for qMSI without a change in the ability to carry out absolute quantification but providing the benefits of the top-hat optical train (i.e., flat energy profile and square ablation spots)-for future qMSI studies.

Comparing NGS-Based identification of bloodstream infections to traditional culture methods for enhanced ICU care: a comprehensive study.

Background: Accurate identification of infectious diseases using molecular techniques, such as PCR and NGS, is well-established. This study aims to assess the utility of Bactfast and Fungifast in diagnosing bloodstream infections in ICU settings, comparing them against traditional culture methods. The objectives include evaluating sensitivity and specificity and identifying a wide range of pathogens, including non-culturable species. Methods: We collected 500 non-duplicate blood samples from ICU patients between January 2023 and December 2023. Specimens underwent traditional culture, MALDI-TOF, VITEK®2 compact system, and NGS-based Bactfast and Fungifast analyses. Results: Out of the 500 samples, 26.8% (n=134) showed bacterial growth via traditional culture methods, while 4.8% (n=24) were positive for fungal growth. MALDI-TOF and VITEK®2 compact system yielded comparable results, identifying 26.4% (n=132) of specimens with bacterial growth. NGS-based Bactfast detected bacterial presence in 38.2% (n=191) of samples, including non-culturable bacteria missed by traditional methods. However, NGS-based Fungifast showed concordant fungal detection rates with culture methods. Among identified pathogens by culture method included Klebsiella pneumoniae 20.89% (n=28), Enterococcus faecalis 18.65% (n=25), Escherichia coli 15.67% (n=21), Pseudomonas aeruginosa 12.68% (n=17), Acinetobacter baumannii 10.44% (n=14), various Streptococcus species 7.46% (n=10), Mycobacterium tuberculosis 6.71% (n=9), Mycobacterium abscessus 4.47% (n=6), and Salmonella spp 2.98% (n=4). Non-culture-based NGS identified additional (n=33) pathogens, including Klebsiella pneumoniae 27.27% (n=9), Bacteroides fragilis 21.21% (n=7), Aerococcus viridans 15.15% (n=5), Elizabethkingia anopheles 12.12% (n=4), Aeromonas salmonicida 9% (n=3), Clostridium 9% (n=3), and Bacteroides vulgatus 6% (n=2). Candida albicans was reported in 5% (n=24) of samples by both methods. Conclusion: NGS-based Bactfast and Fungifast demonstrate high sensitivity in identifying a wide array of bacterial and fungal pathogens in ICU patients, outperforming traditional culture methods in detecting non-culturable organisms. These molecular assays offer rapid and comprehensive diagnostic capabilities, potentially improving clinical outcomes through timely and accurate pathogen identification.

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.

Label-free assessment of complement-dependent cytotoxicity of therapeutic antibodies via a whole-cell MALDI mass spectrometry bioassay.

Potency assessment of monoclonal antibodies or corresponding biosimilars in cell-based assays is an essential prerequisite in biopharmaceutical research and development. However, cellular bioassays are still subject to limitations in sample throughput, speed, and often need costly reagents or labels as they are based on an indirect readout by luminescence or fluorescence. In contrast, whole-cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass Spectrometry (MS) has emerged as a direct, fast and label-free technology for functional drug screening being able to unravel the molecular complexity of cellular response to pharmaceutical reagents. However, this approach has not yet been used for cellular testing of biologicals. In this study, we have conceived, developed and benchmarked a label-free MALDI-MS based cell bioassay workflow for the functional assessment of complement-dependent cytotoxicity (CDC) of Rituximab antibody. By computational evaluation of response profiles followed by subsequent m/z feature annotation via fragmentation analysis and trapped ion mobility MS, we identified adenosine triphosphate and glutathione as readily MS-assessable metabolite markers for CDC and demonstrate that robust concentration-response characteristics can be obtained by MALDI-TOF MS. Statistical assay performance indicators suggest that whole-cell MALDI-TOF MS could complement the toolbox for functional cellular testing of biopharmaceuticals.

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.

Study on interaction with high-abundant blood proteins and identification of low-abundant proteins to 5-phenyl-1-(p-tolyl)-1 H-1,2,3-triazole by serum proteomics.

In this study, a comprehensive investigation was undertaken to elucidate a simple triazole compound, 5-phenyl-1-(p-tolyl)-1 H-1,2,3-triazole (PPTT), its interactions with high-abundant proteins and identification of low-abundant proteins by serum proteomics. Employing a combination of spectroscopic techniques and computational chemistry, the interactions between PPTT and three high-abundance blood globular proteins, namely human serum albumin (HSA), human immunoglobulin G (HIgG), and hemoglobin (BHb), were explored, thereby ascertaining their binding constants and thermodynamic parameters at the molecular level. Subsequently, based on the differential proteomics, utilizing two-dimensional gel electrophoresis (2-DE) in conjunction with matrix-assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF-MS), the research team isolated and identified differentially expressed low-abundance proteins in human blood serum samples following exposure to PPTT. The results showed that there were twenty highly expressed proteins identified from blood serum samples intervened by PPTT. Combining bioinformatics techniques, these proteins were classified, providing preliminary insights like preproprotein or precursors inhibiting the activity of elastase, defending and regulating the immune system, carrying lipid, and other functions into their biological functionalities. One of the differential proteins, apolipoprotein A-1 (ApoA-1) protein, was selected as a possible target to explore the mechanism of action of PPTT intervention on the related signaling pathways involved in human hepatocellular carcinomas(Hep G2) cells. These research findings offer scientifically sound guidance for further in-depth exploration, development, and application of the 1,2,3-triazole compound.