Multimodal MALDI imaging mass spectrometry for improved diagnosis of melanoma.

Imaging mass spectrometry (IMS) provides promising avenues to augment histopathological investigation with rich spatio-molecular information. We have previously developed a classification model to differentiate melanoma from nevi lesions based on IMS protein data, a task that is challenging solely by histopathologic evaluation. Most IMS-focused studies collect microscopy in tandem with IMS data, but this microscopy data is generally omitted in downstream data analysis. Microscopy, nevertheless, forms the basis for traditional histopathology and thus contains invaluable morphological information. In this work, we developed a multimodal classification pipeline that uses deep learning, in the form of a pre-trained artificial neural network, to extract the meaningful morphological features from histopathological images, and combine it with the IMS data. To test whether this deep learning-based classification strategy can improve on our previous results in classification of melanocytic neoplasia, we utilized MALDI IMS data with collected serial H&E stained sections for 331 patients, and compared this multimodal classification pipeline to classifiers using either exclusively microscopy or IMS data. The multimodal pipeline achieved the best performance, with ROC-AUCs of 0.968 vs. 0.938 vs. 0.931 for the multimodal, unimodal microscopy and unimodal IMS pipelines respectively. Due to the use of a pre-trained network to perform the morphological feature extraction, this pipeline does not require any training on large amounts of microscopy data. As such, this framework can be readily applied to improve classification performance in other experimental settings where microscopy data is acquired in tandem with IMS experiments.

Potential of MALDI-TOF MS biotyping to detect deltamethrin resistance in the dengue vector Aedes aegypti.

Insecticide resistance in mosquitoes is spreading worldwide and represents a growing threat to vector control. Insecticide resistance is caused by different mechanisms including higher metabolic detoxication, target-site modification, reduced penetration and behavioral changes that are not easily detectable with simple diagnostic methods. Indeed, most molecular resistance diagnostic tools are costly and labor intensive and then difficult to use for routine monitoring of insecticide resistance. The present study aims to determine whether mosquito susceptibility status against the pyrethroid insecticides (mostly used for mosquito control) could be established by the protein signatures of legs and/or thoraxes submitted to MALDI-TOF Mass Spectrometry (MS). The quality of MS spectra for both body parts was controlled to avoid any bias due to unconformity protein profiling. The comparison of MS profiles from three inbreeds Ae. aegypti lines from French Guiana (IRF, IR03, IR13), with distinct deltamethrin resistance genotype / phenotype and the susceptible reference laboratory line BORA (French Polynesia), showed different protein signatures. On both body parts, the analysis of whole protein profiles revealed a singularity of BORA line compared to the three inbreeding lines from French Guiana origin, suggesting that the first criteria of differentiation is the geographical origin and/or the breeding history rather than the insecticide susceptibility profile. However, a deeper analysis of the protein profiles allowed to identify 10 and 11 discriminating peaks from leg and thorax spectra, respectively. Among them, a specific peak around 4870 Da was detected in legs and thoraxes of pyrethroid resistant lines compared to the susceptible counterparts hence suggesting that MS profiling may be promising to rapidly distinguish resistant and susceptible phenotypes. Further work is needed to confirm the nature of this peak as a deltamethrin resistant marker and to validate the routine use of MS profiling to track insecticide resistance in Ae. aegypti field populations.

Predicting the age of field Anopheles mosquitoes using mass spectrometry and deep learning.

Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control strategies targeting mosquito longevity, as the risk of pathogen transmission increases with mosquito age. However, the available tools to estimate field mosquito age are often approximate and time-consuming. Here, we show a rapid method that combines matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry with deep learning for mosquito age prediction. Using 2763 mass spectra from the head, legs, and thorax of 251 field-collected Anopheles arabiensis mosquitoes, we developed deep learning models that achieved a best mean absolute error of 1.74 days. We also demonstrate consistent performance at two ecological sites in Senegal, supported by age-related protein changes. Our approach is promising for malaria control and the field of vector biology, benefiting other disease vectors like Aedes mosquitoes.

A Case of Bacteremia Caused by Raoultella planticola Direct Identification from Blood Culture by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

Background: Raoultella planticola is an uncommon gram-negative organism found in the environment. Patients and Methods: The patient, an 81-year-old female who had undergone total cystectomy and bilateral ureteral stoma surgery, presented to the hospital with a fever. It was determined that Raoultella planticola was responsible for the bacteremia. Results: Rapid identification of bacteria using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in blood culture samples and appropriate antibacterial treatment was begun and the patient was discharged three days later. Conclusions: This case emphasizes the presence of a rare pathogen as the cause of bacteremia and underscores the importance of utilizing rapid methods for bacterial identification to establish an accurate diagnosis.

Detection of KPC directly from positive blood cultures by MALDI-TOF: From research to the clinical microbiology laboratory routine.

Bloodstream infections (BSI) caused by carbapenem-resistant Gram-negative bacilli (CR-GNB) are a subject of major clinical concern, mainly those associated with carbapenemase-producing isolates. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been proposed to detect specific ß-lactamases, including KPC. We aimed to detect KPC enzyme directly from positive blood cultures using MALDI-TOF MS. Overall, 146 clinical Gram-negative bacilli (46 CR-GNB) recovered from consecutive blood cultures were evaluated. Proteins were extracted using formic acid, isopropyl alcohol, and water and spotted onto a steel target plate using the double-layer sinapinic acid method. The relative ions intensity ≥120 arbitrary units (a.u.) of a peak close to 28,700 m/z indicated the presence of KPC. The results were compared to HRM-qPCR methodology. This specific peak was observed in 11/14 blood bottles with blaKPC positive isolates (78.6% sensitivity), with 3 false-positive results (97.7% specificity). Analysis from colonies reached identical sensitivity (78.6%), but higher specificity (100%). The detection of KPC peaks directly from positive blood cultures using MALDI-TOF MS is feasible and rapid. It's excellent specificity indicates that positive results are consistently associated with the presence of a KPC producer in positive blood culture.

Exploring the fragmentation efficiency of proteins analyzed by MALDI-TOF-TOF tandem mass spectrometry using computational and statistical analyses.

Matrix-assisted laser desorption/ionization time-of-flight-time-of-flight (MALDI-TOF-TOF) tandem mass spectrometry (MS/MS) is a rapid technique for identifying intact proteins from unfractionated mixtures by top-down proteomic analysis. MS/MS allows isolation of specific intact protein ions prior to fragmentation, allowing fragment ion attribution to a specific precursor ion. However, the fragmentation efficiency of mature, intact protein ions by MS/MS post-source decay (PSD) varies widely, and the biochemical and structural factors of the protein that contribute to it are poorly understood. With the advent of protein structure prediction algorithms such as Alphafold2, we have wider access to protein structures for which no crystal structure exists. In this work, we use a statistical approach to explore the properties of bacterial proteins that can affect their gas phase dissociation via PSD. We extract various protein properties from Alphafold2 predictions and analyze their effect on fragmentation efficiency. Our results show that the fragmentation efficiency from cleavage of the polypeptide backbone on the C-terminal side of glutamic acid (E) and asparagine (N) residues were nearly equal. In addition, we found that the rearrangement and cleavage on the C-terminal side of aspartic acid (D) residues that result from the aspartic acid effect (AAE) were higher than for E- and N-residues. From residue interaction network analysis, we identified several local centrality measures and discussed their implications regarding the AAE. We also confirmed the selective cleavage of the backbone at D-proline bonds in proteins and further extend it to N-proline bonds. Finally, we note an enhancement of the AAE mechanism when the residue on the C-terminal side of D-, E- and N-residues is glycine. To the best of our knowledge, this is the first report of this phenomenon. Our study demonstrates the value of using statistical analyses of protein sequences and their predicted structures to better understand the fragmentation of the intact protein ions in the gas phase.

Negative-Ion Electron Capture Dissociation of MALDI-Generated Peptide Anions.

Negative-ion electron capture dissociation (niECD) is an anion MS/MS technique that provides fragmentation analogous to conventional ECD, including high peptide sequence coverage and retention of labile post-translational modifications (PTMs). niECD has been proposed to be the most efficient for salt-bridged zwitterionic precursor ion structures. Several important PTMs, e.g., sulfation and phosphorylation, are acidic and can, therefore, be challenging to characterize in the positive-ion mode. Furthermore, PTM-friendly techniques, such as ECD, require multiple precursor ion-positive charges. By contrast, singly charged ions, refractory to ECD, are most compatible with niECD. Because electrospray ionization (ESI) typically yields multiply charged ions, we sought to explore matrix-assisted laser desorption/ionization (MALDI) in combination with niECD. However, the requirement for zwitterionic gaseous structures may preclude efficient niECD of MALDI-generated anions. Unexpectedly, we found that niECD of anions from MALDI is not only possible but proceeds with similar or higher efficiency compared with ESI-generated anions. Matrix selection did not appear to have a major effect. With MALDI, niECD is demonstrated up to m/z ∼4300. For such larger analytes, multiple electron captures are observed, resulting in triply charged fragments from singly charged precursor ions. Such charge-increased fragments show improved detectability. Furthermore, significantly improved (∼20-fold signal-to-noise increase) niECD spectral quality is achieved with equivalent sample amounts from MALDI vs ESI. Overall, the reported combination with MALDI significantly boosts the analytical utility of niECD.

Evaluation of the utility and cost of secondary confirmatory testing for Neisseria gonorrhoeae identification from culture.

Current guideline recommends the use of two identification methods for Neisseria gonorrhoeae. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) is now used for primary identification and may be sufficient for definitive identification of N. gonorrhoeae. The performance of three secondary tests (BactiCard, RapID NH and NET test) were compared using 45 bacterial isolates, including 37 Neisseria species. These secondary tests demonstrated diminished specificity (67% - 88%) for N. gonorrhoeae compared with MALDI-TOF. Additionally, data from six clinical microbiology laboratories was used to compare confirmatory test costs and the agreement of results with MALDI-TOF. Discrepancies were documented for 9.4% of isolates, though all isolates (n= 288) identified by MALDI-TOF as N. gonorrhoeae were confirmed by the reference laboratory. These data demonstrate that MALDI-TOF alone is sufficient for N. gonorrhoeae identification, as secondary did not add diagnostic value but do add costs to the testing process.

Identification of Mycobacterium abscessus using the peaks of ribosomal protein L29, L30 and hemophore-related protein by MALDI-MS proteotyping.

Mycobacteroides (Mycobacterium) abscessus, which causes a variety of infectious diseases in humans, is becoming detected more frequently in clinical specimens as cases are spreading worldwide. Taxonomically, M. abscessus is composed of three subspecies of M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense, with different susceptibilities to macrolides. In order to identify rapidly these three subspecies, we determined useful biomarker proteins, including ribosomal protein L29, L30, and hemophore-related protein, for distinguishing the subspecies of M. abscessus using the matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) profiles. Thirty-three clinical strains of M. abscessus were correctly identified at the subspecies-level by the three biomarker protein peaks. This study ultimately demonstrates the potential of routine MALDI-MS-based laboratory methods for early identification and treatment for M. abscessus infections.

Cutaneous squamous cell carcinoma characterized by MALDI mass spectrometry imaging in combination with machine learning.

Cutaneous squamous cell carcinoma (SCC) is an increasingly prevalent global health concern. Current diagnostic and surgical methods are reliable, but they require considerable resources and do not provide metabolomic insight. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables detailed, spatially resolved metabolomic analysis of tissue samples. Integrated with machine learning, MALDI-MSI could yield detailed information pertaining to the metabolic alterations characteristic for SCC. These insights have the potential to enhance SCC diagnosis and therapy, improving patient outcomes while tackling the growing disease burden. This study employs MALDI-MSI data, labelled according to histology, to train a supervised machine learning model (logistic regression) for the recognition and delineation of SCC. The model, based on data acquired from discrete tumor sections (n = 25) from a mouse model of SCC, achieved a predictive accuracy of 92.3% during cross-validation on the labelled data. A pathologist unacquainted with the dataset and tasked with evaluating the predictive power of the model in the unlabelled regions, agreed with the model prediction for over 99% of the tissue areas. These findings highlight the potential value of integrating MALDI-MSI with machine learning to characterize and delineate SCC, suggesting a promising direction for the advancement of mass spectrometry techniques in the clinical diagnosis of SCC and related keratinocyte carcinomas.

A Label-Free Approach for Relative Spatial Quantitation of c-di-GMP in Microbial Biofilms.

Microbial biofilms represent an important lifestyle for bacteria and are dynamic three-dimensional structures. Cyclic dimeric guanosine monophosphate (c-di-GMP) is a ubiquitous signaling molecule that is known to be tightly regulated with biofilm processes. While measurements of global levels of c-di-GMP have proven valuable toward understanding the genetic control of c-di-GMP production, there is a need for tools to observe the local changes of c-di-GMP production in biofilm processes. We have developed a label-free method for the direct detection of c-di-GMP in microbial colony biofilms using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We applied this method to the enteric pathogen Vibrio cholerae, the marine symbiont V. fischeri, and the opportunistic pathogen Pseudomonas aeruginosa PA14 and detected spatial and temporal changes in c-di-GMP signal that accompanied genetic alterations in factors that synthesize and degrade the compound. We further demonstrated how this method can be simultaneously applied to detect additional metabolites of interest from a single sample.

Detection accuracy and clinical applications of DP-TOF mass spectrometry.

OBJECTIVE: Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently used in clinical microbiology laboratories. This study aimed to determine whether dual-polarity time-of-flight mass spectrometry (DP-TOF MS) could be applied to clinical nucleotide detection. METHODS: This prospective study included 40 healthy individuals and 110 patients diagnosed with cardiovascular diseases. We used DP-TOF MS and Sanger sequencing to evaluate 17 loci across 11 genes associated with cardiovascular drug responses. In addition, we used DP-TOF MS to test 998 retrospectively collected clinical DNA samples with known results. RESULTS: A, T, and G nucleotide detection by DP-TOF MS and Sanger sequencing revealed 100% concordance, whereas the C nucleotide concordance was 99.86%. Genotyping based on the results of the two methods showed 99.96% concordance. Regarding clinical applications, DP-TOF MS yielded a 99.91% concordance rate for known loci. The minimum detection limit for DNA was 0.4 ng; the inter-assay and intra-assay precision rates were both 100%. Anti-interference analysis showed that aerosol contamination greater than 1013 copies/µL in the laboratory environment could influence the results of DP-TOF MS. CONCLUSIONS: The DP-TOF MS platform displayed good detection performance, as demonstrated by its 99.96% concordance rate with Sanger sequencing. Thus, it may be applied to clinical nucleotide detection.

A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues.

Describing the microbial community within the tumour has been a key aspect in understanding the pathophysiology of the tumour microenvironment. In head and neck cancer (HNC), most studies on tissue samples have only performed 16S rRNA short-read sequencing (SRS) on V3-V5 region. SRS is mostly limited to genus level identification. In this study, we compared full-length 16S rRNA long-read sequencing (FL-ONT) from Oxford Nanopore Technology (ONT) to V3-V4 Illumina SRS (V3V4-Illumina) in 26 HNC tumour tissues. Further validation was also performed using culture-based methods in 16 bacterial isolates obtained from 4 patients using MALDI-TOF MS. We observed similar alpha diversity indexes between FL-ONT and V3V4-Illumina. However, beta-diversity was significantly different between techniques (PERMANOVA - R2 = 0.131, p < 0.0001). At higher taxonomic levels (Phylum to Family), all metrics were more similar among sequencing techniques, while lower taxonomy displayed more discrepancies. At higher taxonomic levels, correlation in relative abundance from FL-ONT and V3V4-Illumina were higher, while this correlation decreased at lower levels. Finally, FL-ONT was able to identify more isolates at the species level that were identified using MALDI-TOF MS (75% vs. 18.8%). FL-ONT was able to identify lower taxonomic levels at a better resolution as compared to V3V4-Illumina 16S rRNA sequencing.

Matrix-free laser desorption/ionization mass spectrometry imaging for rapid evaluation of wood biomass conversion.

RATIONALE: This study overcomes traditional biomass analysis limitations by introducing a pioneering matrix-free laser desorption/ionization (LDI) approach in mass spectrometry imaging (MSI) for efficient lignin evaluation in wood. The innovative acetic acid-peracetic acid (APA) treatment significantly enhances lignin detection, enabling high-throughput, on-site analysis. METHODS: Wood slices, softwood from a conifer tree (Japanese cypress) and hardwood from a broadleaf tree (Japanese beech), were analyzed using MSI with a Fourier transform ion cyclotron resonance mass spectrometer. The developed APA treatment demonstrated effectiveness for MSI analysis of biomass. RESULTS: Our imaging technique successfully distinguishes between earlywood and latewood and enables the distinct visualization of lignin in these and other wood tissues, such as the radial parenchyma. This approach reveals significant contrasts in MSI. It has identified intense ions from ß-O-4-type lignin, specifically in the radial parenchyma of hardwood, highlighting the method's precision and utility in wood tissue analysis. CONCLUSIONS: The benefits of matrix-free LDI include reduced peak overlap, consistent sample quality, preservation of natural sample properties, enhanced analytical accuracy, and reduced operational costs. This innovative approach is poised to become a standard method for rapid and precise biomass evaluation and has important applications in environmental research and sustainable resource management and is crucial for the effective management of diverse biomass, paving the way towards a sustainable, circular society.

Improved detection in untargeted lipidomics through silver-doped infrared matrix-assisted laser desorption electrospray ionization.

RATIONALE: Silver doping of electrospray is known to increase the abundance of olefinic compounds detected by mass spectrometry. While demonstrated in targeted experiments, this has yet to be investigated in an untargeted study. Utilizing infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI-MSI), an untargeted lipidomics experiment on mouse liver was performed to evaluate the advantages of silver-doped electrospray. METHODS: 10 ppm silver nitrate was doped into the IR-MALDESI solvent consisting of 60% acetonitrile and 0.2% formic acid. Using an Orbitrap mass spectrometer in positive ionization mode, MSI was performed, analyzing from m/z 150 to m/z 2000 to capture all lipids with potential silver adducts. The lipids detected in the control and silver-doped electrosprays were compared by annotating using the LIPID MAPS Structural Database and eliminating false positives using the metabolite annotation confidence score. RESULTS: Silver-doped electrospray allowed for the detection of such ions of lipid molecules as [M + H]+ or [M + NH4]+ and as [M + Ag]+. Among the ions seen as [M + H]+ or [M + NH4]+, the signal was comparable between the control and silver-doped electrosprays. The silver-doped electrospray led to a 10% increase in the number of detected lipids, all of which contained a bay region increasing the interaction between silver and alkenes. Silver preferentially interacted with lipids that did not contain hard bases such as phosphates. CONCLUSIONS: Silver-doped electrospray enabled detection of 10% more olefinic lipids, all containing bay regions in their putative structures. This technique is valuable for detecting previously unobserved lipids that have the potential to form bay regions, namely fatty acyls, glycerolipids, prenol lipids, and polyketides.

Accelerated microbial identification "directly" from positive blood cultures using MALDI-TOF MS: Local clinical laboratory challenges.

Rapid identification of microbial pathogens "directly" from positive blood cultures (PBCs) is critical for prompt initiation of empirical antibiotic therapy and clinical outcomes. Towards higher microbial identification rates, we modified a published initial serum separator tubes-based MALDI-TOF-MS protocol, for blood culture specimens received at a non-hospital based standalone diagnostic laboratory, Bangalore, India: (a) "Initial" protocol #1: From 28 PBCs, identification= 39% (Gram-negative= 43%: Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa; Gram-positive: 36%: Enterococcus faecalis, Staphylococcus aureus, Staphylococcus haemolyticus); mis-identification= 14%; non-identification= 47%. (b) "Modified" protocol #2: Quality controls (ATCC colonies spiked in negative blood cultures) From 7 analysis, identification= 100% (Escherichia coli, Klebsiella pneumonia, Klebsiella oxytoca, Pseudomonas aeruginosa, Enterococcus faecalis, Staphylococcus aureus); From 7 PBCs, identification= 57%; mis-identification= 14%; non-identification= 29%. Microbial preparations of highest quality and quantity for proteomic analysis and separate spectra matching reference databases for colonies and PBCs are needed for best clinical utility.

Joint forces of mass spectrometric techniques (ICP-MS and MALDI-TOF-MS) and fluorescence spectrometry in the study of platinum-based cytostatic drugs interactions with metallothionein MT2 and MT3.

Herby, the interaction of metallothioneins with commonly used Pt-based anticancer drugs - cisplatin, carboplatin, and oxaliplatin - was investigated using the combined power of elemental (i.e. LA-ICP-MS, CE-ICP-MS) and molecular (i.e. MALDI-TOF-MS) analytical techniques providing not only required information about the interaction, but also the benefit of low sample consumption. The amount of Cd and Pt incorporated within the protein was determined for protein monomers and dimer/oligomers formed by non-oxidative dimerization. Moreover, fluorescence spectrometry using Zn2+-selective fluorescent indicator - FluoZin3 - was employed to monitor the ability of Pt drugs to release natively occurring Zn from the protein molecule. The investigation was carried out using two protein isoforms (i.e. MT2, MT3), and significant differences in behaviour of these two isoforms were observed. The main attention was paid to elucidating whether the protein dimerization/oligomerization may be the reason for the potential failure of the anticancer therapy based on these drugs. Based on the results, it was demonstrated that the interaction of MT2 (both monomers and dimers) interacted with Pt drugs significantly less compared to MT3 (both monomers and dimers). Also, a significant difference between monomeric and dimeric forms (both MT2 and MT3) was not observed. This may suggest that dimer formation is not the key factor leading to the inactivation of Pt drugs.

High-Throughput Metabolic Pattern Screening Strategy for Early Colorectal and Gastric Cancers Based on Covalent Organic Frameworks-Assisted Laser Desorption/Ionization Mass Spectrometry.

Precise early diagnosis and staging are conducive to improving the prognosis of colorectal cancer (CRC) and gastric cancer (GC) patients. However, due to intrusive inspections and limited sensitivity, the prevailing diagnostic methods impede precisely large-scale screening. In this work, we reported a high-throughput serum metabolic patterns (SMP) screening strategy based on covalent organic frameworks-assisted laser desorption/ionization mass spectrometry (hf-COFsLDI-MS) for early diagnosis and staging of CRC and GC. Notably, 473 high-quality SMP were extracted without any tedious sample pretreatment and coupled with multiple machine learning algorithms; the area under the curve (AUC) value is 0.938 with 96.9% sensitivity for early CRC diagnosis, and the AUC value is 0.974 with 100% sensitivity for early GC diagnosis. Besides, the discrimination of CRC and GC is accomplished with an AUC value of 0.966 for the validation set. Also, the screened-out features were identified by MS/MS experiments, and 8 metabolites were identified as the biomarkers for CRC and GC. Finally, the corresponding disordered metabolic pathways were revealed, and the staging of CRC and GC was completed. This work provides an alternative high-throughput screening strategy for CRC and GC and highlights the potential of metabolic molecular diagnosis in clinical applications.

[Identification and visual analysis of ginsenosides in multi-steamed roots of Panax quinquefolium based on UPLC-Q-TOF-MS/MS and MALDI-MSI].

This study aims to investigate the component variations and spatial distribution of ginsenosides in Panax quinquefolium roots during repeated steaming and drying. Ultra performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) was employed to identify the ginsenosides in the root extract. Matrix-assisted laser desorption/ionization mass spectrometry imaging(MALDI-MSI) was employed to visualize the spatial distribution and spatiotemporal changes of prototype ginsenosides and metabolites in P. quinquefolium roots. The UPLC results showed that 90 ginsenosides were identified during the steaming process of the roots, and polar ginsenosides were converted into low polar or non-polar ginsenosides. The content of prototype ginsenosides decreased, while that of rare ginsenosides increased, which included 20(S/R)-ginsenoside Rg_3, 20(S/R)-ginsenoside Rh_2, and ginsenosides Rk_1, Rg_5, Rs_5, and Rs_4. MALDI-MSI results showed that ginsenosides were mainly distributed in the epidermis and phloem. As the steaming times increased, ginsenosides were transported to the xylem and medulla. This study provides fundamental information for revealing the changes of biological activity and pharmacological effect of P. quinquefolium roots that are caused by repeated steaming and drying and gives a reference for expanding the application scope of this herbal medicine.

MALDI-TOF Mass Spectrometry-Based Assay for Measuring Covalent Target Engagement of KRAS G12C Inhibitors.

MALDI-TOF mass spectrometry enables high-throughput screening of covalent fragment libraries and SAR compound progressions of selective KRAS G12C inhibitors. Using the MALDI-TOF platform instead of the more traditional ESI-MS TOF/orbitrap instrumentation can radically shorten sample acquisition time, allowing up to 384 samples to be screened in 30 min. The typical throughput for a covalent library screen is 1152 samples per 8 h, including processing, calculation, and reporting steps. The throughput can be doubled without any significant assay modification.