Validation of MALDI-MS imaging data of selected membrane lipids in murine brain with and without laser postionization by quantitative nano-HPLC-MS using laser microdissection

Formation of multiple ion types during MALDI imaging mass spectrometry analysis of Mitragyna speciosa alkaloids in dosed rat brain tissue

Mitragyna speciosa, more commonly known as kratom, has emerged as an alternative to treat chronic pain and addiction. However, the alkaloid components of kratom, which are the major contributors to kratom's pharmaceutical properties, have not yet been fully investigated. In this study, matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry was used to map the biodistribution of three alkaloids (corynantheidine, mitragynine, and speciogynine) in rat brain tissues. The alkaloids produced three main ion types during MALDI analysis: [M + H]+, [M - H]+, and [M - 3H]+. Contrary to previous reports suggesting that the [M - H]+ and [M - 3H]+ ion types form during laser ablation, these ion types can also be produced during the MALDI matrix application process. Several strategies are proposed to accurately map the biodistribution of the alkaloids. Due to differences in the relative abundances of the ions in different biological regions of the tissue, differences in ionization efficiencies of the ions, and potential overlap of the [M - H]+ and [M - 3H]+ ion types with endogenous metabolites of the same empirical formula, a matrix that mainly produces the [M + H]+ ion type is optimal for accurate mapping of the alkaloids. Alternatively, the most abundant ion type can be mapped or the intensities of all ion types can be summed together to generate a composite image. The accuracy of each of these approaches is explored and validated.

Large-Scale Screening of Pharmaceutical Compounds to Explore the Application Space of On-Tissue MALDI and MALDI-2 Mass Spectrometry

The successful application of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in pharmaceutical research is strongly dependent on the detection of the drug of interest at physiologically relevant concentrations. Here we explored how insufficient sensitivity due to low ionization efficiency and/or the interaction of the drug molecule with the local biochemical environment of the tissue can be mitigated for many compound classes using the recently introduced MALDI-MSI coupled with laser-induced postionization, known as MALDI-2-MSI. Leveraging a MALDI-MSI screen of about 1,200 medicines/drug-like compounds from a broad range of medicinal application areas, we demonstrate a significant improvement in drug detection and the degree of sensitivity uplift by using MALDI-2 versus traditional MALDI. Our evaluation was made under simulated imaging conditions using liver homogenate sections as substrate, onto which the compounds were spotted to mimic biological conditions to the first order. To enable an evaluable detection by both MALDI and MALDI-2 for the majority of employed compounds, we spotted 1 μL of a 10 mM solution using a spotting robot and performed our experiments with a Bruker timsTOF fleX MALDI-2 instrument in both positive and negative ion modes. Specifically, we demonstrate using a large cohort of drug-like compounds that ∼60% of the tested compounds showed a more than 10-fold increase in signal intensity and ∼16% showed a more than 100-fold increase upon use of MALDI-2 postionization. Such increases in sensitivity could help advance pharmaceutical MALDI-MSI applications toward the single-cell level.

MALDI-MSI-LC-MS/MS Workflow for Single-Section Single Step Combined Proteomics and Quantitative Lipidomics

We introduce a novel approach for comprehensive molecular profiling in biological samples. Our single-section methodology combines quantitative mass spectrometry imaging (Q-MSI) and a single step extraction protocol enabling lipidomic and proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis on the same tissue area. The integration of spatially correlated lipidomic and proteomic data on a single tissue section allows for a comprehensive interpretation of the molecular landscape. Comparing Q-MSI and Q-LC-MS/MS quantification results sheds new light on the effect of MSI and related sample preparation. Performing MSI before Q-LC-MS on the same tissue section led to fewer protein identifications and a lower correlation between lipid quantification results. Also, the critical role and influence of internal standards in Q-MSI for accurate quantification is highlighted. Testing various slide types and the evaluation of different workflows for single-section spatial multiomics analysis emphasized the need for critical evaluation of Q-MSI data. These findings highlight the necessity for robust quantification methods comparable to current gold-standard LC-MS/MS techniques. The spatial information from MSI allowed region-specific insights within heterogeneous tissues, as demonstrated for glioblastoma multiforme. Additionally, our workflow demonstrated the efficiency of a single step extraction for lipidomic and proteomic analyses on the same tissue area, enabling the examination of significantly altered proteins and lipids within distinct regions of a single section. The integration of these insights into a lipid-protein interaction network expands the biological information attainable from a tissue section, highlighting the potential of this comprehensive approach for advancing spatial multiomics research.

Spatial MS multiomics on clinical prostate cancer tissues

Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.

Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture

Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) reveals potential lipid markers between infrapatellar fat pad biopsies of osteoarthritis and cartilage defect patients

The incidence of osteoarthritis (OA) has been expected to increase due to an aging population, as well as an increased incidence of intra-articular (osteo-) chondral damage. Lipids have already been shown to be involved in the inflammatory process of OA. This study aims at revealing region-specific lipid profiles of the infrapatellar fat pad (IPFP) of OA or cartilage defect patients by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which could be used as biomarkers for early OA detection. A higher presence of phospholipids was found in OA patients compared with cartilage defect patients. In addition, a higher abundance of ether-linked phosphatidylethanolamines (PE O-s) containing arachidonic acid was specifically found in OA patients compared with cartilage defect patients. These lipids were mainly found in the connective tissue of the IPFP. Specific lipid species were associated to OA patients compared with cartilage defect patients. PE O-s have been suggested as possible biomarkers for OA. As these were found more abundantly in the connective tissue, the IPFP's intra-tissue heterogeneity might play an important role in biomarker discovery, implying that the amount of fibrous tissue is associated with OA.

Single-cell lipidomics enabled by dual-polarity ionization and ion mobility-mass spectrometry imaging

Single-cell (SC) analysis provides unique insight into individual cell dynamics and cell-to-cell heterogeneity. Here, we utilize trapped ion mobility separation coupled with dual-polarity ionization mass spectrometry imaging (MSI) to enable high-throughput in situ profiling of the SC lipidome. Multimodal SC imaging, in which dual-polarity-mode MSI is used to perform serial data acquisition runs on individual cells, significantly enhanced SC lipidome coverage. High-spatial resolution SC-MSI identifies both inter- and intracellular lipid heterogeneity; this heterogeneity is further explicated by Uniform Manifold Approximation and Projection and machine learning-driven classifications. We characterize SC lipidome alteration in response to stearoyl-CoA desaturase 1 inhibition and, additionally, identify cell-layer specific lipid distribution patterns in mouse cerebellar cortex. This integrated multimodal SC-MSI technology enables high-resolution spatial mapping of intercellular and cell-to-cell lipidome heterogeneity, SC lipidome remodeling induced by pharmacological intervention, and region-specific lipid diversity within tissue.

Desorption Kinetics Evaluation for the Development of Validated Desorption Electrospray Ionization-Mass Spectrometric Assays for Drug Quantification in Tissue Sections

The development of desorption/ionization (DI) mass spectrometric (MS) assays for drug quantification in tissue sections and their validation according to regulatory guidelines would enable their universalization for applications in (clinical) pharmacology. Recently, new enhancements in desorption electrospray ionization (DESI) have highlighted the reliability of this ion source for the development of targeted quantification methods that meet requirements for method validation. However, it is necessary to consider subtle parameters leading to the success of such method developments, such as the morphology of desorption spots, the analytical time, and sample surface, to cite but a few. Here, we provide additional experimental data highlighting an additional important parameter, based on the unique advantage of DESI-MS on continuous extraction during analysis. We demonstrate that considering desorption kinetics during DESI analyses would largely help (i) reducing analytical time during profiling analyses, (ii) verifying solvent-based drug extraction using the selected sample preparation method for profiling and imaging modes, and (iii) predicting the feasibility of imaging assays using samples in a given expected concentration range of the targeted drug. These observations will likely serve as precious guidance for the development of validated DESI-profiling and imaging methods in the future.

Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma

Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Viral Biomarker Detection and Validation Using MALDI Mass Spectrometry Imaging (MSI)

(1) Background: MALDI imaging is a technique that still largely depends on time of flight (TOF)-based instrument such as the Bruker UltrafleXtreme. While capable of performing targeted MS/MS, these instruments are unable to perform fragmentation while imaging a tissue section necessitating the reliance of MS1 values for peptide level identifications. With this premise in mind, we have developed a hybrid bioinformatic/image-based method for the identification and validation of viral biomarkers. (2) Methods: Formalin-Fixed Paraffin-Embedded (FFPE) mouse samples were sectioned, mounted and prepared for mass spectrometry imaging using our well-established methods. Peptide identification was achieved by first extracting confident images corresponding to theoretical viral peptides. Next, those masses were used to perform a Peptide Mmass Fingerprint (PMF) searched against known viral FASTA sequences against a background mouse FASTA database. Finally, a correlational analysis was performed with imaging data to confirm pixel-by-pixel colocalization and intensity of viral peptides. (3) Results: 14 viral peptides were successfully identified with significant PMF Scores and a correlational result of >0.79 confirming the presence of the virus and distinguishing it from the background mouse proteins. (4) Conclusions: this novel approach leverages the power of mass spectrometry imaging and provides confident identifications for viral proteins without requiring MS/MS using simple MALDI Time Of Flight/Time Of Flight (TOF/TOF) instrumentation.

Analyzing cell-type-specific dynamics of metabolism in kidney repair

A common drawback of metabolic analyses of complex biological samples is the inability to consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this limitation, we present an advanced high-spatial-resolution metabolomics approach using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) combined with isotope tracing. This method allows mapping of cell-type-specific dynamic changes in central carbon metabolism in the context of a complex heterogeneous tissue architecture, such as the kidney. Combined with multiplexed immunofluorescence staining, this method can detect metabolic changes and nutrient partitioning in targeted cell types, as demonstrated in a bilateral renal ischemia-reperfusion injury (bIRI) experimental model. Our approach enables us to identify region-specific metabolic perturbations associated with the lesion and throughout recovery, including unexpected metabolic anomalies in cells with an apparently normal phenotype in the recovery phase. These findings may be relevant to an understanding of the homeostatic capacity of the kidney microenvironment. In sum, this method allows us to achieve resolution at the single-cell level in situ and hence to interpret cell-type-specific metabolic dynamics in the context of structure and metabolism of neighboring cells.

Single‐Photon‐Induced Post‐Ionization to Boost Ion Yields in MALDI Mass Spectrometry Imaging**

Matrix‐assisted laser desorption/ionization mass spectrometry imaging (MALDI‐MSI) is a rapidly growing method in the life sciences. However, for many analyte classes, its sensitivity is limited due to poor ionization efficiencies. To mitigate this problem, we here introduce a novel post‐ionization scheme based on single‐photon induced chemical ionization using pulsed RF‐Kr lamps. The fine‐vacuum conditions of a dual ion‐funnel ion source effectively thermalize the evolving MALDI plume and enable ample gas‐phase reactions. Injected chemical dopants crucially support fragment‐less ionization to [M+H]⁺/[M−H]⁻ species. Based on this interplay, numerous glycerophospho‐, sphingo‐, and further lipids, registered from mammalian tissue sections, were boosted by up to three orders of magnitude, similar to results obtained with laser‐based post‐ionization (MALDI‐2). Experiments with deuterated matrix and dopant, however, indicated complex chemical ionization pathways different from MALDI‐2.

Isomer-Resolved Imaging of Prostate Cancer Tissues Reveals Specific Lipid Unsaturation Profiles Associated With Lymphocytes and Abnormal Prostate Epithelia

Prostate cancer is the fourth most common cancer worldwide with definitive diagnosis reliant on biopsy and human-graded histopathology. As with other pathologies, grading based on classical haematoxylin and eosin (H&E) staining of formalin fixed paraffin-embedded material can be prone to variation between pathologists, prompting investigation of biomolecular markers. Comprising around 50% of cellular mass, and with known metabolic variations in cancer, lipids provide a promising target for molecular pathology. Here we apply isomer-resolved lipidomics in combination with imaging mass spectrometry to interrogate tissue sections from radical prostatectomy specimens. Guided by the histopathological assessment of adjacent tissue sections, regions of interest are investigated for molecular signatures associated with lipid metabolism, especially desaturation and elongation pathways. Monitoring one of the most abundant cellular membrane lipids within these tissues, phosphatidylcholine (PC) 34:1, high positive correlation was observed between the n-9 isomer (site of unsaturation 9-carbons from the methyl terminus) and epithelial cells from potential pre-malignant lesions, while the n-7 isomer abundance was observed to correlate with immune cell infiltration and inflammation. The correlation of lipid isomer signatures with human disease states in tissue suggests a future role for isomer-resolved mass spectrometry imaging in assisting pathologists with prostate cancer diagnoses and patient stratification.

Determination of Abundant Metabolite Matrix Adducts Illuminates the Dark Metabolome of MALDI-Mass Spectrometry Imaging Datasets

Spatial metabolomics using mass spectrometry imaging (MSI) is a powerful tool to map hundreds to thousands of metabolites in biological systems. One major challenge in MSI is the annotation of m/z values, which is substantially complicated by background ions introduced throughout the chemicals and equipment used during experimental procedures. Among many factors, the formation of adducts with sodium or potassium ions, or in case of matrix-assisted laser desorption ionization (MALDI)-MSI, the presence of abundant matrix clusters strongly increases total m/z peak counts. Currently, there is a limitation to identify the chemistry of the many unknown peaks to interpret their biological function. We took advantage of the co-localization of adducts with their parent ions and the accuracy of high mass resolution to estimate adduct abundance in 20 datasets from different vendors of mass spectrometers. Metabolites ranging from lipids to amines and amino acids form matrix adducts with the commonly used 2,5-dihydroxybenzoic acid (DHB) matrix like [M + (DHB-H₂O) + H]⁺ and [M + DHB + Na]⁺. Current data analyses neglect those matrix adducts and overestimate total metabolite numbers, thereby expanding the number of unidentified peaks. Our study demonstrates that MALDI-MSI data are strongly influenced by adduct formation across different sample types and vendor platforms and reveals a major influence of so far unrecognized metabolite–matrix adducts on total peak counts (up to one third). We developed a software package, mass2adduct, for the community for an automated putative assignment and quantification of metabolite–matrix adducts enabling users to ultimately focus on the biologically relevant portion of the MSI data.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.

Mass Spectrometry Imaging as a Tool to Investigate Region Specific Lipid Alterations in Symptomatic Human Carotid Atherosclerotic Plaques

Atherosclerosis is characterized by fatty plaques in large and medium sized arteries. Their rupture can causes thrombi, occlusions of downstream vessels and adverse clinical events. The investigation of atherosclerotic plaques is made difficult by their highly heterogeneous nature. Here we propose a spatially resolved approach based on matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging to investigate lipids in specific regions of atherosclerotic plaques. The method was applied to a small dataset including symptomatic and asymptomatic human carotid atherosclerosis plaques. Tissue sections of symptomatic and asymptomatic human carotid atherosclerotic plaques were analyzed by MALDI mass spectrometry imaging (MALDI MSI) of lipids, and adjacent sections analyzed by histology and immunofluorescence. These multimodal datasets were used to compare the lipid profiles of specific histopathological regions within the plaque. The lipid profiles of macrophage-rich regions and intimal vascular smooth muscle cells exhibited the largest changes associated with plaque outcome. Macrophage-rich regions from symptomatic lesions were found to be enriched in sphingomyelins, and intimal vascular smooth muscle cells of symptomatic plaques were enriched in cholesterol and cholesteryl esters. The proposed method enabled the MALDI MSI analysis of specific regions of the atherosclerotic lesion, confirming MALDI MSI as a promising tool for the investigation of histologically heterogeneous atherosclerotic plaques.

Infrared MALDI Mass Spectrometry with Laser-Induced Postionization for Imaging of Bacterial Colonies

Ultraviolet matrix-assisted laser desorption ionization mass spectrometry imaging (UV-MALDI-MSI) is a powerful tool to visualize bacterial metabolites in microbial colonies and in biofilms. However, a challenge for the method is the efficient extraction of analytes from deeper within the bacterial colonies and from the cytoplasm of individual cells during the matrix coating step. Here, we used a pulsed infrared (IR) laser of 2.94 μm wavelength to disrupt and ablate bacterial cells without a prior coating with a MALDI matrix. Instead, tissue water or, in some experiments, in addition a small amount of glycerol was exploited for the deposition of the IR laser energy and for supporting the ionization of the analytes. Compared to water, glycerol exhibits a lower vapor pressure, which prolonged the available measurement time window within an MSI experiment. Mass spectra were acquired with a hybrid Synapt G2-S HDMS instrument at a pixel size of 120 μm. A frequency-quadrupled q-switched Nd:YAG laser with 266 nm wavelength served for laser-induced postionization (MALDI-2). In this way, the ion abundances of numerous small molecules such as nucleobases, 2-alkyl-quinolones, a prominent class of Pseudomonas aeruginosa signaling molecules involved in one of the three quorum-sensing pathways, and also the signals of various bacterial phospholipids were boosted, partially by orders of magnitude. We analyzed single and cocultured colonies of Gram-negative P. aeruginosa and of Gram-positive Bacillus subtilis and Staphylococcus aureus as exemplary bacterial systems. To enable a rapid (within 5 s) MSI-compatible steam inactivation in a custom-made autoclave filled with hot water steam, bacterial cultures were grown on porous polyamide membranes. Compared to a UV-MALDI-2-MS measurement of the same systems, mass spectra with a reduced low mass background were generally generated. This resulted in the unequivocal detection of numerous metabolites only with the IR laser. In a fundamental part of our study, and to optimize the IR-MALDI-2 approach for the highest analytical sensitivity, we characterized the expansion dynamics of the particle plume as generated by the IR laser. Here, we recorded the total ion count and the intensities of selected signals registered from P. aeruginosa samples as a function of the interlaser delay and buffer gas pressure in the ion source. The data revealed that the IR-MALDI-2 ion signals are primarily generated from slow particles having mean velocities of ∼10 m/s. Interestingly, two different pressure/delay time regimes of the optimized ionization efficiency for phospholipids and smaller metabolites, respectively, were revealed, a result pointing to yet-unknown convoluted reaction cascades. The described IR-MALDI-2 method could be a helpful new tool for a microbial mass spectrometry imaging of small molecules requiring little sample preparation.