Metabolic remodeling and its hidden heterogeneity in uterine fibroids: comprehensive metabolomic profiling and mass spectrometry imaging.

Direct Visualization of Neurotransmitters in Rat Brain Slices by Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI - MS).

We developed a model case study to evaluate three internal standard (IS) application strategies (methods I-III) using the psycholeptic phenobarbital (PB) and the isotopically labelled IS phenobarbital-D5 (PB-D5) from in vitro dosed tissues of the golden apple snail (Pomacea diffusa) by desorption electrospray ionization mass spectrometry imaging (DESI-MSI). In method I, the IS was deposited as microspots on top of 10 μm thick snail tissues; in method II, a thin IS film was applied; and in method III, the IS was spiked into the DESI solvent spray. DESI-MSI analyses were performed using a Thermo LTQ mass spectrometer equipped with a custom-built DESI source and two-dimensional moving stage. PB (m/z 231) and PB-D5 (m/z 236) were monitored in selected ion monitoring mode between m/z 227 and 239. The analytical performance of two IS strategies (methods I and II) in DESI-MSI was evaluated based on an intra- and inter-day precision assay, an accuracy assessment, and statistical analysis. In the inter-day DESI-MSI assay, method I exhibited better precision (6.5%-7.4%) than method II (10.7%-17.6%) between 10 and 100 ng/μL. In the accuracy assessment, PB quality controls of 75 ng/μL were back-calculated as 71 ± 4 and 83 ± 9 ng/μL, resulting in relative errors of -5% and 11% for methods I and II, respectively. Method III did not work under the experimental design and was not evaluated. Three IS application strategies were investigated and compared for a routine quantitative DESI-MSI approach. Methods I and II were not statistically significantly different as shown by a Bland-Altman plot, suggesting that these two methods can be used interchangeably. However, method III requires further research for future quantitative DESI-MSI analyses.

Uncaria species (Rubiaceae) are used as traditional Chinese medicines (TCMs) to treat central nervous system (CNS) diseases, and monoterpene indole alkaloids are the main bioactive constituents. Localization and quantification of CNS drugs in fine brain regions are important to provide insights into their pharmacodynamics, for which quantitative mass spectrometry imaging (MSI) has emerged as a powerful technique. A systematic study of the quantitative imaging of seven Uncaria alkaloids in rat brains using desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was presented. The distribution of the alkaloids in thirteen brain regions was quantified successfully using the calibration curves generated by a modified on-tissue approach. The distribution trend of different Uncaria alkaloids in the rat brain was listed as monoterpene indole alkaloids > monoterpene oxindole alkaloids, R-configuration epimers > S-configuration epimers. Particularly, Uncaria alkaloids were detected directly in the pineal gland for the first time and their enrichment phenomenon in this region had an instructive significance in future pharmacodynamic studies.

Desorption Electrospray Ionization Mass Spectrometry Imaging of Cimbi-36, a 5-HT2A Receptor Agonist, with Direct Comparison to Autoradiography and Positron Emission Tomography.

Monitoring Toxic Ionic Liquids in Zebrafish (Danio rerio) with Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI).

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy. However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In our study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal tumor pairs was analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out cross-validation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94 and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status.

<i>In situ</i> DESI-MSI Lipidomic Profiles of Mucosal Margin of Oral Squamous Cell Carcinoma

Distinguishing adenocarcinoma and squamous cell carcinoma subtypes of non-small cell lung cancers is critical to patient care. Preoperative minimally-invasive biopsy techniques, such as fine needle aspiration (FNA), are increasingly used for lung cancer diagnosis and subtyping. Yet, histologic distinction of lung cancer subtypes in FNA material can be challenging. Here, we evaluated the usefulness of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to diagnose and differentiate lung cancer subtypes in tissues and FNA samples. DESI-MSI was used to analyze 22 normal, 26 adenocarcinoma, and 25 squamous cell carcinoma lung tissues. Mass spectra obtained from the tissue sections were used to generate and validate statistical classifiers for lung cancer diagnosis and subtyping. Classifiers were then tested on DESI-MSI data collected from 16 clinical FNA samples prospectively collected from 8 patients undergoing interventional radiology guided FNA. Various metabolites and lipid species were detected in the mass spectra obtained from lung tissues. The classifiers generated from tissue sections yielded 100% accuracy, 100% sensitivity, and 100% specificity for lung cancer diagnosis, and 73.5% accuracy for lung cancer subtyping for the training set of tissues, per-patient. On the validation set of tissues, 100% accuracy for lung cancer diagnosis and 94.1% accuracy for lung cancer subtyping were achieved. When tested on the FNA samples, 100% diagnostic accuracy and 87.5% accuracy on subtyping were achieved per-slide. DESI-MSI can be useful as an ancillary technique to conventional cytopathology for diagnosis and subtyping of non-small cell lung cancers.

Fuzi is a famous toxic traditional herbal medicine, which has long been used for the treatment of various diseases in China and many other Asian countries because of its extraordinary pharmacological activities and high toxicity. Different processing methods to attenuate the toxicity of Fuzi are important for its safe clinical use. In this study, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) with a metabolomics-combined multivariate statistical analysis approach was applied to investigate a series of Aconitum alkaloids and explore potential metabolic markers to understand the differences between raw and processed Fuzi with different steaming time points. Moreover, the selected metabolic markers were visualized by DESI-MSI, and six index alkaloids’ contents were determined through HPLC. The results indicated visible differences among raw and processed Fuzi with different steaming times, and 4.0 h is the proper time for toxicity attenuation and efficacy reservation. A total of 42 metabolic markers were identified to discriminate raw Fuzi and those steamed for 4.0 and 8.0 h, which were clearly visualized in DESI-MSI. The transformation from diester-diterpenoid alkaloids to monoester-diterpenoid alkaloids and then to non-esterified diterpene alkaloids through hydrolysis is the major toxicity attenuation process during steaming. DESI-MSI combined with metabolomics provides an efficient method to visualize the changeable rules and screen the metabolic markers of Aconitum alkaloids during steaming. The wide application of this technique could help identify markers and reveal the possible chemical transition mechanism in the “Paozhi” processes of Fuzi. It also provides an efficient and easy way to quality control and ensures the safety of Fuzi and other toxic traditional Chinese medicine.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is one of the least specimen destructive ambient ionization mass spectrometry tissue imaging methods. It enables rapid simultaneous mapping, measurement, and identification of hundreds of molecules from an unmodified tissue sample. Over the years, since its first introduction as an imaging technique in 2005, DESI-MSI has been extensively developed as a tool for separating tissue regions of various histopathologic classes for diagnostic applications. Recently, DESI-MSI has also emerged as a versatile technique that enables drug discovery and can guide the efficient development of drug delivery systems. For example, it has been increasingly employed for uncovering unique patterns of in vivo drug distribution, the discovery of potentially treatable biochemical pathways, revealing novel druggable targets, predicting therapeutic sensitivity of diseased tissues, and identifying early tissue response to pharmacological treatment. These and other recent advances in implementing DESI-MSI as the tool for the development of novel therapies are highlighted in this review.

Desorption electrospray ionization mass spectrometry imaging (DESI‐MSI) is a molecular imaging method that can be used to elucidate the small‐molecule composition of tissues and map their spatial information using two‐dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI‐MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for which are known to carry various nerve fiber types were harvested from a fresh cadaveric donor: mixed, motor and sensory (sciatic and femoral); cutaneous, sensory (sural); and autonomic (vagus). Tissue samples were harvested to include the nerve bundles in addition to surrounding connective tissue. Samples were flash‐frozen, embedded in optimal cutting temperature compound in cross‐section, and sectioned at 14 μm. Following DESI‐MSI analysis, identical tissue sections were stained with hematoxylin and eosin. In this proof‐of‐concept study, a combination of multivariate and univariate statistical methods was used to evaluate molecular differences between the nerve and adjacent tissue and between nerve subtypes. The acquired mass spectral profiles of the peripheral nerve samples presented trends in ion abundances that seemed to be characteristic of nerve tissue and spatially corresponded to the associated histology of the tissue sections. Principal component analysis (PCA) supported the separation of the samples into distinct nerve and adjacent tissue classes. This classification was further supported by the K‐means clustering analysis, which showed separation of the nerve and background ions. Differences in ion expression were confirmed using ANOVA which identified statistically significant differences in ion expression between the nerve subtypes. The PCA plot suggested some separation of the nerve subtypes into four classes which corresponded with the nerve types. This was supported by the K‐means clustering. Some overlap in classes was noted in these two clustering analyses. This study provides emerging evidence that DESI‐MSI is an effective tool for metabolomic profiling of peripheral nerves. Our results suggest that peripheral nerves have molecular profiles that are distinct from the surrounding connective tissues and that DESI‐MSI may be able to discriminate between nerve subtypes. DESI‐MSI of peripheral nerves may be a valuable technique that could be used to improve our understanding of peripheral nerve anatomy and physiology. The ability to utilize ambient mass spectrometry techniques in real time could also provide an unprecedented advantage for surgical decision making, including in nerve‐sparing procedures in the future.

This study introduces a combination of mass spectrometry-based analytical approaches with little or no sample preparation for the study of zebrafish (Danio rerio) lipid metabolism during early development (0 through 96 h post-fertilization, hpf). Desorption electrospray ionization mass spectrometry (DESI-MS) imaging and nanoelectrospray (nESI) MS were used. Embryos (N = 107) were placed onto filter paper squares and analysed by DESI-MS imaging. Embryos were arranged in rows with each one corresponding to a different developmental time, so that each DESI-MS image contained arrays of samples at different hpf. After completion of DESI-MS acquisition, the arrays were cut into strips of paper, isolating each embryo, which was subsequently inserted into a nESI tip and analysed. All experiments were performed using a linear ion trap mass spectrometer. DESI-MS images were acquired in the positive ion mode using acetonitrile doped with 10 ppm AgNO3, which allowed for the detection of cytosolic neutral lipids, such as cholesteryl esters (CE), diacylglicerols (DAG), triacylglycerols (TAG), squalene, and ubiquinone. For the nESI, experiments were run in full mass scan and MS/MS, in both negative and positive ion mode, using a mixture of dimethylformamide and acetonitrile to detect membrane phospholipids (e.g. phosphatidylcholines and phosphatidylglycerols). Principal component analysis was used to explore DESI-MS images and nESI data in an unsupervised fashion. The combination of DESI-MS imaging, providing chemical and spatial location, and nanoESI, providing a broader and more extensive structural information, showed that the lipid content changes dramatically over the first days of development. Accumulation of DAG and TAG, which are usually concentrated in the embryos yolk sac as an important storage for early development, were observed between 0 and 48 hpf. Embryos at the intermediate phase of development (24 hpf) were distributed between those of 0 and 48 hpf, reflecting the dynamics associated with development and might be correlated with TAG consumption and de novo synthesis. After 72 and 96 hpf, samples differed from prior developmental stages by the content of squalene, ubiquinone, and CE 22 : 5 (overexpressed), while the TAG content decreased. Further decrease of TAGs and ubiquinone occurred between 72 and 96 hpf. These observations indicated that zebrafish embryos rely entirely on the yolk sac for the nutrients needed to sustain growth and survival during the first four days of development. Yolk lipids are the likely source of TAGs, as well as cholesterol, a required component of cell membranes and a precursor for bile acids. The abundance of ubiquinone can be tied to zebrafish embryo growth, differentiation and organogenesis, and activation of mitochondria.

Innovations in spatial omics technologies applied to human tissues have led to breakthrough discoveries in various diseases, including cancer. Two of these approaches—spatial transcriptomics and spatial metabolomics—have blossomed independently, fueled by technologies such as spatial transcriptomics (ST) and mass spectrometry imaging (MSI). Although powerful, these technologies only offer insights into the spatial distributions of restricted classes of molecules and have not yet been integrated to provide more holistic insights into biological questions. These techniques can be performed on adjacent serial sections from the same sample, but section‐to‐section variability can convolute data integration. We present a novel method combining desorption electrospray ionization mass spectrometry imaging (DESI‐MSI) spatial metabolomics and Visium spatial transcriptomics on the same tissue sections. We show that RNA quality is maintained after performing DESI‐MSI on a tissue under ambient conditions and that ST data is unperturbed following DESI‐MSI. We demonstrate this workflow on human breast and lung cancer tissues and identify novel correlations between metabolites and mRNA transcripts in cancer‐specific tissue regions.

The roots and rhizomes of Curcuma longa L. serve as distinct traditional Chinese medicines with varying therapeutic effects, likely attributed to differences in the accumulation and distribution of metabolites in these parts. The study aims to investigate the differences and spatial distribution patterns of metabolites in C. longa L. roots and rhizomes. Metabolite analysis of roots and rhizomes was conducted using ultra-high-performance liquid chromatography-quadruple orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) combined with desorption electrospray ionization mass spectrometry imaging (DESI-MSI). Using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to screen for differential metabolites. The relative contents of differential metabolites were visualized using heat maps. Additionally, the spatial distribution of differential metabolites was analyzed based on DESI-MSI. A total of 49 main chemical components were identified in roots and rhizomes using UHPLC-Q-Orbitrap HRMS. Through nontargeted metabolomics analysis combining UHPLC-Q-Orbitrap HRMS with PCA and OPLS-DA, 24 differential markers were identified; Additionally, using DESI-MSI alongside PCA and OPLS-DA, 18 differential markers were selected. Based on the DESI-MSI results, curcuminoids and sesquiterpenoids, including bisdemethoxycurcumin, demethoxycurcumin, furanodienone, furanogermenone, furanodiene, β-elemene, and curzerene, were more abundant in the rhizomes compared to the roots. And these differential compounds exhibited spatial distribution differences in the epidermis, phloem, and xylem between the roots and rhizomes. The metabolomics analysis using UHPLC-Q-Orbitrap HRMS combined with DESI-MSI suggest differences in the accumulation and spatial distribution of metabolites in C. longa L. roots and rhizomes, possibly related to the biosynthesis of secondary metabolites.

We report a technique for the noninvasive detection of skin cancer by imprint desorption electrospray ionization mass spectrometry imaging (DESI-MSI) using a transfer agent that is pressed against the tissue of interest. By noninvasively pressing a tape strip against human skin, metabolites, fatty acids, and lipids on the skin surface are transferred to the tape with little spatial distortion. Running DESI-MSI on the tape strip provides chemical images of the molecules on the skin surface, which are valuable for distinguishing cancer from healthy skin. Chemical components of the tissue imprint on the tape strip and the original basal cell carcinoma (BCC) section from the mass spectra show high consistency. By comparing MS images (about 150-μm resolution) of same molecules from the tape strip and from the BCC section, we confirm that chemical patterns are successfully transferred to the tape stripe. We also used the technique to distinguish cherry angiomas from normal human skin by comparing the molecular patterns from a tape strip. These results demonstrate the potential of the imprint DESI-MSI technique for the noninvasive detection of skin cancers as well as other skin diseases before and during clinical surgery.