Spatiotemporal metabolic responses to water deficit stress in distinct leaf cell-types of poplar

The impact of water-deficit (WD) stress on plant metabolism has been predominantly studied at the whole tissue level. However, plant tissues are made of several distinct cell types with unique and differentiated functions, which limits whole tissue 'omics'-based studies to determine only an averaged molecular signature arising from multiple cell types. Advancements in spatial omics technologies provide an opportunity to understand the molecular mechanisms underlying plant responses to WD stress at distinct cell-type levels. Here, we studied the spatiotemporal metabolic responses of two poplar (Populus tremula× P. alba) leaf cell types -palisade and vascular cells- to WD stress using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI). We identified unique WD stress-mediated metabolic shifts in each leaf cell type when exposed to early and prolonged WD stresses and recovery from stress. During water-limited conditions, flavonoids and phenolic metabolites were exclusively accumulated in leaf palisade cells. However, vascular cells mainly accumulated sugars and fatty acids during stress and recovery conditions, respectively, highlighting the functional divergence of leaf cell types in response to WD stress. By comparing our MALDI-MSI metabolic data with whole leaf tissue gas chromatography-mass spectrometry (GC-MS)-based metabolic profile, we identified only a few metabolites including monosaccharides, hexose phosphates, and palmitic acid that showed a similar accumulation trend at both cell-type and whole leaf tissue levels. Overall, this work highlights the potential of the MSI approach to complement the whole tissue-based metabolomics techniques and provides a novel spatiotemporal understanding of plant metabolic responses to WD stress. This will help engineer specific metabolic pathways at a cellular level in strategic perennial trees like poplars to help withstand future aberrations in environmental conditions and to increase bioenergy sustainability.

Mass spectrometry imaging of metals in tissues and cells: Methods and biological applications

BACKGROUND

Metals are pervasive throughout biological processes, where they play essential structural and catalytic roles. Metals can also exhibit deleterious effects on human health. Powerful analytical techniques, such as mass spectrometry imaging (MSI), are required to map metals due to their low concentrations within biological tissue.

SCOPE OF REVIEW

This Mini Review focuses on key MSI technology that can image metal distributions in situ, describing considerations for each technique (e.g., resolution, sensitivity, etc.). We highlight recent work using MSI for mapping trace metals in tissues, detecting metal-based drugs, and simultaneously imaging metals and biomolecules.

MAJOR CONCLUSIONS

MSI has enabled significant advances in locating bioactive metals at high spatial resolution and correlating their distributions with that of biomolecules. The use of metal-based immunochemistry has enabled simultaneous high-throughput protein and biomolecule imaging.

GENERAL SIGNIFICANCE

The techniques and examples described herein can be applied to many biological questions concerning the important biological roles of metals, metal toxicity, and localization of metal-based drugs.

Mass spectrometry imaging of natural carbonyl products directly from agar-based microbial interactions using 4-APEBA derivatization

Aliphatic carboxylic acids, aldehydes, and ketones play diverse roles in microbial adaptation to their microenvironment, from excretion as toxins to adaptive metabolites for membrane fluidity. However, the spatial distribution of these molecules throughout biofilms and how microbes in these environments exchange these molecules remain elusive for many of these bioactive species due to inefficient molecular imaging strategies. Herein, we apply on-tissue chemical derivatization (OTCD) using 4-(2-((4-bromophenethyl)dimethylammonio)ethoxy)benzenaminium dibromide (4-APEBA) on a co-culture of a soil bacterium (Bacillus subtilis NCIB 3610) and fungus (Fusarium sp. DS 682) grown on agar as our model system. Using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), we spatially resolved more than 300 different metabolites containing carbonyl groups within this model system. Various spatial patterns are observable in these species, which indicate possible extracellular or intercellular processes of the metabolites and their up- or downregulation during microbial interaction. The unique chemistry of our approach allowed us to bring additional confidence in accurate carbonyl identification, especially when multiple isomeric candidates were possible, and this provided the ability to generate hypotheses about the potential role of some aliphatic carbonyls in this B. subtilis/Fusarium sp. interaction. The results shown here demonstrate the utility of 4-ABEBA-based OTCD MALDI-MSI in probing interkingdom interactions directly from microbial co-cultures, and these methods will enable future microbial interaction studies with expanded metabolic coverage.IMPORTANCEThe metabolic profiles within microbial biofilms and interkingdom interactions are extremely complex and serve a variety of functions, which include promoting colonization, growth, and survival within competitive and symbiotic environments. However, measuring and differentiating many of these molecules, especially in an in situ fashion, remains a significant analytical challenge. We demonstrate a chemical derivatization strategy that enabled highly sensitive, multiplexed mass spectrometry imaging of over 300 metabolites from a model microbial co-culture. Notably, this approach afforded us to visualize over two dozen classes of ketone-, aldehyde-, and carboxyl-containing molecules, which were previously undetectable from colonies grown on agar. We also demonstrate that this chemical derivatization strategy can enable the discrimination of isobaric and isomeric metabolites without the need for orthogonal separation (e.g., online chromatography or ion mobility). We anticipate that this approach will further enhance our knowledge of metabolic regulation within microbiomes and microbial systems used in bioengineering applications.

Applying Multimodal Mass Spectrometry to Image Tumors Undergoing Ferroptosis Following In Vivo Treatment with a Ferroptosis Inducer

Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer. The poor prognosis generally associated with this disease has led to the search for improved therapies such as ferroptosis-inducing agents. Ferroptosis is a form of regulated cell death that is dependent on iron and is characterized by lipid peroxidation. Precise mapping of lipids and iron within tumors exposed to ferroptosis-inducing agents may provide insight into processes of ferroptosis in vivo and ultimately assist in the optimal deployment of ferroptosis inducers in cancer therapy. In this work, we present a method for combining matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) with secondary ion mass spectrometry (SIMS) to analyze changes in spatial lipidomics and metal composition, respectively, in ovarian tumors following exposure to a ferroptosis inducer. Tumors were obtained by injecting human ovarian cancer tumor-initiating cells into mice, followed by treatment with the ferroptosis inducer erastin. SIMS imaging detected iron accumulation in the tumor tissue, and sequential MALDI-MS imaging of the same tissue section displayed two chemically distinct regions of lipids. One region was associated with the iron-rich area detected with SIMS, and the other region encompassed the remainder of the tissue section. Bulk lipidomics confirmed the lipid assignments putatively assigned from the MALDI-MS data. Overall, we demonstrate the ability of multimodal MSI to identify the spatial locations of iron and lipids in the same tissue section and associate these regions with clinical pathology.

Atomistic simulations for investigation of substrate and salt effects on lipid in-source fragmentation in secondary ion mass spectrometry: A follow-up study

In-source fragmentation (ISF) poses a significant challenge in secondary ion mass spectrometry (SIMS). These fragment ions increase the spectral complexity and can lead to incorrect annotation of fragments as intact species. The presence of salt that is ubiquitous in biological samples can influence the fragmentation and ionization of analytes in a significant manner, but their influences on SIMS have not been well characterized. To elucidate the effect of substrates and salt on ISF in SIMS, we have employed experimental SIMS in combination with atomistic simulations of a sphingolipid on a gold surface with various NaCl concentrations as a model system. Our results revealed that a combination of bond dissociation energy and binding energy between N-palmitoyl-sphingomyelin and a gold surface is a good predictor of fragment ion intensities in the absence of salt. However, ion-fragment interactions play a significant role in determining fragment yields in the presence of salt. Additionally, the charge distribution on fragment species may be a major contributor to the varying effects of salt on fragmentation. This study demonstrates that atomistic modeling can help predict ionization potential when salts are present, providing insights for more accurate interpretations of complex biological spectra.

Functionally discrete fine roots differ in microbial assembly, microbial functional potential, and produced metabolites

Traditionally, fine roots were grouped using arbitrary size categories, rarely capturing the heterogeneity in physiology, morphology and functionality among different fine root orders. Fine roots with different functional roles are rarely separated in microbiome-focused studies and may result in confounding microbial signals and host-filtering across different root microbiome compartments. Using a 26-year-old common garden, we sampled fine roots from four temperate tree species that varied in root morphology and sorted them into absorptive and transportive fine roots. The rhizoplane and rhizosphere were characterized using 16S rRNA gene and internal transcribed spacer region amplicon sequencing and shotgun metagenomics for the rhizoplane to identify potential microbial functions. Fine roots were subject to metabolomics to spatially characterize resource availability. Both fungi and bacteria differed according to root functional type. We observed additional differences between the bacterial rhizoplane and rhizosphere compartments for absorptive but not transportive fine roots. Rhizoplane bacteria, as well as the root metabolome and potential microbial functions, differed between absorptive and transportive fine roots, but not the rhizosphere bacteria. Functional differences were driven by sugar transport, peptidases and urea transport. Our data highlights the importance of root function when examining root-microbial relationships, emphasizing different host selective pressures imparted on different root microbiome compartments.

Fungal organic acid uptake of mineral-derived K is dependent on distance from carbon hotspot

IMPORTANCE

Fungal species are foundational members of soil ecosystems with vital contributions that support interspecies resource translocation. The minute details of these biogeochemical processes are poorly investigated. Here, we addressed this knowledge gap by probing fungal growth in a novel mineral-doped soil micromodel platform using spatially-resolved imaging methodologies. We found that fungi uptake K from K-rich minerals using organic acids exuded in a distance-dependent manner from a carbon-rich hotspot. While identification of specific mechanisms within soil remains challenging, our findings demonstrate the significance of reduced complexity platforms such as the mineral-doped micromodel in probing biogeochemical processes. These findings provide visualization into hyphal uptake and transport of mineral-derived nutrients in a resource-limited environment.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Extensive cellular multi-tasking within Bacillus subtilis biofilms

Bacillus subtilis is a soil-dwelling bacterium that can form biofilms, or communities of cells surrounded by a self-produced extracellular matrix. In biofilms, genetically identical cells often exhibit heterogeneous transcriptional phenotypes, so that subpopulations of cells carry out essential yet costly cellular processes that allow the entire population to thrive. Surprisingly, the extent of phenotypic heterogeneity and the relationships between subpopulations of cells within biofilms of even in well-studied bacterial systems like B. subtilis remains largely unknown. To determine relationships between these subpopulations of cells, we created 182 strains containing pairwise combinations of fluorescent transcriptional reporters for the expression state of 14 different genes associated with potential cellular subpopulations. We determined the spatial organization of the expression of these genes within biofilms using confocal microscopy, which revealed that many reporters localized to distinct areas of the biofilm, some of which were co-localized. We used flow cytometry to quantify reporter co-expression, which revealed that many cells "multi-task," simultaneously expressing two reporters. These data indicate that prior models describing B. subtilis cells as differentiating into specific cell types, each with a specific task or function, were oversimplified. Only a few subpopulations of cells, including surfactin and plipastatin producers, as well as sporulating and competent cells, appear to have distinct roles based on the set of genes examined here. These data will provide us with a framework with which to further study and make predictions about the roles of diverse cellular phenotypes in B. subtilis biofilms. IMPORTANCE Many microbes differentiate, expressing diverse phenotypes to ensure their survival in various environments. However, studies on phenotypic differentiation have typically examined only a few phenotypes at one time, thus limiting our knowledge about the extent of differentiation and phenotypic overlap in the population. We investigated the spatial organization and gene expression relationships for genes important in B. subtilis biofilms. In doing so, we mapped spatial gene expression patterns and expanded the number of cell populations described in the B. subtilis literature. It is likely that other bacteria also display complex differentiation patterns within their biofilms. Studying the extent of cellular differentiation in other microbes may be important when designing therapies for disease-causing bacteria, where studying only a single phenotype may be masking underlying phenotypic differentiation relevant to infection outcomes.

Expanded Coverage of Phytocompounds by Mass Spectrometry Imaging Using On-Tissue Chemical Derivatization by 4-APEBA

Probing the entirety of any species metabolome is an analytical grand challenge, especially on a cellular scale. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a common spatial metabolomics assay, but this technique has limited molecular coverage for several reasons. To expand the application space of spatial metabolomics, we developed an on-tissue chemical derivatization (OTCD) workflow using 4-APEBA for the confident identification of several dozen elusive phytocompounds. Overall, this new OTCD method enabled the annotation of roughly 280 metabolites, with only a 10% overlap in metabolic coverage when compared to analog negative ion mode MALDI-MSI on serial sections. We demonstrate that 4-APEBA outperforms other derivatization agents by providing: (1) broad specificity toward carbonyls, (2) low background, and (3) introduction of bromine isotopes. Notably, the latter two attributes also facilitate more confidence in our bioinformatics for data processing. The workflow detailed here trailblazes a path toward spatial hormonomics within plant samples, enhancing the detection of carboxylates, aldehydes, and plausibly other carbonyls. As such, several phytohormones, which have various roles within stress responses and cellular communication, can now be spatially profiled, as demonstrated in poplar root and soybean root nodule.

Experimental Assessment of Mammalian Lipidome Complexity Using Multimodal 21 T FTICR Mass Spectrometry Imaging

Herein, we assess the complementarity and complexity of data that can be detected within mammalian lipidome mass spectrometry imaging (MSI) via matrix-assisted laser desorption ionization (MALDI) and nanospray desorption electrospray ionization (nano-DESI). We do so by employing 21 T Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) with absorption mode FT processing in both cases, allowing unmatched mass resolving power per unit time (≥613k at m/z 760, 1.536 s transients). While our results demonstrated that molecular coverage and dynamic range capabilities were greater in MALDI analysis, nano-DESI provided superior mass error, and all annotations for both modes had sub-ppm error. Taken together, these experiments highlight the coverage of 1676 lipids and serve as a functional guide for expected lipidome complexity within nano-DESI-MSI and MALDI-MSI. To further assess the lipidome complexity, mass splits (i.e., the difference in mass between neighboring peaks) within single pixels were collated across all pixels from each respective MSI experiment. The spatial localization of these mass splits was powerful in informing whether the observed mass splits were biological or artificial (e.g., matrix related). Mass splits down to 2.4 mDa were observed (i.e., sodium adduct ambiguity) in each experiment, and both modalities highlighted comparable degrees of lipidome complexity. Further, we highlight the persistence of certain mass splits (e.g., 8.9 mDa; double bond ambiguity) independent of ionization biases. We also evaluate the need for ultrahigh mass resolving power for mass splits ≤4.6 mDa (potassium adduct ambiguity) at m/z > 1000, which may only be resolved by advanced FTICR-MS instrumentation.

On the importance of color in mass spectrometry imaging

Mass spectrometry imaging (MSI) data visualization relies on heatmaps to show the spatial distribution and measured abundances of molecules within a sample. Nonuniform color gradients such as jet are still commonly used to visualize MSI data, increasing the probability of data misinterpretation and false conclusions. Also, the use of nonuniform color gradients and the combination of hues used in common colormaps make it challenging for people with color vision deficiencies (CVDs) to visualize and accurately interpret data. Here we present best practices for choosing a colormap to accurately display MSI data, improve readability, and accommodate all CVDs. We also provide other resources on the misuse of color in the scientific field and resources on scientifically derived colormaps presented herein.

An optimized approach and inflation media for obtaining complimentary mass spectrometry-based omics data from human lung tissue

Human disease states are biomolecularly multifaceted and can span across phenotypic states, therefore it is important to understand diseases on all levels, across cell types, and within and across microanatomical tissue compartments. To obtain an accurate and representative view of the molecular landscape within human lungs, this fragile tissue must be inflated and embedded to maintain spatial fidelity of the location of molecules and minimize molecular degradation for molecular imaging experiments. Here, we evaluated agarose inflation and carboxymethyl cellulose embedding media and determined effective tissue preparation protocols for performing bulk and spatial mass spectrometry-based omics measurements. Mass spectrometry imaging methods were optimized to boost the number of annotatable molecules in agarose inflated lung samples. This optimized protocol permitted the observation of unique lipid distributions within several airway regions in the lung tissue block. Laser capture microdissection of these airway regions followed by high-resolution proteomic analysis allowed us to begin linking the lipidome with the proteome in a spatially resolved manner, where we observed proteins with high abundance specifically localized to the airway regions. We also compared our mass spectrometry results to lung tissue samples preserved using two other inflation/embedding media, but we identified several pitfalls with the sample preparation steps using this preservation method. Overall, we demonstrated the versatility of the inflation method, and we can start to reveal how the metabolome, lipidome, and proteome are connected spatially in human lungs and across disease states through a variety of different experiments.

Controlled Humidity Levels for Fine Spatial Detail Information in Enzyme-Assisted N-Glycan MALDI MSI

Investigation of the spatial distribution of N-glycans in tissue specimens has emerged as a powerful tool in clinical research, in part, because altered N-glycans are often a hallmark of disease progression. Mass spectrometry imaging of N-glycans relies on peptide N-glycanase spraying and tissue incubation for efficient in situ release of N-glycans from their carrier proteins. Unstandardized and uncontrolled incubation steps often cause significant delocalization of released N-glycans, resulting in the inability to link given N-glycan composition to a specific microanatomical region in the tissue. Herein, we optimized the incubation step to provide accurate and sensitive MALDI-MSI of N-glycans. Specifically, we tested saturated solutions of various salts that maintain constant relative humidity in the incubation chamber. We showed that the best performance was achieved using a saturated solution of KNO₃ that maintains an 89% RH. Under these conditions, near maximal sensitivity was achieved with the minutest ion delocalization, which we demonstrated at a 35 μm spatial resolution, where we observed six distinct spatial patterns that colocalize to distinct microanatomical compartments in a kidney nephrectomy tissue section.

A reference tissue atlas for the human kidney

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

Imaging and Direct Sampling Capabilities of Nanospray Desorption Electrospray Ionization with Absorption-Mode 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Nanospray desorption electrospray ionization mass spectrometry, a powerful ambient sampling and imaging technique, is herein coupled as an isolated source with 21 Tesla (21T) Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). Absorption-mode data, enabled by an external data acquisition system, is applied for improved mass resolution, accuracy, and dynamic range without compromising spectral acquisition rates. Isotopic fine structure (IFS) information is obtained from the ambient sampling of living Bacillus and Fusarium species, allowing for high confidence in molecular annotations with a resolution >830 k (at m/z 825). Tandem mass spectrometry experiments for biological samples are shown to retain the IFS in addition to gained fragmentation information, providing a further degree of annotation confidence from ambient analyses. Rat brain was imaged by nanospray desorption electrospray ionization (nano-DESI) 21T FTICR MS in ∼5 h using 768 ms transients, producing over 800 molecular annotations using the METASPACE platform and low-parts-per-billion mass accuracy at a spatial resolution of ∼25 × 180 μm. Finally, nano-DESI 21T FTICR MS imaging is demonstrated to reveal images corresponding to the IFS, as well as hundreds of additional molecular features (including demonstrated differences as low as 8.96 mDa) that are otherwise undetected by a more conventional imaging methodology.

Review of the Third Conference of the Imaging Mass Spectrometry Society (IMSS 3): Accounts of a Hybrid Virtual and In-Person Meeting and the State and Future of the Field

The third annual conference of the Imaging Mass Spectrometry Society (IMSS3) was held October 3-6, 2021 in a hybrid format that included virtual and in-person attendance (Colorado Springs, CO). Here, we highlight many of the methods and applications presented, the state of the field, and some insights into the emerging areas in the field of imaging mass spectrometry. We also reflect upon the processes behind planning a hybrid conference and discuss the successes and challenges of the event in retrospect.

Elucidating Drought-Tolerance Mechanisms in Plant Roots through 1H NMR Metabolomics in Parallel with MALDI-MS, and NanoSIMS Imaging Techniques

As direct mediators between plants and soil, roots play an important role in metabolic responses to environmental stresses such as drought, yet these responses are vastly uncharacterized on a plant-specific level, especially for co-occurring species. Here, we aim to examine the effects of drought on root metabolic profiles and carbon allocation pathways of three tropical rainforest species by combining cutting-edge metabolomic and imaging technologies in an in situ position-specific ¹³C-pyruvate root-labeling experiment. Further, washed (rhizosphere-depleted) and unwashed roots were examined to test the impact of microbial presence on root metabolic pathways. Drought had a species-specific impact on the metabolic profiles and spatial distribution in Piper sp. and Hibiscus rosa sinensis roots, signifying different defense mechanisms; Piper sp. enhanced root structural defense via recalcitrant compounds including lignin, while H. rosa sinensis enhanced biochemical defense via secretion of antioxidants and fatty acids. In contrast, Clitoria fairchildiana, a legume tree, was not influenced as much by drought but rather by rhizosphere presence where carbohydrate storage was enhanced, indicating a close association with symbiotic microbes. This study demonstrates how multiple techniques can be combined to identify how plants cope with drought through different drought-tolerance strategies and the consequences of such changes on below-ground organic matter composition.

Single-Cell Metabolomics with Rapid Determination of Chemical Formulas from Isotopic Fine Structures

Metabolomic measurements can provide functional readouts of cellular states and phenotypes. Here, we present a protocol for single-cell metabolomics that permits direct untargeted detection of a broad number of metabolites under ambient conditions, without the need for sample processing, and with high confidence in the discovery and identification of the molecular formulas for detected metabolites. This protocol describes combining fiber-based laser ablation electrospray ionization (f-LAESI) with a 21 Tesla Fourier transform ion cyclotron resonance mass spectrometer (21T-FTICR-MS) to obtain high confidence molecular formula information about detected metabolites. The f-LAESI source utilizes mid-infrared laser ablation through a sharp optical fiber tip, affording direct ambient analysis of cells without the need for sample processing. Using the 21T-FTICR-MS as a mass analyzer enabled measurement of the isotopic fine structure (IFS) for numerous metabolites simultaneously from single cells, and the IFSs were in turn computationally processed to rapidly determine the corresponding elemental compositions. This metabolomics technique complements other single cell omics measurement methods, helping to resolve complex molecular interactions that take place within cells unattainable from single cell transcriptomic and proteomics methods.

Rapid Automated Annotation and Analysis of N-Glycan Mass Spectrometry Imaging Data Sets Using NGlycDB in METASPACE

Imaging N-glycan spatial distribution in tissues using mass spectrometry imaging (MSI) is emerging as a promising tool in biological and clinical applications. However, there is currently no high-throughput tool for visualization and molecular annotation of N-glycans in MSI data, which significantly slows down data processing and hampers the applicability of this approach. Here, we present how METASPACE, an open-source cloud engine for molecular annotation of MSI data, can be used to automatically annotate, visualize, analyze, and interpret high-resolution mass spectrometry-based spatial N-glycomics data. METASPACE is an emerging tool in spatial metabolomics, but the lack of compatible glycan databases has limited its application for comprehensive N-glycan annotations from MSI data sets. We created NGlycDB, a public database of N-glycans, by adapting available glycan databases. We demonstrate the applicability of NGlycDB in METASPACE by analyzing MALDI-MSI data from formalin-fixed paraffin-embedded (FFPE) human kidney and mouse lung tissue sections. We added NGlycDB to METASPACE for public use, thus, facilitating applications of MSI in glycobiology.

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.

Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution

Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging method that has the potential to transform the field of metabolomics. This is in part due to LAESI-MS being an ambient ionization method that requires minimal sample preparation and uses (endogenous) water for in situ analysis. This application note details the employment of the "LAESI microscope" source to perform spatially resolved MS analysis of cells and MS imaging (MSI) of tissues at high spatial resolution. This source configuration utilizes a long-working-distance reflective objective that permits both visualization of the sample and a smaller LAESI laser beam profile than conventional LAESI setups. Here, we analyzed 200 single cells of Allium cepa (red onion) and imaged Fittonia argyroneura (nerve plant) in high spatial resolution using this source coupled to a Fourier transform mass spectrometer for high-mass-resolution and high-mass-accuracy metabolomics.

SubTap, a Versatile 3D Printed Platform for Eavesdropping on Extracellular Interactions

Communication within the microbiome occurs through an immense diversity of small molecules. Capturing these microbial interactions is a significant challenge due to the complexity of the exometabolome and its sensitivity to environmental stimuli. Traditional methods for acquiring exometabolomic data from interacting microorganisms are limited by their low throughput or lack of sampling depth. To address this challenge, we introduce subtapping (short for substrate tapping), a technique for tapping into extracellular metabolites that are being transferred through the growth substrate during coculture. High-throughput subtapping is made possible by a new coculturing platform, named SubTap, that we engineered to resemble a 96-well plate. The three-dimensional (3D) printed SubTap platform captures the exometabolome in an agar compartment that connects physically separated growth chambers, which permits cell growth without competition for space. We show how SubTap facilitates replicable and quick detection of exometabolites via direct infusion mass spectrometry analysis. Using bacterial isolates from the soil, we apply SubTap to characterize the effects of growth medium, growth duration, and mixed versus unmixed coculturing on the exometabolome. Finally, we demonstrate SubTap's versatility by interrogating microbial interactions in multicultures with up to four strains. IMPORTANCE Improvements in experimental techniques and instrumentation have led to the discovery that the microbiome plays an essential role in human and environmental health. Nevertheless, there remain major impediments to conducting large-scale interrogations of the microbiome in a high-throughput manner, particularly in the field of exometabolomics. Existing methods to coculture microorganisms and interrogate their interactions are labor-intensive and low throughput. This inspired us to develop a solution for coculturing that was (i) open source, (ii) inexpensive, (iii) scalable, (iv) customizable, and (v) compatible with existing mass spectrometry instrumentation. Here, we present SubTap-a 3D printed coculturing platform that permits tapping directly into the growth substrate between physically separated, but interconnected, growth compartments. SubTap allows multiculture (with up to four distinct growth compartments) in spatially mixed or unmixed configurations and enables repeatable results with mass spectrometry, as shown by our validation with known compounds and cultures of one to four organisms.

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Preserved and variable spatial-chemical changes of lipids across tomato leaves in response to central vein wounding reveals potential origin of linolenic acid in signal transduction cascade

Membrane lipids serve as substrates for the generation of numerous signaling lipids when plants are exposed to environmental stresses, and jasmonic acid, an oxidized product of 18-carbon unsaturated fatty acids (e.g., linolenic acid), has been recognized as the essential signal in wound-induced gene expression. Yet, the contribution of individual membrane lipids in linolenic acid generation is ill-defined. In this work, we performed spatial lipidomic experiments to track lipid changes that occur locally at the sight of leaf injury to better understand the potential origin of linolenic and linoleic acids from individual membrane lipids. The central veins of tomato leaflets were crushed using surgical forceps, leaves were cryosectioned and analyzed by two orthogonal matrix-assisted laser desorption/ionization mass spectrometry imaging platforms for insight into lipid spatial distribution. Significant changes in lipid composition are only observed 30 min after wounding, while after 60 min lipidome homeostasis has been re-established. Phosphatidylcholines exhibit a variable pattern of spatial behavior in individual plants. Among lysolipids, lysophosphatidylcholines strongly co-localize with the injured zone of wounded leaflets, while, for example, lysophosphatidylglycerol (LPG) (16:1) accumulated preferentially toward the apex in the injured zone of wounded leaflets. In contrast, two other LPGs (LPG [18:3] and LPG [18:2]) are depleted in the injured zone. Our high-resolution co-localization imaging analyses suggest that linolenic acids are predominantly released from PCs with 16_18 fatty acid composition along the entire leaf, while it seems that in the apex zone PG (16:1_18:3) significantly contributes to the linolenic acid pool. These results also indicate distinct localization and/or substrate preferences of phospholipase isoforms in leaf tissue.

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

Storage Conditions of Human Kidney Tissue Sections Affect Spatial Lipidomics Analysis Reproducibility

Lipids often are labile, unstable, and tend to degrade overtime, so it is of the upmost importance to study these molecules in their most native state. We sought to understand the optimal storage conditions for spatial lipidomic analysis of human kidney tissue sections. Specifically, we evaluated human kidney tissue sections on several different days throughout the span of a week using our established protocol for elucidating lipids using high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We studied kidney tissue sections stored under five different conditions: open stored at -80 °C, vacuumed sealed and stored at -80 °C, with matrix preapplied before storage at -80 °C, under a nitrogen atmosphere and stored at -80 °C, and at room temperature in a desiccator. Results were compared to data obtained from kidney tissue sections that were prepared and analyzed immediately after cryosectioning. Data was processed using METASPACE. After a week of storage, the sections stored at room temperature showed the largest amount of lipid degradation, while sections stored under nitrogen and at -80 °C retained the greatest number of overlapping annotations in relation to freshly cut tissue. Overall, we found that molecular degradation of the tissue sections was unavoidable over time, regardless of storage conditions, but storing tissue sections in an inert gas at low temperatures can curtail molecular degradation within tissue sections.

Activity-Based Protein Profiling of Chitin Catabolism

The microbial catabolism of chitin, an abundant and ubiquitous environmental organic polymer, is a fundamental cog in terrestrial and aquatic carbon and nitrogen cycles. Despite the importance of this critical bio-geochemical function, there is a limited understanding of the synergy between the various hydrolytic and accessory enzymes involved in chitin catabolism. To address this deficit, we synthesized activity-based probes (ABPs) designed to target active chitinolytic enzymes by modifying the chitin subunits N-acetyl glucosamine and chitotriose. The ABPs were used to determine the active complement of chitinolytic enzymes produced over time by the soil bacterium Cellvibrio japonicus treated with various C substrates. We demonstrate the utility of these ABPs in determining the synergy between various enzymes involved in chitin catabolism. The strategy can be used to gain molecular-level insights that can be used to better understand microbial roles in soil bio-geochemical cycling in the face of a changing climate.

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

Metabolomic profiling of wild-type and mutant soybean root nodules using laser-ablation electrospray ionization mass spectrometry reveals altered metabolism

The establishment of the nitrogen-fixing symbiosis between soybean and Bradyrhizobium japonicum is a complex process. To document the changes in plant metabolism as a result of symbiosis, we utilized laser ablation electrospray ionization-mass spectrometry (LAESI-MS) for in situ metabolic profiling of wild-type nodules, nodules infected with a B. japonicum nifH mutant unable to fix nitrogen, nodules doubly infected by both strains, and nodules formed on plants mutated in the stearoyl-acyl carrier protein desaturase (sacpd-c) gene, which were previously shown to have an altered nodule ultrastructure. The results showed that the relative abundance of fatty acids, purines, and lipids was significantly changed in response to the symbiosis. The nifH mutant nodules had elevated levels of jasmonic acid, correlating with signs of nitrogen deprivation. Nodules resulting from the mixed inoculant displayed similar, overlapping metabolic distributions within the sectors of effective (fix+ ) and ineffective (nifH mutant, fix- ) endosymbionts. These data are inconsistent with the notion that plant sanctioning is cell autonomous. Nodules lacking sacpd-c displayed an elevation of soyasaponins and organic acids in the central necrotic regions. The present study demonstrates the utility of LAESI-MS for high-throughput screening of plant phenotypes. Overall, nodules disrupted in the symbiosis were elevated in metabolites related to plant defense.

Deep learning predicts microbial interactions from self-organized spatiotemporal patterns

Microbial communities organize into spatial patterns that are largely governed by interspecies interactions. This phenomenon is an important metric for understanding community functional dynamics, yet the use of spatial patterns for predicting microbial interactions is currently lacking. Here we propose supervised deep learning as a new tool for network inference. An agent-based model was used to simulate the spatiotemporal evolution of two interacting organisms under diverse growth and interaction scenarios, the data of which was subsequently used to train deep neural networks. For small-size domains (100 µm × 100 µm) over which interaction coefficients are assumed to be invariant, we obtained fairly accurate predictions, as indicated by an average R2 value of 0.84. In application to relatively larger domains (450 µm × 450 µm) where interaction coefficients are varying in space, deep learning models correctly predicted spatial distributions of interaction coefficients without any additional training. Lastly, we evaluated our model against real biological data obtained using Pseudomonas fluorescens and Escherichia coli co-cultures treated with polymeric chitin or N-acetylglucosamine, the hydrolysis product of chitin. While P. fluorescens can utilize both substrates for growth, E. coli lacked the ability to degrade chitin. Consistent with our expectations, our model predicted context-dependent interactions across two substrates, i.e., degrader-cheater relationship on chitin polymers and competition on monomers. The combined use of the agent-based model and machine learning algorithm successfully demonstrates how to infer microbial interactions from spatially distributed data, presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Single-Cell Metabolic Profiling: Metabolite Formulas from Isotopic Fine Structures in Heterogeneous Plant Cell Populations

Characterization of the metabolic heterogeneity in cell populations requires the analysis of single cells. Most current methods in single-cell analysis rely on cell manipulation, potentially altering the abundance of metabolites in individual cells. A small sample volume and the chemical diversity of metabolites are additional challenges in single-cell metabolomics. Here, we describe the combination of fiber-based laser ablation electrospray ionization (f-LAESI) with 21 T Fourier transform ion cyclotron resonance mass spectrometry (21TFTICR-MS) for in situ single-cell metabolic profiling in plant tissue. Single plant cells infected by bacteria were selected and sampled directly from the tissue without cell manipulation through mid-infrared ablation with a fine optical fiber tip for ionization by f-LAESI. Ultrahigh performance 21T-FTICR-MS enabled the simultaneous capture of isotopic fine structures (IFSs) for 47 known and 11 unknown compounds, thus elucidating their elemental compositions from single cells and providing information on metabolic heterogeneity in the cell population.

Sequential Ammonia and Carbon Dioxide Adsorption on Pyrolyzed Biomass to Recover Waste Stream Nutrients

The amine-rich surfaces of pyrolyzed human solid waste (py-HSW) can be "primed" or "regenerated" with carbon dioxide (CO₂) to enhance their adsorption of ammonia (NH₃) for use as a soil amendment. To better understand the mechanism by which CO₂ exposure facilitates NH₃ adsorption to py-HSW, we artificially enriched a model sorbent, pyrolyzed, oxidized wood (py-ox wood) with amine functional groups through exposure to NH₃. We then exposed these N-enriched materials to CO₂ and then resorbed NH₃. The high heat of CO₂ adsorption (Q _st) on py-HSW, 49 kJ mol^-1, at low surface coverage, 0.4 mmol CO₂ g^-1, showed that the naturally occurring N compounds in py-HSW have a high affinity for CO₂. The Q _st of CO₂ on py-ox wood also increased after exposure to NH₃, reaching 50 kJ mol^-1 at 0.7 mmol CO₂ g^-1, demonstrating that the incorporation of N-rich functional groups by NH₃ adsorption is favorable for CO₂ uptake. Adsorption kinetics of py-ox wood revealed continued, albeit diminishing NH₃ uptake after each CO₂ treatment, averaging 5.9 mmol NH₃ g^-1 for the first NH₃ exposure event and 3.5 and 2.9 mmol NH₃ g^-1 for the second and third; the electrophilic character of CO₂ serves as a Lewis acid, enhancing surface affinity for NH₃ uptake. Furthermore, penetration of ¹⁵NH₃ and ¹³CO₂ measured by NanoSIMS reached over 7 μm deep into both materials, explaining the large NH₃ capture. We expected similar NH₃ uptake in py-HSW sorbed with CO₂ and py-ox wood because both materials, py-HSW and py-ox wood sorbed with NH₃, had similar N contents and similarly high CO₂ uptake. Yet NH₃ sorption in py-HSW was unexpectedly low, apparently from potassium (K) bicarbonate precipitation, reducing interactions between NH₃ and sorbed CO₂; 2-fold greater surface K in py-HSW was detected after exposure to CO₂ and NH₃ than before gas exposure. We show that amine-rich pyrolyzed waste materials have high CO₂ affinity, which facilitates NH₃ uptake. However, high ash contents as found in py-HSW hinder this mechanism.

An approach for visualizing the spatial metabolome of an entire plant root system inspired by the Swiss-rolling technique

The spatial configuration and morphology of roots are commonly monitored for a better understanding of plant health and development. However, this approach provides minimal details about the biochemistry regulating the observable traits. Therefore, the ability to metabolically map the entire root structure would be of major value. Here, we developed a sample preparation approach that enables imaging of the entire root within a restricted space (width of microscope slide), which was influenced by the Swiss-rolling technique. We were able to image and confidently identify molecules along the entire root structure from rolled-root tissue sections using multiple spatially resolved mass spectrometry approaches.

Response Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging

Automated spraying devices have become ubiquitous in laboratories employing matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), in part because they permit control of a number of matrix application parameters that can easily be reproduced for intra- and interlaboratory studies. Determining the optimal parameters for MALDI matrix application, such as temperature, flow rate, spraying velocity, number of spraying cycles, and solvent composition for matrix application, is critical for obtaining high-quality MALDI-MSI data. However, there are no established approaches for optimizing these multiple parameters simultaneously. Instead optimization is performed iteratively (i.e., one parameter at a time), which is time-consuming and can lead to overall nonoptimal settings. In this report, we demonstrate the use a novel experimental design and the response surface methodology to optimize five parameters of MALDI matrix application using a robotic sprayer. Thirty-two combinations of MALDI matrix spraying conditions were tested, which allowed us to elucidate relationships between each of the application parameters as determined by MALDI-MS (specifically, using a 15 T Fourier transform ion cyclotron resonance mass spectrometer). As such, we were able to determine the optimal automated spraying parameters that minimized signal delocalization and enabled high MALDI sensitivity. We envision this optimization strategy can be utilized for other matrix application approaches and MALDI-MSI analyses of other molecular classes and tissue types.

In-Situ Metabolomic Analysis of Setaria viridis Roots Colonized by Beneficial Endophytic Bacteria

Over the past decades, crop yields have risen in parallel with increasing use of fossil fuel-derived nitrogen (N) fertilizers but with concomitant negative impacts on climate and water resources. There is a need for more sustainable agricultural practices, and biological nitrogen fixation (BNF) could be part of the solution. A variety of nitrogen-fixing, epiphytic, and endophytic plant growth-promoting bacteria (PGPB) are known to stimulate plant growth. However, compared with the rhizobium-legume symbiosis, little mechanistic information is available as to how PGPB affect plant metabolism. Therefore, we investigated the metabolic changes in roots of the model grass species Setaria viridis upon endophytic colonization by Herbaspirillum seropedicae SmR1 (fix⁺) or a fix^- mutant strain (SmR54) compared with uninoculated roots. Endophytic colonization of the root is highly localized and, hence, analysis of whole-root segments dilutes the metabolic signature of those few cells impacted by the bacteria. Therefore, we utilized in-situ laser ablation electrospray ionization mass spectrometry to sample only those root segments at or adjacent to the sites of bacterial colonization. Metabolites involved in purine, zeatin, and riboflavin pathways were significantly more abundant in inoculated plants, while metabolites indicative of nitrogen, starch, and sucrose metabolism were reduced in roots inoculated with the fix^- strain or uninoculated, presumably due to N limitation. Interestingly, compounds, involved in indole-alkaloid biosynthesis were more abundant in the roots colonized by the fix^- strain, perhaps reflecting a plant defense response.

DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules

INTRODUCTION

Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported.

OBJECTIVES

In this work, we employed an ambient desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) to characterize the metabolome in a mouse model of DKD.

METHODS

DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse models (F1 C57BL/6J-Ins2Akita male mice at 17 weeks of age) of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6).

RESULTS

Multivariate analyses (i.e., PCA and PLS-DA (a 2000 permutation test: P < 0.001)) showed clearly separated clusters for the two groups of mice on the basis of 878 measured m/z's in kidney cortical tissues. Specifically, mice with T1D had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls.

CONCLUSION

Results from the current study support potential key roles of pseudouridine and cardiolipins for maintaining normal RNA structure and normal mitochondrial function, respectively, in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE could serve as powerful new tools to provide insight on fundamental pathways in DKD.

Spatiotemporal Transformation in the Alkaloid Profile of Pinus Roots in Response to Mycorrhization

Root alkaloids remain highly unexplored in ectomycorrhizae development studies. By employing ultrahigh mass resolution mass spectrometry imaging techniques, we showed substantial relocation and transformation of piperidine alkaloids in pine root tips in response to Suillus mycorrhization. We imaged, in the time frame of ectomycorrhizae formation, a completely different alkaloid profile in Pinus strobus, where basidiospores of Suillus spraguei induce morphogenesis of symbiotic tissues, than in Pinus taeda, where such interaction fails to induce morphogenesis. On the basis of spatial colocalization studies, we proposed some alternative routes for biosynthesis of these alkaloids that supplement existing literature data.

Ambient Metabolic Profiling and Imaging of Biological Samples with Ultrahigh Molecular Resolution Using Laser Ablation Electrospray Ionization 21 Tesla FTICR Mass Spectrometry

Mass spectrometry (MS) is an indispensable analytical tool to capture the array of metabolites within complex biological systems. However, conventional MS-based metabolomic workflows require extensive sample processing and separation resulting in limited throughput and potential alteration of the native molecular states in these systems. Ambient ionization methods, capable of sampling directly from tissues, circumvent some of these issues but require high-performance MS to resolve the molecular complexity within these samples. Here, we demonstrate a unique combination of laser ablation electrospray ionization (LAESI) coupled with a 21 tesla Fourier transform ion cyclotron resonance (21T-FTICR) for direct MS analysis and imaging applications. This analytical platform provides isotopic fine structure information directly from biological tissues, enabling the rapid assignment of molecular formulas and delivering a higher degree of confidence for molecular identification.

Insights into the histology of planarian flatworm Phagocata gracilis based on location specific, intact lipid information provided by GCIB-ToF-SIMS imaging

Planarian flatworms are known as the masters of regeneration, re-growing an entire organism from as little as 1/279th part of their body. While the proteomics of these processes has been studied extensively, the planarian lipodome remains relatively unknown. In this study we investigate the lipid profile of planarian tissue sections with imaging Time-of-Flight - Secondary-Ion-Mass-Spectrometry (ToF-SIMS). ToF-SIMS is a label-free technique capable of gathering intact, location specific lipid information on a cellular scale. Lipid identities are confirmed using LC-MS/MS. Our data shows that different organ structures within planarians have unique lipid profiles. The 22-carbon atom poly unsaturated fatty acids (PUFAs) which occur in unusually high amounts in planarians are found to be mainly located in the testes. Additionally, we observe that planarians contain various odd numbered fatty acid species, that are usually found in bacteria, localized in the reproductive and ectodermal structures of the planarian. An abundance of poorly understood ether fatty acids and ether lipids were found in unique areas in planarians as well as a new, yet unidentified class of potential lipids in planarian intestines. Identifying the location of these lipids in the planarian body provides insights into their bodily functions and, in combination with knowledge about their diet and their genome, enables drawing conclusions about planarian fatty acid processing.

Towards resolving the spatial metabolome with unambiguous molecular annotations in complex biological systems by coupling mass spectrometry imaging with structures for lossless ion manipulations

We demonstrate the coupling of liquid extraction surface analysis (LESA) to structures for lossless ion manipulations in conjunction with serpentine ultralong path with extending routing (SLIM SUPER) ion mobility-mass spectrometry (IM-MS) for the unambiguous annotation of important isomeric glycoforms in carbon-fixing communities.

Observed metabolic asymmetry within soybean root nodules reflects unexpected complexity in rhizobacteria-legume metabolite exchange

In this study, the three-dimensional spatial distributions of a number of metabolites involved in regulating symbiosis and biological nitrogen fixation (BNF) within soybean root nodules were revealed using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). While many metabolites exhibited distinct spatial compartmentalization, some metabolites were asymmetrically distributed throughout the nodule (e.g., S-adenosylmethionine). These results establish a more complex metabolic view of plant-bacteria symbiosis (and BNF) within soybean nodules than previously hypothesized. Collectively these findings suggest that spatial perspectives in metabolic regulation should be considered to unravel the overall complexity of interacting organisms, like those relating to associations of nitrogen-fixing bacteria with host plants.

Observed metabolic asymmetry within soybean root nodules reflects unexpected complexity in rhizobacteria-legume metabolite exchange

In this study, the three-dimensional spatial distributions of a number of metabolites involved in regulating symbiosis and biological nitrogen fixation (BNF) within soybean root nodules were revealed using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). While many metabolites exhibited distinct spatial compartmentalization, some metabolites were asymmetrically distributed throughout the nodule (e.g., S-adenosylmethionine). These results establish a more complex metabolic view of plant-bacteria symbiosis (and BNF) within soybean nodules than previously hypothesized. Collectively these findings suggest that spatial perspectives in metabolic regulation should be considered to unravel the overall complexity of interacting organisms, like those relating to associations of nitrogen-fixing bacteria with host plants.

Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data

Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perception of scientific data by as many viewers as possible. We developed a Python module, cmaputil, to create CVD-optimized colormaps, which imports colormaps and modifies them to be perceptually uniform in CVD-safe colorspace while linearizing and maximizing the brightness range. The module is made available to the science community to enable others to easily create their own CVD-optimized colormaps. Here, we present an example CVD-optimized colormap created with this module that is optimized for viewing by those without a CVD as well as those with red-green colorblindness. This colormap, cividis, enables nearly-identical visual-data interpretation to both groups, is perceptually uniform in hue and brightness, and increases in brightness linearly.

Metabolic Noise and Distinct Subpopulations Observed by Single Cell LAESI Mass Spectrometry of Plant Cells in situ

Phenotypic variations and stochastic expression of transcripts, proteins, and metabolites in biological tissues lead to cellular heterogeneity. As a result, distinct cellular subpopulations emerge. They are characterized by different metabolite expression levels and by associated metabolic noise distributions. To capture these biological variations unperturbed, highly sensitive in situ analytical techniques are needed that can sample tissue embedded single cells with minimum sample preparation. Optical fiber-based laser ablation electrospray ionization mass spectrometry (f-LAESI-MS) is a promising tool for metabolic profiling of single cells under ambient conditions. Integration of this MS-based platform with fluorescence and brightfield microscopy provides the ability to target single cells of specific type and allows for the selection of rare cells, e.g., excretory idioblasts. Analysis of individual Egeria densa leaf blade cells (n = 103) by f-LAESI-MS revealed significant differences between the prespecified subpopulations of epidermal cells (n = 97) and excretory idioblasts (n = 6) that otherwise would have been masked by the population average. Primary metabolites, e.g., malate, aspartate, and ascorbate, as well as several glucosides were detected in higher abundance in the epidermal cells. The idioblasts contained lipids, e.g., PG(16:0/18:2), and triterpene saponins, e.g., medicoside I and azukisaponin I, and their isomers. Metabolic noise for the epidermal cells were compared to results for soybean (Glycine max) root nodule cells (n = 60) infected by rhizobia (Bradyrhizobium japonicum). Whereas some primary metabolites showed lower noise in the latter, both cell types exhibited higher noise for secondary metabolites. Post hoc grouping of epidermal and root nodule cells, based on the abundance distributions for certain metabolites (e.g., malate), enabled the discovery of cellular subpopulations characterized by different mean abundance values, and the magnitudes of the corresponding metabolic noise. Comparison of prespecified populations from epidermal cells of the closely related E. densa (n = 20) and Elodea canadensis (n = 20) revealed significant differences, e.g., higher sugar content in the former and higher levels of ascorbate in the latter, and the presence of species-specific metabolites. These results demonstrate that the f-LAESI-MS single cell analysis platform has the potential to explore cellular heterogeneity and metabolic noise for hundreds of tissue-embedded cells.

Multimodal MSI in Conjunction with Broad Coverage Spatially Resolved MS2 Increases Confidence in Both Molecular Identification and Localization

One critical aspect of mass spectrometry imaging (MSI) is the need to confidently identify detected analytes. While orthogonal tandem MS (e.g., LC-MS²) experiments from sample extracts can assist in annotating ions, the spatial information about these molecules is lost. Accordingly, this could cause mislead conclusions, especially in cases where isobaric species exhibit different distributions within a sample. In this Technical Note, we employed a multimodal imaging approach, using matrix assisted laser desorption/ionization (MALDI)-MSI and liquid extraction surface analysis (LESA)-MS²I, to confidently annotate and localize a broad range of metabolites involved in a tripartite symbiosis system of moss, cyanobacteria, and fungus. We found that the combination of these two imaging modalities generated very congruent ion images, providing the link between highly accurate structural information onfered by LESA and high spatial resolution attainable by MALDI. These results demonstrate how this combined methodology could be very useful in differentiating metabolite routes in complex systems.

Laser-ablation electrospray ionization mass spectrometry with ion mobility separation reveals metabolites in the symbiotic interactions of soybean roots and rhizobia

Technologies enabling in situ metabolic profiling of living plant systems are invaluable for understanding physiological processes and could be used for rapid phenotypic screening (e.g., to produce plants with superior biological nitrogen-fixing ability). The symbiotic interaction between legumes and nitrogen-fixing soil bacteria results in a specialized plant organ (i.e., root nodule) where the exchange of nutrients between host and endosymbiont occurs. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is a method that can be performed under ambient conditions requiring minimal sample preparation. Here, we employed LAESI-MS to explore the well characterized symbiosis between soybean (Glycine max L. Merr.) and its compatible symbiont, Bradyrhizobium japonicum. The utilization of ion mobility separation (IMS) improved the molecular coverage, selectivity, and identification of the detected biomolecules. Specifically, incorporation of IMS resulted in an increase of 153 differentially abundant spectral features in the nodule samples. The data presented demonstrate the advantages of using LAESI-IMS-MS for the rapid analysis of intact root nodules, uninfected root segments, and free-living rhizobia. Untargeted pathway analysis revealed several metabolic processes within the nodule (e.g., zeatin, riboflavin, and purine synthesis). Compounds specific to the uninfected root and bacteria were also detected. Lastly, we performed depth profiling of intact nodules to reveal the location of metabolites to the cortex and inside the infected region, and lateral profiling of sectioned nodules confirmed these molecular distributions. Our results established the feasibility of LAESI-IMS-MS for the analysis and spatial mapping of plant tissues, with its specific demonstration to improve our understanding of the soybean-rhizobial symbiosis.

Constant-Distance Mode Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging of Biological Samples with Complex Topography

A new approach for constant-distance mode mass spectrometry imaging (MSI) of biological samples using nanospray desorption electrospray ionization (nano-DESI) was developed by integrating a shear-force probe with the nano-DESI probe. The technical concept and basic instrumental setup, as well as the general operation of the system are described. Mechanical dampening of resonant oscillations due to the presence of shear forces between the probe and the sample surface enabled the constant-distance imaging mode via a computer-controlled closed-feedback loop. The capability of simultaneous chemical and topographic imaging of complex biological samples is demonstrated using living Bacillus subtilis ATCC 49760 colonies on agar plates. The constant-distance mode nano-DESI MSI enabled imaging of many metabolites, including nonribosomal peptides (surfactin, plipastatin, and iturin) on the surface of living bacterial colonies, ranging in diameter from 10 to 13 mm, with height variations up to 0.8 mm above the agar plate. Co-registration of ion images to topographic images provided higher-contrast images. Based on this effort, constant-mode nano-DESI MSI proved to be ideally suited for imaging biological samples of complex topography in their native states.

Quantifying element incorporation in multispecies biofilms using nanoscale secondary ion mass spectrometry image analysis

Elucidating nutrient exchange in microbial communities is an important step in understanding the relationships between microbial systems and global biogeochemical cycles, but these communities are complex and the interspecies interactions that occur within them are not well understood. Phototrophic consortia are useful and relevant experimental systems to investigate such interactions as they are not only prevalent in the environment, but some are cultivable in vitro and amenable to controlled scientific experimentation. Nanoscale secondary ion mass spectrometry (NanoSIMS) is a powerful, high spatial resolution tool capable of visualizing the metabolic activities of single cells within a biofilm, but quantitative analysis of the resulting data has typically been a manual process, resulting in a task that is both laborious and susceptible to human error. Here, the authors describe the creation and application of a semiautomated image-processing pipeline that can analyze NanoSIMS-generated data, applied to phototrophic biofilms as an example. The tool employs an image analysis process, which includes both elemental and morphological segmentation, producing a final segmented image that allows for discrimination between autotrophic and heterotrophic biomass, the detection of individual cyanobacterial filaments and heterotrophic cells, the quantification of isotopic incorporation of individual heterotrophic cells, and calculation of relevant population statistics. The authors demonstrate the functionality of the tool by using it to analyze the uptake of (15)N provided as either nitrate or ammonium through the unicyanobacterial consortium UCC-O and imaged via NanoSIMS. The authors found that the degree of (15)N incorporation by individual cells was highly variable when labeled with (15)NH4 (+), but much more even when biofilms were labeled with (15)NO3 (-). In the (15)NH4 (+)-amended biofilms, the heterotrophic distribution of (15)N incorporation was highly skewed, with a large population showing moderate (15)N incorporation and a small number of organisms displaying very high (15)N uptake. The results showed that analysis of NanoSIMS data can be performed in a way that allows for quantitation of the elemental uptake of individual cells, a technique necessary for advancing research into the metabolic networks that exist within biofilms with statistical analyses that are supported by automated, user-friendly processes.

Cellular Delivery of Nanoparticles Revealed with Combined Optical and Isotopic Nanoscopy

Direct polymerization of an oxaliplatin analogue was used to reproducibly generate amphiphiles in one pot, which consistently and spontaneously self-assemble into well-defined nanoparticles (NPs). Despite inefficient drug leakage in cell-free assays, the NPs were observed to be as cytotoxic as free oxaliplatin in cell culture experiments. We investigated this phenomenon by super-resolution fluorescence structured illumination microscopy (SIM) and nanoscale secondary ion mass spectrometry (NanoSIMS). In combination, these techniques revealed NPs are taken up via endocytic pathways before intracellular release of their cytotoxic cargo. As with other drug-carrying nanomaterials, these systems have potential as cellular delivery vehicles. However, high-resolution methods to track nanocarriers and their cargo at the micro- and nanoscale have been underutilized in general, limiting our understanding of their interactions with cells and tissues. We contend this type of combined optical and isotopic imaging strategy represents a powerful and potentially generalizable methodology for cellular tracking of nanocarriers and their cargo.