Neuropeptide Localization in Lymnaea stagnalis: From the Central Nervous System to Subcellular Compartments

Due to the relatively small number of neurons (few tens of thousands), the well-established multipurpose model organism Lymnaea stagnalis, great pond snail, has been extensively used to study the functioning of the nervous system. Unlike the more complex brains of higher organisms, L. stagnalis has a relatively simple central nervous system (CNS) with well-defined circuits (e.g., feeding, locomotion, learning, and memory) and identified individual neurons (e.g., cerebral giant cell, CGC), which generate behavioral patterns. Accumulating information from electrophysiological experiments maps the network of neuronal connections and the neuronal circuits responsible for basic life functions. Chemical signaling between synaptic-coupled neurons is underpinned by neurotransmitters and neuropeptides. This review looks at the rapidly expanding contributions of mass spectrometry (MS) to neuropeptide discovery and identification at different granularity of CNS organization. Abundances and distributions of neuropeptides in the whole CNS, eleven interconnected ganglia, neuronal clusters, single neurons, and subcellular compartments are captured by MS imaging and single cell analysis techniques. Combining neuropeptide expression and electrophysiological data, and aided by genomic and transcriptomic information, the molecular basis of CNS-controlled biological functions is increasingly revealed

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

Metabolic transformation of microalgae due to light acclimation and genetic modifications followed by laser ablation electrospray ionization mass spectrometry with ion mobility separation.

International audienceMetabolic profiling of various microalga species and their genetic variants, grown under varied environmental conditions, has become critical to accelerate the exploration of phytoplankton biodiversity and biology. The accumulation of valuable metabolites, such as glycerolipids, is also sought in microalgae for biotechnological applications ranging from food, feed, medicine, cosmetics to bioenergy and green chemistry. In this report we describe the direct analysis of metabolites and lipids in small cell populations of the green alga Chlamydomonas reinhardtii, using laser ablation electrospray ionization (LAESI) mass spectrometry (MS) coupled with ion mobility separation (IMS). These microorganisms are capable of redirecting energy storage pathways from starch to neutral lipids depending on environmental conditions and nutrient availability. Metabolite and lipid productions were monitored in wild type (WT), and genetically modified C. reinhardtii strains with an impaired starch pathway. Lipids, such as triacylglycerols (TAG) and diacylglyceryl-N,N,N-trimethylhomoserine (DGTS), were monitored over time under altered light conditions. More than 200 ions related to metabolites, e.g., arginine, cysteine, serine, palmitate, chlorophyll a, chlorophyll b, etc., were detected. The lipid profiles at different light intensities for strains with impaired starch pathway (Sta1 and Sta6) contained 26 glycerolipids, such as DGTS, monogalactosyldiacylglycerol (MGDG) and digalactosyldiacylglycerol (DGDG), as well as 33 TAG species. Results were obtained over a 72 hour time period under high and low light conditions for the WT species and the two mutants. Our results indicate that LAESI-IMS-MS can be utilized for the rapid analysis of increased TAG production at elevated light intensities. Compared to WT, the Sta6 strain showed 2.5 times higher lipid production at 72 hours under high light conditions. The results demonstrate our ability to rapidly observe numerous changes in metabolite and lipid levels in microalgal population. These capabilities are expected to facilitate the exploration of genetically altered microalgal strains for biofuel production

Turnover rates in microorganisms by laser ablation electrospray ionization mass spectrometry and pulse-chase analysis

International audienceBiochemical processes rely on elaborate networks containing thousands of compounds participating in thousands of reaction. Rapid turnover of diverse metabolites and lipids in an organism is an essential part of homeostasis. It affects energy production and storage, two important processes utilized in bioengineering. Conventional approaches to simultaneously quantify a large number of turnover rates in biological systems are currently not feasible. Here we show that pulse-chase analysis followed by laser ablation electrospray ionization mass spectrometry (LAESI-MS) enable the simultaneous and rapid determination of metabolic turnover rates. The incorporation of ion mobility separation (IMS) allowed an additional dimension of analysis, i.e., the detection and identification of isotopologs based on their collision cross sections. We demonstrated these capabilities by determining metabolite, lipid, and peptide turnover in the photosynthetic green algae, Chlamydomonas reinhardtii, in the presence of 15N-labeled ammonium chloride as the main nitrogen source. Following the reversal of isotope patterns in the chase phase by LAESI-IMS-MS revealed the turnover rates and half-lives for biochemical species with a wide range of natural concentrations, e.g., chlorophyll metabolites, lipids, and peptides. For example, the half-lives of lyso-DGTS(16:0) and DGTS(18:3/16:0), t1/2 = 43.6 ± 4.5 h and 47.6 ± 2.2 h, respectively, provided insight into lipid synthesis and degradation in this organism. Within the same experiment, half-lives for chlorophyll a, t1/2 = 24.1 ± 2.2 h, and a 2.8 kDa peptide, t1/2 = 10.4 ± 3.6 h, were also determined

Optical Microscopy-Guided Laser Ablation Electrospray Ionization Ion Mobility Mass Spectrometry: Ambient Single Cell Metabolomics with Increased Confidence in Molecular Identification

Single cell analysis is a field of increasing interest as new tools are continually being developed to understand intercellular differences within large cell populations. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging technique for single cell metabolomics. Over the years, it has been validated that this ionization technique is advantageous for probing the molecular content of individual cells in situ. Here, we report the integration of a microscope into the optical train of the LAESI source to allow for visually informed ambient in situ single cell analysis. Additionally, we have coupled this ‘LAESI microscope’ to a drift-tube ion mobility mass spectrometer to enable separation of isobaric species and allow for the determination of ion collision cross sections in conjunction with accurate mass measurements. This combined information helps provide higher confidence for structural assignment of molecules ablated from single cells. Here, we show that this system enables the analysis of the metabolite content of Allium cepa epidermal cells with high confidence structural identification together with their spatial locations within a tissue

Large-Scale Metabolite Analysis of Standards and Human Serum by Laser Desorption Ionization Mass Spectrometry from Silicon Nanopost Arrays

The unique challenges presented by metabolomics have driven the development of new mass spectrometry (MS)-based techniques for small molecule analysis. We have previously demonstrated silicon nanopost arrays (NAPA) to be an effective substrate for laser desorption ionization (LDI) of small molecules for MS. However, the utility of NAPA-LDI-MS for a wide range of metabolite classes has not been investigated. Here we apply NAPA-LDI-MS to the large-scale acquisition of high-resolution mass spectra and tandem mass spectra from a collection of metabolite standards covering a range of compound classes including amino acids, nucleotides, carbohydrates, xenobiotics, lipids, and other classes. In untargeted analysis of metabolite standard mixtures, detection was achieved for 374 compounds and useful MS/MS spectra were obtained for 287 compounds, without individual optimization of ionization or fragmentation conditions. Metabolite detection was evaluated in the context of 31 metabolic pathways, and NAPA-LDI-MS was found to provide detection for 63% of investigated pathway metabolites. Individual, targeted analysis of the 20 common amino acids provided detection of 100% of the investigated compounds, demonstrating that improved coverage is possible through optimization and targeting of individual analytes or analyte classes. In direct analysis of aqueous and organic extracts from human serum samples, spectral features were assigned to a total of 108 small metabolites and lipids. Glucose and amino acids were quantitated within their physiological concentration ranges. The broad coverage demonstrated by this large-scale screening experiment opens the door for use of NAPA-LDI-MS in numerous metabolite analysis applications

Spatially resolved characterization of tissue metabolic compartments in fasted and high-fat diet livers.

Cells adapt their metabolism to physiological stimuli, and metabolic heterogeneity exists between cell types, within tissues, and subcellular compartments. The liver plays an essential role in maintaining whole-body metabolic homeostasis and is structurally defined by metabolic zones. These zones are well-understood on the transcriptomic level, but have not been comprehensively characterized on the metabolomic level. Mass spectrometry imaging (MSI) can be used to map hundreds of metabolites directly from a tissue section, offering an important advance to investigate metabolic heterogeneity in tissues compared to extraction-based metabolomics methods that analyze tissue metabolite profiles in bulk. We established a workflow for the preparation of tissue specimens for matrix-assisted laser desorption/ionization (MALDI) MSI that can be implemented to achieve broad coverage of central carbon, nucleotide, and lipid metabolism pathways. Herein, we used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic tissue compartmentalization in livers, which becomes disrupted under high fat diet. Fasting caused changes in the abundance of several metabolites, including increased levels of fatty acids and TCA intermediates while fatty livers had higher levels of purine and pentose phosphate-related metabolites, which generate reducing equivalents to counteract oxidative stress. This spatially conserved approach allowed the visualization of liver metabolic compartmentalization at 30 μm pixel resolution and can be applied more broadly to yield new insights into metabolic heterogeneity in vivo

PARP-inhibition reprograms macrophages toward an anti-tumor phenotype

Poly(ADP)ribosylation inhibitors (PARPis) are toxic to cancer cells with homologous recombination (HR) deficiency but not to HR-proficient cells in the tumor microenvironment (TME), including tumor-associated macrophages (TAMs). As TAMs can promote or inhibit tumor growth, we set out to examine the effects of PARP inhibition on TAMs in BRCA1-related breast cancer (BC). The PARPi olaparib causes reprogramming of TAMs toward higher cytotoxicity and phagocytosis. A PARPi-related surge in NAD+ increases glycolysis, blunts oxidative phosphorylation, and induces reverse mitochondrial electron transport (RET) with an increase in reactive oxygen species (ROS) and transcriptional reprogramming. This reprogramming occurs in the absence or presence of PARP1 or PARP2 and is partially recapitulated by addition of NAD derivative methyl-nicotinamide (MNA). In vivo and ex vivo, the effect of olaparib on TAMs contributes to the anti-tumor efficacy of the PARPi. In vivo blockade of the “don’t-eat-me signal” with CD47 antibodies in combination with olaparib improves outcomes in a BRCA1-related BC model.publishedVersio