Single Cell Neurometabolomics

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Single-cell technologies in psoriasis

Psoriasis is a chronic and recurrent inflammatory skin disorder. The primary manifestation of psoriasis arises from disturbances in the cutaneous immune microenvironment, but the specific functions of the cellular components within this microenvironment remain unknown. Recent advancements in single-cell technologies have enabled the detection of multi-omics at the level of individual cells, including single-cell transcriptome, proteome, and metabolome, which have been successfully applied in studying autoimmune diseases, and other pathologies. These techniques allow the identification of heterogeneous cell clusters and their varying contributions to disease development. Considering the immunological traits of psoriasis, an in-depth exploration of immune cells and their interactions with cutaneous parenchymal cells can markedly advance our comprehension of the mechanisms underlying the onset and recurrence of psoriasis. In this comprehensive review, we present an overview of recent applications of single-cell technologies in psoriasis, aiming to improve our understanding of the underlying mechanisms of this disorder.

Single-cell metabolomics in rare disease: From technology to disease

With the development of clinical experience and technology, rare diseases (RDs) are gradually coming into the limelight. As they often lead to poor prognosis, it is urgent to promote the accuracy and rapidity of diagnosis and promote the development of therapeutic drugs. In recent years, with the rapid improvement of single-cell sequencing technology, the advantages of multi-omics combined application in diseases have been continuously explored. Single-cell metabolomics represents a powerful tool for advancing our understanding of rare diseases, particularly metabolic RDs, and transforming clinical practice. By unraveling the intricacies of cellular metabolism at a single-cell resolution, this innovative approach holds the potential to revolutionize diagnosis, treatment, and management strategies, ultimately improving outcomes for RDs patients. Continued research and technological advancements in single-cell metabolomics are essential for realizing its full potential in the field of RDs diagnosis and therapeutics. It is expected that single-cell metabolomics can be better applied to RDs research in the future, for the benefit of patients and society.

Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis

Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites. Mass spectrometry (MS), characterized by its high sensitivity, wide dynamic range, and excellent selectivity, is employed in single-cell metabolic analysis. This review focuses on recent advances and applications of MS-based single-cell metabolic analysis, encompassing three key steps of single-cell isolation, detection, and application. It is anticipated that MS will bring profound implications in biomedical practices, serving as advanced tools to depict the single-cell metabolic landscape.

Emerging Functional Connections Between Metabolism and Epigenetic Remodeling in Neural Differentiation

Stem cells possess extraordinary capacities for self-renewal and differentiation, making them highly valuable in regenerative medicine. Among these, neural stem cells (NSCs) play a fundamental role in neural development and repair processes. NSC characteristics and fate are intricately regulated by the microenvironment and intracellular signaling. Interestingly, metabolism plays a pivotal role in orchestrating the epigenome dynamics during neural differentiation, facilitating the transition from undifferentiated NSC to specialized neuronal and glial cell types. This intricate interplay between metabolism and the epigenome is essential for precisely regulating gene expression patterns and ensuring proper neural development. This review highlights the mechanisms behind metabolic regulation of NSC fate and their connections with epigenetic regulation to shape transcriptional programs of stemness and neural differentiation. A comprehensive understanding of these molecular gears appears fundamental for translational applications in regenerative medicine and personalized therapies for neurological conditions.

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Exploring Single-Cell Exposomics by Mass Spectrometry

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.

Mass spectrometry-based strategies for single-cell metabolomics

Single cell analysis has drawn increasing interest from the research community due to its capability to interrogate cellular heterogeneity, allowing refined tissue classification and facilitating novel biomarker discovery. With the advancement of relevant instruments and techniques, it is now possible to perform multiple omics including genomics, transcriptomics, metabolomics or even proteomics at single cell level. In comparison with other omics studies, single-cell metabolomics (SCM) represents a significant challenge since it involves many types of dynamically changing compounds with a wide range of concentrations. In addition, metabolites cannot be amplified. Although difficult, considerable progress has been made over the past decade in mass spectrometry (MS)-based SCM in terms of processing technologies and biochemical applications. In this review, we will summarize recent progress in the development of promising MS platforms, sample preparation methods and SCM analysis of various cell types (including plant cell, cancer cell, neuron, embryo cell, and yeast cell). Current limitations and future research directions in the field of SCM will also be discussed.

Advances in measuring cancer cell metabolism with subcellular resolution

Characterizing metabolism in cancer is crucial for understanding tumor biology and for developing potential therapies. Although most metabolic investigations analyze averaged metabolite levels from all cell compartments, subcellular metabolomics can provide more detailed insight into the biochemical processes associated with the disease. Methodological limitations have historically prevented the wider application of subcellular metabolomics in cancer research. Recently, however, ways to distinguish and identify metabolic pathways within organelles have been developed, including state-of-the-art methods to monitor metabolism in situ (such as mass spectrometry-based imaging, Raman spectroscopy and fluorescence microscopy), to isolate key organelles via new approaches and to use tailored isotope-tracing strategies. Herein, we examine the advantages and limitations of these developments and look to the future of this field of research.

Single-Cell Mass Spectrometry of Metabolites and Proteins for Systems and Functional Biology

Molecular composition is intricately intertwined with cellular function, and elucidation of this relationship is essential for understanding life processes and developing next-generational therapeutics. Technological innovations in capillary electrophoresis (CE) and liquid chromatography (LC) mass spectrometry (MS) provide previously unavailable insights into cellular biochemistry by allowing for the unbiased detection and quantification of molecules with high specificity. This chapter presents our validated protocols integrating ultrasensitive MS with classical tools of cell, developmental, and neurobiology to assess the biological function of important biomolecules. We use CE and LC MS to measure hundreds of metabolites and thousands of proteins in single cells or limited populations of tissues in chordate embryos and mammalian neurons, revealing molecular heterogeneity between identified cells. By pairing microinjection and optical microscopy, we demonstrate cell lineage tracing and testing the roles the dysregulated molecules play in the formation and maintenance of cell heterogeneity and tissue specification in frog embryos (Xenopus laevis). Electrophysiology extends our workflows to characterizing neuronal activity in sections of mammalian brain tissues. The information obtained from these studies mutually strengthen chemistry and biology and highlight the importance of interdisciplinary research to advance basic knowledge and translational applications forward.

Metabolic Sex Dimorphism of the Brain at the Gene, Cell, and Tissue Level

The palpable observation in the sex bias of disease prevalence in the CNS has fascinated scientists for several generations. Brain sex dimorphism has been visualized by imaging and analytical tools at the tissue, cellular, and molecular levels. Recent work highlighted the specificity of such sex bias in the brain and its subregions, offering a unique lens through which disease pathogenesis can be investigated. The brain is the largest consumer of energy in the body and provides a unique metabolic environment for diverse lineages of cells. Immune cells are increasingly recognized as an integral part of brain physiology, and their function depends on metabolic homeostasis. This review focuses on metabolic sex dimorphism in brain tissue, resident, and infiltrating immune cells. In this context, we highlight the relevance of recent advances in metabolomics and RNA sequencing technologies at the single cell resolution and the development of novel computational approaches.

The limitless applications of single-cell metabolomics

Single-cell metabolomics (SCM) is currently one of the most powerful tools for performing high-throughput metabolic analysis at the cellular level. The power of single-cell metabolomics to determine the metabolic profiles of individual cells makes it very suitable for decoding cell heterogeneity. SCM bears great potential in cell type identification and differentiation within cell colonies. With the development of various equipment and techniques, SCM analysis has become possible for a wide range of biological samples. Many fields have incorporated this cutting-edge analytic tool to generate fruitful findings. This review article pays close attention to the prevalent techniques utilized in SCM and the exciting new findings and applications developed by studies in phytology, neurology, and oncology using SCM.

SpaceM reveals metabolic states of single cells

A growing appreciation of the importance of cellular metabolism and revelations concerning the extent of cell-cell heterogeneity demand metabolic characterization of individual cells. We present SpaceM, an open-source method for in situ single-cell metabolomics that detects >100 metabolites from >1,000 individual cells per hour, together with a fluorescence-based readout and retention of morpho-spatial features. We validated SpaceM by predicting the cell types of cocultured human epithelial cells and mouse fibroblasts. We used SpaceM to show that stimulating human hepatocytes with fatty acids leads to the emergence of two coexisting subpopulations outlined by distinct cellular metabolic states. Inducing inflammation with the cytokine interleukin-17A perturbs the balance of these states in a process dependent on NF-κB signaling. The metabolic state markers were reproduced in a murine model of nonalcoholic steatohepatitis. We anticipate SpaceM to be broadly applicable for investigations of diverse cellular models and to democratize single-cell metabolomics.

Brain on food: The neuroepigenetics of nutrition

Humans have known for millennia that nutrition has a profound influence on health and disease, but it is only recently that we have begun mapping the mechanisms via which the dietary environment impacts brain physiology and behavior. Here we review recent evidence on the effects of energy-dense and methionine diets on neural epigenetic marks, gene expression, and behavior in invertebrate and vertebrate model organisms. We also discuss limitations, open questions, and future directions in the emerging field of the neuroepigenetics of nutrition.

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.

IDH1 mutations induce organelle defects via dysregulated phospholipids

Infiltrating gliomas are devastating and incurable tumors. Amongst all gliomas, those harboring a mutation in isocitrate dehydrogenase 1 mutation (IDH1^mut) acquire a different tumor biology and clinical manifestation from those that are IDH1^WT. Understanding the unique metabolic profile reprogrammed by IDH1 mutation has the potential to identify new molecular targets for glioma therapy. Herein, we uncover increased monounsaturated fatty acids (MUFA) and their phospholipids in endoplasmic reticulum (ER), generated by IDH1 mutation, that are responsible for Golgi and ER dilation. We demonstrate a direct link between the IDH1 mutation and this organelle morphology via D-2HG-induced stearyl-CoA desaturase (SCD) overexpression, the rate-limiting enzyme in MUFA biosynthesis. Inhibition of IDH1 mutation or SCD silencing restores ER and Golgi morphology, while D-2HG and oleic acid induces morphological defects in these organelles. Moreover, addition of oleic acid, which tilts the balance towards elevated levels of MUFA, produces IDH1^mut-specific cellular apoptosis. Collectively, these results suggest that IDH1^mut-induced SCD overexpression can rearrange the distribution of lipids in the organelles of glioma cells, providing new insight into the link between lipid metabolism and organelle morphology in these cells, with potential and unique therapeutic implications.

The understanding of altered lipid metabolism by isocitrate dehydrogenase 1 (IDH1) mutations in gliomas at a compartment-specific level is limited. Here, the authors use Raman spectroscopy to monitor organelle-specific metabolic changes and report that IDH1 mutations induce phospholipid imbalances which lead to ER and Golgi dilation.

Charting Metabolism Heterogeneity by Nanostructure Imaging Mass Spectrometry: From Biological Systems to Subcellular Functions

The study of metabolism heterogeneity is essential to understand the role of metabolites in supporting and regulating biological functions. To this end, several mass spectrometry imaging (MSI) approaches have been proposed for the detection of small molecule metabolites. However, high noise from the ionization matrix and low metabolome coverage hinder their applicability for untargeted metabolomics studies across space. In this context, nanostructure imaging (/initiator) mass spectrometry (NIMS) and NIMS with fluorinated gold nanoparticles (f-AuNPs) are attractive strategies for comprehensive MSI of metabolites in biological systems, which can provide heterogeneous metabolome coverage, ultrahigh sensitivity, and high lateral resolution. In particular, NIMS with f-AuNPs permits the simultaneous detection of polar metabolites and lipids in a single and cohesive analytical session, thus allowing the systems-level interpretation of metabolic changes. In this Perspective article, we discuss the use of NIMS and f-AuNPs in the exploration of metabolism heterogeneity and provide a critical outlook on future applications of this technology for revealing the metabolic architecture that supports biological functions in health and disease, from whole organisms to tissues, single cells, and subcellular compartments.

Systems Biology in Neuroscience: the Paramount Importance of Data Sharing and Citation

The emergence and maturation, in the last decade, of high powerful technologies in the fields of neurogenomics, neurometabolomics, and neuroproteomics has opened exciting novel possibilities of research [...]

Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.

Metabolomics: A Tool to Understand the Impact of Genetic Mutations in Amyotrophic Lateral Sclerosis

Metabolomics studies performed in patients with amyotrophic lateral sclerosis (ALS) reveal a set of distinct metabolites that can shed light on the pathological alterations taking place in each individual. Metabolites levels are influenced by disease status, and genetics play an important role both in familial and sporadic ALS cases. Metabolomics analysis helps to unravel the differential impact of the most common ALS-linked genetic mutations (as C9ORF72, SOD1, TARDBP, and FUS) in specific signaling pathways. Further, studies performed in genetic models of ALS reinforce the role of TDP-43 pathology in the vast majority of ALS cases. Studies performed in differentiated cells from ALS-iPSC (induced Pluripotent Stem Cells) reveal alterations in the cell metabolism that are also found in ALS models and ultimately in ALS patients. The development of metabolomics approaches in iPSC derived from ALS patients allow addressing and ultimately understanding the pathological mechanisms taking place in any patient. Lately, the creation of a "patient in a dish" will help to identify patients that may benefit from specific treatments and allow the implementation of personalized medicine.

Inductively coupled magic angle spinning microresonators benchmarked for high-resolution single embryo metabolomic profiling

The magic angle coil spinning (MACS) technique has been introduced as a very promising extension for solid state NMR detection, demonstrating sensitivity enhancements by a factor of 14 from the very first time it has been reported. The main beneficiary of this technique is the scientific community dealing with mass- and volume-limited, rare, or expensive samples. However, more than a decade after the first report on MACS, there is a very limited number of groups who have continued to develop the technique, let alone it being widely adopted by practitioners. This might be due to several drawbacks associated with the MACS technology until now, including spectral linewidth, heating due to eddy currents, and imprecise manufacturing. Here, we report a device overcoming all these remaining issues, therefore achieving: (1) spectral resolution of approx 0.01 ppm and normalized limit of detection of approx. 13 nmol s^0.5 calculated using the anomeric proton of sucrose at 3 kHz MAS frequency; (2) limited temperature increase inside the MACS insert of only 5 °C at 5 kHz MAS frequency in an 11.74 T magnetic field, rendering MACS suitable to study live biological samples. The wafer-scale fabrication process yields MACS inserts with reproducible properties, readily available to be used on a large scale in bio-chemistry labs. To illustrate the potential of these devices for metabolomic studies, we further report on: (3) ultra-fine ¹H-¹H and ¹³C-¹³C J-couplings resolved within 10 min for a 340 mM uniformly ¹³C-labeled glucose sample; and (4) single zebrafish embryo measurements through ¹H-¹H COSY within 4.5 h, opening the gate for the single embryo NMR studies.

Ultrasensitive Single Cell Metabolomics by Capillary Electrophoresis-Mass Spectrometry with a Thin-Walled Tapered Emitter and Large-Volume Dual Sample Preconcentration

Single cell metabolome analysis is essential for studying microscale life phenomena such as neuronal networks and tumor microenvironments. Capillary electrophoresis-mass spectrometry (CE-MS) is one of the most sensitive technologies; however, its sensitivity is still not enough for single cell analysis on general human cells such as HeLa. To address these issues, we first developed an efficient ionization emitter, named as a "nanoCESI" emitter, that had a thin-walled (∼10 μm) and tapered (5-10 μm) end. The thin conductive wall enabled sheathless ionization and minimized the flow rate of ionizing sample, and the tapered end efficiently ionized analytes via an electrospray ionization mechanism, providing up to 3.5-fold increase in sensitivity compared with a conventional sheathless emitter. Fifty repetitive analyses on 20 amino acids were successfully achieved with a nanoCESI emitter. Relative standard deviations of 50 analyses were 1.5%, 4.4%, and 6.8% for migration time, peak height, and peak area, respectively, where a limit of detection (LOD) of 170 pM (850 zmol) was achieved. Second, a sample enrichment method, large-volume dual preconcentration by isotachophoresis and stacking (LDIS), was applied to a newly designed protocol of nanoCESI-MS. This approach achieved up to 380-fold enhanced sensitivity and LOD of 450 fM. Compared with normal sheathless CE-MS, coupling of nanoCESI and LDIS provided up to 800-fold increase of sensitivity in total. Finally, metabolome analyses of single HeLa cells were performed, where 20 amino acids were successfully quantified with triple-quadrupole MS and 40 metabolites were identified with quadrupole-time-of-flight MS, as a promising analytical platform for microscale bioanalysis for the next generation.

Exploring the Fundamental Structures of Life: Non-Targeted, Chemical Analysis of Single Cells and Subcellular Structures

Cells are a basic functional and structural unit of living organisms. Both unicellular communities and multicellular species produce an astonishing chemical diversity, enabling a wide range of divergent functions, yet each cell shares numerous aspects that are common to all living organisms. While there are many approaches for studying this chemical diversity, only a few are non-targeted and capable of analyzing hundreds of different chemicals at cellular resolution. Here, we review the non-targeted approaches used to perform comprehensive chemical analyses, provide chemical imaging information, or obtain high-throughput single-cell profiling data. Single-cell measurement capabilities are rapidly increasing in terms of throughput, limits of detection, and completeness of the chemical analyses; these improvements enable their application to understand ever more complex physiological phenomena, such as learning, memory, and behavior.

Genetically Encoded Fluorescent Proteins Enable High-Throughput Assignment of Cell Cohorts Directly from MALDI-MS Images

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) provides a unique in situ chemical profile that can include drugs, nucleic acids, metabolites, lipids, and proteins. MSI of individual cells (of a known cell type) affords a unique insight into normal and disease-related processes and is a prerequisite for combining the results of MSI and other single-cell modalities (e.g. mass cytometry and next-generation sequencing). Technological barriers have prevented the high-throughput assignment of MSI spectra from solid tissue preparations to their cell type. These barriers include obtaining a suitable cell-identifying image (e.g. immunohistochemistry) and obtaining sufficiently accurate registration of the cell-identifying and MALDI-MS images. This study introduces a technique that overcame these barriers by assigning cell type directly from mass spectra. We hypothesized that, in MSI from mice with a defined fluorescent protein expression pattern, the fluorescent protein's molecular ion could be used to identify cell cohorts. A method was developed for the purification of enhanced yellow fluorescent protein (EYFP) from mice. To determine EYFP's molecular mass for MSI studies, we performed intact mass analysis and characterized the protein's primary structure and post-translational modifications through various techniques. MALDI-MSI methods were developed to enhance the detection of EYFP in situ, and by extraction of EYFP's molecular ion from MALDI-MS images, automated, whole-image assignment of cell cohorts was achieved. This method was validated using a well-characterized mouse line that expresses EYFP in motor and sensory neurons and should be applicable to hundreds of commercially available mice (and other animal) strains comprising a multitude of cell-specific fluorescent labels.

Nano-Sampling and Reporter Tools to Study Metabolic Regulation in Zebrafish

In the past years, evidence has emerged that hallmarks of human metabolic disorders can be recapitulated in zebrafish using genetic, pharmacological or dietary interventions. An advantage of modeling metabolic diseases in zebrafish compared to other "lower organisms" is the presence of a vertebrate body plan providing the possibility to study the tissue-intrinsic processes preceding the loss of metabolic homeostasis. While the small size of zebrafish is advantageous in many aspects, it also has shortcomings such as the difficulty to obtain sufficient amounts for biochemical analyses in response to metabolic challenges. A workshop at the European Zebrafish Principal Investigator meeting in Trento, Italy, was dedicated to discuss the advantages and disadvantages of zebrafish to study metabolic disorders. This perspective article by the participants highlights strategies to achieve improved tissue-resolution for read-outs using "nano-sampling" approaches for metabolomics as well as live imaging of zebrafish expressing fluorescent reporter tools that inform on cellular or subcellular metabolic processes. We provide several examples, including the use of reporter tools to study the heterogeneity of pancreatic beta-cells within their tissue environment. While limitations exist, we believe that with the advent of new technologies and more labs developing methods that can be applied to minimal amounts of tissue or single cells, zebrafish will further increase their utility to study energy metabolism.

Precision public health to inhibit the contagion of disease and move toward a future in which microbes spread health

Antimicrobial resistance continues to outpace the development of new chemotherapeutics. Novel pathogens continue to evolve and emerge. Public health innovation has the potential to open a new front in the war of "our wits against their genes" (Joshua Lederberg). Dense sampling coupled to next generation sequencing can increase the spatial and temporal resolution of microbial characterization while sensor technologies precisely map physical parameters relevant to microbial survival and spread. Microbial, physical, and epidemiological big data could be combined to improve prospective risk identification. However, applied in the wrong way, these approaches may not realize their maximum potential benefits and could even do harm. Minimizing microbial-human interactions would be a mistake. There is evidence that microbes previously thought of at best "benign" may actually enhance human health. Benign and health-promoting microbiomes may, or may not, spread via mechanisms similar to pathogens. Infectious vaccines are approaching readiness to make enhanced contributions to herd immunity. The rigorously defined nature of infectious vaccines contrasts with indigenous "benign or health-promoting microbiomes" but they may converge. A "microbial Neolithic revolution" is a possible future in which human microbial-associations are understood and managed analogously to the macro-agriculture of plants and animals. Tradeoffs need to be framed in order to understand health-promoting potentials of benign, and/or health-promoting microbiomes and infectious vaccines while also discouraging pathogens. Super-spreaders are currently defined as individuals who play an outsized role in the contagion of infectious disease. A key unanswered question is whether the super-spreader concept may apply similarly to health-promoting microbes. The complex interactions of individual rights, community health, pathogen contagion, the spread of benign, and of health-promoting microbiomes including infectious vaccines require study. Advancing the detailed understanding of heterogeneity in microbial spread is very likely to yield important insights relevant to public health.

Advances in mass spectrometry based single-cell metabolomics

Single cell metabolomics using mass spectrometry can contribute to understanding biological activities in health and disease.

Metabolomics of mammalian brain reveals regional differences

Background

The mammalian brain is organized into regions with specific biological functions and properties. These regions have distinct transcriptomes, but little is known whether they may also differ in their metabolome. The metabolome, a collection of small molecules or metabolites, is at the intersection of the genetic background of a given cell or tissue and the environmental influences that affect it. Thus, the metabolome directly reflects information about the physiologic state of a biological system under a particular condition. The objective of this study was to investigate whether various brain regions have diverse metabolome profiles, similarly to their genetic diversity. The answer to this question would suggest that not only the genome but also the metabolome may contribute to the functional diversity of brain regions.

Methods

We investigated the metabolome of four regions of the mouse brain that have very distinct functions: frontal cortex, hippocampus, cerebellum, and olfactory bulb. We utilized gas- and liquid- chromatography mass spectrometry platforms and identified 215 metabolites.

Results

Principal component analysis, an unsupervised multivariate analysis, clustered each brain region based on its metabolome content, thus providing the unique metabolic profile of each region. A pathway-centric analysis indicated that olfactory bulb and cerebellum had most distinct metabolic profiles, while the cortical parenchyma and hippocampus were more similar in their metabolome content. Among the notable differences were distinct oxidative-anti-oxidative status and region-specific lipid profiles. Finally, a global metabolic connectivity analysis using the weighted correlation network analysis identified five hub metabolites that organized a unique metabolic network architecture within each examined brain region. These data indicate the diversity of global metabolome corresponding to specialized regional brain function and provide a new perspective on the underlying properties of brain regions.

Conclusion

In summary, we observed many differences in the metabolome among the various brain regions investigated. All four brain regions in our study had a unique metabolic signature, but the metabolites came from all categories and were not pathway-centric.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0644-0) contains supplementary material, which is available to authorized users.

NMR and MS-based Stable Isotope-Resolved Metabolomics and Applications in Cancer Metabolism

There is considerable interest in defining metabolic reprogramming in human diseases, which is recognized as a hallmark of human cancer. Although radiotracers have a long history in specific metabolic studies, stable isotope-enriched precursors coupled with modern high resolution mass spectrometry and NMR spectroscopy have enabled systematic mapping of metabolic networks and fluxes in cells, tissues and living organisms including humans. These analytical platforms are high in information content, are complementary and cross-validating in terms of compound identification, quantification, and isotope labeling pattern analysis of a large number of metabolites simultaneously. Furthermore, new developments in chemoselective derivatization and in vivo spectroscopy enable tracking of labile/low abundance metabolites and metabolic kinetics in real-time. Here we review developments in Stable Isotope Resolved Metabolomics (SIRM) and recent applications in cancer metabolism using a wide variety of stable isotope tracers that probe both broad and specific aspects of cancer metabolism required for proliferation and survival.

Fabrication of hydrophilic multilayer magnetic probe for salivary glycopeptidome analysis

Variations in salivary components are closely associated with the predisposition and state of disease, the abnormal changes of salivary glycopeptidome are usually discovered as perilous singals of serious disease. Therefore, the monitoring and analyzing of salivary glycopeptidome are of even more overriding importance. In this work, a low-cost layer-by-layer assembly strategy was adopted to fabricate a hydrophilic multilayer magnetic probe (dubbed Mag-m-G6P) for salivary glycopeptidome analysis. The successful construction of multilayer structure not only guaranteed the good dispersal of probe by protecting magnetic core from itself aggregation tendency, but also endowed the probe with multiple advantages including the good hydrophilicity, uniform mesopore size and strong magnetic responsiveness, etc. As expected, with the optimized experimental conditions, the multifunctional probe showed high enrichemnt sensitivity, unbiased enrichment ability, excellent size-exclusion ability and reusability and so on in the process of standard sample analysis. At last, the Mag-m-G6P was successfully applied to salivary glycopeptidome analysis on further combination with LC-MS/MS analysis, a total of 53 endogenous glycopeptides were identified from human saliva.

The influence of neuronal electrical activity on the mammalian central clock metabolome

INTRODUCTION

Most organisms display circadian rhythms in physiology and behaviour. In mammals, these rhythms are orchestrated by the suprachiasmatic nucleus (SCN). Recently, several metabolites have emerged as important regulators of circadian timekeeping. Metabolomics approaches have aided in identifying some key metabolites in circadian processes in peripheral tissue, but methods to routinely measure metabolites in small brain areas are currently lacking.

OBJECTIVE

The aim of the study was to establish a reliable method for metabolite quantifications in the central circadian clock and relate them to different states of neuronal excitability.

METHODS

We developed a method to collect and process small brain tissue samples (0.2 mm³), suitable for liquid chromatography-mass spectrometry. Metabolites were analysed in the SCN and one of its main hypothalamic targets, the paraventricular nucleus (PVN). Tissue samples were taken at peak (midday) and trough (midnight) of the endogenous rhythm in SCN electrical activity. Additionally, neuronal activity was altered pharmacologically.

RESULTS

We found a minor effect of day/night fluctuations in electrical activity or silencing activity during the day. In contrast, increasing electrical activity during the night significantly upregulated many metabolites in SCN and PVN.

CONCLUSION

Our method has shown to produce reliable and physiologically relevant metabolite data from small brain samples. Inducing electrical activity at night mimics the effect of a light pulses in the SCN, producing phase shifts of the circadian rhythm. The upregulation of metabolites could have a functional role in this process, since they are not solely products of physiological states, they are significant parts of cellular signalling pathways.

NeuroSystematics and Periodic System of Neurons: Model vs Reference Species at Single-Cell Resolution

There is more than one way to develop neuronal complexity, and animals frequently use different molecular toolkits to achieve similar functional outcomes (=convergent evolution). Neurons are different not only because they have different functions, but also because neurons and circuits have different genealogies, and perhaps independent origins at the broadest scale from ctenophores and cnidarians to cephalopods and primates. By combining modern phylogenomics, single-neuron sequencing (scRNA-seq), machine learning, single-cell proteomics, and metabolomic across Metazoa, it is possible to reconstruct the evolutionary histories of neurons tracing them to ancestral secretory cells. Comparative data suggest that neurons, and perhaps synapses, evolved at least 2-3 times (in ctenophore, cnidarian and bilateral lineages) during ∼600 million years of animal evolution. There were also several independent events of the nervous system centralization either from a common bilateral/cnidarian ancestor without the bona fide neurons or from the urbilaterian with diffuse, nerve-net type nervous system. From the evolutionary standpoint, (i) a neuron should be viewed as a functional rather than a genetic character, and (ii) any given neural system might be chimeric and composed of different cell lineages with distinct origins and evolutionary histories. The identification of distant neural homologies or examples of convergent evolution among 34 phyla will not only allow the reconstruction of neural systems' evolution but together with single-cell "omic" approaches the proposed synthesis would lead to the "Periodic System of Neurons" with predictive power for neuronal phenotypes and plasticity. Such a phylogenetic classification framework of Neuronal Systematics (NeuroSystematics) might be a conceptual analog of the Periodic System of Chemical Elements. scRNA-seq profiling of all neurons in an entire brain or Brain-seq is now fully achievable in many nontraditional reference species across the entire animal kingdom. Arguably, marine animals are the most suitable for the proposed tasks because the world oceans represent the greatest taxonomic and body-plan diversity.

Subcellular Peptide Localization in Single Identified Neurons by Capillary Microsampling Mass Spectrometry

Single cell mass spectrometry (MS) is uniquely positioned for the sequencing and identification of peptides in rare cells. Small peptides can take on different roles in subcellular compartments. Whereas some peptides serve as neurotransmitters in the cytoplasm, they can also function as transcription factors in the nucleus. Thus, there is a need to analyze the subcellular peptide compositions in identified single cells. Here, we apply capillary microsampling MS with ion mobility separation for the sequencing of peptides in single neurons of the mollusk Lymnaea stagnalis, and the analysis of peptide distributions between the cytoplasm and nucleus of identified single neurons that are known to express cardioactive Phe-Met-Arg-Phe amide-like (FMRFamide-like) neuropeptides. Nuclei and cytoplasm of Type 1 and Type 2 F group (Fgp) neurons were analyzed for neuropeptides cleaved from the protein precursors encoded by alternative splicing products of the FMRFamide gene. Relative abundances of nine neuropeptides were determined in the cytoplasm. The nuclei contained six of these peptides at different abundances. Enabled by its relative enrichment in Fgp neurons, a new 28-residue neuropeptide was sequenced by tandem MS.

Integrating Mass Spectrometry with Microphysiological Systems for Improved Neurochemical Studies

Microphysiological systems, often referred to as "organs-on-chips", are in vitro platforms designed to model the spatial, chemical, structural, and physiological elements of in vivo cellular environments. They enhance the evaluation of complex engineered biological systems and are a step between traditional cell culture and in vivo experimentation. As neurochemists and measurement scientists studying the molecules involved in intercellular communication in the nervous system, we focus here on recent advances in neuroscience using microneurological systems and their potential to interface with mass spectrometry. We discuss a number of examples - microfluidic devices, spheroid cultures, hydrogels, scaffolds, and fibers - highlighting those that would benefit from mass spectrometric technologies to obtain improved chemical information.

Optically Guided Single Cell Mass Spectrometry of Rat Dorsal Root Ganglia to Profile Lipids, Peptides and Proteins

The mammalian dorsal root ganglia (DRG) are located on the dorsal roots of the spinal nerves and contain cell bodies of primary sensory neurons. DRG cells have been classified into subpopulations based on their size, morphology, intracellular markers, response to stimuli, and neuropeptides. To understand the connections between DRG chemical heterogeneity and cellular function, we performed optically guided, high-throughput single cell profiling using sequential matrix-assisted laser desorption/ionization mass spectrometry (MS) to detect lipids, peptides, and several proteins in individual DRG cells. Statistical analysis of the resulting mass spectra allows stratification of the DRG population according to cellular morphology and, presumably, major cell types. A subpopulation of small cells contained myelin proteins, which are abundant in Schwann cells, and mass spectra of several larger cells contained peaks matching neurofilament, vimentin, myelin basic protein S, and thymosin beta proteins. Of the over 1000 cells analyzed, approximately 78 % produced putative peptide-rich spectra, allowing the population to be classified into three distinct cell types. Two signals with m/z 4404 and 5487 were exclusively observed in a cell type, but could not be matched to results of our previous liquid chromatography-MS analyses.