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Single-cell metabolomics has the potential to reveal unique insights into intracellular mechanisms and biological processes. However, the detection of metabolites from individual cells is challenging due to their versatile chemical properties and concentrations. Here, we demonstrate a tapered probe for pneumatically assisted nanospray desorption electrospray ionization (PA nano-DESI) mass spectrometry that enables both chemical imaging of larger cells and global metabolomics of smaller 15 mu m cells. Additionally, by depositing cells in predefined arrays, we show successful metabolomics from three individual INS-1 cells per minute, which enabled the acquisition of data from 479 individual cells. Several cells were used to optimize analytical conditions, and 93 or 97 cells were used to monitor metabolome alterations in INS-1 cells after exposure to a low or high glucose concentration, respectively. Our analytical approach offers insights into cellular heterogeneity and provides valuable information about cellular processes and responses in individual cells.

Research continues to identify genetic variation, environmental exposures, and their mixtures underlying different diseases and conditions. There is a need for screening methods to understand the molecular outcomes of such factors. Here, we investigate a highly efficient and multiplexable, fractional factorial experimental design (FFED) to study six environmental factors (lead, valproic acid, bisphenol A, ethanol, fluoxetine hydrochloride and zinc deficiency) and four human induced pluripotent stem cell line derived differentiating human neural progenitors. We showcase the FFED coupled with RNA-sequencing to identify the effects of low-grade exposures to these environmental factors and analyse the results in the context of autism spectrum disorder (ASD). We performed this after 5-day exposures on differentiating human neural progenitors accompanied by a layered analytical approach and detected several convergent and divergent, gene and pathway level responses. We revealed significant upregulation of pathways related to synaptic function and lipid metabolism following lead and fluoxetine exposure, respectively. Moreover, fluoxetine exposure elevated several fatty acids when validated using mass spectrometry-based metabolomics. Our study demonstrates that the FFED can be used for multiplexed transcriptomic analyses to detect relevant pathway-level changes in human neural development caused by low-grade environmental risk factors. Future studies will require multiple cell lines with different genetic backgrounds for characterising the effects of environmental exposures in ASD.

Targeted and nontargeted metabolomics has the potential to evaluate and detect global metabolite changes in biological systems. Direct infusion mass spectrometric analysis enables detection of all ionizable small molecules, thus simultaneously providing information on both metabolites and lipids in chemically complex samples. However, to unravel the heterogeneity of the metabolic status of cells in culture and tissue a low number of cells per sample should be analyzed with high sensitivity, which requires low sample volumes. Here, we present the design and characterization of the direct infusion probe, DIP. The DIP is simple to build and position directly in front of a mass spectrometer for rapid metabolomics of chemically complex biological samples using pneumatically assisted electrospray ionization at 1 mu L/min flow rate. The resulting data is acquired in a square wave profile with minimal carryover between samples that enhances throughput and enables several minutes of uniform MS signal from 5 mu L sample volumes. The DIP was applied to study the intracellular metabolism of insulin secreting INS-1 cells and the results show that exposure to 20 mM glucose for 15 min significantly alters the abundance of several small metabolites, amino acids, and lipids.

Single-cell metabolomics with mass spectrometry enables a large variety of metabolites to be simultaneously detected from individual cells, without any preselection or labelling, to map phenotypes on the single cell level. Although the field is relatively young, it is steadily progressing with an increasing number of active research groups, techniques for cell sampling and ionization, tools for data analysis, and applications to answer important biomedical and environmental questions. In addition, the community shows great creativity in overcoming challenges associated with low sample volumes, a wide range of metabolite species, and large datasets. Here, we briefly discuss publications since 2019 and aim to provide the unfamiliar reader with an insight into the field and the expert reader with an update on the current status of the field.

Objective: Metabolic syndrome is prevalent in up to 50% of schizophrenia patients, which reduces their quality of life and their compliance with the treatment. It is unclear whether metabolic adverse effects of these agents are due to their direct effect on insulin-sensitive tissues or are secondary to increased adiposity. The study aimed to investigate the direct effects of the second-generation antipsychotics olanzapine and aripiprazole on human subcutaneous adipose tissue and isolated adipocyte metabolism.

Methods: Abdominal subcutaneous adipose tissue needle biopsies were taken from 72 healthy subjects (49 F/23 M; age: 19-78 yr; BMI: 20.0-35.6 kg/m(2)). Isolated adipocytes or adipose tissue were respectively pre-incubated short- (30 min) and long-term (24 h, 72 h) with or without olanzapine (0.004 mu M - 20 mu M) and aripiprazole (0.002 mu M - 100 mu M). Pre-incubated adipose tissue was then snap-frozen for mRNA expression analysis of adipokines genes and genes involved in inflammation, adipogenesis, and mitochondrial function. Isolated adipocytes were used to measure basal and insulin-stimulated glucose uptake and lipolysis.

Results: Acute treatment with a therapeutic concentration of olanzapine decreases basal lipolysis in isolated adipocytes; this effect was not observed after long-term incubation with the drug. Supra-therapeutic concentration of aripiprazole reduced basal and insulin-stimulated glucose uptake after short- and long-term preincubation. Both drugs at supra-therapeutic concentrations downregulated the expression of the pro-inflammatory cytokines IL6 and IL1B genes after 72 h incubation. Similarly, supra-therapeutic concentrations of both drugs and therapeutic concentration of olanzapine, reduced the expression of PPARGC1A, PDK4, and CPT1B genes involved in the regulation of mitochondria] functions. Neither of the antipsychotics affected the expression of the main adipokines LEP and ADIPOQ, genes involved in the regulation of lipid metabolism, LPL and FASN, nor the master adipogenesis regulator, PPARG.

Conclusion: Therapheutic concentrations of olanzapine and aripiprazole have a moderate direct effect on adipocyte lipid and glucose metabolism, respectively. At supra-therapeutic concentrations, both of the antipsychotics seem to act as anti-inflammatory agents and mildly suppressed genes involved in the regulation of mitochondrial functions, which could potentially contribute to metabolic adverse effects. Alternatively, second-generation antipsychotics could induce metabolic side effects via acting on other insulin-sensitive tissues and central nervous system.