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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.

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.

Metabolomics provides a snapshot of the metabolic status of biological samples. This knowledge can give insights into several biological processes, including understanding the etiology and development of diseases such as cancer or type 2 diabetes. Mass spectrometry is the golden standard technique for metabolite profiling due to its high sensitivity and comprehensive analyte coverage. Although several sampling techniques are available for routine metabolomics studies, these usually require sample sizes of around 1 million cells. The work entailed in this thesis focuses on developing sampling strategies to perform metabolomic studies on challenging samples, namely, low cell number and minute volume samples, down to single cells. 

The direct infusion probe (DIP) that I developed enables the analysis of metabolites and lipids in minute sample volumes with low cell numbers. Specifically, it enables analysis of samples containing as low as 20 cells/µL in 5 µL volumes. The DIP has a user-friendly and simple design that allows for rapidly switching samples. Furthermore, it provides minimal carryover between samples by simply washing with the next sample for 8 seconds, which enhances the analysis throughput by eliminating extra washing steps. I utilized the DIP to conduct metabolite and lipid profiling of insulin-releasing cells (INS-1) exposed to high glucose. I observed that high glucose exposure causes changes in the abundance of amino acids, lipids, and other small molecules. Our results are linked with pathways, such as glycolysis, fatty acid biosynthesis, and glutamate and sphingolipid metabolisms that are altered in type 2 diabetes. 

Another analytically challenging task that I address in this thesis is the chemical analysis of individual cells. Single-cell metabolomics is crucial to decoding cellular heterogeneity and identifying phenotype variations within a cell population. I redesigned the pneumatically assisted nanospray desorption electrospray ionization (PA nano-DESI) probe to enable the analysis of metabolites and lipids from single cells. This was accomplished by reducing the inner diameter of capillaries to enhance ionization and tapering the capillaries of the probe to establish a miniaturized liquid bridge. Then, I utilized the tapered PA nano-DESI probe to profile the metabolome and lipidome of single INS-1 cells and senescent IMR-90 cells. The results show alterations in glutamate and arachidonic acid levels, characteristic of insulin release and aging processes, respectively. 

Overall, the DIP and the tapered PA nano-DESI probes represent significant analytical advances in conducting metabolomic studies of samples containing low cell numbers down to single cells.

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.