The visual selection of specific cells within an ex vivo brain slice, combined with whole-cell patch clamp recording and capillary electrophoresis (CE)-mass spectrometry (MS)-based metabolomics, yields high chemical information on the selected cells. By providing access to a cell's intracellular environment, the whole-cell patch clamp technique allows one to record the cell's physiological activity. A patch clamp pipet is used to withdraw ∼3 pL of cytoplasm for metabolomic analysis using CE-MS. Sampling the cytoplasm, rather than an intact isolated neuron, ensures that the sample arises from the cell of interest and that structures such as presynaptic terminals from surrounding, nontargeted neurons are not sampled. We sampled the rat thalamus, a well-defined system containing gamma-aminobutyric acid (GABA)-ergic and glutamatergic neurons. The approach was validated by recording and sampling from glutamatergic thalamocortical neurons, which receive major synaptic input from GABAergic thalamic reticular nucleus neurons, as well as neurons and astrocytes from the ventral basal nucleus and the dorsal lateral geniculate nucleus. From the analysis of the cytoplasm of glutamatergic cells, approximately 60 metabolites were detected, none of which corresponded to the compound GABA. However, GABA was successfully detected when sampling the cytoplasm of GABAergic neurons, demonstrating the exclusive nature of our cytoplasmic sampling approach. The combination of whole-cell patch clamp with single cell cytoplasm metabolomics provides the ability to link the physiological activity of neurons and astrocytes with their neurochemical state. The observed differences in the metabolome of these neurons underscore the striking cell to cell heterogeneity in the brain.

Cell-to-cell variability and functional heterogeneity are integral features of multicellular organisms. Chemical classification of cells into cell type is important for understanding cellular specialization as well as organismal function and organization. Assays to elucidate these chemical variations are best performed with single cell samples because tissue homogenates average the biochemical composition of many different cells and oftentimes include extracellular components. Several single cell microanalysis techniques have been developed but tend to be low throughput or require preselection of molecular probes that limit the information obtained. Mass spectrometry (MS) is an untargeted, multiplexed, and sensitive analytical method that is well-suited for studying chemically complex individual cells that have low analyte content. In this work, populations of cells from the rat pituitary, the rat pancreatic islets of Langerhans, and from the Aplysia californica nervous system, are classified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI) MS by their peptide content. Cells were dispersed onto a microscope slide to generate a sample where hundreds to thousands of cells were separately located. Optical imaging was used to determine the cell coordinates on the slide, and these locations were used to automate the MS measurements to targeted cells. Principal component analysis was used to classify cellular subpopulations. The method was modified to focus on the signals described by the lower principal components to explore rare cells having a unique peptide content. This approach efficiently uncovers and classifies cellular subtypes as well as discovers rare cells from large cellular populations.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is used for the multiplex detection and characterization of diverse analytes over a wide mass range directly from tissues. However, analyte coverage with MALDI MSI is typically limited to the more abundant compounds, which have m/z values that are distinct from MALDI matrix-related ions. On-tissue analyte derivatization addresses these issues by selectively tagging functional groups specific to a class of analytes, while simultaneously changing their molecular masses and improving their desorption and ionization efficiency. We evaluated electrospray deposition of liquid-phase derivatization agents as a means of on-tissue analyte derivatization using 2-picolylamine; we were able to detect a range of endogenous fatty acids with MALDI MSI. When compared with airbrush application, electrospray led to a 3-fold improvement in detection limits and decreased analyte delocalization. Six fatty acids were detected and visualized from rat cerebrum tissue using a MALDI MSI instrument operating in positive mode. MALDI MSI of the hippocampal area allowed targeted fatty acid analysis of the dentate gyrus granule cell layer and the CA1 pyramidal layer with a 20-μm pixel width, without degrading the localization of other lipids during liquid-phase analyte derivatization.

A receptor binding class of d-amino acid-containing peptides (DAACPs) is formed in animals from an enzymatically mediated post-translational modification of ribosomally translated all-l-amino acid peptides. Although this modification can be required for biological actions, detecting it is challenging because DAACPs have the same mass as their all-l-amino acid counterparts. We developed a suite of mass spectrometry (MS) protocols for the nontargeted discovery of DAACPs and validated their effectiveness using neurons from Aplysia californica. The approach involves the following three steps, with each confirming and refining the hits found in the prior step. The first step is screening for peptides resistant to digestion by aminopeptidase M. The second verifies the presence of a chiral amino acid via acid hydrolysis in deuterium chloride, labeling with Marfey's reagent, and liquid chromatography-mass spectrometry to determine the chirality of each amino acid. The third involves synthesizing the putative DAACPs and comparing them to the endogenous standards. Advantages of the method, the d-amino acid-containing neuropeptide discovery funnel, are that it is capable of detecting the d-form of any common chiral amino acid, and the first two steps do not require peptide standards. Using these protocols, we report that two peptides from the Aplysia achatin-like neuropeptide precursor exist as GdYFD and SdYADSKDEESNAALSDFA. Interestingly, GdYFD was bioactive in the Aplysia feeding and locomotor circuits but SdYADSKDEESNAALSDFA was not. The discovery funnel provides an effective means to characterize DAACPs in the nervous systems of animals in a nontargeted manner.

While droplet microfluidics is becoming an effective tool for biomedical research, sensitive detection of droplet content is still challenging, especially for multiplexed analytes compartmentalized within ultrasmall droplets down to picoliter volumes. To enable such measurements, we demonstrate a silicon-based integrated microfluidic platform for multiplexed analysis of neurochemicals in picoliter droplets via nanoelectrospray ionization (nESI)-mass spectrometry (MS). An integrated silicon microfluidic chip comprising downscaled 7 μm-radius channels, a compact T-junction for droplet generation, and an integrated nESI emitter tip is used for segmentation of analytes into picoliter compartments and their efficient delivery for subsequent MS detection. The developed system demonstrates effective detection of multiple neurochemicals encapsulated within oil-isolated plugs down to low picoliter volumes. Quantitative measurements for each neurochemical demonstrate limits of detection at the attomole level. Such results are promising for applications involving label-free and small-volume detection for monitoring a range of brain chemicals.

Neuropeptides are synthesized in and released from neurons and are involved in a wide range of physiological processes, including temperature homeostasis, learning, memory, and disease. When working with sparse neuronal networks, the ability to collect and characterize small sample volumes is important as neurons often release only a small proportion of their mass-limited content. Microfluidic systems are well suited for the study of neuropeptides. They offer the ability to control and manipulate the extracellular environment and small sample volumes, thereby reducing the dilution of peptides following release. We present an approach for the culture and stimulation of a neuronal network within a microfluidic device, subsequent collection of the released peptides, and their detection via mass spectrometry. The system employs microvalve-controlled stimulation channels to selectively stimulate a low-density neuronal culture, allowing us to determine the temporal onset of peptide release. Released peptides from the well-characterized, peptidergic bag cell neurons of Aplysia californica were collected and their temporal pattern of release was characterized with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. We show a robust difference in the timing of release for chemical solutions containing elevated K(+) (7 ± 3 min), when compared to insulin (19 ± 7 min) (p < 0.000 01).

Mammalian circadian rhythm is maintained by the suprachiasmatic nucleus (SCN) via an intricate set of neuropeptides and other signaling molecules. In this work, peptidomic analyses from two times of day were examined to characterize variation in SCN peptides using three different label-free quantitation approaches: spectral count, spectra index and SIEVE. Of the 448 identified peptides, 207 peptides were analyzed by two label-free methods, spectral count and spectral index. There were 24 peptides with significant (adjusted p-value < 0.01) differential peptide abundances between daytime and nighttime, including multiple peptides derived from secretogranin II, cocaine and amphetamine regulated transcript, and proprotein convertase subtilisin/kexin type 1 inhibitor. Interestingly, more peptides were analyzable and had significantly different abundances between the two time points using the spectral count and spectral index methods than with a prior analysis using the SIEVE method with the same data. The results of this study reveal the importance of using the appropriate data analysis approaches for label-free relative quantitation of peptides. The detection of significant changes in so rich a set of neuropeptides reflects the dynamic nature of the SCN and the number of influences such as feeding behavior on circadian rhythm. Using spectral count and spectral index, peptide level changes are correlated to time of day, suggesting their key role in circadian function.

The integration of disparate data types provides a more complete picture of complex biological systems. Here we combine small-volume metabolomic and transcriptomic platforms to determine subtle chemical changes and to link metabolites and genes to biochemical pathways. Capillary electrophoresis-mass spectrometry (CE-MS) and whole-genome gene expression arrays, aided by integrative pathway analysis, were utilized to survey metabolomic/transcriptomic hippocampal neurochemistry. We measured changes in individual hippocampi from the mast cell mutant mouse strain, C57BL/6 Kit(W-sh/W-sh). These mice have a naturally occurring mutation in the white spotting locus that causes reduced c-Kit receptor expression and an inability of mast cells to differentiate from their hematopoietic progenitors. Compared with their littermates, the mast cell-deficient mice have profound deficits in spatial learning, memory, and neurogenesis. A total of 18 distinct metabolites were identified in the hippocampus that discriminated between the C57BL/6 Kit(W-sh/W-sh) and control mice. The combined analysis of metabolite and gene expression changes revealed a number of altered pathways. Importantly, results from both platforms indicated that multiple pathways are impacted, including amino acid metabolism, increasing the confidence in each approach. Because the CE-MS and expression profiling are both amenable to small-volume analysis, this integrated analysis is applicable to a range of volume-limited biological systems.