ArticleAnalytical chemistry2014
Patch clamp electrophysiology and capillary electrophoresis-mass spectrometry metabolomics for single cell characterization.
Article in Analytical chemistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
60 citing papers in PubMed, 142 citations in OpenAlex.
- Multimodal atlas of single neuron metabolic electrophysiological coupling uncovers circadian rewiring.iScience · 2026Article
- Resolving subcellular sucrose concentrations in plant tissues.Journal of experimental botany · 2026Review
- Patch-Clamp Single-Cell Proteomics in Acute Brain Slices: A Framework for Recording, Retrieval, and Interpretation.ACS chemical neuroscience · 2026Article
- Patch-Clamp Single-Cell Proteomics in Acute Brain Slices: A Framework for Recording, Retrieval, and Interpretation.bioRxiv : the preprint server for biology · 2025Article
- Recent Developments in Single-Cell Metabolomics by Mass Spectrometry─A Perspective.Journal of proteome research · 2025Review
- Integrative single-cell metabolomics and phenotypic profiling reveals metabolic heterogeneity of cellular oxidation and senescence.Nature communications · 2025Article
- Miniature origami robot for various biological micromanipulations.Nature communications · 2025Article
- Targeted and Untargeted Amine Metabolite Quantitation in Single Cells with Isobaric Multiplexing.Chemistry (Weinheim an der Bergstrasse, Germany) · 2024Article
- Microfluidic-Based Electrical Operation and Measurement Methods in Single-Cell Analysis.Sensors (Basel, Switzerland) · 2024Review
- Sex differences in single neuron function and proteomics profiles examined by patch-clamp and mass spectrometry in the locus coeruleus of the adult mouse.Acta physiologica (Oxford, England) · 2024Article
- Single-cell omic molecular profiling using capillary electrophoresis-mass spectrometry.Trends in analytical chemistry : TRAC · 2023Article
- Electrochemically Etched Tapered-Tip Stainless-Steel Electrospray-Ionization Emitters for Capillary Electrophoresis-Mass Spectrometry.Journal of proteome research · 2023Article
- Single cell metabolism: current and future trends.Metabolomics : Official journal of the Metabolomic Society · 2022Review
- Profiling 26,000 Aplysia californica neurons by single cell mass spectrometry reveals neuronal populations with distinct neuropeptide profiles.The Journal of biological chemistry · 2022Article
- The Intriguing Landscape of Single-Cell Protein Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY.Mass spectrometry reviews · 2022Review
- Review
- Single-Cell Mass Spectrometry of Metabolites and Proteins for Systems and Functional Biology.Neuromethods · 2022Article
- When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective.Frontiers in oncology · 2022Review
- Advanced tools and methods for single-cell surgery.Microsystems & nanoengineering · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.