Project description:In this project, we enabled mass spectrometry based proteomics characterization of single neurons in sections of the mouse brain. We accessed cells in a whole-cell patch clamp configuration and aspirated a portion of the neuronal soma into the patch clamp probe. The collected aspirate was expelled into a microvial, where proteins were extracted and processed for shot-gun analysis. The resulting trace amounts of protein digests were analyzed on a custom-built microanalytical capillary electrophoresis platform that was connected to an electrospray ionization high-resolution mass spectrometer. This “patch proteomics” technology identified ~150 proteins from triplicate measurement of single dopaminergic neurons in the mouse substantia nigra.
Project description:Most single cell RNA sequencing protocols start with single cells dispersed from intact tissue. High-throughput processing of the separated cells is enabled using microfluidics platforms. However, dissociation of tissue results in loss of information about cell location and morphology and potentially alters the transcriptome. An alternative approach for collecting RNA from single cells is to re-purpose the electrophysiological technique of patch clamp recording. A hollow patch pipette is attached to individual cells, enabling the recording of electrical activity, after which the cytoplasm may be extracted for single cell RNA-Seq (“Patch-Seq”). Since the tissue is not disaggregated, the location of cells is readily determined, and the morphology of the cells is maintained, making possible the correlation of single cell transcriptomes with cell location, morphology and electrophysiology. Recent Patch-Seq studies utilizes PCR amplification to increase amount of nucleic acid material to the level required for current sequencing technologies. PCR is prone to create biased libraries – especially with the extremely high degrees of exponential amplification required for single cell amounts of RNA. We compared a PCR-based approach with linear amplifications and demonstrate that aRNA amplification (in vitro transcription, IVT) is more sensitive and robust for single cell RNA collected by a patch clamp pipette.
Project description:We obtained full transcriptome data from single cortical neurons after whole-cell patch-clamp recording (termed “Patch-seq”). By applying “Patch-seq” to cortical neurons, we reveal a close link between biophysical membrane properties and genes coding for neurotransmitter receptors and channels, including well-established and hitherto undescribed subtypes.
Project description:This study combined single-cell RNA-seq with whole-cell patch-clamp recording to profile the neurons in mouse preoptic area with characterized temperature-sensitivity
Project description:To find the molecular basis for abnormal excitability in human iPSC-derived motor neurons with the SOD1 A4V mutation and its involvement in risk of cell loss, we conducted a patch-seq, which combines genome-wide RNA sequencing and patch-clamp recording. This experiment enables excitability and gene expression to be measured simultaneously at a single cell level such that the links between the two could be explored.
Project description:The suprachiasmatic nucleus (SCN) encodes time of day through changes in daily firing, with neurons being generally more active during the day and more silent at night. However, molecular mechanisms by which the SCN encodes and times behavior are not fully understood. To identify factors that could encode day/night differences in activity we combined patch-clamp recordings and single-cell sequencing (Patch-RNAseq) of individual SCN neurons in mice.
Project description:Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomics analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.
