Cantlon, J. | Search bioRxiv

bioRxiv2021

High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip

Global quantification of protein abundances in single cells would provide more direct information on cellular function phenotypes and complement transcriptomics measurements. However, single-cell proteomics (scProteomics) is still immature and confronts technical challenges, including limited proteome coverage, poor reproducibility, as well as low throughput. Here we describe a nested nanoPOTS (N2) chip to dramatically improve protein recovery, operation robustness, and processing throughput for isobaric-labeling-based scProteomics workflow. The N2 chip allows reducing cell digestion volume to <30 nL and increasing processing capacity to > 240 single cells in one microchip. In the analysis of [~]100 individual cells from three different cell lines, we demonstrate the N2 chip-based scProteomics platform can robustly quantify [~]1500 proteins and reveal functional differences. Our analysis also reveals low protein abundance variations (median CVs < 16.3%), highlighting the utility of such measurements, and also suggesting the single-cell proteome is highly stable for the cells cultured under identical conditions.

systems biology↗

bioRxiv2020

Entropy, complexity, and maturity in children's neural responses during naturalistic mathematics learning

AO_SCPLOWBSTRACTC_SCPLOWA major goal of human neuroscience is to understand how the brain functions in the real world, and to measure neural processes under naturalistic conditions that are more ecologically valid than traditional laboratory tasks. A critical step toward this goal is understanding how neural activity during real world naturalistic tasks relates to neural activity in more traditional laboratory tasks. In the present study, we used intersubject correlations to locate reliable stimulus-driven neural processes among children and adults in naturalistic and laboratory versions of a mathematics task that shared the same content. We show that relative to a control condition with grammatical content, naturalistic and simplified mathematics tasks evoked overlapping activation within brain regions previously associated with math semantics. We further examined the temporal properties of childrens neural responses during the naturalistic and laboratory tasks to determine whether temporal patterns of neural activity change over development, or dissociate based on semantic or task content. We introduce a rather novel measure, not yet used in fMRI studies of child learning: neural multiscale entropy. In addition to showing new evidence of naturalistic mathematics processing in the developing brain, we show that neural maturity and neural entropy are two independent but complementary markers of functional brain development. We discuss the implications of these results for the development of neural complexity in children.

neuroscience↗