“…Conversely the DCX+ populations, isolated from the DCX-YFP lines show proteins involved in neural differentiation-related pathways including axon development and neuron projection guidance. You can see examples of expected results in ( Melliou et al., 2022 ) and Figure 3 . Figure 3 An example for visualizing the proteomic analysis of raw LC-MS/MS data files (A) Volcano plot of differentially abundant proteins between SOX2+ (right) and DCX+ (left) organoid cell populations.…”
Section: Expected Outcomesmentioning
confidence: 68%
“…The exact timepoint to take organoids out of the culture will depend on the expression levels of the peptides of interest. In our work, we have used cerebral organoids that were 4–8 weeks old ( Melliou et al., 2022 ). However, we have tested our protocol for organoid cultures up to 10 weeks old.…”
Section: Step-by-step Methods Detailsmentioning
confidence: 99%
“…This generalizable approach can be used to study temporal and cell-type-specific protein dynamics in developing cerebral organoids. For complete details on the use and execution of this protocol, please refer to Melliou et al. (2022) .…”
mentioning
confidence: 99%
“…For complete details on the use and execution of this protocol, please refer to Melliou et al. (2022) .…”
“…Conversely the DCX+ populations, isolated from the DCX-YFP lines show proteins involved in neural differentiation-related pathways including axon development and neuron projection guidance. You can see examples of expected results in ( Melliou et al., 2022 ) and Figure 3 . Figure 3 An example for visualizing the proteomic analysis of raw LC-MS/MS data files (A) Volcano plot of differentially abundant proteins between SOX2+ (right) and DCX+ (left) organoid cell populations.…”
Section: Expected Outcomesmentioning
confidence: 68%
“…The exact timepoint to take organoids out of the culture will depend on the expression levels of the peptides of interest. In our work, we have used cerebral organoids that were 4–8 weeks old ( Melliou et al., 2022 ). However, we have tested our protocol for organoid cultures up to 10 weeks old.…”
Section: Step-by-step Methods Detailsmentioning
confidence: 99%
“…This generalizable approach can be used to study temporal and cell-type-specific protein dynamics in developing cerebral organoids. For complete details on the use and execution of this protocol, please refer to Melliou et al. (2022) .…”
mentioning
confidence: 99%
“…For complete details on the use and execution of this protocol, please refer to Melliou et al. (2022) .…”
“…While previous studies have investigated post-transcriptional regulation of specific genes or the impact of loss of key RNA-binding proteins (Hoye and Silver, 2020), proteome-scale analyses of gene regulation during human corticogenesis have been lacking. Currently available proteome data from hiPSC-derived neural progenitors and neurons (Djuric et al, 2017; Varderidou-Minasian et al, 2020), cerebral organoids (McClure-Begley et al, 2018; Melliou et al, 2022; Nascimento et al, 2019), and the fetal brain (Djuric et al, 2017; Kim et al, 2014; Melliou et al, 2022) are an important step towards establishing a human neurodevelopmental proteomic repertoire. However, these studies suffer from some of the following limitations: a) due to the inherent diversity of cell types present during corticogenesis, bulk tissue data do not provide cell type-specific information, b) cell sorting strategies result in datasets that suffer from low number of successfully detected proteins, and c) importantly, a direct comparison of the transcript and protein expression to understand posttranscriptional gene regulation has been missing.…”
During development of the human cerebral cortex, multipotent neural progenitors generate excitatory neurons and glial cells. Investigations of the transcriptome and epigenome have revealed important gene regulatory networks underlying this crucial developmental event. However, the post-transcriptional control of gene expression and protein abundance during human corticogenesis remains poorly understood. We addressed this issue by using human telencephalic brain organoids grown using a dual reporter cell line to isolate neural progenitors and neurons and performed cell type and developmental stagespecific transcriptome and proteome analysis. Integrating the two datasets revealed modules of gene expression during human corticogenesis. Investigation of one such module uncovered mTOR-mediated translational regulation of the 5’TOP element-enriched translation machinery in early progenitor cells. We show that in early progenitors partial inhibition of the translation of ribosomal genes prevents precocious translation of differentiation markers. Overall, our multiomics approach reveals novel posttranscriptional regulatory mechanisms crucial for the fidelity of cortical development.HighlightsTranscriptome and proteome-based gene expression regulation during human corticogenesisDistinct posttranscriptional mechanisms for cell type-specific temporal gene expressionRibosomal mRNAs with 5’TOP motif are translated less efficiently in early progenitorsTranslational regulation of 5’TOP mRNAs ensures fidelity of cortical development
The human brain represents one of the most complex biological structures with significant spatiotemporal molecular plasticity occurring through early development, learning, aging, and disease. While much progress has been made in mapping its transcriptional architecture, more downstream phenotypic readouts are relatively scarce due to limitations with tissue heterogeneity and accessibility, as well as an inability to amplify protein species prior to global -OMICS analysis. To address some of these barriers, our group has recently focused on using mass-spectrometry workflows compatible with small amounts of formalin-fixed paraffin-embedded tissue samples. This has enabled exploration into spatiotemporal proteomic signatures of the brain and disease across otherwise inaccessible neurodevelopmental timepoints and anatomical niches.Given the similar theme and approaches, we introduce an integrated online portal, "The Brain Protein Atlas (BPA)" (www.brainproteinatlas.org), representing a public resource that allows users to access and explore these amalgamated datasets. Specifically, this portal contains a growing set of peer-reviewed mass-spectrometry-based proteomic datasets, including spatiotemporal profiles of human cerebral development, diffuse gliomas, clinically aggressive meningiomas, and a detailed anatomic atlas of glioblastoma. One barrier to entry in mass spectrometry-based proteomics data analysis is the steep learning curve required to extract biologically relevant data. BPA, therefore, includes several built-in analytical tools to generate relevant plots (e.g., volcano plots, heatmaps, boxplots, and scatter plots) and evaluate the spatiotemporal patterns of proteins of interest. Future iterations aim to expand available datasets, including those generated by the community at large, and analytical tools for exploration. Ultimately, BPA aims to improve knowledge dissemination of proteomic information across the neuroscience community in hopes of accelerating the biological understanding of the brain and various maladies.
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