Quantitative Mass Spectrometry-based Proteomics Reveals the Dynamic Range of Primary Mouse Astrocyte Protein Secretion

Growing appreciation for astrocytes as active participants in nervous system development, neurovascular metabolic coupling, and neurological disease progression has stimulated recent investigation into specific astrocyte-secreted proteins that may mediate these functions. The current work utilized SILAC-generated isotope reference proteomes to quantify relative protein abundances between the astrocyte proteome and secretome. Multidimensional GeLC−MS/MS analysis of astrocyte conditioned media and cell lysates resulted in the relative quantification of 516 proteins, 92 of which were greater than 1.5-fold enriched in astrocyte-conditioned media (ACM). Eighty of the ACM-enriched proteins had N-terminal signal peptides, comprising well-known classically secreted proteins, such as apolipoprotein E and SPARC, and several cathepsins that localize to endosomal/lysosomal compartments. The remaining twelve ACM-enriched proteins, such as vimentin, ferritins, and histones, lacked N-terminal signal peptides. Also, 47 proteins contained predicted N-terminal signal peptides but were not enriched in ACM (<1.5-fold), 25 of which were localized to ER, Golgi, or mitochondria membrane-bound compartments. Overall, by combining quantitative proteomics with subcellular localization prediction, an informative description of protein distribution can be obtained, providing insights into protein secretion

Quantitative Mass Spectrometry-based Proteomics Reveals the Dynamic Range of Primary Mouse Astrocyte Protein Secretion

Growing appreciation for astrocytes as active participants in nervous system development, neurovascular metabolic coupling, and neurological disease progression has stimulated recent investigation into specific astrocyte-secreted proteins that may mediate these functions. The current work utilized SILAC-generated isotope reference proteomes to quantify relative protein abundances between the astrocyte proteome and secretome. Multidimensional GeLC−MS/MS analysis of astrocyte conditioned media and cell lysates resulted in the relative quantification of 516 proteins, 92 of which were greater than 1.5-fold enriched in astrocyte-conditioned media (ACM). Eighty of the ACM-enriched proteins had N-terminal signal peptides, comprising well-known classically secreted proteins, such as apolipoprotein E and SPARC, and several cathepsins that localize to endosomal/lysosomal compartments. The remaining twelve ACM-enriched proteins, such as vimentin, ferritins, and histones, lacked N-terminal signal peptides. Also, 47 proteins contained predicted N-terminal signal peptides but were not enriched in ACM (<1.5-fold), 25 of which were localized to ER, Golgi, or mitochondria membrane-bound compartments. Overall, by combining quantitative proteomics with subcellular localization prediction, an informative description of protein distribution can be obtained, providing insights into protein secretion

Quantitative Mass Spectrometry-based Proteomics Reveals the Dynamic Range of Primary Mouse Astrocyte Protein Secretion

Growing appreciation for astrocytes as active participants in nervous system development, neurovascular metabolic coupling, and neurological disease progression has stimulated recent investigation into specific astrocyte-secreted proteins that may mediate these functions. The current work utilized SILAC-generated isotope reference proteomes to quantify relative protein abundances between the astrocyte proteome and secretome. Multidimensional GeLC−MS/MS analysis of astrocyte conditioned media and cell lysates resulted in the relative quantification of 516 proteins, 92 of which were greater than 1.5-fold enriched in astrocyte-conditioned media (ACM). Eighty of the ACM-enriched proteins had N-terminal signal peptides, comprising well-known classically secreted proteins, such as apolipoprotein E and SPARC, and several cathepsins that localize to endosomal/lysosomal compartments. The remaining twelve ACM-enriched proteins, such as vimentin, ferritins, and histones, lacked N-terminal signal peptides. Also, 47 proteins contained predicted N-terminal signal peptides but were not enriched in ACM (<1.5-fold), 25 of which were localized to ER, Golgi, or mitochondria membrane-bound compartments. Overall, by combining quantitative proteomics with subcellular localization prediction, an informative description of protein distribution can be obtained, providing insights into protein secretion

RNAseq data.

The presence of large protein inclusions is a hallmark of neurodegeneration, and yet the precise molecular factors that contribute to their formation remain poorly understood. Screens using aggregation-prone proteins have commonly relied on downstream toxicity as a readout rather than the direct formation of aggregates. Here, we combined a genome-wide CRISPR knockout screen with Pulse Shape Analysis, a FACS-based method for inclusion detection, to identify direct modifiers of TDP-43 aggregation in human cells. Our screen revealed both canonical and novel proteostasis genes, and unearthed SRRD, a poorly characterized protein, as a top regulator of protein inclusion formation. APEX biotin labeling reveals that SRRD resides in proximity to proteins that are involved in the formation and breakage of disulfide bonds and to intermediate filaments, suggesting a role in regulation of the spatial dynamics of the intermediate filament network. Indeed, loss of SRRD results in aberrant intermediate filament fibrils and the impaired formation of aggresomes, including blunted vimentin cage structure, during proteotoxic stress. Interestingly, SRRD also localizes to aggresomes and unfolded proteins, and rescues proteotoxicity in yeast whereby its N-terminal low complexity domain is sufficient to induce this affect. Altogether this suggests an unanticipated and broad role for SRRD in cytoskeletal organization and cellular proteostasis.</div

Figs S1-S15.

The presence of large protein inclusions is a hallmark of neurodegeneration, and yet the precise molecular factors that contribute to their formation remain poorly understood. Screens using aggregation-prone proteins have commonly relied on downstream toxicity as a readout rather than the direct formation of aggregates. Here, we combined a genome-wide CRISPR knockout screen with Pulse Shape Analysis, a FACS-based method for inclusion detection, to identify direct modifiers of TDP-43 aggregation in human cells. Our screen revealed both canonical and novel proteostasis genes, and unearthed SRRD, a poorly characterized protein, as a top regulator of protein inclusion formation. APEX biotin labeling reveals that SRRD resides in proximity to proteins that are involved in the formation and breakage of disulfide bonds and to intermediate filaments, suggesting a role in regulation of the spatial dynamics of the intermediate filament network. Indeed, loss of SRRD results in aberrant intermediate filament fibrils and the impaired formation of aggresomes, including blunted vimentin cage structure, during proteotoxic stress. Interestingly, SRRD also localizes to aggresomes and unfolded proteins, and rescues proteotoxicity in yeast whereby its N-terminal low complexity domain is sufficient to induce this affect. Altogether this suggests an unanticipated and broad role for SRRD in cytoskeletal organization and cellular proteostasis.</div

APEX2 proximity labeling reveals SRRD in close proximity to intermediate filaments and regulators of IF oligomerization.

1) HEK293Ts stably expressing SRRD-HA stained for HA and either CANX or mitochondria. B) Schematic of APEX2 proximity labeling experiment where APEX2 is fused to SRRD or to an NES control. C) Volcano plot of APEX2 proximity labeling mass spectrometry output, where fold change (x-axis) is plotted by significance (y-axis). Colored dots correspond to STRING clusters in 2E. (*) correspond to indicate functional annotations of interest highlighted in STRING cluster in 2E. D) Filtered GSEA (cellular compartment) of SRRD-APEX2 dataset. E) Clustering of top protein-protein interactions (STRING database) of top 88 proteins ranked by fold change and p-value. Clusters generated with MCL clustering and excludes proteins with no known connections and clusters with insignificant p-values. Clusters colored based on STRING annotated GO terms and proteins with functional annotations of interested are highlighted as follows: Protein-disulfide isomerases circled in pink, proteins involved in calcium binding circled in orange.</p

TDP-43 screen hits (less aggregation).

The presence of large protein inclusions is a hallmark of neurodegeneration, and yet the precise molecular factors that contribute to their formation remain poorly understood. Screens using aggregation-prone proteins have commonly relied on downstream toxicity as a readout rather than the direct formation of aggregates. Here, we combined a genome-wide CRISPR knockout screen with Pulse Shape Analysis, a FACS-based method for inclusion detection, to identify direct modifiers of TDP-43 aggregation in human cells. Our screen revealed both canonical and novel proteostasis genes, and unearthed SRRD, a poorly characterized protein, as a top regulator of protein inclusion formation. APEX biotin labeling reveals that SRRD resides in proximity to proteins that are involved in the formation and breakage of disulfide bonds and to intermediate filaments, suggesting a role in regulation of the spatial dynamics of the intermediate filament network. Indeed, loss of SRRD results in aberrant intermediate filament fibrils and the impaired formation of aggresomes, including blunted vimentin cage structure, during proteotoxic stress. Interestingly, SRRD also localizes to aggresomes and unfolded proteins, and rescues proteotoxicity in yeast whereby its N-terminal low complexity domain is sufficient to induce this affect. Altogether this suggests an unanticipated and broad role for SRRD in cytoskeletal organization and cellular proteostasis.</div

Plasmids submitted to AddGene.

The presence of large protein inclusions is a hallmark of neurodegeneration, and yet the precise molecular factors that contribute to their formation remain poorly understood. Screens using aggregation-prone proteins have commonly relied on downstream toxicity as a readout rather than the direct formation of aggregates. Here, we combined a genome-wide CRISPR knockout screen with Pulse Shape Analysis, a FACS-based method for inclusion detection, to identify direct modifiers of TDP-43 aggregation in human cells. Our screen revealed both canonical and novel proteostasis genes, and unearthed SRRD, a poorly characterized protein, as a top regulator of protein inclusion formation. APEX biotin labeling reveals that SRRD resides in proximity to proteins that are involved in the formation and breakage of disulfide bonds and to intermediate filaments, suggesting a role in regulation of the spatial dynamics of the intermediate filament network. Indeed, loss of SRRD results in aberrant intermediate filament fibrils and the impaired formation of aggresomes, including blunted vimentin cage structure, during proteotoxic stress. Interestingly, SRRD also localizes to aggresomes and unfolded proteins, and rescues proteotoxicity in yeast whereby its N-terminal low complexity domain is sufficient to induce this affect. Altogether this suggests an unanticipated and broad role for SRRD in cytoskeletal organization and cellular proteostasis.</div

Loss of SRRD results in disorganized and downregulated IFs.

A) Confocal images of indicated cells lines stained for VIM. B) Volcano plot of quantitative proteomics experiment comparing SRRD clonal KO HEK293Ts to WT HEK293Ts where fold change (x-axis) is plotted by significance (y-axis). Horizontal dashed line represents adjusted p-value cutoff of 0.05, vertical line represents fold change of -1. Orange and green colored dots correspond to STRING clusters in 3C. C) Select clusters of top depleted proteins in SRRD KO (STRING database) ranked by fold change and p-value. Clusters generated with MCL clustering and excludes proteins with insignificant p-values. Clusters colored based on STRING annotated GO terms. D) Filtered GSEA (cellular compartment) of quantitative proteomics dataset. E) Representative images of NGN2 neurons transduced with SRRD CRISPRi sgRNA or non-targeting control, stained for MAP2 and INA. F) Quantification of the area per cell covered by INA and MAP2 signal in SRRD CRISPRi and NTC control NGN2 neurons.</p

Processed quantitative proteomics data.

The presence of large protein inclusions is a hallmark of neurodegeneration, and yet the precise molecular factors that contribute to their formation remain poorly understood. Screens using aggregation-prone proteins have commonly relied on downstream toxicity as a readout rather than the direct formation of aggregates. Here, we combined a genome-wide CRISPR knockout screen with Pulse Shape Analysis, a FACS-based method for inclusion detection, to identify direct modifiers of TDP-43 aggregation in human cells. Our screen revealed both canonical and novel proteostasis genes, and unearthed SRRD, a poorly characterized protein, as a top regulator of protein inclusion formation. APEX biotin labeling reveals that SRRD resides in proximity to proteins that are involved in the formation and breakage of disulfide bonds and to intermediate filaments, suggesting a role in regulation of the spatial dynamics of the intermediate filament network. Indeed, loss of SRRD results in aberrant intermediate filament fibrils and the impaired formation of aggresomes, including blunted vimentin cage structure, during proteotoxic stress. Interestingly, SRRD also localizes to aggresomes and unfolded proteins, and rescues proteotoxicity in yeast whereby its N-terminal low complexity domain is sufficient to induce this affect. Altogether this suggests an unanticipated and broad role for SRRD in cytoskeletal organization and cellular proteostasis.</div