Biology subjects

Carr, S. A.

Publications and source records attributed to Carr, S. A..

89 records · Page 5Linked to original sources

bioRxiv2020

RNA-protein interaction mapping via MS2 or Cas13-based APEX targeting

RNA-protein interactions underlie a wide range of cellular processes. Improved methods are needed to systematically map RNA-protein interactions in living cells in an unbiased manner. Capitalizing on the ability of the engineered peroxidase APEX2 to identify protein interaction partners via proximity-dependent biotinylation, we used two approaches to target APEX2 to specific cellular RNAs. Both an MS2-MCP system and an engineered CRISPR-Cas13 system were able to deliver APEX2 to the human telomerase RNA hTR with high specificity. One-minute proximity biotinylation captured endogenous protein interaction partners of hTR, including more than a dozen proteins not previously linked to hTR. We validated the unexpected interaction between hTR and the N6-methyladenosine (m6A) demethylase ALKBH5. Further investigation showed that endogenous hTR is modified by m6A, which can be erased by ALKBH5, and that ALKBH5 influences both telomerase complex assembly and activity. These results highlight the ability of MS2- and Cas13-targeted APEX2 to identify novel RNA-protein interactions in living cells.

molecular biology↗

bioRxiv2020

Thousands of novel unannotated proteins expand the MHC I immunopeptidome in cancer

Tumor epitopes - peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumor-specific peptides, targetable by immunotherapies.

cancer biology↗

bioRxiv2019

A conserved translation factor is required for optimal synthesis of a membrane protein family in mycobacteria

Ribosomes require the activity of associated GTPases to synthesize proteins. Despite strong evolutionary conservation, the roles of many of these remain unknown. For example, LepA (also known as elongation factor 4) is a ribosome-associated GTPase found in bacteria, mitochondria, and chloroplasts, yet its physiological contribution to cell survival is not clear. Recently, we found that loss of lepA in Mycobacterium smegmatis (Msm) altered tolerance to rifampin, a drug that targets a non-ribosomal cellular process. To uncover the determinants of LepA-mediated drug tolerance, we characterized the whole-cell proteomes and transcriptomes of a lepA deletion mutant relative to a wild-type strain. We find that LepA is important for the steady-state abundance of an outer membrane porin, which is integral to nutrient uptake and drug susceptibility. Loss of LepA leads to a decreased amount of porin in the membrane, resulting in the drug tolerance phenotype of the lepA mutant. LepA control requires a sequence motif in the 5 region of the porin transcript. Thus, LepA controls the abundance of specific proteins, likely through its activity during translation. ImportanceOur understanding of how ribosomes properly synthesis an entire cellular proteome, in all its complexity, is still evolving. Ribosomal GTPases are often highly conserved, but the roles of many are not well understood. For example, elongation factor 4, or LepA, is a ribosome-associated GTPase conserved across bacteria, mitochondria, and chloroplasts. Using whole-cell proteomics and RNA-sequencing of wild type and a lepA deletion mutant, we find that LepA improves translation of mycobacterial porins in a message-specific manner. As porins play a key role in cell wall permeability, loss of LepA produces a plethora of phenotypic changes. These findings underline the problem of building proteins into a complex cell wall, such as that of mycobacteria, and point to a solution in the use of GTPases such as LepA, that have evolved to aid in specific protein synthesis.

microbiology↗

bioRxiv2019

Cell-Surface Proteomic Profiling in the Fly Brain Uncovers New Wiring Regulators

Molecular interactions at the cellular interface mediate organized assembly of single cells into tissues, and thus govern the development and physiology of multicellular organisms. Here, we developed a cell-type-specific, spatiotemporally-resolved approach to profile cell-surface proteomes in intact tissues. Quantitative profiling of cell-surface proteomes of Drosophila olfactory projection neurons (PNs) in pupae and adults revealed a global down-regulation of wiring molecules and an up-regulation of synaptic molecules in the transition from developing to mature PNs. A proteome-instructed in vivo screen identified 20 new cell-surface molecules regulating neural circuit assembly, many of which belong to evolutionarily conserved protein families not previously linked to neural development. Genetic analysis further revealed that the lipoprotein receptor LRP1 cell-autonomously controls PN dendrite targeting, contributing to the formation of a precise olfactory map. These findings highlight the power of temporally-resolved in situ cell-surface proteomic profiling in discovering new regulators of brain wiring.

neuroscience↗

bioRxiv2019

Microscaled Proteogenomic Methods for Precision Oncology

Cancer proteogenomics integrates genomics, transcriptomics and mass spectrometry (MS)-based proteomics to gain insights into cancer biology and treatment efficacy. A proteogenomics approach was therefore developed for frozen core biopsies using tissue-sparing specimen processing with a \"microscaled\" proteomics workflow. For technical proof-of-principle, biopsies from ERBB2 positive breast cancers before and 48-72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy were analyzed. ERBB2 protein and phosphosite levels, as well as mTOR target phosphosites, were significantly more suppressed upon treatment in cases associated with pathological complete response, suggesting MS-based pharmacodynamics is achievable. Furthermore, integrated analyses indicated potential causes of treatment resistance including the absence of ERBB2 amplification (false-ERBB2 positive) and insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2 positive). Candidate resistance features in true-ERBB2+ cases, including androgen receptor signaling, mucin expression and an inactive immune microenvironment were observed. Thus, proteogenomic analysis of needle core biopsies is feasible and clinical utility should be investigated.

cancer biology↗

bioRxiv2019

Dual protease type XIII/pepsin digestion offers superior resolution and overlap for the analysis of histone tails by HX-MS

The N-terminal regions of histone proteins (tails) are dynamic elements that protrude from the nucleosome and are involved in many aspects of chromatin organization. Their epigenetic role is well-established, and post-translational modifications (PTMs) present on these regions contribute to transcriptional regulation. While hydrogen/deuterium exchange mass spectrometry (HX-MS) is well-suited for the analysis of dynamic structures, it has seldom been employed to analyze histones due to the poor N-terminal coverage obtained using pepsin. Here, we test the applicability of a dual protease type XIII/pepsin digestion column to this class of proteins. We optimize online digestion conditions using the H4 monomer, and extend the method to the analysis of histones in monomeric states and nucleosome core particles (NCPs). We show that the dual protease column generates many short and overlapping N-terminal peptides. We evaluate our method by performing hydrogen exchange experiments of NCPs for different time points and present full coverage of the tails at excellent resolution. We further employ electron transfer dissociation (ETD) and showcase an unprecedented degree of overlap across multiple peptides that is several fold higher than previously reported methods. The method we report here may be readily applied to the HX-MS investigation of histone dynamics and to the footprints of histone binding proteins on nucleosomes.

biochemistry↗

bioRxiv2019

UbiFast, a rapid and deep-scale ubiquitylation profiling approach for biology and translational research

Protein ubiquitylation is involved in a plethora of cellular processes. Defects in the ubiquitin system are at the root of many acquired and hereditary diseases. While antibodies directed at ubiquitin remnants (K-{varepsilon}-GG) have improved the ability to monitor ubiquitylation using mass spectrometry, methods for highly-multiplexed measurement of ubiquitylation in tissues and primary cells using sub-milligram amounts of sample remains a challenge. Here we present a highly-sensitive, rapid and multiplexed protocol for quantifying [~]10,000 ubiquitylation sites from as little as 500 ug peptide per sample from cells or tissue in a TMT10 plex in ca. 5 hr. High-field Asymmetric Ion Mobility Spectrometry (FAIMS) is used to improve quantitative accuracy for posttranslational modification analysis. We use the approach to rediscover substrates of the E3 ligase targeting drug lenalidomide and to identify proteins modulated by ubiquitylation in models of basal and luminal human breast cancer. The sensitivity and speed of the UbiFast method makes it suitable for large-scale studies in primary tissue samples.

biochemistry↗

bioRxiv2019

Glucocorticoids Induce the Expansion of an Immature Human CFU-E Population

Despite effective clinical use, the mechanistic bases for the regulation of human erythropoiesis by glucocorticoids remain poorly understood. Here, we employed an erythroid culture system to differentiate primary human CD34+ cells isolated from control peripheral blood, cord blood and patients with Diamond Blackfan anemia (DBA), as model of an erythropoietic disorder treated with glucocorticoids. We found that the response to Dexamethasone is dependent on the developmental origin of the source of CD34+ cells, specifically increasing the expansion of CD34+ cells from peripheral blood but not cord blood. We also demonstrated that Dex treatment leads to the expansion of a novel immature colony-forming unit-erythroid (CFU-E) population in peripheral blood which is uniquely responsible for the proliferative effects observed during human adult erythropoiesis. Dex treatment of peripheral blood CFU-E cells also induced p57Kip2 expression while patients with DBA resistant to steroids had altered p57Kip2 expression that did not increase with Dex. Furthermore, shRNA knockdown of p57Kip2 reduced proliferation and abrogated the effects of Dex. Finally, proteomics of Dex-treated CFU-E from peripheral blood and cord blood additionally revealed novel Dex targets in the erythroid system. Altogether, these results provide novel insights into the regulation of human erythropoiesis by glucocorticoids.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC=\"FIGDIR/small/722850v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@c5c076org.highwire.dtl.DTLVardef@dec2f9org.highwire.dtl.DTLVardef@d27737org.highwire.dtl.DTLVardef@190c795_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2019

Domain-specific quantification of prion protein in cerebrospinal fluid by targeted mass spectrometry

Therapies currently in preclinical development for prion disease seek to lower prion protein (PrP) expression in the brain. Trials of such therapies are likely to rely on quantification of PrP in cerebrospinal fluid (CSF) as a pharmacodynamic biomarker and possibly as a trial endpoint. Studies using PrP ELISA kits have reproducibly shown that CSF PrP is lowered in the symptomatic phase of disease, a potential confounder for reading out the effect of PrP-lowering drugs in symptomatic patients. To date it has been unclear whether the reduced abundance of PrP in CSF results from its incorporation into plaques, retention in intracellular compartments, downregulation as a function of the disease process, or other factors. Because misfolding or proteolytic cleavage could potentially render PrP invisible to ELISA even if its concentration were constant or increasing in disease, we sought to establish an orthogonal method for CSF PrP quantification. We developed a targeted mass spectrometry method based on multiple reaction monitoring (MRM) of nine PrP tryptic peptides quantified relative to known concentrations of isotopically labeled standards. Analytical validation experiments showed process replicate coefficients of variation below 15%, good dilution linearity and recovery, and suitable performance for both CSF and brain homogenate and across humans as well as preclinical species of interest. In N=55 CSF samples from individuals referred to prion surveillance centers with rapidly progressive dementia, all six human PrP peptides, spanning the N- and C-terminal domains of PrP, were uniformly reduced in prion disease cases compared to individuals with non-prion diagnoses. This confirms the findings from ELISA studies, demonstrating that lowered CSF PrP concentration in prion disease is a genuine result of the disease process and not merely an artifact of ELISA-based measurement. We provide a targeted mass spectrometry-based method suitable for preclinical and clinical quantification of CSF PrP as a tool for drug development.

neuroscience↗

bioRxiv2019

Avant-garde: An automated data-driven DIA data curation tool.

Data-Independent Acquisition (DIA) is a technique that promises to comprehensively detect and quantify all peptides above an instruments limit of detection. Several software tools to analyze DIA data have been developed in recent years. However, several challenges still remain, like confidently identifying peptides, defining integration boundaries, dealing with interference for selected transitions, and scoring and filtering of peptide signals in order to control false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. Avant-garde is a new tool to refine DIA (and PRM) by removing interfered transitions, adjusting integration boundaries and scoring peaks to control the FDR. Unlike other tools where MS runs are scored independently from each other, Avant-garde uses a novel data-driven scoring strategy. DIA signals are refined by learning from the data itself, using all measurements in all samples together to achieve the best optimization. We evaluated the performances of Avant-garde with a calibrated sample using spiked-in standards in a complex background, a phospho-enriched dataset (Abelin et al, 2016), and two complex hybrid proteome samples for benchmarking DIA software tools. The results clearly showed that Avant-garde is capable of improving the selectivity, accuracy, and reproducibility of the quantification results in very complex biological matrices. We have further shown that it can evaluate the suitability of a peak to be used for quantification reaching the same levels of selectivity, accuracy, and reproducibility obtained with manual validation.

bioinformatics↗

bioRxiv2018

A schizophrenia risk gene, NRGN, bidirectionally modulates synaptic plasticity via regulating the neuronal phosphoproteome

NRGN is a schizophrenia risk gene identified in recent genetic studies, encoding a small neuronal protein, neurogranin (Ng). Individuals carrying a risk variant of NRGN showed decreased hippocampal activation during contextual fear conditioning. Furthermore, the expression of Ng was reduced in the post-mortem brains of schizophrenic patients. Using the mouse model, we found that the translation of Ng in hippocampus is rapidly increased in response to novel context exposure, and this up-regulation is required for encoding contextual memory. The extent and degree of the effect that altered Ng expression has on neuronal cellular functions are largely unknown. Here, we found that Ng bidirectionally regulates synaptic plasticity in the hippocampus. Elevated Ng levels facilitated long-term potentiation (LTP), whereas decreased Ng levels impaired LTP. Quantitative phosphoproteomic analysis revealed that decreasing Ng caused a significant shift in the phosphorylation status of postsynaptic density proteins, highlighting clusters of schizophrenia- and autism-related genes. In particular, decreasing Ng led to the hypo-phosphorylation of NMDAR subunit Grin2A at newly identified sites, resulting in accelerated decay of NMDAR-mediated channel currents. blocking protein phosphatase PP2B activity rescued the accelerated synaptic NMDAR current decay and the impairment of LTP caused by decreased Ng levels, suggesting that enhanced synaptic PP2B activity led to the deficits. Taken together, our work suggests that altered Ng levels under pathological conditions affect the phosphorylation status of neuronal proteins by tuning PP2B activity and thus the induction of synaptic plasticity, revealing a novel mechanistic link of a schizophrenia risk gene to cognitive deficits.

neuroscience↗

bioRxiv2018

Brain-Specific Deletion of GIT1 Impairs Cognition and Alters Phosphorylation of Synaptic Protein Networks Implicated in Schizophrenia Susceptibility

Despite tremendous effort, the molecular and cellular basis of cognitive deficits in schizophrenia remain poorly understood. Recent progress in elucidating the genetic architecture of schizophrenia has highlighted the association of multiple loci and rare variants that may impact susceptibility. One key example, given their potential etiopathogenic and therapeutic relevance, is a set of genes that encode proteins that regulate excitatory glutamatergic synapses in brain. A critical next step is to delineate specifically how such genetic variation impacts synaptic plasticity and to determine if and how the encoded proteins interact biochemically with one another to control cognitive function in a convergent manner. Towards this goal, here we study the roles of GPCR-kinase interacting protein 1 (GIT1), a synaptic scaffolding and signaling protein with damaging coding variants found in schizophrenia patients, as well as copy number variants found in patients with neurodevelopmental disorders. We generated conditional neural-selective GIT1 knockout mice and find that these mice have deficits in fear conditioning learning and spatial memory. Using global quantitative phospho-proteomics, we revealed that GIT1 deletion in brain perturbs specific networks of GIT1-interacting synaptic proteins. Importantly, several schizophrenia and neurodevelopmental disorder risk genes are present within these networks. We propose that GIT1 regulates the phosphorylation of a network of synaptic proteins and other critical regulators of neuroplasticity, and that perturbation of these networks may contribute to cognitive deficits observed in schizophrenia and neurodevelopmental disorders.

neuroscience↗

bioRxiv2018

Tetracyclines Modify Translation By Targeting Key Human rRNA Substructures.

Apart from their antimicrobial properties, tetracyclines demonstrate clinically validated effects in the amelioration of pathological inflammation and human cancer. Delineation of the target(s) and mechanism(s) responsible for these effects, however, has remained elusive. Here, employing quantitative mass spectrometry-based proteomics, we identified human 80S ribosomes as targets of the tetracyclines Col-3 and doxycycline. We then developed in cell click selective crosslinking with RNA sequence profiling (icCL-Seq) to map binding sites for these tetracyclines on key human rRNA substructures at nucleotide resolution. Importantly, we found that structurally and phenotypically variant tetracycline analogs could chemically discriminate these rRNA binding sites. We also found that tetracyclines both subtly modify human ribosomal translation and selectively activate the cellular integrated stress response (ISR). Together, the data reveal that targeting of specific rRNA substructures, activation of the ISR, and inhibition of translation are correlated with the anti-proliferative properties of tetracyclines in human cancer cell lines.

cell biology↗

bioRxiv2017

Directed evolution of TurboID for efficient proximity labeling in living cells and organisms

Protein interaction networks and protein compartmentation underlie every signaling process and regulatory mechanism in cells. Recently, proximity labeling (PL) has emerged as a new approach to study the spatial and interaction characteristics of proteins in living cells. However, the two enzymes commonly used for PL come with tradeoffs - BioID is slow, requiring tagging times of 18-24 hours, while APEX peroxidase uses substrates that have limited cell permeability and high toxicity. To address these problems, we used yeast display-based directed evolution to engineer two mutants of biotin ligase, TurboID and miniTurbo, with much greater catalytic efficiency than BioID, and the ability to carry out PL in cells in much shorter time windows (as little as 10 minutes) with non-toxic and easily deliverable biotin. In addition to shortening PL time by 100-fold and increasing PL yield in cell culture, TurboID enabled biotin-based PL in new settings, including yeast, Drosophila, and C. elegans.

bioengineering↗

bioRxiv2017

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations

Though the added value of proteomic measurements to gene expression profiling has been demonstrated, profiling of gene expression on its own remains the dominant means of understanding cellular responses to perturbation. Direct protein measurements are typically limited due to issues of cost and scale; however, the recent development of high-throughput, targeted sentinel mass spectrometry assays provides an opportunity for proteomics to contribute at a meaningful scale in high-value areas for drug development. To demonstrate the feasibility of a systematic and comprehensive library of perturbational proteomic signatures, we profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays -- one measuring global changes of epigenetic marks on histone proteins and another measuring a set of peptides reporting on the phosphoproteome -- for a total of more than 3,400 samples. This effort represents a first-of-its-kind resource for proteomics. The majority of tested drugs generated reproducible responses in both phosphosignaling and chromatin states, but we observed differences in the responses that were cell line-and assay-specific. We formalized the process of comparing response signatures within the data using a concept called connectivity, which enabled us to integrate data across cell types and assays. Furthermore, it facilitated incorporation of transcriptional signatures. Consistent connectivity among cell types revealed cellular responses that transcended cell-specific effects, while consistent connectivity among assays revealed unexpected associations between drugs that were confirmed by experimental follow-up. We further demonstrated how the resource could be leveraged against public domain external datasets to recognize therapeutic hypotheses that are consistent with ongoing clinical trials for the treatment of multiple myeloma and acute lymphocytic leukemia (ALL). These data are available for download via the Gene Expression Omnibus (accession GSE101406), and web apps for interacting with this resource are available at https://clue.io/proteomics.\n\nHighlightsO_LIFirst-of-its-kind public resource of proteomic responses to systematically administered perturbagens\nC_LIO_LIDirect proteomic profiling of phosphosignaling and chromatin states in cells for 90 drugs in six different cell lines\nC_LIO_LIExtends Connectivity Map concept to proteomic data for integration with transcriptional data\nC_LIO_LIEnables recognition of unexpected, cell type-specific activities and potential translational therapeutic opportunities\nC_LI

systems biology↗

bioRxiv2017

CRISPR/Cas9-APEX-mediated proximity labeling enables discovery of proteins associated with a predefined genomic locus in living cells

The activation or repression of a genes expression is primarily controlled by changes in the proteins that occupy its regulatory elements. The most common method to identify proteins associated with genomic loci is chromatin immunoprecipitation (ChIP). While having greatly advanced our understanding of gene expression regulation, ChIP requires specific, high quality, IP-competent antibodies against nominated proteins, which can limit its utility and scope for discovery. Thus, a method able to discover and identify proteins associated with a particular genomic locus within the native cellular context would be extremely valuable. Here, we present a novel technology combining recent advances in chemical biology, genome targeting, and quantitative mass spectrometry to develop genomic locus proteomics, a method able to identify proteins which occupy a specific genomic locus.

biochemistry↗

bioRxiv2017

Specter: linear deconvolution as a new paradigm for targeted analysis of data-independent acquisition mass spectrometry proteomics

Mass spectrometry with data-independent acquisition (DIA) has emerged as a promising method to greatly improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory systematically measuring all peptide precursors within a biological sample. Despite the technical maturity of DIA, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms and alternative site localizations in phosphoproteomics data. We have developed Specter, an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly in terms of a spectral library, circumventing the problems associated with typical fragment correlation-based approaches. We validate the sensitivity of Specter and its performance relative to other methods by means of several complex datasets, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

bioinformatics↗