Biology subjects

Reiter, L.

Publications and source records attributed to Reiter, L..

17 recordsLinked to original sources

bioRxiv2026

Deconvolving the structural heterogeneity of alpha-Synuclein in vitro and in situ

The structural states of proteins in cells and tissues provide important insight into their functional states, but studying protein structures in situ remains challenging. Furthermore, a single protein can adopt multiple conformations in cells, which typically cannot be assessed by most structural approaches. Here we developed a novel approach, based on structural proteomics fingerprints, for the quantitative analysis of the distribution of structural states of a protein in vitro and in situ. We applied it to the Parkinsons disease hallmark protein alpha-synuclein (aSyn), for which various structural states (disordered, helical, oligomeric and amyloid fibrillar, among others) have been characterized in vitro, but for which the in vivo structural states remain hotly debated. We measured structure-specific proteolytic fingerprints from well-characterized aSyn in vitro conformations and used them to quantitatively determine the aSyn conformational composition in samples of interest. We first benchmarked our approach using ground truth datasets of known composition and showed that, during in vitro amyloid fibril formation, we could simultaneously detect a time-dependent decrease in disordered monomeric aSyn, an increase in {beta}-sheet-rich oligomers, and a delayed rise in amyloid fibrils. We then applied the method to complex, biologically relevant samples. In a S. cerevisiae aSyn overex-pression model, aSyn was predominantly helical, with an increased helical fraction accompanying its relocalization from the plasma membrane to cytosolic lipid droplets. This shift was linked to proteome-wide changes in lipid droplet homeostasis and fatty acid and ergosterol metabolism, underscoring the role of lipid metabolism and droplet formation in aSyn biology. Importantly, we also detected helical aSyn in human iPSC-derived cortical neurons, supporting the physiological relevance of this conformation. Finally, neurons differentiated from PD patient-derived iPSCs showed elevated levels of {beta}-sheet-rich aSyn compared to wild-type cells. Our approach allowed the in situ identification and quantification of different structural states of aSyn directly in cell lysates. Since several proteins can adopt multiple, functionally-relevant conformations in cells, our approach should be broadly applicable to in situ, quantitative structural and functional studies of proteins.

neuroscience↗

bioRxiv2026

A Parallel Accumulation-Mobility Aligned Fragmentation Strategy Utilizing High-Resolution Ion Mobility for High Performance Proteomics Analysis

Here we present a novel data independent acquisition (DIA) mass spectrometry (MS) operating mode termed parallel accumulation-mobility aligned fragmentation (PAMAF) that offers enhanced speed and sensitivity of ion fragmentation analysis for nontargeted discovery workflows such as bottom-up proteomics. This mode of operation leverages high-resolution ion mobility (HRIM) separation capabilities of the structures for lossless ion manipulation (SLIM) technology to achieve HRIM-based precursor isolation in place of traditional quadrupole filtering approaches. This PAMAF mode of operation increases the number of features that can be identified per MS1/MS2 acquisition cycle by employing mobility-based time alignment to associate fragment ions with their corresponding precursor ions. By using a high-speed, lossless separation technique for precursor isolation instead of the comparatively slow and wasteful quadrupole filtering method, we can avoid ion losses up to 99% while simultaneously increasing the rate at which precursor ions are sequentially fragmented and detected. Additionally, by storing ions in a trapping region while the previous packet of ions is being analyzed, the PAMAF mode achieves [~]100% ion utilization efficiency. Benchmarking results of LC-PAMAF-MS analysis of a whole cell protein digest showed approximately 6x more protein group identifications compared to a standard data-dependent acquisition (DDA) analysis without HRIM on the same QTOF instrument, and to over 100x improvement for low-load workflows. Quantitative evaluations demonstrated that PAMAF mode could quantify low abundance peptides, including those undetectable by DDA. Additionally, since precursor isolation in PAMAF mode is size-based rather than m/z-based, many coeluting isobars and isomers can be resolved prior to fragmentation to eliminate chimeric spectra that compromise identification accuracy. In this work we also explored the benefits of combining HRIM and quadrupole isolation to achieve improved specificity. This approach, known as DIA-PAMAF mode, further reduces the frequency of chimeric fragmentation spectra, and enabled the detection of over 8,000 protein groups from a HeLa digest analysis. PAMAF mode brings a powerful new technique to the field of proteomics that has the potential to improve the sensitivity and selectivity of mass spectrometry-based proteomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/704896v1_ufig1.gif" ALT="Figure 1"> View larger version (114K): org.highwire.dtl.DTLVardef@7984c3org.highwire.dtl.DTLVardef@1fb2fe3org.highwire.dtl.DTLVardef@50d35org.highwire.dtl.DTLVardef@1a62926_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

A flexible end-to-end automated sample preparation workflow enables reproducible large-scale bottom-up proteomics

Bottom-up proteomics holds significant promise for clinical applications due to its high sensitivity and precision, but is limited by labor-intensive, low-throughput sample preparation methods. Advanced automation is essential to enhance throughput, reproducibility, and accuracy and to allow standardization to make bottom-up proteomics amenable for large-scale studies. We developed a fully integrated, automated sample preparation platform that covers the entire process from biological sample input to mass spectrometry-ready peptide output and can be applied on a multitude of biological samples. With this end-to-end solution, we achieved high intra- and inter-plate reproducibility, as well as longitudinal consistency, resulting in precise and reproducible workflows. We showed that our automated workflow surpasses established manual and semi-automated workflows, while improving time efficiency. Finally, we demonstrated the suitability of our automated sample preparation platform for drug development by performing a high-content compound characterization for targeted protein degradation, where high throughput and quantitative accuracy are indispensable. For this, we coupled application-specific workflows to perform proteome profiling and confirm target degradation by precise protein quantification. Overall, our results highlight the selective degradation of specific proteins of interest for ten selected compounds across two cell lines. Thus, the automated sample preparation platform facilitates rapid adaptation to emerging developments in proteomics sample preparation, combining standardization, flexibility, and high-throughput capabilities to drive significant advancements in clinical assays and proteomics research.

biochemistry↗

bioRxiv2025

Enhanced Identifications and Quantification through Retention Time Down-Sampling in Fast-Cycling diagonal-PASEF Methods

Data-independent acquisition mass spectrometry is essential for comprehensive quantification of proteomes, enabling deeper insights into cellular processes and disease mechanisms. On the timsTOF platform, diagonal-PASEF acquisition methods have recently been introduced to directly and continuously cover the observed diagonal shape of the peptide precursor ion distributions. Although diagonal-PASEF has shown great promise, its broad adoption as a routine workflow has been hampered by a lack of available algorithmic solutions and a paucity of demonstrated real-world applications. Here, we conducted a systematic and comprehensive optimization of diagonal-PASEF for 17-minute gradients on the timsTOF HT in conjunction to Spectronaut 19. We demonstrate that Spectronaut 19 fully supports all tested diagonal-PASEF methods independent of the number of slices or overlaps and with minimal user intervention required. Using our optimized analysis strategy we coupled diagonal-PASEF acquisitions to retention time down-sampling by summation (RTsum), thereby providing a novel mode of analysis of this data that exploits the fast-cycling nature of diagonal-PASEF methods. Through the combination of RTsum with diagonal-PASEF, we demonstrate that this strategy yields higher signal-to-noise ratios while retaining the peak shape for analytes of interest. Importantly, combining RTsum with diagonal-PASEF improved overall identifications and quantitative precision when compared to dia-PASEF with static or variable quadrupole isolation widths and across different input amounts for cell line injections. We also tested the performance of diagonal-PASEF in controlled quantitative experiments where diagonal-PASEF outperformed dia-PASEF in the overall number of retained candidates, quantitative precision and identifications on peptide level. These data indicate that RTsum demonstrates a positive use case of the high sampling rate of diagonal-PASEF. Collectively, our findings imply that diagonal-PASEF methods are superior for peptide and protein level analyses especially at lower input amounts.

biochemistry↗

bioRxiv2024

A Comprehensive and Robust Multiplex-DIA Workflow Profiles Protein Turnover Regulations Associated with Cisplatin Resistance

Measuring protein turnover is essential for understanding cellular biological processes and advancing drug discovery. The multiplex DIA mass spectrometry (DIA-MS) approach, combined with dynamic SILAC labeling (pulse-SILAC, or pSILAC), has proven to be a reliable method for analyzing protein turnover and degradation kinetics. Previous multiplex DIA-MS workflows have employed various strategies, including leveraging the highest isotopic labeling channels of peptides to enhance the detection of isotopic MS signal pairs or clusters. In this study, we introduce an improved and robust workflow that integrates a novel machine learning strategy and channel-specific statistical filtering, enabling dynamic adaptation to systematic or temporal variations in channel ratios. This allows comprehensive profiling of protein turnover throughout the pSILAC experiment without relying solely on the highest channel signals. Additionally, we developed KdeggeR, a data processing and analysis package optimized for pSILAC-DIA experiments, which estimates and visualizes peptide and protein degradation rates and dynamic profiles. Our integrative workflow was benchmarked on both 2-channel and 3-channel standard DIA datasets and workflow to an aneuploid cancer cell model before and after cisplatin resistance development demonstrated a strong negative correlation between transcript regulation and protein degradation for major protein complex subunits. We also identified specific protein turnover signatures associated with cisplatin resistance.

systems biology↗

bioRxiv2024

Exosomes Released from Senescent Cells and Circulatory Exosomes Isolated from Human Plasma Reveal Aging-associated Proteomic and Lipid Signatures

Senescence emerged as significant mechanism of aging and age-related diseases, offering an attractive target for clinical interventions. Senescent cells release a senescence-associated secretory phenotype (SASP), including exosomes that may act as signal transducers between distal tissues, propagating secondary or bystander senescence and signaling throughout the body. However, the composition of exosome SASP remains underexplored, presenting an opportunity for novel unbiased discovery. We present a detailed proteomic and lipidomic analysis of exosome SASP using mass spectrometry from human plasma from young and older individuals and from tissue culture of senescent primary human lung fibroblasts. We identified [~]1,300 exosome proteins released by senescent cells induced by three different senescence inducers. In parallel, a human plasma cohort from young (20-26 years) and old (65-74 years) individuals revealed over 1,350 exosome proteins and 171 plasma exosome proteins were regulated when comparing old vs young individuals. Of the age-regulated plasma exosome proteins, we observed 52 exosome SASP factors that were also regulated in exosomes from the senescent fibroblasts, including serine protease inhibitors (SERPINs), Prothrombin, Coagulation factor V, Plasminogen, and Reelin. 247 lipids were identified in exosome samples. Following senescence induction, identified phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins increased significantly indicating cellular membrane changes. Interestingly, significantly changed proteins were related to extracellular matrix remodeling and inflammation, both potentially detrimental pathways that can damage surrounding tissues and even induce secondary senescence. Our findings reveal mechanistic insights and potential senescence biomarkers, enabling a better approach to surveilling the senescence burden in the aging population and offering therapeutic targets for interventions.

cell biology↗

bioRxiv2024

Glial expression of Drosophila UBE3A causes spontaneous seizures modulated by 5-HT signaling

Misexpression of the E3 ubiquitin ligase UBE3Ais thought to contribute to a range of neurological disorders. In the context of Dup15q syndrome, excess genomic copies of UBE3A is thought to contribute to the autism, muscle tone and spontaneous seizures characteristic of the disorder. In a Drosophila model of Dup 15q syndrome, it was recently shown glial-driven expression of the UBE3A ortholog dube3a led to a "bang-sensitive" phenotype, where mechanical shock triggers convulsions, suggesting glial dube3a expression contributes to hyperexcitability in flies. Here we directly compare the consequences of glial- and neuronal-driven dube3a expression on motor coordination and neuronal excitability in Drosophila. We utilized IowaFLI tracker and developed a hidden Markov Model to classify seizure-related immobilization. Both glial and neuronal driven dube3a expression led to clear motor phenotypes. However, only glial-driven dube3a expression displayed spontaneous immobilization events, that were exacerbated at high-temperature (38 {degrees}C). Using a tethered fly preparation we monitored flight muscle activity, we found glial-driven dube3a flies display spontaneous spike discharges which were bilaterally synchronized indicative of seizure activity. Neither control flies, nor neuronal-dube3a overexpressing flies display such firing patterns. Prior drug screen indicated bang-sensitivity in glial-driven dube3a expressing flies could be suppressed by certain 5-HT modulators. Consistent with this report, we found glial-driven dube3a flies fed the serotonin reuptake inhibitor vortioxetine and the 5HT2A antagonist ketanserin displayed reduced immobilization and spike bursting. Together these findings highlight the potential for glial pathophysiology to drive Dup15q syndrome-related seizure activity.

neuroscience↗

bioRxiv2023

Substantial Downregulation of Mitochondrial and Peroxisomal Proteins during Acute Kidney Injury revealed by Data-Independent Acquisition Proteomics

Acute kidney injury (AKI) manifests as a major health concern, particularly for the elderly. Understanding AKI-related proteome changes is critical for prevention and development of novel therapeutics to recover kidney function and to mitigate the susceptibility for recurrent AKI or development of chronic kidney disease. In this study, mouse kidneys were subjected to ischemia-reperfusion injury, and the contralateral kidneys remained uninjured to enable comparison and assess injury-induced changes in the kidney proteome. A fast-acquisition rate ZenoTOF 7600 mass spectrometer was introduced for data-independent acquisition (DIA) for comprehensive protein identification and quantification. Short microflow gradients and the generation of a deep kidney-specific spectral library allowed for high-throughput, comprehensive protein quantification. Upon AKI, the kidney proteome was completely remodeled, and over half of the 3,945 quantified protein groups changed significantly. Downregulated proteins in the injured kidney were involved in energy production, including numerous peroxisomal matrix proteins that function in fatty acid oxidation, such as ACOX1, CAT, EHHADH, ACOT4, ACOT8, and Scp2. Injured mice exhibited severely declined health. The comprehensive and sensitive kidney-specific DIA assays highlighted here feature high-throughput analytical capabilities to achieve deep coverage of the kidney proteome and will serve as useful tools for developing novel therapeutics to remediate kidney function.

molecular biology↗

bioRxiv2021

Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area

The plasma proteome has the potential to enable a holistic analysis of the health state of an individual. However, plasma biomarker discovery is difficult due to its high dynamic range and variability. Here, we present a novel automated analytical approach for deep plasma profiling and applied it to a 180-sample cohort of human plasma from lung, breast, colorectal, pancreatic, and prostate cancer. Using a controlled quantitative experiment, we demonstrate a 257% increase in protein identification and a 263% increase in significantly differentially abundant proteins over neat plasma. In the cohort, we identified 2,732 proteins. Using machine learning, we discovered biomarker candidates such as STAT3 in colorectal cancer and developed models that classify the disease state. For pancreatic cancer, a separation by stage was achieved. Importantly, biomarker candidates came predominantly from the low abundance region, demonstrating the necessity to deeply profile because they would have been missed by shallow profiling.

cancer biology↗

bioRxiv2021

Molecular Changes in Prader-Willi Syndrome Neurons Reveals Clues About Increased Autism Susceptibility.

BackgroundPrader-Willi syndrome (PWS) is a neurodevelopmental disorder characterized by hormonal dysregulation, obesity, intellectual disability, and behavioral problems. Most PWS cases are caused by paternal interstitial deletions of 15q11.2-q13.1, while a smaller number of cases are caused by chromosome 15 maternal uniparental disomy (PW-UPD). Children with PW-UPD are at higher risk for developing autism spectrum disorder (ASD) than the neurotypical population. In this study, we used expression analysis of PW-UPD neurons to try to identify the molecular cause for increased autism risk. MethodsDental pulp stem cells (DPSC) from neurotypical control and PWS subjects were differentiated to neurons for mRNA sequencing. Significantly differentially expressed transcripts among all groups were identified. Downstream protein analysis including immunocytochemistry and immunoblots were performed to confirm the transcript level data and pathway enrichment findings. ResultsWe identified 9 transcripts outside of the PWS critical region (15q11.2-q13.1) that may contribute to core PWS phenotypes. Moreover, we discovered a global reduction in mitochondrial transcripts in the PW-UPD +ASD group. We also found decreased mitochondrial abundance along with mitochondrial aggregates in the cell body and neural projections of +ASD neurons. LimitationsDPSC derived neuronal cultures used here were immature (3 weeks old), while important for studying the development of the disorder, it will be critical to confirm these mitochondrial defects in more mature neurons or postmortem brain tissue. Our PW-UPD -ASD group included only females, but the sample size in downstream image analysis was increased to include males for the analysis of mitochondrial phenotypes. The ASD diagnostic tool we use is the Social Communication Questionnaire (SCQ), which has been used extensively, but is not the gold standard for ASD diagnosis. ConclusionsThe 9 transcripts we identified common to all PWS subtypes may reveal PWS specific defects during neurodevelopment. Importantly, we found a global reduction in mitochondrial transcripts in PW-UPD +ASD neurons versus control and other PWS subtypes. We then confirmed mitochondrial defects in neurons from individuals with PWS at the cellular level. Quantification of this phenotype supports our hypothesis that the increased incidence of ASD in PW-UPD subjects may arise from mitochondrial defects in developing neurons.

neuroscience↗

bioRxiv2021

Comprehensive Profiling of Plasma Exosomes Using Data Independent Acquisitions, New Tools for Aging Cohort Studies

Aging is a complex biological process associated with progressive loss of physiological function and susceptibility to several diseases, such as cancer and neurodegeneration. Exosomes are involved in many cellular signaling pathways, and their cargo may serve as promising disease or aging biomarkers. These membrane-bound extracellular vesicles facilitate the transport of intracellular contents to proximal and distal cells in the body. Here, we investigated two omics approaches for exosome analysis. To overcome the challenges of plasma exosome contamination with abundant soluble plasma proteins, we developed a high-throughput method to isolate highly purified exosomes from human plasma by sequential size-exclusion chromatography and ultrafiltration. First, we used data-dependent acquisitions from offline high-pH reversed-phase fractions of exosome lysate to generate a deep spectral library comprising [~]2,300 exosome proteins. Second, in a pilot aging study, we used comprehensive data-independent acquisitions to compare plasma exosomes from young (20-26 yrs) and old (60-66 yrs) individuals. We quantified 1,318 exosome proteins, and levels of 144 proteins were significantly different in young and old plasma groups (Q<0.05 and >1.5-fold change). We also analyzed exosome miRNA cargo and detected 331 miRNAs. Levels of several were significantly different in young and old individuals. In addition, 88 and 17 miRNAs were unique to old and young individuals, respectively. Plasma exosome biomarkers have great potential for translational studies investigating biomarkers of aging and age-related diseases and to monitor therapeutic aging interventions.

cell biology↗

bioRxiv2020

Immunopeptidomics for Dummies: Detailed Experimental Protocols and Rapid, User-Friendly Visualization of MHC I and II Ligand Datasets with MhcVizPipe

Immunopeptidomics refers to the science of investigating the composition and dynamics of peptides presented by major histocompatibility complex (MHC) class I and class II molecules using mass spectrometry (MS). Here, we aim to provide a technical report to any non-expert in the field wishing to establish and/or optimize an immunopeptidomic workflow with relatively limited computational knowledge and resources. To this end, we thoroughly describe step-by-step instructions to isolate MHC class I and II-associated peptides from various biological sources, including mouse and human biospecimens. Most notably, we created MhcVizPipe (MVP) (https://github.com/CaronLab/MhcVizPipe), a new and easy-to-use open-source software tool to rapidly assess the quality and the specific enrichment of immunopeptidomic datasets upon the establishment of new workflows. In fact, MVP enables intuitive visualization of multiple immunopeptidomic datasets upon testing sample preparation protocols and new antibodies for the isolation of MHC class I and II peptides. In addition, MVP enables the identification of unexpected binding motifs and facilitates the analysis of non-canonical MHC peptides. We anticipate that the experimental and bioinformatic resources provided herein will represent a great starting point for any non-expert and will therefore foster the accessibility and expansion of the field to ultimately boost its maturity and impact.

bioinformatics↗

bioRxiv2020

An unbiased drug screen for seizure suppressors in Dup15q syndrome reveals 5HT1A and dopamine pathway activation as potential therapies

Duplication 15q syndrome (Dup15q) is a rare neurogenetic disorder characterized by autistic features and difficult to control (pharmacoresistant) epileptic seizures. Most individuals with isodicentric (idic15) have been on multiple medications to control their seizures and some are still seizing after years of treatment. We recently developed a model of Dup15q in Drosophila by elevating levels of fly Dube3a in glial cells, not neurons. Unlike other Dup15q models, these flies develop seizures that worsen as flies age. Here we used this new model to screen for previously approved compounds from the Prestwick Chemical Library which are able to suppress seizures in flies over-expressing Dube3a in glia using the pan glial driver repo-GAL4. We identified 17 out of 1280 compounds in the library that could suppress a bang sensitive (seizure) phenotype. Eight of these compounds were able to suppress seizures significantly in both males and females by at least 50%. Half of these strong seizure suppressors regulated either serotoninergic or dopaminergic signaling and subsequent experiments confirmed that seizure suppression occurs through stimulation of serotonin receptor 5-HT1A but can be further suppressed with the addition of L-Dopa (Levodopa). We provide further support for a seizure model where Dube3a regulation of the Na+/K+ exchanger ATP in glia can also be modulated by serotonin/dopamine signaling. Finally, based on these pharmacological and genetic studies, we present an argument for the use of 5-HT1A agonists in the treatment of Dup15q epilepsy.

neuroscience↗

bioRxiv2019

LiP-Quant, an automated chemoproteomic approach to identify drug targets in complex proteomes

Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in developing optimized small-molecule compounds. Current unbiased approaches cannot directly pinpoint the interaction surfaces between ligands and protein targets. To address his limitation we have developed a new drug target deconvolution approach based on limited proteolysis coupled with mass spectrometry that works across species including human cells (LiP-Quant). LiP-Quant features an automated data analysis pipeline and peptide-level resolution for the identification of any small-molecule binding sites, Here we demonstrate drug target identification by LiP-Quant across compound classes, including compounds targeting kinases and phosphatases. We demonstrate that LiP-Quant estimates the half maximal effective concentration (EC50) of compound binding sites in whole cell lysates. LiP-Quant identifies targets of both selective and promiscuous drugs and correctly discriminates drug binding to homologous proteins. We finally show that the LiP-Quant technology identifies targets of a novel research compound of biotechnological interest.

systems biology↗

bioRxiv2019

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition (DIA) without the need for spectral libraries

Quantitative phosphoproteomics has in recent years revolutionized understanding of cell signaling, but it remains a challenge to scale the technology for high-throughput analyses. Here we present a rapid and reproducible phosphoproteomics approach to systematically analyze hundreds of samples by fast liquid chromatography tandem mass spectrometry using data independent acquisition (DIA). To overcome the inherent issue of positional phosphopeptide isomers in DIA-based phosphoproteomics, we developed and employed an accurate site localization scoring algorithm, which is incorporated into the Spectronaut software tool. Using a library of synthetic phosphopeptides spiked-in to a yeast phosphoproteome in different ratios we show that it is on par with the top site localization score for data-dependent acquisition (DDA) based phosphoproteomics. Single-shot DIA-based phosphoproteomics achieved an order of magnitude broader dynamic range, higher reproducibility of identification and improved sensitivity and accuracy of quantification compared to state-of-the-art DDA-based phosphoproteomics. Importantly, direct DIA without the need of spectral libraries performed almost on par with analyses using specific project-specific libraries. Moreover, we implemented and benchmarked an algorithm for globally determining phosphorylation site stoichiometry in DIA. Finally, we demonstrate the scalability of the DIA approach by systematically analyzing the effects of thirty different kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that a large proportion of EGF-dependent phospho-regulation is mediated by a specific set of protein kinases.

biochemistry↗

bioRxiv2019

De novo Classification of Mouse B Cell Types using Surfaceome Proteotype Maps

System-wide quantification of the cell surface proteotype and identification of extracellular glycosylation sites is challenging when sample is limiting. We miniaturized and automated the previously described Cell Surface Capture technology increasing sensitivity, reproducibility, and throughput. We used this technology, which we call autoCSC, to create population-specific surfaceome maps of developing mouse B cells and used targeted flow cytometry to uncover developmental cell subpopulations.

biochemistry↗

bioRxiv2018

Quantifying dynamic protein acetylation using quantitative stoichiometry

Protein acetylation is a widespread post-translational modification implicated in many cellular processes. Recent advances in mass spectrometry have enabled the cataloging of thousands of sites throughout the cell, however identifying regulatory acetylation marks have proven to be a daunting task. Knowledge of the kinetics and stoichiometry of site-specific acetylation are important factors to uncover function. Here, an improved method of quantifying acetylation stoichiometry was developed and validated, providing a detailed landscape of dynamic acetylation stoichiometry within cellular compartments. The dynamic nature of site-specific acetylation in response to serum stimulation was revealed. In two distinct human cell lines, growth factor stimulation led to site-specific, temporal acetylation changes, revealing diverse kinetic profiles that clustered into several groups. Overlap of dynamic acetylation sites among two different human cell lines suggested similar regulatory control points across major cellular pathways that include splicing, translation, and protein homeostasis. Rapid increases in acetylation on protein translational machinery suggest a positive regulatory role under pro-growth conditions. Lastly, higher median stoichiometry was observed in cellular compartments where active acetyltransferases are well-described.

biochemistry↗