Biology subjects

Olsen, J. V.

Publications and source records attributed to Olsen, J. V..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Global analysis of protein turnover dynamics in single cells

Even with recent improvements in sample preparation and instrumentation, single-cell proteomics (SCP) analyses mostly measure protein abundances, making the field unidimensional. In this study, we employ a pulsed stable isotope labeling by amino acids in cell culture (SILAC) approach to simultaneously evaluate protein abundance and turnover in single cells (SC-pSILAC). Using state-of-the-art SCP workflow, we demonstrated that two SILAC labels are detectable from [~]4000 proteins in single HeLa cells recapitulating known biology. We investigated drug effects on global and specific protein turnover in single cells and performed a large-scale time-series SC-pSILAC analysis of undirected differentiation of human induced pluripotent stem cells (iPSC) encompassing six sampling times over two months and analyzed >1000 cells. Abundance measurements highlighted cell-specific markers of stem cells and various organ-specific cell types. Protein turnover dynamics highlighted differentiation-specific co-regulation of core members of protein complexes with core histone turnover discriminating dividing and non-dividing cells with potential in stem cell and cancer research. Our study represents the most comprehensive SCP analysis to date, offering new insights into cellular diversity and pioneering functional measurements beyond protein abundance. This method distinguishes SCP from other single-cell omics approaches and enhances its scientific relevance in biological research in a multidimensional manner.

systems biology↗

bioRxiv2024

Palaeoproteomic identification of a whale bone tool from Bronze Age Heiloo, the Netherlands

Identification of the taxonomic origin of bone tools is an important, but often complicated, component of studying past societies. The species used for bone tool production provide insight into what species were exploited, potentially how, and for what purpose. Additionally, the choice of species may have important implications for the place of the tool within the larger toolkit. However, the taxonomic identification of bone tools is often unsuccessful based on morphology. Here we apply three palaeoproteomic techniques, ZooMS, SPIN-like data analysis and a targeted database search to narrow down the taxonomic identification of an unusually large Bronze Age bone tool from Heiloo, the Netherlands, to the North Atlantic right whale (Eubalaena glacialis). Additionally, the tool was investigated for use-wear, which showed that it was likely used for the processing of plant fibres. The assignment of the tool as whale bone adds support to the exploitation of whales by coastal Bronze Age populations, not just for meat, as previously suggested, but also for bone as a resource for tool production. We know of no other parallel of a bone tool such as this in terms of size, use, hafting, and taxonomic identity.

evolutionary biology↗

bioRxiv2024

Deciphering molecular mechanisms of synergistic growth reduction in kinase inhibitor combinations

In cancer treatment, the persistent challenge of unresponsiveness of certain patients to drugs or the development of resistance post-treatment remains a significant concern. Drug combinations that synergistically reduce tumor growth emerge as a promising avenue to address this issue. Here, we aimed to characterize the mechanism of action of two synergistic drug combinations that target PI3K together with MEK1 or with TAK1 and used time course measurements of phosphoproteomics and transcriptomics in response to single inhibitors and their combinations. Our analysis untangled those responses driven by single drugs and responses that were unique to the combinations. We observed a high overlap between single-drug responses and their combinations, suggesting that single-drug mechanisms dominate the mechanism of action of the combinations of the kinase inhibitors. Despite a high overlap, both drug combinations exhibited a synergistic modulation of several cell fate regulators found at the convergence points of the targeted pathways, including the key regulator of intrinsic apoptosis BCL2L11. Interestingly, the responses in both combinations were largely limited to the targeted pathways, namely PI3K/AKT and MAPKs, with very limited change of any other additional cell fate decision pathways. In addition, we observed a strong downregulation of nucleotide metabolism and tRNA biosynthesis uniquely in the combinations, which could be attributed to the reduced activity of mTOR and ATF4. Our approach provides insights into the molecular mechanisms affected by the PI3Ki-TAK1i and PI3Ki-MEKi combinations and can serve as a flexible framework for dissecting drug combination responses based on multi-omics measurements.

cancer biology↗

bioRxiv2024

Automated high-throughput biological sex identification from archaeological human dental enamel using targeted proteomics

Biological sex is key information for archaeological and forensic studies, which can be determined by proteomics. However, lack of a standardised approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to high-resolution parallel reaction monitoring assay allowing for a throughput of 200 samples-per-day with high quantitative performance enabling confident identification of both males and females. Additionally, we have developed a streamlined data analysis pipeline and integrated it into an R-Shiny interface for ease-of-use. The method was first developed and optimised using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archaeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by tenfold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archaeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens.

biochemistry↗

bioRxiv2024

STREAMLINED PROTEOME-WIDE IDENTIFICATION OF DRUG TARGETS INDICATES ORGAN-SPECIFIC ENGAGEMENT

Proteins are the primary targets of almost all small molecule drugs. However, even the most selectively designed drugs can potentially target several unknown proteins. Identification of potential drug targets can facilitate design of new drugs and repurposing of existing ones. Current state-of-the-art proteomics methodologies enable screening of thousands of proteins against a limited number of drug molecules. Here we report the development of a label-free quantitative proteomics approach that enables proteome-wide screening of small organic molecules in a scalable, reproducible, and rapid manner by streamlining the proteome integral solubility alteration (PISA) assay. We used rat organs ex-vivo to determine organ specific targets of medical drugs and enzyme inhibitors to identify novel drug targets for common drugs such as Ibuprofen. Finally, global drug profiling revealed overarching trends of how small molecules affect the proteome through either direct or indirect protein interactions.

biochemistry↗

bioRxiv2024

Phosphoproteomic investigation of targets of protein phosphatases in EGFR signaling

Receptor tyrosine kinases (RTKs) initiate cellular signaling pathways, which are regulated through a delicate balance of phosphorylation and dephosphorylation events. While many studies of RTKs have focused on downstream-activated kinases catalyzing the site-specific phosphorylation, few studies have focused on the phosphatases carrying out the dephosphorylation. In this study, we analyzed six protein phosphatase networks using chemical inhibitors in context of epidermal growth factor receptor (EGFR) signaling by mass spectrometry-based phosphoproteomics. Specifically, we focused on protein phosphatase 2C (PP2C), involved in attenuating p38-dependent signaling pathways in various cellular responses, and confirmed its effect in regulating p38 activity in EGFR signaling. Furthermore, utilizing a p38 inhibitor, we classified phosphosites whose phosphorylation status depends on PP2C inhibition into p38-dependent and p38-independent sites. This study provides a large-scale dataset of phosphatase-regulation of EGF-responsive phosphorylation sites, which serves as a useful resource to deepen our understanding of EGFR signaling.

cell biology↗

bioRxiv2023

Fully automated workflow for integrated sample digestion and Evotip loading enabling high-throughput clinical proteomics

Protein identification and quantification is an important tool for biomarker discovery. With the increased sensitivity and speed of modern mass spectrometers, sample-preparation remains a bottleneck for studying large cohorts. To address this issue, we prepared and evaluated a simple and efficient workflow on the Opentrons OT-2 (OT-2) robot that combines sample digestion, cleanup and Evotip loading in a fully automated manner, allowing the processing of up to 192 samples in 6 hours. Our results demonstrate a highly sensitive workflow yielding both reproducibility and stability even at low sample inputs. The workflow is optimized for minimal sample starting amount to reduce the costs for reagents needed for sample preparation, which is critical when analyzing large biological cohorts. Building on the digesting workflow, we incorporated an automated phosphopeptide enrichment step using magnetic Ti-IMAC beads. This allows for a fully automated proteome and phosphoproteome sample preparation in a single step with high sensitivity. Using the integrated workflow, we evaluated the effects of cancer immune therapy on the plasma proteome in metastatic melanoma patients.

molecular biology↗

bioRxiv2023

Multi-layered proteomics identifies insulin-induced upregulation of the EphA2 receptor via the ERK pathway and dependent on low IGF1R level

Insulin resistance impairs the cellular insulin response and frequently precedes metabolic disorders, like type 2 diabetes, which are affecting an increasing number of people globally. Given the critical role of the liver in glucose and lipid metabolism, understanding the molecular mechanisms in hepatic insulin resistance is essential for early preventive treatments. To elucidate changes in insulin signal transduction associated with hepatocellular resistance, we employed a multi-layered mass spectrometry-based proteomics approach focusing on insulin receptor (IR) signaling at the interactome, phosphoproteome, and proteome levels.in a long-term hyperinsulinemia-induced insulin-resistant HepG2 cell line with a knockout of the insulin-like growth factor 1 receptor (IGF1R KO). Analysis of the dynamic insulin-induced IR interactome revealed recruitment of the PI3K complex in both insulin-sensitive and -resistant cells. From the phosphoproteomics dataset, a change in insulin-stimulated signaling responses in insulin resistance was observed and showed attenuated signaling via the metabolic PI3K-AKT pathway but sustained extracellular signal-regulated kinase (ERK) activity. At the proteome level, the ephrin type-A receptor 2 (EphA2) showed an insulin-induced increase in expression. This receptor belongs to the Eph receptor family and participates in various cellular processes, such as cell adhesion, migration, and tissue development. The protein abundance regulation of EphA2 occurred through the ERK signaling pathway and was concordantly independent of insulin resistance. Induction of EphA2 by insulin was confirmed in other cell lines and observed uniquely in cells with high levels of IR compared to IGF1R. The multi-layered proteomics dataset provided insights into insulin signaling in general and in the context of insulin resistance, and it can going forward serve as a resource to generate and test hypotheses, leading to an improved understanding of insulin resistance.

cell biology↗

bioRxiv2023

High-throughput and scalable single cell proteomics identifies over 5000 proteins per cell

The emergence of mass spectrometry (MS)-based single-cell proteomics (SCP) promise to revolutionize the study of cellular biology and biomedicine by providing an unparalleled view of the proteome in individual cells. Despite its groundbreaking potential, SCP is nascent and faces challenges including limited sequence depth, throughput, and reproducibility, which have constrained its broader utility. This study introduces key methodological advances, which considerably improve the sensitivity, coverage and dependability of protein identification from single cells. We developed an almost lossless SCP workflow encompassing sample preparation to MS analysis, doubling the number of identified proteins from roughly 2000 to over 5000 in individual HeLa cells. A comprehensive evaluation of analytical software tools, alongside strict false discovery rate (FDR) controls solidified the reliability of our results. These enhancements also facilitated the direct detection of post-translational modifications (PTMs) in single cells, negating the need for enrichment and thereby simplifying the analytical process. Although throughput in MS remains a challenge, our study demonstrates the feasibility of processing up to 80 label-free SCP samples per day. Moreover, an optimized tissue dissociation buffer enabled effective single cell disaggregation of drug-treated cancer cell spheroids, refining the overall proteomic analysis. Our workflow sets a new benchmark in SCP for sensitivity and throughput, with broad applications ranging from the study of cellular development to disease progression and the identification of cell type-specific markers and therapeutic targets.

systems biology↗

bioRxiv2023

Systematic optimization of automated phosphopeptide enrichment for high-sensitivity phosphoproteomics

Improving coverage, robustness and sensitivity is crucial for routine phosphoproteomics analysis by single-shot liquid chromatography tandem mass spectrometry (LC-MS/MS) runs from minimal peptide inputs. Here, we systematically optimized key experimental parameters for automated on-beads phosphoproteomics sample preparation with focus on low input samples. Assessing the number of identified phosphopeptides, enrichment efficiency, site localization scores and relative enrichment of multiply-phosphorylated peptides pinpointed critical variables influencing the resulting phosphoproteome. Optimizing glycolic acid concentration in the loading buffer, percentage of ammonium hydroxide in the elution buffer, peptide-to-beads ratio, binding time, sample and loading buffer volumes, allowed us to confidently identify >16,000 phosphopeptides in half-an-hour LC-MS/MS on an Orbitrap Exploris 480 using 30 {micro}g of peptides as starting material. Furthermore, we evaluated how sequential enrichment can boost phosphoproteome coverage and showed that pooling fractions into a single LC-MS/MS analysis increased the depth. We also present an alternative phosphopeptide enrichment strategy based on stepwise addition of beads thereby boosting phosphoproteome coverage by 20%. Finally, we applied our optimized strategy to evaluate phosphoproteome depth with the Orbitrap Astral MS using a cell dilution series and were able to identify >32,000 phosphopeptides from 0.5 million HeLa cells in half-an-hour LC-MS/MS using narrow-window data-independent acquisition (nDIA). Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=159 HEIGHT=200 SRC="FIGDIR/small/568418v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@f455d9org.highwire.dtl.DTLVardef@130537eorg.highwire.dtl.DTLVardef@1b99287org.highwire.dtl.DTLVardef@42e72e_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

Spatiotemporal Proteomics Deciphers Functional Selectivity of EGFR ligands

The epidermal growth factor receptor (EGFR) induces different signaling outputs depending on ligand identity and biological context. This phenomenon is known as functional selectivity, but the underlying molecular mechanisms remain elusive. Here, we investigated this on a global scale and time-resolved by high-throughput multilayered proteomics integrating dynamic changes in the EGFR interaction network by proximity biotinylation using EGFR- TurboID, phosphoproteome, and proteome in response to stimulation with the six highest-affinity EGFR ligands. We obtained comprehensive temporal profiles of protein recruitment and phosphosite changes pinpointing signaling proteins differentially regulated by the six ligands with key impact on EGFR endocytic fate, e.g. degradation or recycling. Specifically, the Epsin family protein, Clint1 was identified to control the endocytic trafficking of EGFR towards degradation. Moreover, we characterized the protein interaction selectivity of EGFR C-terminally phosphorylated tyrosine residues using a panel of tyrosine mutated constructs showing STAT5 specificity for EGFR Y1173. These data provide a comprehensive resource deciphering functional selectivity of EGFR signaling to support discovery of novel drug targets.

molecular biology↗

bioRxiv2023

One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes

We present One-Tip, a lossless proteomics methodology that seamlessly combines swift, one-pot sample preparation with narrow-window data-independent acquisition mass spectrometric analysis. With simplest sample processing, One-Tip reproducibly identifies > 9,000 proteins from [~]1000 cells and [~] 6,000 proteins in a single mouse zygote with a throughput of 40 samples-per-day. This easy-to-use method expands capabilities of proteomics research by enabling greater depth, scalability and throughput covering low to high input samples.

biochemistry↗

bioRxiv2023

Enamel proteins reveal biological sex and genetic variability within southern African Paranthropus

The evolutionary relationships among extinct African hominin taxa are highly debated and largely unresolved, due in part to a lack of molecular data. Even within taxa, it is not always clear, based on morphology alone, whether ranges of variation are due to sexual dimorphism versus potentially undescribed taxonomic diversity. For Paranthropus robustus, a Pleistocene hominin found only in South Africa, both phylogenetic relationships to other taxa 1,2 and the nature of intraspecific variation 3-6 are still disputed. Here we report the mass spectrometric (MS) sequencing of enamel proteomes from four ca. 2 million year (Ma) old dental specimens attributed morphologically to P. robustus, from the site of Swartkrans. The identification of AMELY-specific peptides and semi-quantitative MS data analysis enabled us to determine the biological sex of all the specimens. Our combined molecular and morphometric data also provide compelling evidence of a significant degree of variation within southern African Paranthropus, as previously suggested based on morphology alone 6. Finally, the molecular data also confirm the taxonomic placement of Paranthropus within the hominin clade. This study demonstrates the feasibility of recovering informative Early Pleistocene hominin enamel proteins from Africa. Crucially, it also shows how the analysis of these proteins can contribute to understanding whether hominin morphological variation is due to sexual dimorphism or to taxonomic differences. We anticipate that this approach can be widely applied to geologically-comparable sites within South Africa, and possibly more broadly across the continent.

evolutionary biology↗

bioRxiv2023

Narrow-window DIA: Ultra-fast quantitative analysis of comprehensive proteomes with high sequencing depth

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here, we present an ultra-fast scanning data-independent acquisition (DIA) strategy consisting on 2-Th precursor isolation windows, dissolving the differences between data-dependent and independent methods. This is achieved by pairing a Quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer that provides >200 Hz MS/MS scanning speed, high resolving power and sensitivity, as well as low ppm-mass accuracy. Narrow-window DIA enables profiling of up to 100 full yeast proteomes per day, or [~]10,000 human proteins in half-an-hour. Moreover, multi-shot acquisition of fractionated samples allows comprehensive coverage of human proteomes in [~]3h, showing comparable depth to next-generation RNA sequencing and with 10x higher throughput compared to current state-of-the-art MS. High quantitative precision and accuracy is demonstrated with high peptide coverage in a 3-species proteome mixture, quantifying 14,000+ proteins in a single run in half-an-hour. TeaserAccurate and precise label-free quantification with comprehensive proteome coverage using narrow-window DIA

systems biology↗

bioRxiv2023

Optimizing linear ion trap data independent acquisition towards single cell proteomics

A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

biochemistry↗

bioRxiv2022

Hybrid-DIA: Intelligent Data Acquisition for Simultaneous Targeted and Discovery Phosphoproteomics in Single Spheroids

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging when analyzing tiny sample amounts. We present a novel hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem MS scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmarked hybrid-DIA against state-of-the-art targeted MS methods (i.e. SureQuant) using EGF-stimulated HeLa cells and found the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiled the global phosphoproteome. To demonstrate the robustness, sensitivity and potential of hybrid-DIA, we profiled chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluated the difference of cancer cells in 2D vs 3D culture. Altogether, we showed that hybrid-DIA is the way-to-go method in highly sensitive phospho-proteomics experiments.

systems biology↗

bioRxiv2022

Matrix Gla Protein acts as a driver of stemness and tumor initiation in ovarian cancer

Ovarian cancer (OC) displays the highest mortality among gynecological tumors, mainly due to early peritoneal dissemination, the high frequency of tumor relapse following primary debulking and the development of chemoresistance. All these events are thought to be initiated and sustained by a subpopulation of neoplastic cells, termed ovarian cancer stem cells (OCSC), that are endowed with self-renewing and tumor-initiating properties. This implies that interfering with OCSC function should offer novel therapeutic perspectives to defeat OC progression. To this aim, a better understanding of the molecular and functional makeup of OCSC in clinically relevant model systems is essential. We have profiled the transcriptome of OCSC vs. their bulk cell counterpart from a panel of patient-derived OC cell cultures. This revealed that Matrix Gla Protein (MGP), classically known as a calcification-preventing factor in cartilage and blood vessels, is markedly enriched in OCSC. Functional assays showed that MGP confers several stemness-associated traits to OC cells, including a transcriptional reprogramming. Patient-derived organotypic cultures pointed to the peritoneal microenvironment as a major inducer of MGP expression in OC cells. Furthermore, MGP was found to be necessary and sufficient for tumor initiation in OC mouse models, by shortening tumor latency and increasing dramatically the frequency of tumor-initiating cells. Mechanistically, MGP-driven OC stemness was mediated by the stimulation of Hedgehog signaling, in particular through the induction of the Hedgehog effector GLI1, thus highlighting a novel MGP/Hedgehog pathway axis in OCSC. Finally, MGP expression was found to correlate with poor prognosis in OC patients, and was increased in tumor tissue after chemotherapy, supporting the clinical relevance of our findings. Thus, MGP is a novel driver in OCSC pathophysiology, with a major role in stemness and in tumor initiation.

cancer biology↗

bioRxiv2022

Loss of N-terminal acetyltransferase A activity induces thermally unstable ribosomal proteins and increases their turnover

Protein N-terminal (Nt) acetylation is one of the most abundant modifications in eukaryotes, covering [~]50-80 % of the proteome, depending on species. Cells with defective Nt-acetylation display a wide array of phenotypes such as impaired growth, mating defects and increased stress sensitivity. However, the pleiotropic nature of these effects has hampered our understanding of the functional impact of protein Nt-acetylation. The main enzyme responsible for Nt-acetylation throughout the eukaryotic kingdom is the N-terminal acetyltransferase NatA. Here we employed a multi-dimensional proteomics approach to analyze Saccharomyces cerevisiae lacking NatA activity, which caused global proteome remodeling. Pulsed-SILAC experiments revealed that NatA-deficient strains consistently increased degradation of ribosomal proteins compared to wild type. Explaining this phenomenon, thermal proteome profiling uncovered decreased thermostability of ribosomes in NatA-knockouts. Our data are in agreement with a role for Nt-acetylation in promoting stability for parts of the proteome by enhancing the avidity of protein-protein interactions and folding. TeaserA multidimensional proteomics approach reveals the effect of N-terminal acetylation on Saccharomyces cerevisiae cytosolic ribosomal proteins.

biochemistry↗