Biology subjects

Saei, A. A.

Publications and source records attributed to Saei, A. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Conjunctive Targeting Links Drug Synergy to Emergent Proteome Structural States

Combinatorial therapies are widely used in the treatment of acute myeloid leukemia (AML) to address disease heterogeneity, adaptive resistance, and rewired signaling and metabolic states. Yet drug prioritization remains largely guided by clinical or phenotypic evidence, while the molecular mechanisms underlying effective drug combinations remain incompletely defined. To narrow this gap, we developed Combinatorial high-ratio Partial proteolysis with reference PRoteome Analysis (CoPPRA), a structural proteomics workflow based on limited proteolysis of cell lysates that profiles drug-associated changes in regional protein accessibility at peptide-level resolution. Here, we applied CoPPRA to ruxolitinib and ulixertinib, individually and in combination, in AML-related cell lysates. Our findings extend conjunctive targeting (CT), a recently proposed mechanism of combinatorial drug action in which combined exposure produces protein targeting patterns not observed with either drug alone. Previously identified through combination-associated changes in protein solubility/stability, CT is examined here at peptide-level resolution through regional differences in proteolytic accessibility. The ruxolitinib-ulixertinib combination produced broad peptide-level accessibility changes, including a subset meeting the predefined criteria for CT. CT candidates predominantly exhibited regional accessibility changes, with altered peptide regions occurring against comparatively small changes across the remaining quantified peptides from the same proteins. MAP2K1 and ATP6V1G1 showed pronounced differences between overlapping peptide sequences, highlighting localized variation in combination-associated accessibility, including an ATP6V1G1 peptide mapping to an annotated helical region. Combination-associated increases in peptide signals were also observed in PIK3R1, BRD4, and PTPN11, linking regional accessibility changes to signaling and transcriptional regulators relevant to AML. Functional enrichment and network analyses further implicated nucleotide and glucose metabolism, ficolin-1-rich granules, ribosome-associated processes, and phagocytic vesicles. These results extend conjunctive targeting from protein-level solubility/stability changes to regional differences in proteolytic accessibility, showing that combination-associated effects can be concentrated within specific peptide regions rather than distributed uniformly across proteins. More broadly, CoPPRA provides a peptide-resolved approach for investigating the molecular features of combinatorial drug action and prioritizing protein regions for subsequent mechanistic validation.

biochemistry↗

bioRxiv2026

Chemical Proteomics of Residual Acute Myeloid Leukemia Cells Reveals Therapeutic Vulnerabilities

Venetoclax combined with azacitidine has improved treatment outcomes in acute myeloid leukemia (AML), yet relapse and treatment persistence remain major clinical challenges. To investigate proteomic mechanisms associated with venetoclax-azacitidine response and adaptation, we applied a multi-layer combinatorial proteome integral solubility/stability alteration analysis (CoPISA) strategy in SKM-1 AML cells. Cells were treated with venetoclax, azacitidine, their combination, or vehicle control and profiled across four orthogonal layers: short-term lysate CoPISA, short-term intact-cell CoPISA, long-term intact-cell CoPISA after 5 days of treatment, and long-term expression proteomics of surviving cells. The venetoclax-azacitidine combination induced treatment-specific protein solubility and abundance changes that were not fully reproduced by either single agent. Long-term surviving cells displayed extensive proteomic remodeling, consistent with the emergence of an adaptive drug-tolerant state, although contributions from pre-existing resilient cell populations cannot be excluded. Integration of short- and long-term solubility changes with abundance remodeling revealed distinct adaptive regimes, including retained biochemical targets, dosage-compensated targets, sensitive-state-specific targets, and remodeled adaptive targets. This framework prioritized candidate resistance-associated proteins, including NRP2, RPL18, PLP2, RPS28, and NOTCH1. NRP2 emerged as a top candidate across all proteomics layers, consistently showing increased abundance. Overall, this study shows that combining CoPISA with expression proteomics can resolve temporally distinct proteomic states of venetoclax-azacitidine response and identify candidate adaptive vulnerabilities in AML.

cancer biology↗

bioRxiv2026

Deep nanoparticle protein corona plasma proteomics resolves a stage-specific peripheral signature of Alzheimer's disease

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSAlzheimers disease (AD) progresses over decades, yet plasma biomarkers that resolve disease stage rather than simply detect disease remain scarce. This distinction is clinically consequential because effective AD intervention depends on identifying patients before disease biology has progressed beyond a therapeutically responsive stage. METHODSWe used small-molecule-modulated protein corona proteomics to profile plasma from 90 individuals in the Australian Imaging, Biomarker and Lifestyle cohort, stratified by Centiloid (CL) A{beta}-amyloid burden (30 amyloid- negative, CL < 15; 30 moderate-to-high, CL 26 to 100; 30 very high, CL > 100). We quantified 3,176 proteins and applied differential abundance and actual causality analyses to identify stage-specific and candidate causal proteins. RESULTSDifferential protein abundance was exclusively captured during the moderate-to-high AD transition, revealing a discrete proteomic "switch." The switch was marked by accumulation of the autophagy receptor CALCOCO1, together with coordinated depletion of the S100A8/S100A9 calprotectin complex and core erythroid-cytoskeletal network structural markers (e.g., SPTA1, SPTB, ANK1). Adhesion G protein-coupled receptor G6 (ADGRG6) showed a significant moderate positive monotonic association with absolute CL burden, providing a proportional molecular anchor for cumulative disease burden. Actual causality analysis identified COL6A2, FOXRED2, P3H1, PRR4, and GOLGA5 as candidate upstream drivers linking matrix remodeling, Golgi trafficking, and collagen processing to AD progression. DISCUSSIONThese findings suggest a candidate blood-accessible framework for staging AD by active disease biology, which, if replicated in independent cohorts, may have implications for therapeutic selection and mechanism-guided clinical trials. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/740710v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1ead718org.highwire.dtl.DTLVardef@cfa523org.highwire.dtl.DTLVardef@62a367org.highwire.dtl.DTLVardef@1d5c9a5_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Multi-omics uncovers interaction in the vaginal microbiome and a type II secretion/Tad pilus system in Gardnerella vaginalis

The vaginal microbiome is a critical determinant of womens health. We investigated the genetic basis of common vaginal microbiome species and their biofilm formation. Genomic analysis of Gardnerella vaginalis (Gv) revealed a fundamental phylogenetic split correlating with high- versus low-biofilm phenotypes, driven by clade-specific genomic islands and allelic variants. In a dual-species coculture model of five key vaginal bacteria, Gv achieved numerical dominance, triggering extensive, asymmetric proteomic reprogramming in partner species while showing limited shifts itself. Proteins from biofilm-associated modules showed functional divergence, supported by AI-predicted structural variations in a type II secretion/Tad pilus system, which is first discovered from Gv strains. Integrated metabolomics identified a methyl-{beta}-carboline compound that is elevated in cocultures containing Prevotella bivia (Pb). This compound acts as a potent and selective inhibitor of Gv and Pb biofilms, sparing Lactobacillus crispatus. This work establishes a direct genomic basis for Gv virulence and demonstrates how interspecies interactions govern community dynamics and antimicrobial metabolite production. HighlightsO_LIComprehensive genomic resource comparing with high-quality long-read whole genomes and reference Gardnerella vaginalis and Lactobacillus iners strains. C_LIO_LIIntegrated multi-omics and functional analysis on the most common vaginal microbiome species using 16S rRNA gene sequencing, proteomics, metabolomics, and in vitro assays. C_LIO_LIKey phenotypes quantified, including biofilm formation and polymicrobial interactions. C_LIO_LIConserved Type II Secretion/Tad Pilus System identified across all Gardnerella vaginalis strains, with AI-predicted structural modeling. C_LIO_LIEvaluation of growth inhibition using metabolites against a panel of relevant microbes, including vaginal microbes and opportunistic pathogens. C_LI

microbiology↗

bioRxiv2026

A systemic circadian nicotinic acid riboside (NaR) signal engages the unfolded protein response and adipogenesis via the prefoldin complex

Daily light-dark cycles impose predictable environmental fluctuations that require coordinated temporal regulation of cellular physiology. This coordination is mediated by the circadian clock, which operates as a network of tissue oscillators; however, the molecular signals that convey circadian information between organs remain incompletely defined. Here, we identify nicotinic acid riboside (NaR) as a circulating metabolite whose rhythmicity depends on the liver clock. In differentiating 3T3-L1 adipocytes, NaR engages unfolded protein response (UPR) gene programs and modulates adipogenic competence. Proteome-wide stability profiling implicates the prefoldin complex as a molecular target of NaR signaling, linking NaR exposure to altered proteostasis. Functionally, NaR-induced UPR signaling converges on the adipogenic transcription factor CEBPA, which is a central regulator of adipogenesis. Importantly, sustained NaR exposure suppresses adipocyte lipid deposition, whereas temporally restricted NaR stimulation enhances adipogenesis, indicating that NaR acts in a time-dependent manner. Together, these findings identify NaR as a liver clock-controlled circulating metabolite that couples systemic circadian metabolism to adipocyte proteostasis and differentiation, revealing a mechanism by which temporal metabolic signals shape tissue-specific physiological outcomes. HighlightsO_LIThe circadian clock is required for rhythmic regulation of circulating nicotinic acid riboside (NaR). C_LIO_LIThe liver clock is sufficient to generate NaR rhythmicity. C_LIO_LINaR engages the prefoldin complex to regulate unfolded protein response signaling and Cebpa expression. C_LIO_LITime-dependent NaR exposure differentially regulates CEBPA levels and adipocyte lipid deposition. C_LI

systems biology↗

bioRxiv2026

Recalibrating Nanoparticle Protein Corona Analysis for Accurate Biological Identity and Soluble Plasma Proteome Profiling

The nanoparticle (NP) protein corona is considered the biological identity that determines NP fate, safety, targeting, and therapeutic effectiveness in biofluids. Nonetheless, standard corona isolation workflows assume the recovered protein signature originates primarily from plasma proteins adsorbed directly onto the NP surface, while largely overlooking co-isolation of endogenous nanoscale biological structures such as extracellular vesicles (EVs). This oversight can distort the apparent "biological identity" of the NP. Here, we show that EVs are a major hidden contributor to the perceived protein corona composition in human plasma. Using highly monodispersed polystyrene NPs (50-1000 nm) and superparamagnetic beads, we compared corona formation in standard human plasma and plasma depleted of an EV- enriched sedimentable fraction by ultracentrifugation at 100,000 x g for 2 h, with the recovered vesicles subsequently characterized by MACSPlex immunoaffinity analysis. Mass spectrometry revealed that EV depletion reduced the number of proteins identified on polystyrene NPs by 60-75% and on magnetic beads by 45-50%, demonstrating a substantial fraction of the conventionally assigned corona proteome arises from EV- associated carryover. EV depletion also restructured the apparent abundance hierarchy, increasing the relative prominence of soluble plasma proteins such as albumin and shifting dominant signals away from intracellular cytoskeletal component proteins that are characteristic of EV carryover towards genuine soluble plasma proteins and complement factors. These results highlight that standard corona workflows can inadvertently co-isolate a vast array of EV-associated material and thereby yield inaccurate assignments of protein origin. Distinguishing proteins adsorbed from the soluble phase from EV-surface and intravesicular material is essential for accurate interpretation of NP-biofluid interactions, biomarker discovery, and therapeutic targeting because molecular compartment determines both analytical meaning and drug accessibility. Significance StatementThe nanoparticle (NP) "protein corona" defines how engineered nanomaterials interact with living systems, influencing therapeutic safety, efficacy, and diagnostic utility. Conventionally, corona isolation workflows assume that recovered proteins were adsorbed directly from the fluid phase. This study reveals a major, previously overlooked source of analytical distortion: standard separation techniques routinely co-isolate endogenous extracellular vesicles (EVs), drastically distorting the perceived biological identity of NPs. Depletion of an EV-enriched sedimentable fraction by ultracentrifugation reduced identified corona proteins by up to 75% and restructures the apparent proteomic hierarchy. Distinguishing true soluble adsorbates from vesicular carryover is essential for accurately predicting NP behavior in vivo and prevents false positives in nano- diagnostics, establishing a critical new standard for high-fidelity biomarker discovery and nanomedicine.

bioengineering↗

bioRxiv2025

Lipid nanoparticle protein coronas form via lipoprotein fusion rather than shell-like adsorption

The protein corona influences the in vivo biodistribution of ionizable lipid nanoparticles (LNPs) in nucleic acid delivery, yet its structural architecture remains poorly defined. Using cryo-transmission electron microscopy, we visualized LNP-protein interactions in their native state. We show that, unlike the discrete "fuzzy" shells observed on hard nanoparticles, LNPs displayed no peripheral protein shell. Instead, controlled incubation and competitive "dual-particle" assays, supported by molecular dynamics simulations, indicate that LNP membranes undergo localized thickening and electron-dense remodeling consistent with lipoprotein integration rather than surface adsorption. Similar features were observed in extracellular vesicles, suggesting this behavior is shared among lipid-based carriers, and proteomic analysis identified apolipoproteins as the dominant associated proteins. Together, these findings support a model in which the biological identity of LNPs arises through membrane remodeling rather than shell-like adsorption, and provide a framework for the rational design of targeted nanomedicines. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/695162v2_ufig1.gif" ALT="Figure 1"> View larger version (79K): org.highwire.dtl.DTLVardef@a6f2b2org.highwire.dtl.DTLVardef@879d12org.highwire.dtl.DTLVardef@159196dorg.highwire.dtl.DTLVardef@945749_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Towards a species search engine: KISSE offers a rigorous statistical framework for bone collagen tandem mass spectrometry data

DNA and bone collagen are two key sources of resilient molecular markers used to identify species from their remains. Collagen is more stable than DNA, and thus it is preferred for ancient and degraded samples. Current mass spectrometry-based collagen sequencing approaches are empirical and lack a rigorous statistical framework. Based on the well-developed approaches to protein identification in shotgun proteomics, we introduce a first approximation of the species search engine (SSE). Our SSE named KISSE is based on a species-specific library of collagenous peptides that uses both peptide sequences and their relative abundances. The developed statistical model can identify the species and the probability of correct identification, as well as determine the likelihood of the analyzed species not being in the library. We discuss the advantages and limitations of the proposed approach and the possibility of extending it to other tissues.

zoology↗

bioRxiv2025

Above-Filter Digestion Proteomics reveals drug targets and localizes ligand binding site

While a number of efficient chemical proteomics methods are available for determining protein targets of pharmaceutical drugs, each approach exhibits its own "blind spot" and development of complementary techniques is needed. Here, we introduce the Above-Filter Digestion Proteomics (AFDIP) approach based on the monitoring of the rate of trypsin digestion. Digestion rate is decreased at the site of ligand binding to its target protein, while other sites may simultaneously experience an increase the digestion rate. Molecular dynamics (MD) simulations revealed that this increase may be due to allosteric structural changes related to backbone flexibility. We showcase the utility of AFDIP for deconvoluting the targets of versatile drugs and metabolites. Like other techniques, AFDIP allows for a two-dimensional analysis, with the second dimension based on drug concentration. AFDIP exhibits structural resolution, identifying drug target binding sites within [≤]10 [A], and for larger proteins often [≤]5 [A] of the crystallography-determined binding sites. Compared to earlier introduced limited proteolysis approaches, AFDIP provides easier sample preparation, deeper proteome analysis and broader sequence coverage. AFDIP is expected to find its place among the most efficient chemical proteomics methods currently available.

biochemistry↗

bioRxiv2024

Antibiotics that Kill Gram-negative Bacteria by Restructuring the Outer Membrane Protein BamA

The essential outer membrane protein insertase BamA has recently emerged as a valid target for killing Gram-negative bacteria. Bamabactins, competitive inhibitors targeting the lateral gate of BamA, disrupt the substrate folding process, compromise the outer membrane integrity, and lead to bacterial cell death. Despite their promise, the full pharmacological potential of bamabactins remains underexploited. We applied phylogenetic genome mining and synthetic biology to identify xenorceptides which selectively kill Enterobacteriaceae. Mode of action studies show that xenorceptide A2 integrates itself into BamA as an additional {beta}-strand between {beta}1 and {beta}16 at the lateral gate, inducing a conformation of BamA that has not been observed before. Biological evaluation of xenorceptide A2 shows promising activity in vitro and in vivo, and limited resistance which differentiates it from other bamabactin antibiotics. Our data show that the chemical diversity of bamabactins is far greater than previously recognized and thus an attractive source for antibiotic discovery.

microbiology↗

bioRxiv2024

Exploring Mechanisms of Action in Combinatorial Therapy through Stability/Solubility Alterations: Advancing AML Treatment

Acute myeloid leukemia (AML) remains a formidable clinical challenge due to genetic heterogeneity, high relapse rates, and toxicities associated with conventional chemotherapies. Rationally designed drug combinations offer improved efficacy, yet their selection is often empirical and lacks molecular mechanistic understanding. Here, we present CoPISA workflow (Proteome Integral Solubility/Stability Alteration Analysis for Combinations), a high-throughput proteomics workflow that captures protein solubility/stability alterations unique to combinatorial drug treatments, revealing mechanisms unattainable through single-drug analyses. Applying CoPISA to two rationally designed AML drug pairs, LY3009120-sapanisertib (LS) and ruxolitinib-ulixertinib (RU), we mapped primary (lysate) and secondary (living cell) protein target landscapes. Notably, our analysis uncovered an emergent mechanistic principle, "conjunctional targeting" (i.e., conjunctional inhibition), wherein cooperative drug actions induce treatment-specific targets not achievable individually, analogous to an AND-gate logic model. LS-specific AND-gate proteins converged on SUMOylation, chromatin condensation, and VEGF-linked adhesion, while RU-specific targets disrupted DNA-damage checkpoints, mitochondrial bioenergetics, and RNA-splicing machinery, collectively implicating synthetic-lethal vulnerabilities. Additionally, the post-translational modifications (PTMs) profiling of differential soluble proteins confirms several combination-induced modifications (e.g., acetylation, dimethylation, phosphorylation) on key AML proteins, such as NPM1. Network interrogation of AML-associated proteins showed that a high percentage of targeted proteins are unique to the combinations, including frequently mutated drivers DNMT3A, NPM1, and TP53. CoPISA exposes how drug pairs enact multi-axis pressure on AML cells through conjunctional targeting, a mechanistic layer beyond classical synergy. By pinpointing combination-exclusive protein targets and signaling pathways, CoPISA provides a blueprint for precision-guided regimen design in AML and other heterogeneous cancers. Data are available via ProteomeXchange with identifier PXD066812.

biochemistry↗

bioRxiv2024

One-Pot Time-Induced Proteome Integral Solubility Alteration (OPTI-PISA) assay for automated and sensitive drug target identification

Proteome Integral Solubility Alteration (PISA) assay is widely used for identifying drug targets, but it is labour-intensive and time-consuming, and requires a substantial amount of biological sample. Aiming at enabling automation and greatly reducing the sample amount, we developed One-Pot Time-Induced (OPTI)-PISA. Here we demonstrate OPTI-PISA performance on identifying targets of multiple drugs in cell lysate and scaling down the sample amount to sub-microgram levels, making PISA method suitable for NanoProteomics.

biochemistry↗

bioRxiv2024

ThermoTargetMiner as a proteome integral solubility alteration target database for prospective drugs against lung cancer

Knowledge of the targets of therapeutic compounds is vital for understanding their action mechanisms and side effects, but such valuable data is seldom available. The multiple complementary techniques needed for comprehensive target characterization must combine data reliability with sufficient analysis throughput. Here, we leveraged the Proteome Integral Solubility Alteration (PISA) assay to characterize the targets of 67 approved and experimental compounds against two main lung cancer subtypes, which is now provided through the website https://thermotargetminer.serve.scilifelab.se/app/thermotargetminer. Novel target candidates (pro-targets) were found for 77% of the tested molecules. Comparison of the protein solubility shifts in lysate vs. living cells highlighted the targets directly interacting with the compounds. We verified that the drug PEITC exerts cytotoxicity through the inhibition of a pro-target PAFAH1B. As PISA is now joining the arsenal of fast and reliable target characterization techniques, the presented database, ThermoTargetMiner, will become a useful resource in lung cancer research.

biochemistry↗

bioRxiv2024

Standardizing protein corona characterization in nanomedicine: a multi-center study to enhance reproducibility and data homogeneity

Our recent findings reveal substantial variability in the characterization of identical protein corona across different proteomics facilities, demonstrating that protein corona datasets are not easily comparable between independent studies. We have shown that heterogeneity in the final composition of the identical protein corona mainly originates from variations in sample preparation protocols, liquid chromatography mass spectrometry (LC-MS) workflows, and raw data processing. Here, to address this issue, we developed standardized protocols and unified sample preparation workflows, and distributed identical protein corona digests to several proteomics centers that performed better in our previous study. Additionally, we examined the influence of using similar mass spectrometry instruments on data homogeneity. Furthermore, we evaluated whether standardizing database search parameters and data processing workflows could enhance data uniformity. More specifically, our new findings reveal a remarkable, stepwise improvement in protein corona data consistency across various proteomics facilities. Streamlining the whole workflow results in a dramatic increase in protein ID overlaps from 11% for good centers to 40% across core facilities that utilized similar instruments and were subjected to a uniform database search. This comprehensive analysis identifies key factors contributing to data heterogeneity in mass spectrometry-based proteomics of protein corona and plasma-related samples. By streamlining these processes, our findings significantly advance the potential for consistent and reliable nanomedicine-based diagnostics and therapeutics across different studies.

bioengineering↗

bioRxiv2024

Gel-Assisted Proteome Position Integral Shift (GAPPIS) Assay Returns Molecular Weight to Shotgun Proteomics and Identifies Novel Caspase 3 Substrates

Here we present a high-throughput virtual top-down proteomics approach that restores the molecular weight (MW) information in shotgun proteomics, and demonstrate its utility in studying proteolytic events in programmed cell death. With Gel-Assisted Proteome Position Integral Shift (GAPPIS), we quantified over 7000 proteins in staurosporine-induced apoptotic HeLa cells and identified 84 proteins exhibiting in a statistically significant manner at least two of the following features: 1) a negative MW shift; 2) an elevated ratio in a pair of a semi-tryptic and tryptic peptide, 3) a negative shift in the standard deviation of MW estimated for different peptides, and 4) a negative shift in skewness of the same data. Of these proteins, 58 molecules were novel caspase 3 substrates. Further analysis identified the preferred cleavage sites consistent with the known caspase cleavages after the DXXD motif. As a powerful tool for high-throughput MW analysis simultaneously with the conventional expression analysis, GAPPIS assay can prove useful in studying a broad range of biological processes involving proteolytic events.

biochemistry↗

bioRxiv2023

Chemical proteomics reveals that the anticancer drug everolimus affects ubiquitin-proteasome system

Rapamycin is a natural antifungal, immunosuppressive, and antiproliferative compound allosterically inhibiting mTOR complex 1. The ubiquitin-proteasome system (UPS) responsible for protein turnover is usually not listed among the pathways affected by mTOR signaling; however, a number of reports indicated the interplay between UPS and mTOR. It is also reported that rapamycin and analogs can allosterically inhibit the proteasome itself. We studied the molecular effect of rapamycin and its analogs (rapalogs), everolimus, and temsirolimus by expression chemical proteomics on A549 cell line. The analysis revealed that the cellular response to everolimus differs dramatically from that of rapamycin and temsirolimus. In cluster analysis the effect of everolimus was similar to that of bortezomib, a well-established proteasome inhibitor. UPS-related pathways were enriched in the cluster of proteins specifically up-regulated upon everolimus and bortezomib treatments, suggesting that both compounds have similar proteasome inhibition effects. In particular, the total amount of ubiquitin was significantly elevated in the samples treated with everolimus and bortezomib, and the analysis of the polyubiquitination patterns revealed elevated intensities of the ubiquitin peptide with a GG modification at K48 residue, consistent with a bottleneck in the proteasomal protein degradation. Moreover, everolimus treatment resulted in both ubiquitin phosphorylation and a significant amount of semi-tryptic peptides illustrating the induction of protease activity. These observations suggest that everolimus affects the ubiquitin-proteasome system in a unique way and its mechanism of action is strikingly different from that of its close chemical analogs, rapamycin and temsirolimus. Data are available via ProteomeXchange with identifier PXD045774.

cancer biology↗

bioRxiv2023

Multifaceted proteome analysis at solubility, redox, and expression dimensions for target identification

Multifaceted interrogation of the proteome deepens the system-wide understanding of biological systems; however, mapping the redox changes in the proteome has so far been significantly more challenging than expression and solubility/stability analyses. Here, we devise the first high- throughput redox proteomics approach integrated with expression analysis (REX) and combine it with Proteome Integral Solubility Alteration (PISA) assay. The whole PISA-REX experiment with up to four biological replicates can be multiplexed into a single tandem mass tag TMTpro set. For benchmarking this compact tool, we analyzed HCT116 cells treated with auranofin, showing great improvement compared with previous such studies. Then we applied PISA-REX to study proteome remodeling upon stimulation of human monocytes by interferon . We also studied the proteome changes in plasmacytoid dendritic cells isolated from wild type vs. Ncf1- mutant mice treated with interferon , showing that NCF1 deficiency enhances the STAT1 pathway and modulates the expression, solubility and redox state of interferon-induced proteins. Providing comprehensive multifaceted information on the proteome, the compact PISA-REX has the potential to become an industry standard in proteomics and to open new windows into the biology of health and disease.

biochemistry↗

bioRxiv2023

Massive solubility changes of neuronal proteins upon simulated traumatic brain injury reveal the role of shockwave in irreversible damage

The immediate molecular consequences of traumatic brain injuries or TBI are poorly understood. Here, we simulated TBI using an innovative laboratory apparatus that employs a 5.1 kg dummy head holding neuronal cells and generating a [≤]4,000 g-force acceleration upon impact. Dynamic impact led to both reduction in neuron viability and massive solubility changes in the proteome profiled using Proteome Integral Solubility Alteration (PISA) assay. The affected proteins mapped not only to the expected pathways like cell adhesion, collagen and laminin structures, as well as response to stress, but also to other dense protein networks, such as immune response, complement and coagulation cascades. The cellular effects are found to be mainly due to the shockwave rather than the g-force acceleration. Soft materials could reduce the impact severity only until being fully compressed. This study shows way to develop a proteome-based meter for measuring irreversible shockwave-induced cell damage and provides a resource for identifying TBI protein biomarkers and potential drug targets for developing products aiming at primary prevention and intervention.

neuroscience↗