Biology subjects

Jafari, M.

Publications and source records attributed to Jafari, M..

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

An N-terminal amphipathic helix governs activity and conformational dynamics of Nramp metal transporters

Nramps are a family of proton-coupled divalent metal ion transporters that play critical roles in maintaining homeostasis of essential metals. In humans, Nramp2 (DMT1) mediates iron uptake to support both cellular and systemic iron homeostasis, whereas Nramp1 exports metals from phagosomes, contributing to antimicrobial defense. A survey of experimentally solved Nramp structures reveals that an N-terminal helix (A) immediately preceding TM1 is folded only in the outward-facing or outward-facing occluded states, raising the question of its role in Nramp transport. Here, we combined mutagenesis, transport assays, and molecular dynamics simulations to investigate A. Our results show that deletion or substitution of conserved residues in A markedly reduces Fe2+ transport. Simulations indicate that A behaves as an amphipathic helix in the outward-facing state and preferentially stabilizes this conformation over the inward-facing state, thus acting as a key player in controlling conformational equilibrium. This study provides new insights into structural dynamics of Nramps and potentially sheds light on other LeuT-fold transporters.

biochemistry↗

bioRxiv2025

3D-printing-assisted, microfabricated devices reveal hierarchical and temporal mechanosensing in high-density fibroblast culture

Understanding how cells integrate mechanical forces across multiple directions, length scales, and timescales remains a fundamental challenge in mechanobiology. Deciphering how cells integrate this information is particularly important in the context of wound healing, where the timing and duration of the fibroblast-to-myofibroblast transition can determine healing outcomes. Here, we discovered that fibroblasts in engineered tissues respond to directional anisotropy in stress through a hierarchical temporal cascade, with individual cell elongation (24 hr) preceding collective alignment (40 hr), which then drives -smooth muscle actin expression and myofibroblast transition (96h). To enable this discovery, we developed a modified hydrogel-assisted stereolithographic elastomer (HASTE) prototyping platform to incorporate a detergent that improves wettability of template agar hydrogels by poly(dimethylsiloxane) elastomer. HASTE allowed rapid prototyping of intricate 3D micropost arrays that provides isotropic (8-post) versus anisotropic (4-post) boundary conditions. Fibroblasts sensed and responded to stress directionality before bulk tissue reorganization occurs. Computational modeling predicted steady-state activation patterns based on initial stress anisotropy rather than magnitude, and our experiments reveal that reaching this state requires sequential mechanosensitive processes operating across distinct timescales. This temporal hierarchy persists even when extensive cell-cell contacts might be expected to mask matrix-mediated mechanical signals. Our findings demonstrate that fibroblast mechanosensing involves adaptive responses encoded through progressive cell and tissue reorganization. Results provide insight into how nanoscale mechanosensing scales up to direct tissue-level organization, with implications for understanding wound healing, understanding fibrosis, and engineering functional tissue replacements.

bioengineering↗

bioRxiv2025

Adhesive implant interfaces prevent fibrosis by disrupting mechanobiological feedback

Fibrotic encapsulation around medical implants affects millions of patients annually. Current approaches targeting inflammation or implant material properties have failed clinically, but the mechanical origins of implant-induced fibrosis remain unexplored. Here, we demonstrate that directional imbalance of mechanical forces ("tension anisotropy") is the primary driver of fibroblast activation at implant-tissue interfaces, and that it can be eliminated through adhesive bonding strategies. Computational modeling reveals a mechanistic basis for successful adhesive anti-fibrotic interfaces: conventional sutured implants generate highly anisotropic stress fields between discrete suture anchor points that activate fibroblasts, while adhesive interfaces distribute forces isotropically, maintaining a mechanical environment that does not activate fibroblasts. In vivo experiments from the literature across multiple animal models confirm these predictions: as predicted, adhesive interfaces completely prevent fibrotic capsule formation for up to 12 weeks across diverse organs, while maintaining identical implant composition and geometry compared to sutured controls. Results establish tension anisotropy as a mechanical regulator of implant fibrosis and provide a mechanistic foundation explaining why adhesive interfaces succeed where all previous anti-fibrotic strategies have failed. By addressing the root mechanical cause of fibrosis, this mechanobiology-driven approach may enable a universal approach for preventing fibrosis across all categories of implantable medical devices. Significance statementMillions of patients suffer from medical device failure due to fibrotic encapsulation, in which a surgically implanted item such as pacemaker leads or a vascular graft loses function by becoming covered with scar tissue. Implants affixed to soft tissues by sutures are especially prone to this form of failure, but implants affixed with a recently invented adhesive are not. We present the discovery that directional imbalance of forces ("tension anisotropy") drives conversion of healing tissue into scar tissue. Conventional sutured implants create highly anisotropic stress fields between anchor points that activate fibroblasts, while adhesive interfaces distribute forces isotropically, attenuating scarring. This mechanistic insight explains why adhesive implant-tissue interfaces successfully prevent fibrotic capsule formation across multiple animal models and organ systems, where all previous anti-fibrotic approaches have failed. By addressing root mechanical causes of fibrotic remodeling, this discovery provides a pathway for clinical remediation of fibrotic encapsulation.

biophysics↗

bioRxiv2025

Extracellular Matrix Physical Properties Regulate Cancer Cell Morphological Transitions in 3D Hydrogel Microtissues

Cancer cells can adopt a range of morphological states linked to distinct functional behaviors during tumor progression. Some remain in a proliferative state, forming tight clusters; others detach and elongate into an invasive state; and some retain a rounded amoeboid form with minimal matrix adhesion. However, factors that determine which morphological state a cell adopts remain poorly understood. Using a combined theoretical and experimental framework, we showed that extracellular matrix (ECM) mechanics regulate cancer cell morphology in three-dimensional (3D) environments. We developed a theoretical model based on the principle of minimum energy, which predicts that a cell will adopt the morphological state--rounded, elongated, or clustered-- that minimizes the total energy of the cell-ECM system. Using MDA-MB-231 breast cancer cells, we established a reliable protocol for encapsulating cells into 3D naturally-derived hydrogels with controlled stiffness and pore size. We validated the models predictions in vitro over an extended culture period. In soft ECMs, cells transitioned over time to an elongated morphology, while in stiff ECMs, cells favored clustered configurations. These transitions were governed by the physical-- not chemical--properties of the hydrogel-based ECM, as confirmed by using chemically distinct yet mechanically matched composite matrices. These new insights have implications for cancer invasion modeling and potential drug screening.

biophysics↗

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↗

bioRxiv2025

Tension-Induced Stiffening of Cytoskeletal Components Regulates Cardiomyocyte Contractility

Cardiomyocytes continuously experience mechanical stimuli that regulate their contractile behavior and contribute to overall heart function. Despite the importance of mechanotransduction in cardiac physiology, the mechanisms by which cardiomyocytes integrate external mechanical cues, such as stretch and environmental stiffness, remain poorly understood. In this study, we present a combined theoretical and experimental framework to investigate how strain-induced cytoskeletal stiffening modulates cardiomyocyte contractility and force generation. Our study elucidates that regulating the mechanical tension cardiomyocytes experience in tissue--whether by modulating environmental stiffness, external stretching, or cardiac fibroblast activation--can effectively tune their contractility, with cytoskeletal strain stiffening playing a central role in this mechanotransductive response.

biophysics↗

bioRxiv2024

Targeting AML Resistance with LY3009120-Sapanisertib and Ruxolitinib-Ulixertinib Combinations Demonstrate Superior Efficacy in FLT3, TP53, and MUC4 mutations

Acute myeloid leukemia (AML) is a genetically heterogeneous malignancy characterized by the clonal expansion of myeloid precursor cells. Despite the advent of venetoclax-based regimens, resistance mechanisms remain a major clinical challenge, particularly in patients with high-risk mutations such as TP53, MUC4, HLA-B and FLT3. This study aims to investigate the efficacy of drug combinations for the treatment of AML using both, AML cell lines and zebrafish embryo xenograft model. Specifically, we focus on two drug combinations; the pan-RAF inhibitor LY3009120 combined with the mTOR inhibitor sapanisertib (designated as LS), and the JAK1/2 inhibitor ruxolitinib combined with the ERK inhibitor ulixertinib (designated as RU). The study integrates real-time cell viability assays, xenograft imaging, and genomic analyses to assess drug efficacy and explore correlations between treatment responses and mutational profiles, particularly TP53, MUC4, HLA-B and FLT3 mutations. Both combinations demonstrated superior efficacy compared to venetoclax-based therapy, with LS notably reducing viability in MOLM-16 and SKM-1 cells, and RU showing comparable efficacy with a favorable safety profile. In zebrafish embryos, LS combination effectively inhibited the proliferation of xenografted human AML cells, as evidenced by decreased fluorescence signals, indicating cell death. The RU combination also disrupted survival of cancer cells, showing promise as a therapeutic strategy. Furthermore, a correlation was identified between drug response and mutational profiles, with TP53, MUC4, HLA-B and FLT3 mutations significantly influencing sensitivity to the LS and RU combinations. These findings support the further development of LS and RU as effective alternatives to current clinical regimens, with implications for personalized AML treatment.

cancer biology↗

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

Molecular insights into substrate translocation in an elevator-type metal transporter

The Zrt/Irt-like protein (ZIP) metal transporters are key players in maintaining the homeostasis of a panel of essential microelements. The prototypical ZIP from Bordetella bronchiseptica (BbZIP) is an elevator transporter, but how the metal substrate moves along the transport pathway and how the transporter changes conformation to allow alternating access remain to be elucidated. Here, we combined structural, biochemical, and computational approaches to investigate the process of metal substrate translocation along with the global structural rearrangement. Our study revealed an upward hinge motion of the transport domain in a high-resolution crystal structure of a cross-linked variant, elucidated the mechanisms of metal release from the transport site into the cytoplasm and activity regulation by a cytoplasmic metal-binding loop, and unraveled an unusual elevator mode in enhanced sampling simulations that distinguishes BbZIP from other elevator transporters. This work provides important insights into the metal transport mechanism of the ZIP family.

biochemistry↗

bioRxiv2024

Deep Plasma Proteome Profiling by Modulating Single Nanoparticle Protein Corona with Small Molecules

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients (namely, glucose, triglyceride, diglycerol, phosphatidylcholine, phosphatidylethanolamine, L--phosphatidylinositol, inosine 5'-monophosphate, and B complex), into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 {micro}g/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depleted the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. By employing an optimized data-independent acquisition (DIA) approach, the inclusion of phosphatidylcholine led to the detection of 1436 proteins in a single plasma sample. Our molecular dynamic results revealed that phosphatidylcholine interacts with albumin via hydrophobic interactions, h-bonds, and water-bridges. Addition of phosphatidylcholine also enabled the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. These significant achievements are made utilizing only a single NP type and one small molecule to analyze a single plasma sample, setting a new standard in plasma proteome profiling. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate widespread adoption of this methodology for identification and clinical translation of proteomic biomarkers into FDA approved diagnostics.

bioengineering↗

bioRxiv2023

DORSSAA: Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay

Advancements in high-throughput techniques such as Thermal Proteome Profiling (TPP) and the high-throughput Proteome Integral Solubility Alteration (PISA) assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce DORSSAA (Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 480,456 potential protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies; methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAAs utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Unlike data repositories and interaction knowledgebases, DORSSAA provides assay-native, protein-level MoA evidence with rigorous per-study FDR control, enabling context-specific target nomination, off-target deconvolution, and combination-aware discovery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/573639v4_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@2ba68dorg.highwire.dtl.DTLVardef@1c39c19org.highwire.dtl.DTLVardef@13d5f73org.highwire.dtl.DTLVardef@45b119_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Delivering biochemicals with precision using bioelectronic devices enhanced with feedback control

Precision medicine tailors treatment in a way that accounts for variations in patient response. Treatment strategies can be determined based on factors such as genetic mutations, age, and diet. Another way of implementing precision medicine in a dynamic fashion is through bioelectronics equipped with real-time sensing and intelligent actuation. Bioelectronic devices such as ion pumps can be utilized to deliver therapeutic drugs. To be able to perform precision medicine, medical devices need to be able to deliver drugs with high precision. For this, closed-loop control is required to be able to change the treatment strategy as new information about the response and progression of the biological system is received. To this end, a sliding mode controller is utilized given its ability to perform satisfactory control actions when there is model uncertainty. The controller is used in an experiment with the goal of delivering a pre-determined dosage of fluoxetine throughout a period of time.

systems biology↗

bioRxiv2023

Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling

Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that the combinations of ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective with the least toxicity and best synergistic effects on blasts. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML treatment. Key PointsO_LIRuxolitinib-ulixertinib and sapanisertib-LY3009120 have the best synergistic effects on AML, with the least toxicity. C_LIO_LIThis studys combinations destroy blasts without harming other healthy cells, unlike standard chemotherapy, which is less specific. C_LI

cancer biology↗

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↗

bioRxiv2022

Monitoring Functional Post-Translational Modifications Using a Data-Driven Proteome Informatic Pipeline Based on PEIMAN2

Post-translational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor- intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs, and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

biochemistry↗

bioRxiv2022

Mechanobiology of Fibroblast Activation in Skin Grafting

Mechanical stretching of living tissues can activate long-lived changes in tissue cells such as fibroblasts, increasing their contractility and initiating phenotypic transformations. Increased mechanical stimulus typically leads to monotonically increasing activation of fibroblasts cultured in 2D, but activation levels are difficult to predict for cells in 3D fibrous tissues, leading to variable outcomes in procedures such as skin grafting. Here we report that the source of this variation is cell-extracellular matrix (ECM) interactions and their variation with the duration and magnitude of applied stretch, and present a model that can predict the degree to which stretch will either increase or decrease long-term activation levels of fibroblasts cultured within a stretched, three-dimensional collagen matrix. Combining experimental and mathematical approaches across multiple scales, we show that the viscoplasticity of the ECM regulates this nonmonotonic, long-term cell activation. Results demonstrate that feedback between cell and ECM determines how cells retain memory of mechanical stretch.

biophysics↗