Proteome Dynamics Research Articles

REPRESENTATION LEARNING OF PROTEOME DYNAMICS TO CHARACTERIZE ORGANISMIC COMMUNICATION AND INTRINSIC HEALTH

Abstract Co-regulation and interactions among organ systems are crucial to maintain health. Therefore, understanding patterns of such organismic communication using proteome dynamics could be an innovative and effective strategy for quantifying intrinsic human health. In this preliminary study, we conducted a case-control study involving six participants with severe genetic mitochondrial disease and six age- and sex-matched healthy subjects. We measured and recorded the salivary proteome of each participant (n=2922 proteins) at 0-, 30-, and 45-minutes post-awakening as well as bedtime (pm), over two days, representing a natural physiological challenge known to involve systems-wide physiological recalibrations. We then analyzed the changes in protein levels across successive time points using a high-dimensional two-sample testing approach (Cai, Liu, and Xia 2013). The protein co-regulation pattern (captured by the covariance matrix of their changes in expression) was significantly different between the healthy and mitochondrial disease participants (p=0.01), thereby linking proteome dynamics with health status. We then implemented Weighted Correlation Network Analysis to identify representative features showing a significant correlation with the subject’s health status between pairs of successive time points (0-30, 30-45, 45-pm). The correlation between the extracted feature and the self-rated health was as high as 0.39 (p-value=0.03) for the 30-45 time period. This finding reveals an association between health status and salivary protein co-regulation patterns, and suggests a promising representation learning strategy to quantify the manifestation of health into accessible proteome dynamics.

INTRINSIC HEALTH: TOWARD A FRAMEWORK FOR THE OBJECTIVE STUDY OF THE BIOLOGY OF HEALTH

Abstract Many definitions of health have been proposed over the years, but all share the characteristic of being subjective and therefore hard to tie to objective measures of biology. While there are undoubtedly subjective aspects of health, here we propose the notion of “intrinsic health” as the capacity of an organism to maintain its internal, biological dynamic equilibrium. Building on first principles, Cohen and Picard show how intrinsic health emerges from the dynamic interplay of energy, communication, and structure at multiple levels of biological organization. The following three talks then propose novel ways to measure intrinsic health. Khan and Wei show how quantile aberrance – modeling when biomarker values are extreme based on the joint distributions of many biomarkers – can be used to quantify intrinsic health. Liu, Xu, Honfo, and Cohen show how metrics of proteome dynamics reflect communication within the organism and can be extracted to quantify health. Finally, Wang and Pei show how transfer entropy – the synchronization between multiple time series – can be extracted to measure health. While these three metrics are still in preliminary stages of development, they show the potential to measure health based on the multivariate dynamics of our internal systems. Going forward, these and other approaches may be integrated to derive robust, objective metrics of intrinsic health, and could serve as the basis for a novel understanding of how aging emerges from declines in intrinsic health over time.

Reverse stable isotope labelling with Raman spectroscopy for microbial proteomics.

Global proteome changes in microbes affect the survival and overall production of commercially relevant metabolites through different bioprocesses. The existing methods to monitor proteome level changes are destructive in nature. Stable isotope probing (SIP) coupled with Raman spectroscopy is a relatively new approach for proteome analysis. However, applying this approach for monitoring changes in a large culture volume is not cost-effective. In this study, for the first time we are presenting a novel method of combining reverse SIP using 13 C-glucose and Deuterium to monitor the proteome changes through Raman spectroscopy. The findings of the study revealed visible changes (blue shifts) in proteome related peaks that can be used for monitoring proteome dynamics, that is, synthesis of nascent amino acids and its turnover with time in a non-destructive, cost-effective, and label-free manner.

Combined with dynamic serum proteomics and clinical follow-up to screen the serum proteins to promote the healing of diabetic foot ulcer.

Non-healing diabetic foot ulcers are a leading cause of disability and death in diabetic patients, which often results in lower limb amputation. This study aimed to investigate the impact of biomarkers on the healing of diabetic foot ulcers by utilizing dynamic serum proteomics and skin proteomic analysis, combined with clinical case follow-up studies. To analyze dynamic serum proteomic changes in four groups, age-matched normal subjects, diabetic patients, pretreatment diabetic foot ulcer patients, and healed diabetic foot ulcer patients were selected. The differential proteins were screened in conjunction with normal and diabetic foot ulcer skin proteomics. In this study, a total of 80 patients with diabetic foot ulcers were enrolled and monitored for 3-6 months during treatment. To verify the significance of the differential proteins, age-matched diabetic patients (240 patients) and healthy controls (160 patients) were included as controls. Dynamic serum proteomics trend showed that the level of negative regulatory proteins related to endothelial cell migration, angiogenesis, and vascular development was significantly decreased after treatment of diabetic foot ulcer. GO enrichment analysis suggested that differentially expressed proteins were mainly enriched in protein activation cascade, immunoglobulin production, and complement activation. The researchers identified the core proteins APOA1, LPA, and APOA2 through a convergence of serum and skin proteomics screening. Clinical cases further validated that APOA1 levels are decreased in diabetic foot ulcer patients and are correlated with disease severity. In addition, animal experiments showed that APOA1 could promote wound healing in diabetic mice. Based on our dynamic proteomics and clinical case studies, our bioinformatic analysis suggests that APOA1 plays a critical role in linking coagulation, inflammation, angiogenesis, and wound repair, making it a key protein that promotes the healing of diabetic foot ulcers.

Spatially resolved mapping of proteome turnover dynamics with subcellular precision

Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology.

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Microbial modulation of hormone signaling, proteomic dynamics, and metabolomics in plant drought adaptation

AbstractThe symbiotic synergy between proteome shifts in plants and microbial colonization orchestrates adaptive responses. This thorough review delves into the less explored domain of proteomic and metabolomic changes triggered by drought stress, shedding light on how they are influenced by interactions with microbiota. Notably, microbial mediation at the crossroads of hormone signaling, proteomic and metabolomic dynamics in drought adaptation emerges as a crucial focal point. Understanding the regulatory mechanisms that orchestrate these complex interactions offers a holistic view of the molecular foundation underlying a plant's ability to endure water scarcity. The insights gained from this exploration hold the potential to reshape agricultural practices and enhance drought‐tolerance through microbiota‐mediated mechanisms, supported by proteomic and metabolomic insights. As this review seamlessly integrates the latest developments in understanding drought stress responses, microbiota dynamics, proteomics and metabolomic, it reveals the interconnected molecular basis that underlies these aspects. Specifically, the review emphasizes the crucial role of microbial mediation at the crossroads of hormone signaling, proteomic and metabolomic dynamics during drought adaptation. This enhanced understanding of the intricate interactions among these components presents new opportunities for envisioning sustainable agricultural approaches in the face of the escalating challenges presented by intensifying drought scenarios.

Physiological Temperature and Osmotic Changes Drive Dynamic Proteome Alterations in the Leptospiral Outer Membrane and Enhance Protein Export Systems.

Leptospirosis, a remerging zoonosis, has no effective vaccine or an unambiguous early diagnostic reagent. Proteins differentially expressed (DE) under pathogenic conditions will be useful candidates for antileptospiral measures. We employed a multipronged approach comprising high-resolution TMT-labeled LC-MS/MS-based proteome analysis coupled with bioinformatics on leptospiral proteins following Triton X-114 subcellular fractionation of leptospires treated under physiological temperature and osmolarity that mimic infection. Although there were significant changes in the DE proteins at the level of the entire cell, there were notable changes in proteins at the subcellular level, particularly on the outer membrane (OM), that show the significance of subcellular proteome analysis. The detergent-enriched proteins, representing outer membrane proteins (OMPs), exhibited a dynamic nature and upregulation under various physiological conditions. It was found that pathogenic proteins showed a higher proportion of upregulation compared to the nonpathogenic proteins in the OM. Further analysis identified 17 virulent proteins exclusively upregulated in the outer membrane during infection that could be useful for vaccine and diagnostic targets. The DE proteins may aid in metabolic adaptation and are enriched in pathways related to signal transduction and antibiotic biosynthesis. Many upregulated proteins belong to protein export systems such as SEC translocase, T2SSs, and T1SSs, indicating their sequential participation in protein transport to the outer leaflet of the OM. Further studies on OM-localized proteins may shed light on the pathogenesis of leptospirosis and serve as the basis for effective countermeasures.

Experience-Induced Remodeling of the Hippocampal Post-synaptic Proteome and Phosphoproteome

The postsynaptic density (PSD) of excitatory synapses contains a highly organized protein network with thousands of proteins and is a key node in the regulation of synaptic plasticity. To gain new mechanistic insight into experience-induced changes in the PSD, we examined the global dynamics of the hippocampal PSD proteome and phosphoproteome in mice following four different types ofexperience. Mice were trained using an inhibitory avoidance (IA) task and hippocampal PSD fractions were isolated from individual mice to investigate molecular mechanisms underlying experience-dependent remodeling of synapses. We developed a new strategy to identify and quantify the relatively low level of site-specific phosphorylation of PSD proteome from the hippocampus, by using a modified iTRAQ-based TiSH protocol. In the PSD, we identified 3938 proteins and 2761 phosphoproteins in the sequential strategy covering a total of 4968 unique protein groups (at least two peptides including a unique peptide). On the phosphoproteins, we identified a total of 6188 unambiguous phosphosites (75%<site-localization probability). Strikingly, of the significantly IA-regulated phosphoproteins, a large fraction of these displayed an overall decrease in phosphorylation level. Bioinformatic analysis of proteins and phosphoproteins that were regulated by IA were annotated for involvement in the regulation of glutamate receptor functionality, RHO GTPase cycle, and synaptic plasticity. We also identified synaptic kinases, phosphatases, and their respective phosphosites regulated by IA training or immediate shock. Furthermore, we found that AMPA receptor surface expression was regulated by Mg2+/Mn2+ dependent protein phosphatase 1H (Ppm1h). Together, these results unravel the dynamic remodeling ofthe PSD upon IA learning or immediate shock and serve asa resource for elucidating the synaptic proteome dynamics induced by experience-dependent plasticity.

Exploring the structural and molecular interaction landscape of nirmatrelvir and Mpro complex: The study might assist in designing more potent antivirals targeting SARS-CoV-2 and other viruses

BackgroundSeveral therapeutics have been developed and approved against SARS-CoV-2 occasionally; nirmatrelvir is one of them. The drug target of nirmatrelvir is Mpro, and therefore, it is necessary to comprehend the structural and molecular interaction of the Mpro-nirmatrelvir complex. MethodsIntegrative bioinformatics, system biology, and statistical models were used to analyze the macromolecular complex. ResultsUsing two macromolecular complexes, the study illustrated the interactive residues, H-bonds, and interactive interfaces. It informed of six and nine H-bond formations for the first and second complex, respectively.The maximum bond length was observed as 3.33 Å. The ligand binding pocket's surface area and volume were noted as 303.485 Å2 and 295.456 Å3 for the first complex and 308.397 Å2 and 304.865 Å3 for the second complex. The structural proteome dynamics were evaluated by analyzing the complex's NMA mobility, eigenvalues, deformability, and B-factor. Conversely, a model was created to assess the therapeutic status of nirmatrelvir. ConclusionsOur study reveals the structural and molecular interaction landscape of Mpro-nirmatrelvir complex. The study will guide researchers in designing more broad-spectrum antiviral molecules mimicking nirmatrelvir, which assist in fighting against SARS-CoV-2 and other infectious viruses. It will also help to prepare for future epidemics or pandemics.

PLASMA PROTEOMICS AND MACHINE LEARNING FOR NOVEL BIOMARKER DISCOVERY IN ADULT MALIGNANT GLIOMA

Abstract AIMS Plasma is a valuable source for identifying non-invasive biomarkers, and when combined with an examination of the highly dynamic proteome, it has the potential to lead to the identification of novel biomarkers in glioma. The aim of this study was to uncover plasma-based protein biomarkers for adult malignant glioma. METHOD Mass spectrometry-based proteomics with tandem mass tag (TMT) labelling of plasma from healthy individuals and adult malignant gliomas was performed. A differential abundance analysis was carried out to identify proteins that were deregulated in primary gliomas compared to healthy individuals. Machine learning was employed to identify a diagnostic biomarker panel. RESULTS When comparing plasma from healthy individuals to that of primary gliomas, several high and low abundant proteins were found to be deregulated. To improve the accuracy and ability of biomarkers to detect malignant gliomas, machine learning was employed and led to a development of a classifier, which performed with high accuracy, specificity, and sensitivity. CONCLUSIONS The discovery of a plasma-based protein classifier, once validated, may facilitate an earlier diagnosis of glioma patients, and thereby reduce time-to-treatment.

Multiplex Cas9-based excision of CLCuV betasatellite and DNA-A revealed reduction of viral load with asymptomatic cotton plants.

Multiplexed Cas9-based genome editing of cotton resulted in reduction of viral load with asymptomatic cotton plants. In depth imaging of proteomic dynamics of resulting CLCuV betasatellite and DNA-A protein was also performed. The notorious cotton leaf curl virus (CLCuV), which is transmitted by the sap-sucking insect whitefly, continuously damages cotton crops. Although the application of various toxins and RNAi has shown some promise, sustained control has not been achieved. Consequently, CRISPR_Cas9 was applied by designing multiplex targets against DNA-A (AC2 and AC3) and betasatellite (βC1) of CLCuV using CRISPR direct and ligating into the destination vector of the plant using gateway ligation method. The successful ligation of targets into the destination vector was confirmed by the amplification of 1049 bp using a primer created from the promoter and target, while restriction digestion using the AflII and Asc1 enzymes determined how compact the plasmid developed and the nucleotide specificity of the plasmid was achieved through Sanger sequencing. PCR confirmed the successful introduction of plasmid into CKC-1 cotton variety. Through Sanger sequencing and correlation with the mRNA expression of DNA-A and betasatellite in genome-edited cotton plants subjected to agroinfiltration of CLCuV infectious clone, the effectiveness of knockout was established. The genome-edited cotton plants demonstrated edited efficacy of 72% for AC2 and AC3 and 90% for the (βC1) through amplicon sequencing, Molecular dynamics (MD) simulations were used to further validate the results. Higher RMSD values for the edited βC1 and AC3 proteins indicated functional loss caused by denaturation. Thus, CRISPR_Cas9 constructs can be rationally designed using high-throughput MD simulation technique. The confidence in using this technology to control plant virus and its vector was determined by the knockout efficiency and the virus inoculation assay.

Unbalanced redox status network as an early pathological event in congenital cataracts

The lens proteome undergoes dramatic composition changes during development and maturation. A defective developmental process leads to congenital cataracts that account for about 30% of cases of childhood blindness. Gene mutations are associated with approximately 50% of early-onset forms of lens opacity, with the remainder being of unknown etiology. To gain a better understanding of cataractogenesis, we utilized a transgenic mouse model expressing a mutant ubiquitin protein in the lens (K6W-Ub) that recapitulates most of the early pathological changes seen in human congenital cataracts. We performed mass spectrometry-based tandem-mass-tag quantitative proteomics in E15, P1, and P30 control or K6W-Ub lenses. Our analysis identified targets that are required for early normal differentiation steps and altered in cataractous lenses, particularly metabolic pathways involving glutathione and amino acids. Computational molecular phenotyping revealed that glutathione and taurine were spatially altered in the K6W-Ub cataractous lens. High-performance liquid chromatography revealed that both taurine and the ratio of reduced glutathione to oxidized glutathione, two indicators of redox status, were differentially compromised in lens biology. In sum, our research documents that dynamic proteome changes in a mouse model of congenital cataracts impact redox biology in lens. Our findings shed light on the molecular mechanisms associated with congenital cataracts and point out that unbalanced redox status due to reduced levels of taurine and glutathione, metabolites already linked to age-related cataract, could be a major underlying mechanism behind lens opacities that appear early in life.

The tomato chloroplast stromal proteome compendium elucidated by leveraging a plastid protein-localization prediction Atlas.

Tomato (Solanum lycopersicum) is a model species for studying fruit development, wounding, herbivory, and pathogen attack. Despite tomato's world-wide economic importance and the role of chloroplasts as metabolic hubs and integrators of environmental cues, little is known about the stromal proteome of tomato. Using a high-yielding protocol for chloroplast and stromal protein isolation, MudPIT nano-LC-MS/MS analyses, a robust in-house protein database (the Atlas) for predicting the plastid localization of tomato proteins, and rigorous selection criteria for inclusion/exclusion in the stromal proteome, we identified 1,278 proteins of the tomato stromal proteome. We provide one of the most robust stromal proteomes available to date with empirical evidence for 545 and 92 proteins not previously described for tomato plastids and the Arabidopsis stroma, respectively. The relative abundance of tomato stromal proteins was determined using the exponentially modified protein abundance index (emPAI). Comparison of the abundance of tomato and Arabidopsis stromal proteomes provided evidence for the species-specific nature of stromal protein homeostasis. The manual curation of the tomato stromal proteome classified proteins into ten functional categories resulting in an accessible compendium of tomato chloroplast proteins. After curation, only 91 proteins remained as unknown, uncharacterized or as enzymes with unknown functions. The curation of the tomato stromal proteins also indicated that tomato has a number of paralogous proteins, not present in Arabidopsis, which accumulated to different levels in chloroplasts. As some of these proteins function in key metabolic pathways or in perceiving or transmitting signals critical for plant adaptation to biotic and abiotic stress, these data suggest that tomato may modulate the bidirectional communication between chloroplasts and nuclei in a novel manner. The stromal proteome provides a fertile ground for future mechanistic studies in the field of tomato chloroplast-nuclear signaling and are foundational for our goal of elucidating the dynamics of the stromal proteome controlled by the solanaceous-specific, stromal, and wound-inducible leucine aminopeptidase A of tomato.

Role of TRDMT1/DNMT2 in stress adaptation and its influence on transcriptome and proteome dynamics under osmotic stress in Physcomitrium patens.

Early land plants such as the moss Physcomitrium patens lack several morphological traits that offer protection to tracheophytes from environmental stresses. These plants instead have evolved several physiological and biochemical mechanisms that facilitate them to adapt to terrestrial stresses such as drought. We have previously shown that loss-of-function mutants of tRNA (cytosine(38)-C(5))-methyltransferase TRDMT1/DNMT2 in P. patens are highly sensitive to oxidative and osmotic stress. To gain insight into the role of PpTRDMT1/PpDNMT2 in modulating genetic networks under osmotic stress, genome-wide transcriptome and proteome studies were undertaken in wild-type and ppdnmt2 plants. Transcriptome analysis revealed 375 genes to be differentially expressed in the ppdnmt2 under stress compared to the WT. Most of these genes are affiliated with carbohydrate metabolic pathways, photosynthesis, cell wall biogenesis, pathways related to isotropic and polarised cell growth and transcription factors among others. Histochemical staining showed elevated levels of reactive oxygen species in ppdnmt2 while transmission electron microscopy revealed no distinct defects in the ultrastructure of chloroplasts. Immunoprecipitation using PpDNMT2-specific antibody coupled with mass spectrometry revealed core proteins of the glycolytic pathway, antioxidant enzymes, proteins of amino acid biosynthetic pathways and photosynthesis-related proteins among others to co-purify with PpTRDMT1/PpDNMT2 under osmotic stress. Yeast two-hybrid assays, protein deletion and α-galactosidase assays showed the cytosol glycolytic protein glyceraldehyde 3-phosphate dehydrogenase to bind to the catalytic motifs in PpTRDMT1/PpDNMT2. Results presented in this study allow us to better understand genetic networks linking enzymes of energy metabolism, epigenetic processes and RNA pol II-mediated transcription during osmotic stress tolerance in P. patens.

Proteomic Shift in Mouse Embryonic Fibroblasts Pfa1 during Erastin, ML210, and BSO-Induced Ferroptosis

Ferroptosis is a unique variety of non-apoptotic cell death, driven by massive lipid oxidation in an iron-dependent manner. Since ferroptosis was introduced as a concept in 2012, it has demonstrated its essential role in the pathogenesis in neurodegenerative diseases and an important role in therapy-resistant cancer cells. Thus, detailed molecular understanding of both canonical and alternative ferroptosis pathways is required. There is a set of widely used chemical agents to modulate ferroptosis using different pathway targets: erastin blocks cystine–glutamate antiporter, system xc-; ML210 directly inactivates GPX4; and L-buthionine sulfoximine (BSO) inhibits γ-glutamylcysteine synthetase, an essential enzyme for glutathione synthesis de novo. Most studies have focused on the lipidomic profiling of model systems undergoing death in a ferroptotic modality. In this study, we developed high-quality shotgun proteome sequencing during ferroptosis induction by three widely used chemical agents (erastin, ML210, and BSO) before and after 24 and 48 h of treatment. Chromato-mass spectra were registered in DDA mode and are suitable for further label-free quantification. Both processed and raw files are publicly available and could be a valuable dynamic proteome map for further ferroptosis investigation.

Real-Time Search-Assisted Multiplexed Quantitative Proteomics Reveals System-Wide Translational Regulation of Non-Canonical Short Open Reading Frames

Abnormal expression of histone deacetylases (HDACs) is reported to be associated with angiogenesis, metastasis and chemotherapy resistance regarding cancer in a wide range of previous studies. Suberoylanilide hydroxamic acid (SAHA) is well known to function as a pan-inhibitor for HDACs and recognized as one of the therapeutic drug candidates to epigenetically coordinate cancer cell fate regulation on a genomic scale. Here, we established a Real-Time Search (RTS)-assisted mass spectrometric platform for system-wide quantification of translated products encoded by non-canonical short open reading frames (ORFs) as well as already annotated protein coding sequences (CDSs) on the human transciptome and applied this methodology to quantitative proteomic analyses of suberoylanilide hydroxamic acid (SAHA)-treated human HeLa cells to evaluate proteome-wide regulation in response to drug perturbation. Very intriguingly, our RTS-based in-depth proteomic analysis enabled us to identify approximately 5000 novel peptides from the ribosome profiling-based short ORFs encoded in the diversified regions on presumed ‘non-coding’ nucleotide sequences of mRNAs as well as lncRNAs and nonsense mediated decay (NMD) transcripts. Furthermore, TMT-based multiplex large-scale quantification of the whole proteome changes upon differential SAHA treatment unveiled dose-dependent selective translational regulation of a limited fraction of the non-canonical short ORFs in addition to key cell cycle/proliferation-related molecules such as UBE2C, CENPF and PRC1. Our study provided the first system-wide landscape of drug-perturbed translational modulation on both canonical and non-canonical proteome dynamics in human cancer cells.

THRONCAT: metabolic labeling of newly synthesized proteins using a bioorthogonal threonine analog

Profiling the nascent cellular proteome and capturing early proteomic changes in response to external stimuli provides valuable insights into cellular physiology. Existing metabolic protein labeling approaches based on bioorthogonal methionine- or puromycin analogs allow for the selective visualization and enrichment of newly synthesized proteins. However, their applications are limited as they often require methionine-free conditions, auxotrophic cells and/or are toxic to cells. Here, we introduce THRONCAT, a threonine-derived non-canonical amino acid tagging method based on the bioorthogonal threonine analog β-ethynylserine (βES) that enables efficient labeling of the nascent proteome in complete growth media within minutes. We use THRONCAT for the visualization and enrichment of nascent proteins in bacteria, mammalian cells and Drosophila melanogaster. We profile immediate proteome dynamics of B-cells in response to B-cell receptor activation simply by adding βES to the culture medium, demonstrating the ease-of-use of the method and its potential to address diverse biological questions. In addition, using a Drosophila model of Charcot-Marie-Tooth peripheral neuropathy, we show that THRONCAT enables visualization and quantification of relative protein synthesis rates in specific cell types in vivo.

FRI-407 - Platelets proteome dynamics and its association with liver severity in severe alcoholic hepatitis

FRI-407 - Platelets proteome dynamics and its association with liver severity in severe alcoholic hepatitis

Deep Profiling of the Proteome Dynamics of Pseudomonas aeruginosa Reference Strain PAO1 under Different Growth Conditions.

As one of the most common bacterial pathogens causing nosocomial infections, Pseudomonas aeruginosa is highly adaptable to survive under various conditions. Here, we profiled the abundance dynamics of 3489 proteins across different growth stages in the P. aeruginosa reference strain PAO1 using data-independent acquisition-based quantitative proteomics. The proteins differentially expressed during the planktonic growth exhibit several distinct patterns of expression profiles and are relevant to various biological processes, highlighting the continuous adaptation of the PAO1 proteome during the transition from the acceleration phase to the stationary phase. By contrasting the protein expressions in a biofilm to planktonic cells, the known roles of T6SS, phenazine biosynthesis, quorum sensing, and c-di-GMP signaling in the biofilm formation process were confirmed. Additionally, we also discovered several new functional proteins that may play roles in the biofilm formation process. Lastly, we demonstrated the general concordance of protein expressions within operons across various growth states, which permits the study of coexpression protein units, and reversely, the study of regulatory components in the operon structure. Taken together, we present a high-quality and valuable resource on the proteomic dynamics of the P. aeruginosa reference strain PAO1, with the potential of advancing our understanding of the overall physiology of Pseudomonas bacteria.