Solventā€induced proteome profiling for proteomic quantitation and target discovery of small molecular drugs

Proteomics (Wiley)

Wiley: PROTEOMICS: Table of Contents

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Solventā€induced proteome profiling for proteomic quantitation and target discovery of small molecular drugs

Abstract

Target identification by modification-free proteomic approaches can potentially reveal the pharmacological mechanism of small molecular compounds. By combining the recent solvent-induced protein precipitation (SIP) method with TMT-labeling quantitative proteomics, we propose solvent-induced proteome profiling (SIPP) approach to identify small moleculeā€“protein interactions. The SIPP approach enables to depict denaturation curves of the target protein by varying concentrations of organic solvents to induce unfolding and precipitation of the cellular proteome. By using this approach, we have successfully identified the known targets of market drugs and natural products and extended the proteome information of SIP for target identification.

Chengli Yu,
Xiuzhen Chen,
Weiwei Xu,
Simin Li,
Qian Chai,
Yinan Zhang
March 5, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202200281?af=R

The ups and downs of biological oscillators: A comparison of time-delayed negative feedback mechanisms

BioRxiv

bioRxiv Subject Collection: Systems Biology
This feed contains articles for bioRxiv Subject Collection "Systems Biology"

The ups and downs of biological oscillators: A comparison of time-delayed negative feedback mechanisms

Many biochemical oscillators are driven by the periodic rise and fall of protein concentrations or activities. A negative feedback loop underlies such oscillations. The feedback can act on different parts of the biochemical network. Here, we mathematically compare time-delay models where the feedback affects production and degradation. We show a mathematical connection between the linear stability of the two models, and derive how both mechanisms impose different constraints on the production and degradation rates that allow oscillations. We show how oscillations are affected by the inclusion of a distributed delay, of double regulation (acting on production and degradation), and of enzymatic degradation.
Rombouts, J., Verplaetse, S., Gelens, L.
March 4, 2023
http://biorxiv.org/cgi/content/short/2023.03.03.530971v1?rss=1

An integrated workflow for quantitative analysis of the newly synthesized proteome

BioRxiv

bioRxiv Subject Collection: Systems Biology
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An integrated workflow for quantitative analysis of the newly synthesized proteome

The analysis of proteins that are newly synthesized upon a cellular perturbation can provide detailed insight in the proteomic response that is elicited by specific cues. This can be investigated by pulse-labeling of cells with clickable and stable-isotope-coded amino acids for enrichment and mass spectrometric characterization of newly synthesized proteins (NSPs), however convoluted protocols prohibit their routine application. Here we optimized multiple steps in sample preparation, mass spectrometry and data analysis, and integrated them in a semi-automated workflow for the quantitative analysis of the newly synthesized proteome (QuaNPA). Reduced input requirements and data-independent acquisition (DIA) enabled analysis of triple-SILAC-labeled NSP samples, with enhanced throughput while featuring high quantitative accuracy. We applied QuaNPA to investigate the time-resolved cellular response to interferon-gamma (IFNg), observing rapid induction of known and novel targets 2h after IFNg treatment. QuaNPA provides a powerful approach for large-scale investigation of NSPs to gain insight in complex cellular processes.
Bortecen, T., Mueller, T., Krijgsveld, J.
March 4, 2023
http://biorxiv.org/cgi/content/short/2023.03.03.530942v1?rss=1

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance

BioRxiv

bioRxiv Subject Collection: Systems Biology
This feed contains articles for bioRxiv Subject Collection "Systems Biology"

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance

Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. "Diversity Outbred in Australia (DOz)" is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscles contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focussing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complimentary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin resistant mouse muscle, and palmitate induced insulin resistant myotubes demonstrated potent insulin action restoration, potentially via up-regulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems level analysis by identifying potential therapeutics for insulin resistance.
Masson, S. W., Madsen, S., Cooke, K. C., Potter, M., Vegas, A. D., Carroll, L., Thillainadesan, S., Walder, K. R., Cooney, G. J., Morahan, G., StoĢˆckli, J., James, D. E.
March 4, 2023
http://biorxiv.org/cgi/content/short/2023.03.01.530673v1?rss=1

Inferring gene regulatory networks using transcriptional profiles as dynamical attractors

BioRxiv

bioRxiv Subject Collection: Systems Biology
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Inferring gene regulatory networks using transcriptional profiles as dynamical attractors

Genetic regulatory networks (GRNs) regulate the flow of genetic information from the genome to expressed messenger RNAs (mRNAs) and thus are critical to controlling the phenotypic characteristics of cells. Numerous methods exist for profiling mRNA transcript levels and identifying protein-DNA binding interactions at the genome-wide scale. These enable researchers to determine the structure and output of transcriptional regulatory networks, but uncovering the complete structure and regulatory logic of GRNs remains a challenge. The field of GRN inference aims to meet this challenge using computational modeling to derive the structure and logic of GRNs from experimental data and to encode this knowledge in Boolean networks, Bayesian networks, ordinary differential equation (ODE) models, or other modeling frameworks. However, most existing models do not incorporate dynamic transcriptional data since it has historically been less widely available in comparison to "static" transcriptional data. We report the development of an evolutionary algorithm-based ODE modeling approach that integrates kinetic transcription data and the theory of attractor matching to infer GRN architecture and regulatory logic. Our method outperformed six leading GRN inference methods, none of which incorporate kinetic transcriptional data, in predicting regulatory connections among TFs when applied to a small-scale engineered synthetic GRN in Saccharomyces cerevisiae. Moreover, we demonstrate the potential of our method to predict unknown transcriptional profiles that would be produced upon genetic perturbation of the GRN governing a two-state cellular phenotypic switch in Candida albicans. We established an iterative refinement strategy to facilitate candidate selection for experimentation; the experimental results in turn provide validation or improvement for the model. In this way, our GRN inference approach can expedite the development of a sophisticated mathematical model that can accurately describe the structure and dynamics of the in vivo GRN.
Li, R., Rozum, J. C., Quail, M. M., Qasim, M. N., Sindi, S. S., Nobile, C. J., Albert, R., Hernday, A.
March 4, 2023
http://biorxiv.org/cgi/content/short/2023.03.03.530929v1?rss=1

Integrated tandem affinity protein purification using the polyhistidine plus extra 4 amino acids (HiP4) tag system

Proteomics (Wiley)

Wiley: PROTEOMICS: Table of Contents

Table of Contents for PROTEOMICS. List of articles from both the latest and EarlyView issues.

Integrated tandem affinity protein purification using the polyhistidine plus extra 4 amino acids (HiP4) tag system

Abstract

Peptide tag systems are a robust biophysical and biochemical method that is widely used for protein detection and purification. Here, we developed a novel tag system termed ā€œHiP4ā€ (histidine plus four amino acids) whose epitope sequence comprises only seven amino acids (HHHDYDI) that partially overlap with the conventional 6x histidine tag (6xHis-tag). We produced a monoclonal antibody against the HiP4 tag that can be used in multiple immunoassays with high specificity and affinity. Using this system, we developed a tandem affinity purification (TAP) and mass spectrometry (TAP-MS) system for comprehensive protein interactome analysis. The integrated use of nickel bead purification followed by HiP4 tag immunoprecipitation made it possible to reduce nonspecific binding and improve selectivity, leading to the recovery of previously unrecognized proteins that interact with hepatitis B virus X (HBx) protein or TAR DNA-binding protein 43 (TARDBP or TDP-43). Our results indicate that this system may be viable as a simple and powerful tool for TAP-MS that can achieve low background and high selectivity in comprehensive proteinā€“protein interaction analyses.

Yoko Ino,
Yutaro Yamaoka,
Kiho Tanaka,
Kei Miyakawa,
Mayuko Nishi,
Yasuyoshi Hatayama,
Hirokazu Kimura,
Yayoi Kimura,
Akihide Ryo
March 4, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202200334?af=R

Identification of proteoforms by topā€down proteomics using twoā€dimensional low/low pH reversedā€phase liquid chromatographyā€mass spectrometry

Proteomics (Wiley)

Wiley: PROTEOMICS: Table of Contents

Table of Contents for PROTEOMICS. List of articles from both the latest and EarlyView issues.

Identification of proteoforms by topā€down proteomics using twoā€dimensional low/low pH reversedā€phase liquid chromatographyā€mass spectrometry

Abstract

In top-down (TD) proteomics, efficient proteoform separation is crucial to reduce the sample complexity and increase the depth of the analysis. Here, we developed a two-dimensional low pH/low pH reversed-phase liquid chromatography separation scheme for TD proteomics. The first dimension for offline fractionation was performed using a polymeric reversed-phase (PLRP-S) column with trifluoroacetic acid as ion-pairing reagent. The second dimension, a C4 nanocolumn with formic acid as ion-pairing reagent, was coupled online with a high-field asymmetric ion mobility spectrometry (FAIMS) Orbitrap Tribrid mass spectrometer. For both dimensions several parameters were optimized, such as the adaption of the LC gradients in the second dimension according to the elution time (i.e., fraction number) in the first dimension. Avoidance of elevated temperatures and prolonged exposure to acidic conditions minimized cleavage of acid labile aspartateā€“proline peptide bonds. Furthermore, a concatenation strategy was developed to reduce the total measurement time. We compared our low/low pH with a previously published high pH (C4, ammonium formate)/low pH strategy and found that both separation strategies led to complementary proteoform identifications, mainly below 20Ā kDa, with a higher number of proteoforms identified by the low/low pH separation. With the optimized separation scheme, more than 4900 proteoforms from 1250 protein groups were identified in Caco-2 cells.

Philipp T. Kaulich,
Liam Cassidy,
Andreas Tholey
March 4, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202200542?af=R

[ASAP] Electrochemically Etched Tapered-Tip Stainless-Steel Electrospray-Ionization Emitters for Capillary Electrophoresisā€“Mass Spectrometry

Journal of Proteome Research

Journal of Proteome Research: Latest Articles (ACS Publications)

latest articles published in Journal of Proteome Research

[ASAP] Electrochemically Etched Tapered-Tip Stainless-Steel Electrospray-Ionization Emitters for Capillary Electrophoresisā€“Mass Spectrometry

TOC Graphic

Journal of Proteome Research
DOI: 10.1021/acs.jproteome.3c00076

Jordan T. Aerts, Per E. AndreĢn, and Erik T. Jansson
March 3, 2023
http://dx.doi.org/10.1021/acs.jproteome.3c00076

Rapid screening of highā€priority Nā€nitrosamines in pharmaceutical, forensic, and environmental samples with paper spray ionization and filter cone spray ionizationā€mass spectrometry

Rapid Communications in Mass Spectrometry

Wiley: Rapid Communications in Mass Spectrometry: Table of Contents

Table of Contents for Rapid Communications in Mass Spectrometry. List of articles from both the latest and EarlyView issues.

Rapid screening of highā€priority Nā€nitrosamines in pharmaceutical, forensic, and environmental samples with paper spray ionization and filter cone spray ionizationā€mass spectrometry

Rationale

The burgeoning concern of N-nitrosamine (NAM) contamination found in various pharmaceutical compositions has increased the demand for rapid and reliable screening methods to better assess the breadth of the problem. These carcinogenic compounds are also found in food, water, and soil, and they have been used in poison-related homicides.

Methods

A combination of complementary, ambient ionization methods, paper spray ionization (PSI) and filter cone spray ionization (FCSI)-mass spectrometry (MS), was characterized towards trace-level residue screening of select NAMs (e.g., N-nitrosodimethylamine, N-nitrosodiethylamine, N-nitrosodibutylamine) directly from complex and problematic matrices of interest, including prescription and over-the-counter tablets, drinking water, soil, and consumable goods. Spectral data for analyte confirmation and detection limit studies were collected using a Thermo LCQ Fleet ion trap mass spectrometer.

Results

PSI-MS and FCSI-MS readily produced mass spectral data marked by their simplicity (e.g., predominantly protonated molecular ions observed) and congruence with traditional electrospray ionization mass spectra in under 2Ā min. per sample. Both methods proved robust to the complex matrices tested, yielding ion signatures for target NAMs, as well as active pharmaceutical ingredients for analyzed tablets, flavorants inherent to food products, etc. Low part-per-million detection limits were observed but were shown dependent on sample composition.

Conclusions

PSI-MS and FCSI-MS were successful in detecting trace-level NAMS in complex liquid- and solid-phase matrices with little to no prior preparation. This work suggests that these methodologies can provide a means for assessing problematic pharmaceutical adulterants/degradants for expedited quality control, as well as enhancing environmental stewardship efforts and forensic investigations.

Trevor J. McDaniel,
Jessica M. Holtz,
Ebenezer H. Bondzie,
Makoy Overfelt,
Patrick W. Fedick,
Christopher C. Mulligan
March 3, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/rcm.9493?af=R

Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts

BioRxiv

bioRxiv Subject Collection: Systems Biology
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Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts

Fibroblasts are essential regulators of extracellular matrix deposition following cardiac injury. These cells exhibit highly plastic responses in phenotype during fibrosis in response to environmental stimuli. Here, we test whether and how candidate anti-fibrotic drugs differentially regulate measures of cardiac fibroblast phenotype, which may help identify treatments for cardiac fibrosis. We conducted a high content microscopy screen of human cardiac fibroblasts treated with 13 clinically relevant drugs in the context of TGF{beta} and/or IL-1{beta}, measuring phenotype across 137 single-cell features. We used the phenotypic data from our high content imaging to train a logic-based mechanistic machine learning model (LogiMML) for fibroblast signaling. The model predicted how pirfenidone and Src inhibitor WH-4-023 reduce F-actin assembly and F-actin stress fiber formation, respectively. Validating the LogiMML model prediction that PI3K partially mediates the effects of Src inhibition, we found that PI3K inhibition reduces F-actin fiber formation and procollagen I production in human cardiac fibroblasts. In this study, we establish a modeling approach combining the strengths of logic-based network models and regularized regression models, apply this approach to predict mechanisms that mediate the differential effects of drugs on fibroblasts, revealing Src inhibition acting via PI3K as a potential therapy for cardiac fibrosis.
Nelson, A. R., Christiansen, S. L., Naegle, K. M., Saucerman, J. J.
March 3, 2023
http://biorxiv.org/cgi/content/short/2023.03.01.530599v1?rss=1

Proteomic analysis identifies dysregulated proteins and associated molecular pathways in a cohort of gallbladder cancer patients of African ancestry

Clinical Proteomics

Most Recent Articles: Clinical Proteomics

Most Recent Articles: Clinical Proteomics

Proteomic analysis identifies dysregulated proteins and associated molecular pathways in a cohort of gallbladder cancer patients of African ancestry

Gallbladder cancer (GBC) is a lethal cancer with a poor prognosis. The lack of specific and sensitive biomarkers results in delayed diagnosis with most patients presenting at late stages of the disease. Furth…

Pavan Baichan, Previn Naicker, Tanya Nadine Augustine, Martin Smith, Geoffrey Candy, John Devar and Ekene Emmanuel Nweke
March 2, 2023
https://clinicalproteomicsjournal.biomedcentral.com/articles/10.1186/s12014-023-09399-9

Bounds on the Ultrasensitivity of Biochemical ReactionCascades

BioRxiv

bioRxiv Subject Collection: Systems Biology
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Bounds on the Ultrasensitivity of Biochemical ReactionCascades

The ultrasensitivity of a dose response function can be quantifiably defined using the generalized Hill coefficient of the function. Our group examined an upper bound for the Hill coefficient of the composition of two functions, namely the product of their individual Hill coefficients. We proved that this upper bound holds for compositions of Hill functions, and that there are instances of counterexamples that exist for more general sigmoidal functions. Additionally, we tested computationally other types of sigmoidal functions, such as the logistic and inverse trigonometric functions, and we provided evidence that in these cases the inequality also holds. We show that in large generality there is a limit to how ultrasensitive the composition of two functions can be, which has applications to understanding signaling cascades in biochemical reactions.
Pajoh-Casco, M., Vinujudson, A., Enciso, G.
March 2, 2023
http://biorxiv.org/cgi/content/short/2023.02.28.529800v1?rss=1

Microbial community-scale metabolic modeling predicts personalized short-chain-fatty-acid production profiles in the human gut.

BioRxiv

bioRxiv Subject Collection: Systems Biology
This feed contains articles for bioRxiv Subject Collection "Systems Biology"

Microbial community-scale metabolic modeling predicts personalized short-chain-fatty-acid production profiles in the human gut.

Microbially-derived short-chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro, ex vivo, and in vivo data. Next, we identify associations between MCMM SCFA predictions and a panel of blood-based clinical chemistries in a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.
Bohmann, N., Wilmanski, T., Levy, L., Lampe, J., Gurry, T., Rappaport, N., Diener, C., Gibbons, S. M.
March 2, 2023
http://biorxiv.org/cgi/content/short/2023.02.28.530516v1?rss=1

Metabolomics investigation of post-mortem human pericardial fluid

BioRxiv

bioRxiv Subject Collection: Systems Biology
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Metabolomics investigation of post-mortem human pericardial fluid

Introduction. Due to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or Post-Mortem Interval based on pericardial fluids has still rarely been attempted. Objectives. We applied a metabolomic approach based on 1H Nuclear Magnetic Resonance Spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for Post-Mortem Interval estimation. Methods. Pericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 hours after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of 1H Nuclear Magnetic Resonance and multivariate statistical data analysis. Results. The pericardial fluid samples treated with the two experimental protocols did not show significant differences in the dis-tribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33 – 34 hours depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 hours, the prediction power of the model was significantly improved with an error of 13-15 hours depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model. Conclusion. The present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.
Chighine, A., Stocchero, M., Ferino, G., De-Giorgio, F., Conte, C., Nioi, M., d’Aloja, E., Locci, E.
March 2, 2023
http://biorxiv.org/cgi/content/short/2023.02.28.530436v1?rss=1

Efficient and scalable prediction of spatio-temporal stochastic gene expression in cells and tissues using graph neural networks

BioRxiv

bioRxiv Subject Collection: Systems Biology
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Efficient and scalable prediction of spatio-temporal stochastic gene expression in cells and tissues using graph neural networks

The simulation of spatial stochastic models is highly computationally expensive, an issue that has severely limited our understanding of the spatial nature of gene expression. Here we devise a graph neural network based method to learn, from stochastic trajectories in a small region of space, an effective master equation for the time-dependent marginal probability distributions of mRNA and protein numbers at sub-cellular resolution for every cell in a tissue. Numerical solution of this equation leads to accurate results in a small fraction of the computation time of standard simulation methods. Moreover its predictions can be extrapolated to a spatial organisation (a cell network topology) and regions of parameter space unseen in its neural network training. The scalability and accuracy of the method suggest it is a promising approach for whole cell modelling and for detailed comparisons of stochastic models with spatial genomics data.
Cao, Z., Chen, R., Xu, L., Zhou, X., Fu, X., Zhong, W., Grima, R.
March 2, 2023
http://biorxiv.org/cgi/content/short/2023.02.28.530379v1?rss=1

Systematic Identification of Post-Transcriptional Regulatory Modules

BioRxiv

bioRxiv Subject Collection: Systems Biology
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Systematic Identification of Post-Transcriptional Regulatory Modules

In our cells, a limited number of RNA binding proteins (RBPs) are responsible for all aspects of RNA metabolism across the entire transcriptome. To accomplish this, RBPs form regulatory units that act on specific target regulons. However, the landscape of RBP combinatorial interactions remains poorly explored. Here, we performed a systematic annotation of RBP combinatorial interactions via multimodal data integration. We built a large-scale map of RBP protein neighborhoods by generating in vivo proximity-dependent biotinylation datasets of 50 human RBPs. In parallel, we used CRISPR interference with single-cell readout to capture transcriptomic changes upon RBP knockdowns. By combining these physical and functional interaction readouts, along with the atlas of RBP mRNA targets from eCLIP assays, we generated an integrated map of functional RBP interactions. We then used this map to match RBPs to their context-specific functions and validated the predicted functions biochemically for four RBPs. This study highlights the previously underappreciated scale of the inter-RBP interactions, be it genetic or physical, and is a first step towards a more comprehensive understanding of post-transcriptional regulatory processes and their underlying molecular grammar.
Khoroshkin, M. S., Buyan, A., Dodel, M., Navickas, A., Yu, J., Trejo, F., Doty, A., Baratam, R., Zhou, S., Joshi, T., Miglani, S., Choi, B., Subramanyam, V., Modi, H., Corces, R., Markett, D., Kulakovskiy, I. V., Mardakheh, F. K., Goodarzi, H.
March 2, 2023
http://biorxiv.org/cgi/content/short/2023.02.27.530345v1?rss=1

Isobaric labelingā€based quantitative proteomics of FACSā€purified immune cells and epithelial cells from the intestine of Crohn’s disease patients reveals proteome changes of potential importance in disease pathogenesis

Proteomics (Wiley)

Wiley: PROTEOMICS: Table of Contents

Table of Contents for PROTEOMICS. List of articles from both the latest and EarlyView issues.

Isobaric labelingā€based quantitative proteomics of FACSā€purified immune cells and epithelial cells from the intestine of Crohn’s disease patients reveals proteome changes of potential importance in disease pathogenesis

Abstract

Crohn’s disease (CD) is a chronic condition characterized by recurrent flares of inflammation in the gastrointestinal tract. Disease etiology is poorly understood and is characterized by dysregulated immune activation that progressively destroys intestinal tissue. Key cellular compartments in disease pathogenesis are the intestinal epithelial layer and its underlying lamina propria. While the epithelium contains predominantly epithelial cells, the lamina propria is enriched in immune cells. Deciphering proteome changes in different cell populations is important to understand CD pathogenesis. Here, using isobaric labeling-based quantitative proteomics, we perform an exploratory study to analyze in-depth proteome changes in epithelial cells, immune cells and stromal cells in CD patients compared to controls using cells purified by FACS. Our study revealed increased proteins associated with neutrophil degranulation and mitochondrial metabolism in immune cells of CD intestinal mucosa. We also found upregulation of proteins involved in glycosylation and secretory pathways in epithelial cells of CD patients, while proteins involved in mitochondrial metabolism were reduced. The distinct alterations in protein levels in immune- versus epithelial cells underscores the utility of proteome analysis of defined cell types. Moreover, our workflow allowing concomitant assessment of cell-type specific changes on an individual basis enables deeper insight into disease pathogenesis.

Johannes Alfredsson,
Ivo Fabrik,
Frida Gorreja,
Charles Caƫr,
Carina Sihlbom,
Mattias Block,
Lars G. Bƶrjesson,
Elinor Bexe Lindskog,
Mary Jo Wick
March 2, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202200366?af=R

Proteomicsā€based scoring of cellular response to stimuli for improved characterization of signaling pathway activity

Proteomics (Wiley)

Wiley: PROTEOMICS: Table of Contents

Table of Contents for PROTEOMICS. List of articles from both the latest and EarlyView issues.

Proteomicsā€based scoring of cellular response to stimuli for improved characterization of signaling pathway activity

Abstract

Omics technologies focus on uncovering the complex nature of molecular mechanisms in cells and organisms, including biomarkers and drug targets discovery. Aiming at these tasks, we see that information extracted from omics data is still underused. In particular, characteristics of differentially regulated molecules can be combined in a single score to quantify the signaling pathway activity. Such a metric can be useful for comprehensive data interpretation to follow: (1) developing molecular responses in time; (2) potency of a drug on a certain cell culture; (3) ranking the signaling pathway activity in stimulated cells; and (4) integration of the omics data and assay-based measurements of cell viability, cytotoxicity, and proliferation. With recent advances in ultrafast mass spectrometry for quantitative proteomics allowing data collection in a few minutes, proteomics score for cellular response to stimuli can become a fast, accurate, and informative complement to bioassays. Here, we utilized an interquartile-based selection of differentially regulated features and a variety of schemes for quantifying cellular responses to come up with the quantitative metric for total cellular response and pathway activity. Validation was performed using antiproliferative and virus assays and label-free proteomics data collected for cancer cells subjected to drug stimulation.

Elizaveta M. Kazakova,
Elizaveta M. Solovyeva,
Lev I. Levitsky,
Julia A. Bubis,
Daria D. Emekeeva,
Anastasia A. Antonets,
Alexey A. Nazarov,
Mikhail V. Gorshkov,
Irina A. Tarasova
March 2, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202200275?af=R

Proteomic and phosphoproteomic landscape of salivary extracellular vesicles to assess OSCC therapeutical outcomes

Proteomics (Wiley)

Wiley: PROTEOMICS: Table of Contents

Table of Contents for PROTEOMICS. List of articles from both the latest and EarlyView issues.

Proteomic and phosphoproteomic landscape of salivary extracellular vesicles to assess OSCC therapeutical outcomes

Abstract

Circulating extracellular vesicles (EVs) have emerged as an appealing source for surrogates to evaluate the disease status. Herein, we present a novel proteomic strategy to identify proteins and phosphoproteins from salivary EVs to distinguish oral squamous cell carcinoma (OSCC) patients from healthy individuals and explore the feasibility to evaluate therapeutical outcomes. Bi-functionalized magnetic beads (BiMBs) with Ti (IV) ions and a lipid analog, 1,2-Distearoyl-3-sn-glycerophosphoethanolamine (DSPE) are developed to efficiently isolate EVs from small volume of saliva. In the discovery stage, label-free proteomics and phosphoproteomics quantification showed 315 upregulated proteins and 132 upregulated phosphoproteins in OSCC patients among more than 2500 EV proteins and 1000 EV phosphoproteins, respectively. We further applied targeted proteomics by coupling parallel reaction monitoring with parallel accumulation-serial fragmentation (prm-PASEF) to measure panels of proteins and phosphoproteins from salivary EVs collected before and after surgical resection. A panel of three total proteins and three phosphoproteins, most of which have previously been associated with OSCC and other cancer types, show sensitive response to the therapy in individual patients. Our study presents a novel strategy to the discovery of effective biomarkers for non-invasive assessment of OSCC surgical outcomes with small amount of saliva.

Jie Sun,
Xiaole Wang,
Yajie Ding,
Bolin Xiao,
Xinxin Wang,
Muhammad Mujahid Ali,
Leyao Ma,
Zhuoying Xie,
Zhongze Gu,
Gang Chen,
W. Andy Tao
March 2, 2023
https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202200319?af=R