scholarly journals Rapid profiling of protein complex re-organization in perturbed systems

2021 ◽  
Author(s):  
Isabell Bludau ◽  
Charlotte Nicod ◽  
Claudia Martelli ◽  
Peng Xue ◽  
Moritz Heusel ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Protein Complex ◽  
Protein Complexes ◽  
Experimental Designs ◽  
Biological Information ◽  
Condition Numbers ◽  
Complex Organization ◽  
Biological Insight ◽  
Large Measurement

Protein complexes constitute the primary functional modules of cellular activity. To respond to perturbations, complexes undergo changes in their abundance, subunit composition or state of modification. Understanding the function of biological systems requires global strategies to capture this contextual state information on protein complexes and interaction networks. Methods based on co-fractionation paired with mass spectrometry have demonstrated the capability for deep biological insight but the scope of studies using this approach has been limited by the large measurement time per biological sample and challenges with data analysis. As such, there has been little uptake of this strategy beyond a few expert labs into the broader life science community despite rich biological information content. We present a rapid integrated experimental and computational workflow to assess the re-organization of protein complexes across multiple cellular states. It enables complex experimental designs requiring increased sample/condition numbers. The workflow combines short gradient chromatography and DIA/SWATH mass spectrometry with a data analysis toolset to quantify changes in complex organization. We applied the workflow to study the global protein complex rearrangements of THP-1 cells undergoing monocyte to macrophage differentiation and a subsequent stimulation of macrophage cells with lipopolysaccharide. We observed massive proteome organization in functions related to signaling, cell adhesion, and extracellular matrix during differentiation, and less pronounced changes in processes related to innate immune response induced by the macrophage stimulation. We therefore establish our integrated differential pipeline for rapid and state-specific profiling of protein complex organization with broad utility in complex experimental designs.

Illustration of SID-IM-SID (surface-induced dissociation-ion mobility-SID) mass spectrometry: homo and hetero model protein complexes

The Analyst ◽  
2015 ◽  
Vol 140 (20) ◽  
pp. 7012-7019 ◽  
Author(s):  
Royston S. Quintyn ◽  
Sophie R. Harvey ◽  
Vicki H. Wysocki
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Protein Complex ◽  
Protein Complexes ◽  
Second Stage ◽  
Surface Induced Dissociation ◽  
Model Protein ◽  
Complex Architecture

Surface collisions generate subcomplexes, which are then separated by ion mobility and dissociated into their individual subunitsviaa second stage of surface collisions to elucidate protein complex architecture and assembly.

scholarly journals A Co-Fractionation Mass Spectrometry-based Prediction of Protein Complex Assemblies in the Developing Rice Aleurone-subaleurone

2021 ◽  
Author(s):  
Youngwoo Lee ◽  
Thomas W Okita ◽  
Daniel B Szymanski
Keyword(s):  
Mass Spectrometry ◽  
Protein Complex ◽  
Large Scale ◽  
Rna Binding ◽  
Seed Quality ◽  
Protein Complexes ◽  
Early Stage ◽  
Practical Significance ◽  
Rice Seed ◽  
Complex Composition

Multiprotein complexes execute and coordinate diverse cellular processes such as organelle biogenesis, vesicle trafficking, cell signaling, and metabolism. Knowledge about their composition and localization provides useful clues about the mechanisms of cellular homeostasis and systems-level control. This is of great biological importance and practical significance in heterotrophic rice endosperm and aleurone-subaleurone tissues that are a primary source of seed vitamins and stored energy. Dozens of protein complexes have been implicated in the synthesis, transport, and storage of seed proteins, lipids, vitamins, and minerals. Mutations in protein complexes that control RNA transport result in aberrant endosperm with shrunken and floury phenotypes, significantly reducing seed yield and quality. The purpose of this research is to broadly predict protein complex composition in the aleurone-subaleurone layers of developing rice seeds using co-fractionation mass spectrometry. Following orthogonal chromatographic separations of biological replicates, thousands of protein elution profiles were subjected to distance-based clustering to enable a large-scale determination of multimerization state and complex composition. Predictions included evolutionarily conserved proteins across diverse functional categories, including novel heteromeric RNA binding protein complexes that influence seed quality. This effective and open-ended proteomics pipeline provides useful clues about systems-level controls in the early stage of rice seed development.

scholarly journals Cloud-based DIA data analysis module for signal refinement improves accuracy and throughput of large datasets

2021 ◽  
Author(s):  
Karen E. Christianson ◽  
Jacob. D. Jaffe ◽  
Steven A. Carr ◽  
Alvaro Sebastian Vaca Jacome
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Large Scale ◽  
Mass Spectrometry Data ◽  
Avant Garde ◽  
Data Independent Acquisition ◽  
Large Scale Data ◽  
Biological Insight ◽  
Computational Resources ◽  
User Friendly

AbstractData-independent acquisition (DIA) is a powerful mass spectrometry method that promises higher coverage, reproducibility, and throughput than traditional quantitative proteomics approaches. However, the complexity of DIA data caused by fragmentation of co-isolating peptides presents significant challenges for confident assignment of identity and quantity, information that is essential for deriving meaningful biological insight from the data. To overcome this problem, we previously developed Avant-garde, a tool for automated signal refinement of DIA and other targeted mass spectrometry data. AvG is designed to work alongside existing tools for peptide detection to address the reliability and quantitative suitability of signals extracted for the identified peptides. While its use is straightforward and offers efficient refinement for small datasets, the execution of AvG for large DIA datasets is time-consuming, especially if run with limited computational resources. To overcome these limitations, we present here an improved, cloud-based implementation of the AvG algorithm deployed on Terra, a user-friendly cloud-based platform for large-scale data analysis and sharing, as an accessible and standardized resource to the wider community.

scholarly journals Discovery–Versus Hypothesis–Driven Detection of Protein–Protein Interactions and Complexes

2021 ◽  
Vol 22 (9) ◽  
pp. 4450
Author(s):  
Isabell Bludau
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Protein Interactions ◽  
Prior Information ◽  
Protein Complexes ◽  
Functional Modules ◽  
Protein Protein Interactions ◽  
Future Studies ◽  
Protein Protein Interaction ◽  
Selection Of

Protein complexes are the main functional modules in the cell that coordinate and perform the vast majority of molecular functions. The main approaches to identify and quantify the interactome to date are based on mass spectrometry (MS). Here I summarize the benefits and limitations of different MS-based interactome screens, with a focus on untargeted interactome acquisition, such as co-fractionation MS. Specific emphasis is given to the discussion of discovery- versus hypothesis-driven data analysis concepts and their applicability to large, proteome-wide interactome screens. Hypothesis-driven analysis approaches, i.e., complex- or network-centric, are highlighted as promising strategies for comparative studies. While these approaches require prior information from public databases, also reviewed herein, the available wealth of interactomic data continuously increases, thereby providing more exhaustive information for future studies. Finally, guidance on the selection of interactome acquisition and analysis methods is provided to aid the reader in the design of protein-protein interaction studies.

scholarly journals Bioinformatic Analysis of Temporal and Spatial Proteome Alternations During Infections

2021 ◽  
Vol 12 ◽  
Author(s):  
Matineh Rahmatbakhsh ◽  
Alla Gagarinova ◽  
Mohan Babu
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Missing Values ◽  
Mass Spectrometry Data ◽  
Microbial Pathogens ◽  
Biological Information ◽  
Multidimensional Data ◽  
Learning Approaches ◽  
Host Pathogen ◽  
Temporal And Spatial

Microbial pathogens have evolved numerous mechanisms to hijack host’s systems, thus causing disease. This is mediated by alterations in the combined host-pathogen proteome in time and space. Mass spectrometry-based proteomics approaches have been developed and tailored to map disease progression. The result is complex multidimensional data that pose numerous analytic challenges for downstream interpretation. However, a systematic review of approaches for the downstream analysis of such data has been lacking in the field. In this review, we detail the steps of a typical temporal and spatial analysis, including data pre-processing steps (i.e., quality control, data normalization, the imputation of missing values, and dimensionality reduction), different statistical and machine learning approaches, validation, interpretation, and the extraction of biological information from mass spectrometry data. We also discuss current best practices for these steps based on a collection of independent studies to guide users in selecting the most suitable strategies for their dataset and analysis objectives. Moreover, we also compiled the list of commonly used R software packages for each step of the analysis. These could be easily integrated into one’s analysis pipeline. Furthermore, we guide readers through various analysis steps by applying these workflows to mock and host-pathogen interaction data from public datasets. The workflows presented in this review will serve as an introduction for data analysis novices, while also helping established users update their data analysis pipelines. We conclude the review by discussing future directions and developments in temporal and spatial proteomics and data analysis approaches. Data analysis codes, prepared for this review are available from https://github.com/BabuLab-UofR/TempSpac, where guidelines and sample datasets are also offered for testing purposes.

Rapid Online Buffer Exchange: A Method for Screening of Proteins, Protein Complexes, and Cell Lysates by Native Mass Spectrometry

2019 ◽  
Author(s):  
Zachary VanAernum ◽  
Florian Busch ◽  
Benjamin J. Jones ◽  
Mengxuan Jia ◽  
Zibo Chen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Speed ◽  
Structural Information ◽  
Protein Complexes ◽  
High Sensitivity ◽  
Native Mass Spectrometry ◽  
Structural Features ◽  
Consumer Products ◽  
Cell Lysates ◽  
Protein Expression And Purification

It is important to assess the identity and purity of proteins and protein complexes during and after protein purification to ensure that samples are of sufficient quality for further biochemical and structural characterization, as well as for use in consumer products, chemical processes, and therapeutics. Native mass spectrometry (nMS) has become an important tool in protein analysis due to its ability to retain non-covalent interactions during measurements, making it possible to obtain protein structural information with high sensitivity and at high speed. Interferences from the presence of non-volatiles are typically alleviated by offline buffer exchange, which is timeconsuming and difficult to automate. We provide a protocol for rapid online buffer exchange (OBE) nMS to directly screen structural features of pre-purified proteins, protein complexes, or clarified cell lysates. Information obtained by OBE nMS can be used for fast (<5 min) quality control and can further guide protein expression and purification optimization.

Mass Spectrometry for Proteomics and Recent Developments in ESI, MALDI and other Ionization Methodologies

2019 ◽  
Vol 16 (4) ◽  
pp. 267-276
Author(s):  
Qurat ul Ain Farooq ◽  
Noor ul Haq ◽  
Abdul Aziz ◽  
Sara Aimen ◽  
Muhammad Inam ul Haq
Keyword(s):  
Mass Spectrometry ◽  
Electrospray Ionization ◽  
New Technologies ◽  
Protein Complexes ◽  
Imaging Techniques ◽  
Desorption Electrospray Ionization ◽  
High Throughput Analysis ◽  
Enhanced Sensitivity ◽  
Recent Developments ◽  
The Way

Background: Mass spectrometry is a tool used in analytical chemistry to identify components in a chemical compound and it is of tremendous importance in the field of biology for high throughput analysis of biomolecules, among which protein is of great interest. Objective: Advancement in proteomics based on mass spectrometry has led the way to quantify multiple protein complexes, and proteins interactions with DNA/RNA or other chemical compounds which is a breakthrough in the field of bioinformatics. Methods: Many new technologies have been introduced in electrospray ionization (ESI) and Matrixassisted Laser Desorption/Ionization (MALDI) techniques which have enhanced sensitivity, resolution and many other key features for the characterization of proteins. Results: The advent of ambient mass spectrometry and its different versions like Desorption Electrospray Ionization (DESI), DART and ELDI has brought a huge revolution in proteomics research. Different imaging techniques are also introduced in MS to map proteins and other significant biomolecules. These drastic developments have paved the way to analyze large proteins of >200kDa easily. Conclusion: Here, we discuss the recent advancement in mass spectrometry, which is of great importance and it could lead us to further deep analysis of the molecules from different perspectives and further advancement in these techniques will enable us to find better ways for prediction of molecules and their behavioral properties.

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