Proteomics in Systems Biology: Methods and Protocols (Methods in Molecular Biology, 2456)

✍ Scribed by Jennifer Geddes-McAlister (editor)

• Publisher: Humana
• Year: 2022
• Tongue: English
• Leaves: 372
• Category: Library

✦ Synopsis

This detailed book highlights the diverse techniques and applications of proteomics in an accessible, informative, and concise manner. The collection features sample preparation from distinct extraction, quantification, enrichment, modification, as well as interactome methodology for the in-depth exploration of biological systems, and the application of proteomics to clinical, infectious disease, and agricultural practices. Moreover, cutting-edge bioinformatics tools, encompassing machine learning and data integration strategies, are explored, as are techniques expanding beyond proteomics into the realm of metabolomics. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting known pitfalls.
Comprehensive and practical, Proteomics in Systems Biology:Methods and Protocols emphasizes the importance of proteomics and demonstrates a plethora of approaches for investigating diverse biological entities from a systems perspective.

✦ Table of Contents

Preface
Contents
Contributors
Chapter 1: Review of the Real and Sometimes Hidden Costs in Proteomics Experimental Workflows
1 Introduction
2 Quality Assurance of Samples
2.1 Sample Selection, Collection, and Storage
2.2 Ensuring High-Quality Samples to Begin with
2.3 How Much Data Is Really Needed?
3 Nanoflow LC-The Costly Achilles´ Heel of Proteomics
4 Balancing Replication vs. Fractionation
5 Costs of Quantitation
6 Conclusions
References
Chapter 2: High-Throughput Mass Spectrometry-Based Proteomics with dia-PASEF
1 Introduction
2 Materials
2.1 Samples
2.2 Liquid Chromatography
2.3 Mass Spectrometry
2.4 Data Analysis
3 Methods
3.1 Instrument Setup and Ion Mobility Calibration
3.2 Setting up a dia-PASEF Acquisition Method
3.3 Setting up an LC-MS Acquisition Method
3.4 Acquire a Sequence of dia-PASEF Experiments
3.5 Data Processing and Expected Results
4 Notes
References
Chapter 3: Isolation of Detergent Insoluble Proteins from Mouse Brain Tissue for Quantitative Analysis Using Data Independent ...
1 Introduction
2 Materials
2.1 Tissue Lysis
2.2 Centrifugation
2.3 Trypsin Digestion of Proteins
2.4 Stage Tips
2.5 Fractionation of Peptide Library
2.6 DDA Library Generation
2.7 DIA Mass Spec
2.8 Data Analysis
3 Methods
3.1 Tissue Lysis
3.2 Centrifugation and Protein Concentration Measurement
3.3 Protein Digestion and Peptide Elution
3.4 Stage Tipping
3.4.1 Prepare Stage Tips
3.4.2 Conditioning of Stage Tips
3.4.3 Stage Tipping of Samples
3.5 Library Generation
3.6 Mass Spectrometry Analysis of Library Using Data Dependent Acquisition (DDA)
3.7 Mass Spectrometry Analysis of Samples (Data Independent Acquisition, DIA)
3.8 Spectral Library Generation
3.9 Data Analysis of DIA Samples
3.10 directDIA Analysis
3.11 Analysis of Pooled Standards
3.12 Results: Reproducibly of DIA Workflow
4 Notes
References
Chapter 4: Rodent Lung Tissue Sample Preparation and Processing for Shotgun Proteomics
1 Introduction
2 Materials
2.1 Tissue Homogenization and Protein Extraction
2.2 Total Protein Quantitation
2.3 SDS-PAGE
2.4 Protein Reduction and Alkylation
2.5 Protein Clean Up Using Single-Pot, Solid-Phase-Enhanced Sample Preparation (SP3)
2.6 Trypsin Digestion
2.7 Peptide Clean Up
2.8 Instruments
3 Methods
3.1 Tissue Homogenization
3.2 Protein Quantification
3.3 Quality Assessment
3.4 Sample Preparation for MS
3.4.1 To Prepare Protein Lysate for SP3 Protein Clean Up
3.4.2 To Prepare SP3 Beads
3.4.3 Perform Protein Clean Up
3.4.4 Trypsin Digestion
3.4.5 Peptide Desalting (See Note 5)
3.5 Running Samples on LC-MS/MS
3.5.1 Preparation Prior to LC-MS Analysis
3.5.2 Determine Peptide Concentration Using NanoDrop Spectrophotometer
4 Notes
References
Chapter 5: Protein Purification and Digestion Methods for Bacterial Proteomic Analyses
1 Introduction
2 Materials
2.1 Bacterial Cell Lysis
2.2 Protein Purification and Solubilization
2.2.1 Acetone Precipitation
2.2.2 TRIzol-Based Protein Extraction
2.3 Protein Reduction, Alkylation, and Digestion
2.3.1 In-solution Digestion
2.3.2 On-filter Digestion
3 Methods
3.1 Cell Harvest, Lysis and Acetone Precipitation and Solubilization (SDS or SDC)
3.2 Cell Harvest, Lysis and TRIzol-Based Extraction and Solubilization with SDS
3.3 In-solution Digestion (SDC)
3.4 Filter-Aided Desalting and Digest
4 Notes
References
Chapter 6: Mapping Cell Surface Proteolysis with Plasma Membrane-Targeted Subtiligase
1 Introduction
2 Materials
2.1 Cell Culture and Cell Line Construction
2.2 Subtiligase Cell Labeling
2.3 Fluorescence Imaging
2.4 Cell Harvest and Cell Lysis
2.5 N-Terminal Peptide Enrichment
2.6 Peptide Desalting
2.7 LC-MS/MS Analysis
3 Methods
3.1 Lentivirus Production
3.2 Lentivirus Infection of HEK293T Cells
3.3 Fluorescence Imaging to Validate Subtiligase-TM Expression and Activity
3.4 Cell Harvest
3.5 Subtiligase-TM Labeling
3.6 Cell Lysis
3.7 Biotinylated Protein Enrichment
3.8 Reduction, Alkylation, and Trypsin Digestion
3.9 TEV Protease Elution of N-Terminal Peptides
3.10 Sample Desalting
3.11 LC-MS/MS and Data Analysis
4 Notes
References
Chapter 7: N-Terminomics/TAILS of Tissue and Liquid Biopsies
1 Introduction
2 Materials
3 Methods
3.1 Tissue Homogenization
3.2 Pre-Enrichment TAILS and TAILS
3.2.1 Protein Preparation, Denaturation, Alkylation, and Amine Labeling
3.2.2 Protein Precipitation and Trypsinization
3.2.3 PreTAILS Fraction and Polymer Selection
3.2.4 TAILS Fraction and Filtration
3.3 Alternative Labeling Option for Analysis of More than 2 Conditions: Tandem Mass Tag (TMT) Labeling (or iTRAQ)
4 Notes
References
Chapter 8: HUNTER: Sensitive Automated Characterization of Proteolytic Systems by N Termini Enrichment from Microscale Specimen
1 Introduction
2 Materials
3 Methods
3.1 Sample Preparation
3.1.1 Sample Lysis
3.1.2 Protein Reduction and Alkylation
3.2 SP3 Bead Binding and Proteome Clean up
3.2.1 Prepare SP3 Beads
3.2.2 Binding and Clean up
3.3 Protein Dimethyl Labeling
3.3.1 Initiate Labeling Reaction
3.3.2 Quench Labeling Reaction
3.4 Protein Digestion
3.5 Undecanal-Based Enrichment of Protein N Termini
3.5.1 Undecanal Labeling
3.5.2 Peptide Clean up / Removal of Excess Undecanal
3.5.3 Sample Desalting (Second C18 Clean up)
3.6 Automated HUNTER (for Plasma Sample)
3.6.1 Sample Preparation
3.6.2 SP3 Bead Particles Preparation
3.6.3 Determine the Amount of Ethanol for Sample Binding
3.6.4 Determine the Working Stock Concentration of Dimethyl Labeling Reagents
3.6.5 Determine the Amount of Undecanal Labeling Reagents
3.6.6 Set up Application Workflow
3.6.7 Application a: Day 1 Part 1
3.6.8 Application B: Day 1 Part 2
3.6.9 Application C: Day 2
3.7 Offline High pH Fractionation (Optional)
3.8 Mass Spectrometry Analysis by DDA and DIA
3.8.1 Concatenated Samples
3.8.2 Individual Samples
3.8.3 Instrumentation Setup
3.9 Data Processing and Statistical Analysis
3.9.1 DDA Data on Individual Samples
3.9.2 Sample Spectral Library Generation
3.9.3 DIA Data on Samples
3.9.4 Data Analysis for DDA and DIA
4 Notes
References
Chapter 9: Phosphoproteomics and Organelle Proteomics in Pancreatic Islets
1 Introduction
2 Materials
2.1 Islet Isolation
2.2 Total Proteome and Phosphoproteome Sample Preparation
2.3 Organelle Fractionation
2.4 Equipment
3 Methods
3.1 Islet Isolation
3.2 Phosphoproteome Sample Preparation
3.3 Organelle Fractionation
3.3.1 Preparation of Gradient Tubes
3.3.2 Lysis of Islets
3.3.3 Ultracentrifugation and Collection of Gradient Samples
3.3.4 Protein Precipitation and Total Proteome Sample Preparation
3.3.5 Stage Tip Preparation
StageTip activation
3.3.6 Sample Load and in StageTip Wash
3.3.7 Elution of Peptides from StageTip Membrane
3.3.8 Bioinformatic Analysis of PCP Data
Identification of Separable Compartments and Organelle Markers
Support Vector Machines (SVM)-Based Assignment of the Main Organelle
Assignment of a Secondary Organellar Localization by Correlation Analysis
4 Notes
References
Chapter 10: Phosphoproteomic Sample Preparation for Global Phosphorylation Profiling of a Fungal Pathogen
1 Introduction
2 Materials
2.1 Culturing of C. neoformans
2.2 Proteome Analysis
3 Methods
3.1 Growth of C. neoformans
3.2 Protein Extraction from C. neoformans
3.3 Phosphoenrichment for MS Analysis
3.4 Peptide Purification
3.5 Mass Spectrometry and Data Analysis
4 Notes
References
Chapter 11: Glycopeptide-Centric Approaches for the Characterization of Microbial Glycoproteomes
1 Introduction
2 Materials
2.1 Preparation of Proteome Samples
2.2 Hydrophilicity-Based Glycopeptide Enrichment
2.3 Antibody-Based Glycopeptide Enrichment
2.4 Glycopeptide MS Analysis
2.5 Bioinformatic Analysis of Microbial Glycopeptides
3 Methods
3.1 Preparation of Proteome Samples for Glycopeptide Enrichment/Analysis
3.2 Hydrophilicity-Based Glycopeptide Enrichment
3.3 Antibody-Based Glycopeptide Enrichment
3.3.1 Coupling of Antibodies to Protein A/G Beads
3.3.2 Cross-Linking Antibodies to Protein A/G Beads
3.3.3 Antibody-Based Affinity Purification of Glycopeptides
3.4 Glycopeptide MS Analysis
3.5 Bioinformatic Analysis of Microbial Glycopeptides
4 Notes
References
Chapter 12: Integrated Network Discovery Using Multi-Proteomic Data
1 Introduction
2 Multi-P Overview
3 Methods
3.1 Prepare proteinGroup.txt
3.2 Network Enrichment Analysis
3.3 Multi-P & SIV Calculation
References
Chapter 13: Targeted Cross-Linking Mass Spectrometry on Single-Step Affinity Purified Molecular Complexes in the Yeast Sacchar...
1 Introduction
2 Materials
2.1 Titrating the SM(PEG)2 Cross-Linker
2.1.1 Small-Scale ssAP
2.1.2 Two Steps SM(PEG)2 Cross-Linking Titration
2.2 Estimating CH-Tagged Protein Amounts from Isolated Small-Scale ssAP Complexes
2.2.1 Method 1
2.2.2 Method 2
2.3 Large-scale ssAP-anchXL-MS
2.3.1 Large-scale ssAP
2.3.2 SM(PEG)2 Two-Step Reaction
2.3.3 IMAC Enrichment of CH-Tagged Cross-Linked Peptides
2.4 MS Method and Analysis
3 Method
3.1 Starting Amount of Material and ssAP Buffer Optimization
3.2 Titrating the SM(PEG)2 Cross-Linker
3.2.1 Small-scale ssAP
3.2.2 Titrating the SM(PEG)2 Cross-Linker
3.2.3 Estimating CH-Tagged protein Amounts from Isolated Small-scale ssAP Complexes
Method 1
Method 2
3.3 Large-scale ssAP-anchXL-MS
3.3.1 Large-scale ssAP
3.3.2 SM(PEG)2 Controlled Two-Step Reactions
3.3.3 On-Bead Trypsin Digestion of ssAP-anchXL Complexes
3.3.4 IMAC Enrichment of Anchored chXL Peptides
3.3.5 Mass Spectrometry
3.3.6 ssAP-anchXL-MS Data Analysis Using pLink2
4 Notes
References
Chapter 14: A Crosslinking Mass Spectrometry Protocol for the Structural Analysis of Microtubule-Associated Proteins
1 Introduction
2 Materials
2.1 Protein Preparations
2.2 Buffers and Stock Reagents
2.3 Required Equipment
3 Methods
3.1 MT-MAP Preparation and Initial Testing
3.2 Evaluation of the MAP-MT Construct by Fluorescence Microscopy
3.3 Crosslinking of MAP-MT and Preparation for LC-MS
3.4 LC-MS Analysis
3.5 XL-MS Data Analysis
4 Notes
References
Chapter 15: Comprehensive Interactome Mapping of Nuclear Receptors Using Proximity Biotinylation
1 Introduction
2 Materials
2.1 Plasmids and Lentivirus Production
2.2 Lentiviral Transduction
2.3 Construct Validation in Polyclonal Populations and Clonal Isolation
2.4 Cell Induction for TurboID
2.5 TurboID
2.6 Peptide Desalting
3 Methods
3.1 Plasmid and Lentivirus Production
3.2 Lentiviral Transduction
3.3 Construct Validation in a Polyclonal Population and Monoclonal Cell Population Isolation
3.4 MDA-MB-231 Cell Induction for TurboID
3.5 MCF-7 Cell Induction for TurboID
3.6 TurboID
3.7 Peptide Desalting
3.8 MS Data Acquisition
3.9 MS Data Analysis
3.10 MS Data Archiving
4 Notes
References
Chapter 16: Mining Proteomics Datasets to Uncover Functional Pseudogenes
1 Introduction
2 Materials
2.1 Sample Preparation
2.2 PRM/MRM Analysis
3 Methods
3.1 Identification of Pseudogenes
3.1.1 Pseudogene Database Search
3.1.2 Transcription Evidence Search
3.1.3 Translation Verification
3.1.4 Translation Analysis
3.1.5 Protein Expression
3.1.6 Interaction Databases
3.2 Validation of Functional Pseudogenes
3.2.1 Protein Specific Unique Heavy Peptide Design
3.2.2 Optimization of Peptide Detection by MS
3.2.3 Sample Preparation
3.3 Options for Functional Analysis of Identified Pseudogene
4 Notes
References
Chapter 17: Proteomic Profiling of the Interplay Between a Bacterial Pathogen and Host Uncovers Novel Anti-Virulence Strategies
1 Introduction
2 Materials
2.1 Culturing of Klebsiella pneumoniae
2.2 Culturing Macrophages
2.3 Cellular Proteome Analysis
3 Methods
3.1 Culturing K. pneumoniae Cells
3.2 Culturing of Macrophages
3.2.1 Seeding Macrophages
3.2.2 Passaging Macrophages for Co-culture
3.3 Co-culture of Macrophages with K. pneumoniae
3.4 Collection of Cells
3.5 Proteome Extraction
3.6 Mass Spectrometry
3.7 Data Analysis
4 Notes
References
Chapter 18: Affinity Enrichment of Salmonella-Modified Membranes from Murine Macrophages for Proteomic Analyses
1 Introduction
2 Materials
2.1 Basic Equipment for Cell Cultivation, Infection, and Harvest
2.1.1 Cell Culture: Host
2.1.2 Cell Culture: Pathogen Salmonella enterica
2.2 Basic Equipment for Protein Extraction and Affinity Enrichment
2.2.1 Protein Extraction for Affinity Enrichment
2.2.2 Labeling of Protein G Magnetic Beads with M45 Antibody
2.2.3 Affinity Enrichment of Salmonella-Modified Membranes
3 Methods
3.1 RAW264.7 Cell Infection
3.2 Preparation of Protein Fraction for Affinity Enrichment
3.3 Labeling of Magnetic Beads for Affinity Enrichment
3.4 Affinity Enrichment of Salmonella-Modified Membranes (SMM)
4 Notes
References
Chapter 19: Proteomic Profiling of Interplay Between Agrobacterium tumefaciens and Nicotiana benthamiana for Improved Molecula...
1 Introduction
2 Materials
2.1 Plant Material
2.2 Protein Extraction
2.3 Protein Digestion
2.4 Peptide Purification
2.5 TMT Labeling
3 Methods
3.1 Preparing Plant Material
3.2 Protein Extraction
3.3 Protein Digestion
3.4 Peptide Purification
3.5 TMT Labeling
3.6 Mass Spectrometry
3.7 Data Analysis
4 Notes
References
Chapter 20: Label-Free Quantitative Proteomic Profiling of Fusarium Head Blight in Wheat
1 Introduction
2 Materials
2.1 Media for Inoculation
2.2 Inoculation and Harvest
2.3 Total Protein Extraction
2.4 Stop-and-Go Extraction Tips (STAGE-Tip) Desalting
2.5 Liquid Chromatography with Tandem Mass Spectrometry (LC-MS/MS)
2.6 Bioinformatics
3 Methods
3.1 Culturing Fusarium graminearum and Inoculating Triticum aestivum
3.2 Tissue Disruption and Protein Extraction
3.3 Protein Solubilization, Quantification, and Digestion
3.4 Preparing and equilibrating the C18 Stop-and-Go Extraction Tips (STAGE-Tip)
3.5 STAGE-Tip Samples
3.6 LC-MS/MS Analysis
3.7 Proteome Data Analysis
4 Notes
References
Chapter 21: DIA Proteomics and Machine Learning for the Fast Identification of Bacterial Species in Biological Samples
1 Introduction
2 Materials
2.1 Sample Preparation
2.2 High-pH Reversed-Phase High-Pressure Liquid Chromatography
2.3 NanoLC-MS/MS Analysis
2.4 Software
3 Methods
3.1 Spectral Libraries: Sample Preparation
3.2 Spectral Libraries: DDA LC-MS/MS Analysis
3.3 Spectral Libraries: Bioinformatic Treatment
3.4 Training Step: Sample Preparation of Bacterial Inoculates
3.5 Training Step: DIA LC-MS/MS Analysis
3.6 Training Step: DIA Signal Extraction
3.7 Training Step: Machine Learning Model and Signature Identification
3.8 Identification Step: Monitoring of Peptide Signature with PRM
4 Notes
References
Chapter 22: Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies
1 Introduction
2 Peptide and Protein Identification
2.1 Mass Spectrum Acquisition
2.2 Peptide Identification with Database Search
2.3 Protein Sequence Database Choice
2.4 Protein Sequence Database Search
2.5 Spectral Library Search
2.6 Assessment of Peptide-Spectrum Match Quality and False Discovery Rate Estimation
2.7 De Novo Sequencing
3 Peptide and Protein Quantification
3.1 Workflows Combining Identification and Quantification
4 Data Refinement
4.1 Normalization
4.2 Data Imputation
4.3 Data Aggregation
5 Data Mining and Functional Analysis
5.1 Taxonomic Analysis
5.2 Functional Analysis
5.3 Metaproteomics Data Visualization
6 Application: Metaproteomics Analytical Methods in Action with Real-World Data
References
Chapter 23: MaxQuant Module for the Identification of Genomic Variants Propagated into Peptides
1 Introduction
2 Materials
2.1 Data Downloads
2.2 Software
3 Methods
3.1 Variant Extraction
3.2 Variant-Aware MaxQuant Proteomics Search
3.3 Data Analysis
3.3.1 Proteogenomic Analysis of Ultra-deep HeLa Proteome
3.3.2 Immunopeptidomic Analysis of HLA Peptides
4 Notes
References
Chapter 24: Untargeted Metabolomic Profiling of Fungal Species Populations
1 Introduction
1.1 Culturing Methodology
1.2 UPLC-HRMS
1.3 Data Analysis
2 Materials
2.1 Materials for Biological Sample Culturing and Extraction
2.2 Materials for UPLC-HRMS
2.3 Materials for Data Analysis and Mining
3 Methods
3.1 Fermentation
3.2 Solvent Extraction
3.3 UPLC-HRMS Analysis
3.4 Metabolomics Data Preprocessing
3.5 Data Processing (in ``R´´ Environment)
4 Notes
References
Correction to: DIA Proteomics and Machine Learning for the Fast Identification of Bacterial Species in Biological Samples
Index