Proteomics and Omics Techniques Overview
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Questions and Answers

What is meant by the term 'proteoform'?

  • The general structure of all proteins
  • A specific type of protein variant
  • The diversity of protein variants (correct)
  • A type of protein modification

    • There are approximately 20,000 protein variants in the human genome.

    False

    Name one method used to measure protein levels.

    Mass spectrometry

    A mass spectrometer operates in a ______ environment.

    <p>vacuum</p> Signup and view all the answers

    Match the following mass spectrometry components with their functions:

    <p>Ionization Source = Converts samples into gas phase ions Analyzer = Sorts ions based on their mass-to-charge ratio Detector = Measures the intensity of ionized samples Mass Spectrum = Represents the distribution of ions</p> Signup and view all the answers

    What is the main purpose of omics techniques in the context of biopharmaceuticals?

    <p>To identify molecular targets for biologics development</p> Signup and view all the answers

    Proteomics focuses solely on the DNA sequences of organisms.

    <p>False</p> Signup and view all the answers

    What are the four main types of omics techniques mentioned?

    <p>Genomics, Transcriptomics, Proteomics, Metabolomics</p> Signup and view all the answers

    The study of the set of proteins being expressed at a given time is known as ______.

    <p>Proteomics</p> Signup and view all the answers

    Match the following omics types with their definitions:

    <p>Genomics = Study of genes in chromosomes Transcriptomics = Study of mRNA molecules expressed Proteomics = Study of proteins and their modifications Metabolomics = Study of small molecules in biological samples</p> Signup and view all the answers

    Which of the following techniques is NOT associated with proteomics?

    <p>RNA-sequencing</p> Signup and view all the answers

    Metabolomics provides insights into the genomic structure of organisms.

    <p>False</p> Signup and view all the answers

    Name one application of omics in personalized medicine.

    <p>Target discovery for specific patient treatments</p> Signup and view all the answers

    What is the primary purpose of overlapping reads in next-generation sequencing?

    <p>To form contigs and assemble fragmented sequences</p> Signup and view all the answers

    Third-generation sequencing provides shorter reads compared to second-generation sequencing.

    <p>False</p> Signup and view all the answers

    What does WGS stand for in the context of NGS applications?

    <p>Whole-genome sequencing</p> Signup and view all the answers

    In transcriptomics, techniques like _____ and RNA-Seq are used to study an organism's whole transcriptome.

    <p>DNA microarrays</p> Signup and view all the answers

    Match the following NGS applications with their descriptions:

    <p>WGS = Sequencing of the entire genome WES = Focusing on the coding regions of the genome GWAS = Associating genotype with phenotype using large cohorts RNA-Seq = Analyzing the expressed RNA in a sample</p> Signup and view all the answers

    Which of the following describes a benefit of third-generation sequencing?

    <p>It can map reads in difficult genomic regions effectively.</p> Signup and view all the answers

    Single-cell transcriptomics allows for the study of transcription at the level of individual cells.

    <p>True</p> Signup and view all the answers

    What type of variations might be investigated in genomics related to cancer?

    <p>Copy number variations</p> Signup and view all the answers

    What method is primarily used in proteomic workflows to analyze peptide fragments?

    <p>Tandem Mass Spectrometry</p> Signup and view all the answers

    The MS/MS method produces peptide fragmentation without requiring prior ionization.

    <p>False</p> Signup and view all the answers

    What is a major challenge in absolute quantification of peptides?

    <p>Peptides have different ionization and fragmentation properties</p> Signup and view all the answers

    Relative quantification is less complicated than absolute quantification.

    <p>True</p> Signup and view all the answers

    What is the first step in a typical bottom-up mass spectrometry proteomics workflow?

    <p>Digestion</p> Signup and view all the answers

    What is the role of chemical labeling in quantitative proteomics?

    <p>Enables the study of multiple samples in one LC-MS/MS run.</p> Signup and view all the answers

    In mass spectrometry, the measurement of ions is referred to as ______.

    <p>m/z</p> Signup and view all the answers

    Match the following steps with their corresponding descriptions in the mass spectrometry workflow:

    <p>Digestion = Breaking down proteins into peptides Ionization = Converting peptides into ions Isolation = Selecting specific peptide ions Fragmentation = Breaking peptide ions into smaller fragments</p> Signup and view all the answers

    The technique that helps identify disease subgroups for personalized treatment is called _____ data.

    <p>expression</p> Signup and view all the answers

    Which of the following benefits is associated with studying the secretome?

    <p>Identifying potential drug targets</p> Signup and view all the answers

    Which of the following is NOT a type of ion discussed in peptide fragmentation?

    <p>Stability ions</p> Signup and view all the answers

    Trypsin cleavage pattern known helps to simplify the search space in MS/MS.

    <p>True</p> Signup and view all the answers

    Match the following omics application with its purpose:

    <p>Proteomics = Identifying biomarkers for diseases Transcriptomics = Understanding gene expression Pharmacogenomics = Stratifying patient treatment responses Epigenomics = Studying modifications that affect gene expression</p> Signup and view all the answers

    What complicates the mapping of peptides to proteins and further to genes?

    <p>Ambiguities in identification</p> Signup and view all the answers

    What is the purpose of calculating the false discovery rate in large scale experiments?

    <p>To assess the reliability of results</p> Signup and view all the answers

    In mass spectrometry, the method used to score peptide candidates is based on probabilistic ______.

    <p>assumptions</p> Signup and view all the answers

    How can omics contribute to precision medicine?

    <p>By identifying relevant biomarkers and stratifying diseases.</p> Signup and view all the answers

    Which Nobel Prize was awarded to Fenn in 2002?

    <p>Nobel Prize in Chemistry</p> Signup and view all the answers

    What is the primary purpose of gene expression profiling in breast cancer?

    <p>To identify intrinsic subtypes</p> Signup and view all the answers

    The PAM50 classification utilizes a gene panel of 25 genes to identify intrinsic subtypes of breast cancer.

    <p>False</p> Signup and view all the answers

    What analytical challenge does mass spectrometry-based proteomics face?

    <p>Dynamic range problem</p> Signup and view all the answers

    The commercial test used for the PAM50 classification is called __________.

    <p>Prosigna</p> Signup and view all the answers

    Match the following technologies with their description:

    <p>Somascan technology = Aptamer-based quantification Olink technology = Antibody+sequence-based quantification Mass Spectrometry = Protein measurement Dynamic Range Problem = Analytical limitations of protein detection</p> Signup and view all the answers

    What is a potential outcome of utilizing PAM50 classification?

    <p>Guidance in treatment decisions</p> Signup and view all the answers

    Current instruments can measure up to 12,000 proteins in a single cell or tissue sample within 24 hours.

    <p>True</p> Signup and view all the answers

    What is one of the limitations mentioned regarding measuring proteins in serum or plasma samples?

    <p>Dynamic range</p> Signup and view all the answers

    Study Notes

    Biopharmaceuticals (2024) - Omics Techniques for Target Identification and Biologics Development

    • Omics techniques are used for target discovery, including genomics, transcriptomics, proteomics, and metabolomics.
    • Comprehensive analysis of omics data is crucial for identifying targets for personalized medicine.
    • Proteomics focuses on proteins and their applications.
    • Omics techniques offer a powerful approach to target identification and biologics development.
    • Learning objectives include understanding how omics assists in identifying suitable targets and developing biologics, conceptual understanding of omics techniques, and the concepts of personalized medicine.

    Omics - Studies of the Entire Collection of a Type of Molecules

    • Genomics studies the entire set of genes in chromosomes.
    • Transcriptomics studies the mRNA molecules expressed at a given time under specified conditions.
    • Proteomics studies the proteins expressed at a given time under specified conditions and their modifications.
    • Metabolomics studies the small molecules at a given time under specified conditions.
    • The central dogma of biology describes the flow of biological information, starting from DNA to RNA to protein, and then how metabolism is driven and altered.

    OMICS Glossary

    • Genomics: The study of the collection of genes in the chromosomes.
    • Transcriptomics: The study of the collection of mRNA molecules expressed at a given time and under certain conditions.
    • Proteomics: The study of the collection of proteins expressed, including their modifications, at a specific time and given conditions.
    • Metabolomics: The study of the collection of small molecules at a specific time and given conditions.
    • Phenotype is a composite of observable characteristics of an organism.

    Omics for Target Identification (Target Selection)

    • Discover molecular differences between healthy and diseased states using patient samples, like biopsies or cell lines.
    • Compare samples to isolate differences between disease and normal populations.
    • Identify causative differences to pinpoint suitable targets for treatment.

    Some Techniques for Omics

    • Genomics: Whole-genome sequencing, exome sequencing, chip-based variant detection.
    • Transcriptomics: RNA sequencing, cDNA microarrays, single-cell sequencing.
    • Proteomics: Mass spectrometry, affinity-based proteomics.
    • Metabolomics: Mass spectrometry, NMR.
    • Epigenetics: NGS or microarrays.
    • Spatial omics: Imaging and NGS.

    NGS - Massively Parallel Sequencing

    • The cost of sequencing a full human genome has significantly decreased over time, particularly for the NGS technology.
    • NGS technologies are pivotal for diverse applications in biology.

    Sequencing: How Does It Work?

    • Sanger sequencing and next-generation sequencing (NGS) are crucial for analyzing genetic material.
    • NGS processes involve shearing genomic DNA, ligation of adaptors, and chain termination PCR using fluorescently labeled nucleotides. This allows for sequencing DNA and measuring its quantity.

    Brief about the Bioinformatics Workflow for NGS Data

    • Paired-end reads of next-generation sequencing data are mapped to a reference genome.
    • Overlapping reads form contigs. Contigs and gaps of known length form scaffolds.
    • Sequencing data analysis steps are critical for extracting usable information.

    Third-Generation Sequencing (Long-Read Sequencing)

    • Generates longer reads compared to second-generation sequencing.
    • Utilizes various techniques, like PacBio and Oxford Nanopore technologies.
    • Useful for mapping reads, especially in regions with complex structures like repeats, facilitating the comprehensive analysis of isoform determination and gene expression.

    NGS Applications in Human Health

    • Genomics and transcriptomics data are leveraged in disease diagnostics.
    • Epigenomics and metabolomics data are essential in understanding the metabolic pathways concerning diseases.
    • Bioinformatics, the data analysis process, is necessary to understand the results of using NGS for specific biological questions.

    Genomics

    • Find genome variations which could potentially cause disease.
    • Point mutations, indels, and copy number variations are assessed, particularly in cancers.
    • Genome-wide association studies (GWAS) seek associations between genotypes and phenotypes, requiring large cohorts for statistical power.

    Transcriptomics

    • Study of genes being expressed at a given time.
    • Assess the genes being expressed, essential for discovering the mechanism of the expression alterations.

    Transcriptomics Technologies

    • Include both DNA microarrays and next-generation sequencing technologies, known as RNA-Seq.
    • Single-cell transcriptomics (ScRNASeq) studies gene expression at the individual cell level.
    • Spatial transcriptomics combines imaging techniques with transcript readouts using probes or NGS technologies, enabling researchers to pinpoint cell types with unique gene expression signatures.

    RNA-Sequencing vs Microarrays

    • RNA-Seq is a next-generation sequencing-based approach, measuring gene expression using sequences.
    • Microarrays are based on hybridization of fluorescently labelled probes to the genomic template, measuring gene expression using fluorescence intensity.
    • RNA-Seq is often preferred for its sequence resolution.

    Data Processing of Analysis for Target Discovery using RNA-Sequencing

    • Quality Control (QC), such as filtering out low-quality reads, is essential.
    • Alignment, and matrix generation using counts.
    • Quality control checks at sample and gene levels.
    • Statistical analysis is crucial.
    • System biology and enrichment analysis are used to further interpret findings and interpret the biological meanings associated with it.

    QC: PCA analyses for Sample QC and QC: Gene Level Filtering

    • Principal Component Analysis (PCA) and gene dispersion estimates are helpful in quality control.
    • Reduced experimental noise for biologically relevant variations.

    Data Normalisation

    • Normalisation techniques (like global LOESS normalisation) are used to account for the differences in sample amounts and other variations impacting the accuracy of the results.

    Between Sample Normalisation and Global LOESS Normalisation

    • Statistical tests are essential in identifying and analyzing the differences between sample groups, adjusting for multiple tests in the analysis.

    Differential Expression Analyses

    • Analyze and find differences between conditions (like disease and control) in the sample's gene expression.
    • Assess gene abundance by analyzing, for example, fluorescence in microarrays and read counts in sequencing.
    • Categorize these genes into upregulated or downregulated (based on condition comparison) to find genes with altered expression between conditions.

    Gene Expression, Variations and Conditions

    • Gene expressions vary across tissues and conditions to provide nuanced insights.
    • The expression profile of a condition, like specific tissues, correlates with the specific interactions.

    Network Analyses and Systems Biology

    • Genes and proteins do not function alone, but contribute to dynamic networks and pathways and the influence of specific co-regulators in these changes.
    • Networks' representations of complex systems help researchers understand and visualize the global patterns in omics data.

    Pathway Analyses, Visualization for Interpretation

    • Analyze pathways for detailed interpretations using integrative knowledge.
    • Integrate omics information, like gene expression data.
    • Visualizations, like heatmaps and other graphics, are important aids in interpretation and understanding the results of using omics.

    Gene Set Enrichment Analyses

    • Statistical methods analyze altered expression levels of genes to identify related pathways.
    • Apply tools like gene set enrichment analysis (GSEA) to find pathways or groups of altered genes to find relevant hubs.

    Network Analyses for Signatures

    • Multilayered omics signatures, combining genomics, transcriptomics, proteomics, and metabolomics, provide insights into individual variations, molecular mechanisms, and disease classification.
    • Network analyses provide rich biological information and further insights in understanding complex biological systems.

    Genome Scale Models for Organisms and Tissue Metabolism

    • Creating models to study organismal and tissue metabolic processes requires comprehensive data.
    • Topology-based analyses use computational methods to interpret network interactions.

    Topological Analyses of Networks

    • Incorporating various omics datasets to discover metabolic pathways, enzyme interactions, and identify key metabolites.
    • Gain biological context and identify important regulatory components, providing insights that are challenging to achieve using other techniques.

    Things to Consider

    • Assess the reproducibility and repeatability of results obtained from omics studies with different samples.
    • Batch effects or randomizations could affect the reproducibility of results.
    • Validation strategies can be used to demonstrate biological meaning.

    Proteomics

    • Proteomics is closer to the phenotype than genomics or transcriptomics, and explores protein function as well as modifications.

    Why Bother?

    • RNA sequencing may not suffice for understanding protein function, localization, interactions, or modifications..

    Omics and Complexity

    • Omics data reflects the complexity of biological processes incorporating gene expression, processing, translations, protein synthesis, protein modifications, interactions and phenotypes.

    Challenges

    • The vast diversity of proteins and post-translational modifications, requiring extensive consideration of dynamic range.

    How to Measure Protein Levels?

    • Mass spectrometry analyzes protein levels based on interactions and protein quantity among others.
    • Affinity reagents and antibodies are also used for protein quantification.

    Basic Principles of Mass Spectrometry

    • Sample ionization, ion sorting, and ion detection are integral parts.
    • Mass spectrometry uses principles of gas-phase ion formation and measurements to understand samples (like peptides, proteins).

    A Typical (Bottom-up) Mass Spectrometry Proteomic Workflow

    • Samples are processed for digestion, followed by peptide separation (HPLC), fragmentation (MS/MS), peptide identification, and quantification.
    • Bioinformatic analysis to interpret the results.

    MS/MS Peptide Fragmentation

    • This describes the process of breaking down peptides into smaller constituents.
    • Techniques like mass spectrometry are used for sequencing by analyzing the peptide fragments using the MS/MS analysis.

    MS/MS of Peptide

    • This involves the tandem mass spectrometry (MS/MS) and the analysis of data using appropriate software for interpretation.

    Search Space Decreased as Trypsin Cleavage Pattern is Known

    • Pattern identification of trypsin cleavage to streamline the search of datasets.
    • Using known patterns, search space is reduced and analysis is improved.

    Match Scoring

    • Scoring of peptide candidates for matching against identified fragments is essential to reduce the search space.

    Quantification

    • Peak intensities provide relative protein levels across samples.
    • Absolute peptide levels are more challenging to derive using traditional techniques because peptides have different ionization and fragmentation properties, influencing the spectrum.

    What to Do with Quantitative Proteomics Data

    • Differential abundance comparison between sample groups.
    • Data mapping to existing pathways and other findings.
    • Challenges in peptide mapping and the role of post-translational modifications.

    Benefits

    • Relevant proteome sub-components can be studied further for drug development, including secreted proteins, cell surface proteins, and the phosphoproteome in signaling.

    Omics and Precision Medicine

    • Some diseases are heterogeneous, and people respond to treatment differently.
    • Omics approaches aid in stratifying diseases and patients, enabling precision medicine and personalized treatments tailored to each patient's needs and risk factors.

    Subclassification of Disease Using Expression Data

    • Cancer heterogeneity.
    • Subgroups response variably to treatment.
    • Understanding gene expression provides tools for new cancer classification and personalized treatment options.

    Breast Cancer Example

    • Gene expression profiling is used to classify breast cancer into subtypes.
    • PAM50 classification uses a specific gene panel for subtype identification. - Clinical implications of these subtypes aid in treatment decisions, especially targeted therapies.

    Unsupervised Clustering of Tumor Biopsies

    • Unsupervised learning algorithms cluster tumor samples based on PAM50 proteins and mRNA expression data.
    • Provides insights into cancer heterogeneity.

    Dynamic Range Problem

    • The wide range in protein concentrations presents a challenge for mass spectrometry-based proteomics.

    Reference Intervals for Protein Analytes in Plasma

    • Showing the different ranges of plasma proteins under normal and diseased conditions highlighting the challenge of this research area.

    Sample Fractionation and New Instruments Help

    • Sample separation may be crucial for detecting additional proteins and improving quantification outcomes because many proteins have different concentrations.

    Some Current Figures

    • Current techniques for measuring proteins in large-scale biological samples.

    Affinity Binder-based Quantification

    • The application of affinity binders for protein quantification.

    Recent UK Biobank Example

    • Data regarding quantitative proteomic analysis conducted on the UK Biobank.
    • Biobank's role in providing a substantial resource for investigating the association of proteins with genetics and health.

    Pan-Cancer Plasma Proteomics

    • Applying next-generation techniques to analyze proteome signatures in blood samples.
    • Enabling a holistic understanding of the multifaceted roles of proteins.

    Interaction Proteomics

    • Interaction proteomics is a technique that elucidates the complex interactions between proteins, allowing the in depth analysis of disease mechanisms and the use of these data for drug repurposing and the discovery of novel drug targets.

    Interaction Proteomics – SARS-CoV-2 Example

    • A specific case study, illustrating the use of interaction proteomics for identifying drug targets for repurposing in a viral infection, highlighting the usefulness for discovery of drug targets, and validation in multiple assay systems.

    Metabolomics

    • Metabolomics techniques explore and quantify metabolites to uncover metabolic interactions and complex biological processes.

    Target Discovery Followed by Biologics Development

    • Target identification is followed by the development of biologics to address the identified targets, while considering various factors, and examining potential side effects.

    Summary

    • Omics techniques provide detailed molecular information about differences between healthy and sick states, and further subtypes.
    • Data analysis and complex network analyses are important.
    • The choice of techniques and availability of samples play roles in choosing strategies.
    • Large multi-omics studies can advance precision medicine, and offer opportunities for improvement in medical approaches to diseases.

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    Kimn10 Omics 2024 (PDF)

    Description

    Test your knowledge on proteomics and various omics techniques related to biopharmaceuticals. This quiz covers definitions, methods, and applications relevant to the study of proteins and their variants. Understand key concepts and improve your grasp of modern biological sciences.

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