iTRAQ is a quantitative proteomics technique that uses isobaric tags to label peptides from up to 8 samples for identification and quantification by mass spectrometry. The iTRAQ reagent contains four amine-reactive labels with different reporter masses but the same overall tag mass. Labeled peptides are indistinguishable by mass but produce distinct reporter ions upon fragmentation, allowing relative quantification of proteins across samples. The technique provides advantages over previous methods through multiplexing, precision, and expanded proteome coverage, though errors can arise from variability in sample processing and digestion efficiency.
Mass Spectrometry-Based Proteomics Quantification: iTRAQ Creative Proteomics
For more information, please visit: https://www.creative-proteomics.com/services/itraq-based-proteomics-analysis.htm
iTRAQ (isobaric tag for relative and absolute quantitation), is an isobaric labeling method to determine the amount of proteins from different sources in just one single experiment by mass spectrometry, which was developed by Applied Biosystems Incorporation in 2004.
iTRAQ technology utilizes isobaric reagents to label the primary amines of peptides and proteins. The iTRAQ reagents usually consist of an N-methyl piperazine reporter group, a balance group, and an N-hydroxy succinimide ester group that is reactive with the primary amines of peptides.
https://www.creative-proteomics.com/services/itraq-based-proteomics-analysis.htm
Mass Spectrometry-Based Proteomics Quantification: iTRAQ Creative Proteomics
For more information, please visit: https://www.creative-proteomics.com/services/itraq-based-proteomics-analysis.htm
iTRAQ (isobaric tag for relative and absolute quantitation), is an isobaric labeling method to determine the amount of proteins from different sources in just one single experiment by mass spectrometry, which was developed by Applied Biosystems Incorporation in 2004.
iTRAQ technology utilizes isobaric reagents to label the primary amines of peptides and proteins. The iTRAQ reagents usually consist of an N-methyl piperazine reporter group, a balance group, and an N-hydroxy succinimide ester group that is reactive with the primary amines of peptides.
https://www.creative-proteomics.com/services/itraq-based-proteomics-analysis.htm
Protein qualitative analysis based on mass spectrometry explores protein expression within organisms. Mass spectrometry offers highly efficient, robust, and accurate results and is one of the core technologies for proteomic research. Protein identification is a common topic for biochemistry research, and mass spectrometry is considered one of the most useful techniques that solve this issue. Two major strategies that are widely used for protein identification by mass spectrometry are MALDI-TOF-based protein fingerprinting and LC-MS/MS-based peptide sequencing. Meanwhile, LC-MS/MS reserved higher sensitivity and ability than MALDl-TOF and can accurately identify multiple protein components from a single sample. https://www.creative-proteomics.com/services/protein-identification.htm
protein microarray_k.b institute (m.pharm pharmacology) .pptxNittalVekaria
1: Introduction
Welcome to our presentation on Protein Microarrays.
Discover the revolutionary technology transforming protein analysis and biomolecular research
2: What are Protein Microarrays?
Protein microarrays are high-throughput platforms for studying protein-protein interactions, protein function, and biomarker discovery.
They consist of thousands of immobilized proteins on a solid surface, allowing for simultaneous analysis of multiple proteins.
3Components of Protein Microarrays
Substrate: Glass slides, membranes, or beads.
Proteins: Target proteins immobilized on the substrate.
Detection System: Fluorescent dyes, antibodies, or other probes.
Imaging System: Scanners or cameras for data acquisition.
4: Types of Protein Microarrays
Analytical Microarrays: Used for studying protein-protein interactions, protein expression profiling, and protein function analysis.
Antibody Microarrays: Utilized for detecting and quantifying specific proteins or antibodies in biological samples.
Reverse-Phase Protein Arrays (RPPAs): Designed for high-throughput protein expression profiling and signaling pathway analysis.
5:Applications of Protein Microarrays
Biomarker Discovery: Identification of disease-specific biomarkers for diagnosis, prognosis, and treatment monitoring.
Drug Discovery: High-throughput screening of drug candidates and target validation.
Functional Proteomics: Mapping protein-protein interactions, post-translational modifications, and protein function analysis.
Clinical Diagnostics: Detection of infectious diseases, cancer biomarkers, and autoimmune disorders.
6: Workflow of Protein Microarray Experiment
Protein immobilization: Spotting or printing target proteins onto the microarray substrate.
Sample incubation: Incubating the microarray with biological samples containing proteins of interest.
Detection and analysis: Using fluorescent probes or antibodies to detect bound proteins and quantifying the signals.
Data interpretation: Analyzing and interpreting the results to extract meaningful biological insights.
7: Advantages of Protein Microarrays
-High-throughput analysis of thousands of proteins in parallel.
Small sample volume requirement.
Enables multiplexed assays for comprehensive protein profiling.
Facilitates rapid biomarker discovery and validation.
8: Challenges and Considerations
Standardization of protocols and reagents.
Optimization of protein immobilization and detection methods.
Data analysis and interpretation complexities.
Cost and accessibility of microarray platforms.
9: Future Perspectives
Integration with other omics technologies for holistic biological insights.
Development of miniaturized and portable microarray platforms for point-of-care diagnostics.
Advancements in data analysis algorithms and bioinformatics tools.
Expanding applications in personalized medicine and precision healthcare
10: Conclusion
Protein microarrays offer a powerful and versatile tool for protein analysis and biomarker discover
protein microarray_k.b institute (m.pharm pharmacology) .pptxNittalVekaria
1: Introduction
Welcome to our presentation on Protein Microarrays.
Discover the revolutionary technology transforming protein analysis and biomolecular research
2: What are Protein Microarrays?
Protein microarrays are high-throughput platforms for studying protein-protein interactions, protein function, and biomarker discovery.
They consist of thousands of immobilized proteins on a solid surface, allowing for simultaneous analysis of multiple proteins.
3Components of Protein Microarrays
Substrate: Glass slides, membranes, or beads.
Proteins: Target proteins immobilized on the substrate.
Detection System: Fluorescent dyes, antibodies, or other probes.
Imaging System: Scanners or cameras for data acquisition.
4: Types of Protein Microarrays
Analytical Microarrays: Used for studying protein-protein interactions, protein expression profiling, and protein function analysis.
Antibody Microarrays: Utilized for detecting and quantifying specific proteins or antibodies in biological samples.
Reverse-Phase Protein Arrays (RPPAs): Designed for high-throughput protein expression profiling and signaling pathway analysis.
5:Applications of Protein Microarrays
Biomarker Discovery: Identification of disease-specific biomarkers for diagnosis, prognosis, and treatment monitoring.
Drug Discovery: High-throughput screening of drug candidates and target validation.
Functional Proteomics: Mapping protein-protein interactions, post-translational modifications, and protein function analysis.
Clinical Diagnostics: Detection of infectious diseases, cancer biomarkers, and autoimmune disorders.
6: Workflow of Protein Microarray Experiment
Protein immobilization: Spotting or printing target proteins onto the microarray substrate.
Sample incubation: Incubating the microarray with biological samples containing proteins of interest.
Detection and analysis: Using fluorescent probes or antibodies to detect bound proteins and quantifying the signals.
Data interpretation: Analyzing and interpreting the results to extract meaningful biological insights.
7: Advantages of Protein Microarrays
-High-throughput analysis of thousands of proteins in parallel.
Small sample volume requirement.
Enables multiplexed assays for comprehensive protein profiling.
Facilitates rapid biomarker discovery and validation.
8: Challenges and Considerations
Standardization of protocols and reagents.
Optimization of protein immobilization and detection methods.
Data analysis and interpretation complexities.
Cost and accessibility of microarray platforms.
9: Future Perspectives
Integration with other omics technologies for holistic biological insights.
Development of miniaturized and portable microarray platforms for point-of-care diagnostics.
Advancements in data analysis algorithms and bioinformatics tools.
Expanding applications in personalized medicine and precision healthcare
10: Conclusion
Protein microarrays offer a powerful and versatile tool for protein analysis and biomarker discover
A brief introfuction of label-free protein quantification methodsCreative Proteomics
If you want to know more about our services, please visit https://www.creative-proteomics.com/services/label-free-quantification.htm.
Label-free protein quantification is a mass spectrometry-based method for identifying and quantifying relative changes in two or more biological samples instead of using a stable isotope-containing compound to label proteins.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Protein qualitative analysis based on mass spectrometry explores protein expression within organisms. Mass spectrometry offers highly efficient, robust, and accurate results and is one of the core technologies for proteomic research. Protein identification is a common topic for biochemistry research, and mass spectrometry is considered one of the most useful techniques that solve this issue. Two major strategies that are widely used for protein identification by mass spectrometry are MALDI-TOF-based protein fingerprinting and LC-MS/MS-based peptide sequencing. Meanwhile, LC-MS/MS reserved higher sensitivity and ability than MALDl-TOF and can accurately identify multiple protein components from a single sample. https://www.creative-proteomics.com/services/protein-identification.htm
protein microarray_k.b institute (m.pharm pharmacology) .pptxNittalVekaria
1: Introduction
Welcome to our presentation on Protein Microarrays.
Discover the revolutionary technology transforming protein analysis and biomolecular research
2: What are Protein Microarrays?
Protein microarrays are high-throughput platforms for studying protein-protein interactions, protein function, and biomarker discovery.
They consist of thousands of immobilized proteins on a solid surface, allowing for simultaneous analysis of multiple proteins.
3Components of Protein Microarrays
Substrate: Glass slides, membranes, or beads.
Proteins: Target proteins immobilized on the substrate.
Detection System: Fluorescent dyes, antibodies, or other probes.
Imaging System: Scanners or cameras for data acquisition.
4: Types of Protein Microarrays
Analytical Microarrays: Used for studying protein-protein interactions, protein expression profiling, and protein function analysis.
Antibody Microarrays: Utilized for detecting and quantifying specific proteins or antibodies in biological samples.
Reverse-Phase Protein Arrays (RPPAs): Designed for high-throughput protein expression profiling and signaling pathway analysis.
5:Applications of Protein Microarrays
Biomarker Discovery: Identification of disease-specific biomarkers for diagnosis, prognosis, and treatment monitoring.
Drug Discovery: High-throughput screening of drug candidates and target validation.
Functional Proteomics: Mapping protein-protein interactions, post-translational modifications, and protein function analysis.
Clinical Diagnostics: Detection of infectious diseases, cancer biomarkers, and autoimmune disorders.
6: Workflow of Protein Microarray Experiment
Protein immobilization: Spotting or printing target proteins onto the microarray substrate.
Sample incubation: Incubating the microarray with biological samples containing proteins of interest.
Detection and analysis: Using fluorescent probes or antibodies to detect bound proteins and quantifying the signals.
Data interpretation: Analyzing and interpreting the results to extract meaningful biological insights.
7: Advantages of Protein Microarrays
-High-throughput analysis of thousands of proteins in parallel.
Small sample volume requirement.
Enables multiplexed assays for comprehensive protein profiling.
Facilitates rapid biomarker discovery and validation.
8: Challenges and Considerations
Standardization of protocols and reagents.
Optimization of protein immobilization and detection methods.
Data analysis and interpretation complexities.
Cost and accessibility of microarray platforms.
9: Future Perspectives
Integration with other omics technologies for holistic biological insights.
Development of miniaturized and portable microarray platforms for point-of-care diagnostics.
Advancements in data analysis algorithms and bioinformatics tools.
Expanding applications in personalized medicine and precision healthcare
10: Conclusion
Protein microarrays offer a powerful and versatile tool for protein analysis and biomarker discover
protein microarray_k.b institute (m.pharm pharmacology) .pptxNittalVekaria
1: Introduction
Welcome to our presentation on Protein Microarrays.
Discover the revolutionary technology transforming protein analysis and biomolecular research
2: What are Protein Microarrays?
Protein microarrays are high-throughput platforms for studying protein-protein interactions, protein function, and biomarker discovery.
They consist of thousands of immobilized proteins on a solid surface, allowing for simultaneous analysis of multiple proteins.
3Components of Protein Microarrays
Substrate: Glass slides, membranes, or beads.
Proteins: Target proteins immobilized on the substrate.
Detection System: Fluorescent dyes, antibodies, or other probes.
Imaging System: Scanners or cameras for data acquisition.
4: Types of Protein Microarrays
Analytical Microarrays: Used for studying protein-protein interactions, protein expression profiling, and protein function analysis.
Antibody Microarrays: Utilized for detecting and quantifying specific proteins or antibodies in biological samples.
Reverse-Phase Protein Arrays (RPPAs): Designed for high-throughput protein expression profiling and signaling pathway analysis.
5:Applications of Protein Microarrays
Biomarker Discovery: Identification of disease-specific biomarkers for diagnosis, prognosis, and treatment monitoring.
Drug Discovery: High-throughput screening of drug candidates and target validation.
Functional Proteomics: Mapping protein-protein interactions, post-translational modifications, and protein function analysis.
Clinical Diagnostics: Detection of infectious diseases, cancer biomarkers, and autoimmune disorders.
6: Workflow of Protein Microarray Experiment
Protein immobilization: Spotting or printing target proteins onto the microarray substrate.
Sample incubation: Incubating the microarray with biological samples containing proteins of interest.
Detection and analysis: Using fluorescent probes or antibodies to detect bound proteins and quantifying the signals.
Data interpretation: Analyzing and interpreting the results to extract meaningful biological insights.
7: Advantages of Protein Microarrays
-High-throughput analysis of thousands of proteins in parallel.
Small sample volume requirement.
Enables multiplexed assays for comprehensive protein profiling.
Facilitates rapid biomarker discovery and validation.
8: Challenges and Considerations
Standardization of protocols and reagents.
Optimization of protein immobilization and detection methods.
Data analysis and interpretation complexities.
Cost and accessibility of microarray platforms.
9: Future Perspectives
Integration with other omics technologies for holistic biological insights.
Development of miniaturized and portable microarray platforms for point-of-care diagnostics.
Advancements in data analysis algorithms and bioinformatics tools.
Expanding applications in personalized medicine and precision healthcare
10: Conclusion
Protein microarrays offer a powerful and versatile tool for protein analysis and biomarker discover
A brief introfuction of label-free protein quantification methodsCreative Proteomics
If you want to know more about our services, please visit https://www.creative-proteomics.com/services/label-free-quantification.htm.
Label-free protein quantification is a mass spectrometry-based method for identifying and quantifying relative changes in two or more biological samples instead of using a stable isotope-containing compound to label proteins.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
1. ISOBARIC TAG FOR RELATIVE AND
ABSOLUTE QUANTIFICATION (iTRAQ)
ASHOKKUMAR P
I – MSc Genetics & Plant Breeding
2022508002
2. iTRAQ
• Isobaric Tag for Relative and Absolute
quantification
• The identification and quantification of complex
protein mixtures have been facilitated by the mass
spectrometry based quantitative proteomic
techniques.
• The iTRAQ reagent consists of amine specific stable
isotope reagents that can label peptides of upto 4
to 8 different biological samples.
Isobaric tags for relative and absolute quantitation
(iTRAQ) is an isobaric labeling method used in
quantitative proteomics by tandem mass
spectrometry to determine the amount of
proteins from different sources in a single
experiment. It uses stable isotope labeled
molecules that can be covalent bonded to the N-
terminus and side chain amines of proteins.
3. iTRAQ
• Isobaric Tag for Relative and Absolute
quantification
• The identification and quantification of complex
protein mixtures have been facilitated by the mass
spectrometry based quantitative proteomic
techniques.
• The iTRAQ reagent consists of amine specific stable
isotope reagents that can label peptides of upto 4
to 8 different biological samples.
4. iTRAQ
• Isobaric Tag for Relative and Absolute
quantification
• The identification and quantification of complex
protein mixtures have been facilitated by the mass
spectrometry based quantitative proteomic
techniques.
• The iTRAQ reagent consists of amine specific stable
isotope reagents that can label peptides of upto 4
to 8 different biological samples.
5. Quantitative Proteomics : Invitro
labelling methods
• Invitro labelling method rely on use of labelling reactions at a specific site in
proteins or peptides, based on various labellling chemistry different types of
strategies have been developed to introduce isotopes at either protein or
peptide level.
6. Use of Mass Spectrometry in iTRAQ
• Mass Spectrometry has played avery major role in
proteomics and now it is becoming a very essential tool
to study the complex biological system in various
diseases.
• iTRAQ is a mass spec based technique for relative and
absolute quantitation of proteins present in upto 4 to 8
samples depending upon the type of iTRAQ tags, and
these labels can be provided in the proteins where the
N-terminal.
• The iTRAQ and ICAT are the only currently available
commercial tagging technologies, where quantitation
can be carried out in the MS/MS mode.
7. iTRAQ
• The iTRAQ technique was first time described by
Ross et. al, in 2004 and it was subsequently
commercialized by the applied biosystems.
• These iTRAQ reagents are set of multiplexed,
amine-specific isotope reagents.
• It enables simultaneous identification and
quantitation, both relative and absolute.
• There are two types of iTRAQ reagents –
• 4-plex for processing up to 4 samples
• 8-plex for processing up to 8 samples
8. iTRAQ method
• In iTRAQ all derivativatized peptides of a given
sequence are isobaric and coeluted (derived from
control and treatment biological samples)
• Upon collision induced dissociation in MS/MS
experiments, it provides reporter ions(signature)
that differ in m/z value( reporter ions can be used
to monitor the relative quantitation for proteins)
9. iTRAQ Reagent
• There are a set of four isobaric amine specific labelling reagents 114,115,116 and 117.
• The reagent consists of a reporter group, a balancer group, and a peptide reactive group.
• The protein group labels the n terminals of all peptides as well as the free amine group of lysine side chains.
• The neutral balance portion and the reporter group provide total mass of 145, so this method can allow multiplexing of upto 4 or 8
different samples in a single LC MS/MS experiment.
• The different distribution of isotopes between the reporter and balance group makes the label isobaric and it enables the detection
upon fragmentation and the release in mass spec.
10. Reporter
Provides signature ion in MS/MS
Maintains the charge state and ionization efficiency of peptide
Balancer
Balances mass charge of reporter to provide total mass of 145
Neutral loss in MS/MS
11. iTRAQ components
• Components of iTRAQ multiplexed isobaric tagging
chemistry
1) Reporter group based on N,N-dimethylpiperazine
2) Mass balance carbonyl group
3) A peptide-reactive group (ester of N-
hydroxysuccinimide,NHS)
The m/z value of the reporter group ranges from 114.1 –
117.1.
The balance group mass is 28 – 31 Da.
The overall mass of reporter plus balance components
remains constant. 145.1 Da for all four reagents.
12. iTRAQ Experiment - Procedure
1) Protein reduction and cysteine blocking
• Dissolve protein sample in o.5M triethyl
ammoniumbicarbonate, pH 8.5
• Reduction step by adding a reducing agent
• Incubate samples at 60° C for 1H
• Block cysteine by adding a Cysteine blocking reagent
• Add trypsin solution
• Incubate overnight at 37°C
• Clean up samples using zip tip
15. 4) Purification
Pooled samples are purified on a strong cation
exchange column to remove excess unbound
reagent.
This step facilitates sample clean up.
18. iTRAQ Advantages
• Performs relative (or absolute) quantification in up
to 4 or 8 samples
• Multiplexing
• Increased analytical precision and accuracy, saves
MS run time (since isobaric labels)
• Expanded coverage of proteome by tagging tryptic
peptides
• Eliminates limitation of ICAT for dependence on
cysteine.
19. iTRAQ Disadvantages
• Possible errors in quantitation due to
• Differences in efficiency of enzymatic digestion
• Peptide pre-fractionation step
• Variability in initial protein digestion
• Tagging is performed only after individual sample
processing is done, which leads to some variations
• Reagents are very costly
• New search algorithms and databases required
21. CONCLUSION
• iTRAQ is a very straightforward technique because the
labeling chemistry works very well, and labeling efficiency is
very important for how well the quantification works.
• iTRAQ has advantages over the previous technologies, and it
is a very good method for quantitative proteomics as well as
toxicogenomics.
• iTRAQ is also more sensitive than previous methods for
protein quantification because a lot of the protein changes
that we were not able to see before and this high sensitivity
is needed to be able to see changes in low-abundance
proteins.
• Despite some of its weaknesses, iTRAQ is a powerful tool for
proteomics research. Continual improvements in its
usability and technical specifications should make iTRAQ a
must have for anyone doing proteomics.