Proteomics uses mass spectrometry to characterize proteins in a biological sample on a large scale. It provides information about which proteins are present, how much of each protein exists, and how proteins are modified. Mass spectrometry coupled with protein separation techniques and database searching represents a major advancement for protein analysis, allowing characterization of entire proteomes. Key aspects of proteomics include separating proteins, ionizing peptides using techniques like MALDI and ESI, and identifying proteins by matching mass spectra to in silico digests or sequencing peptides de novo. While sample preparation and computational methods are still developing, proteomics offers insights beyond what is possible with genomics alone.
Peptide Mass Fingerprinting (PMF) and Isotope Coded Affinity Tags (ICAT)Suresh Antre
Analytical technique for identifying unknown protein. The peptide mass are compared to database containing the theoretical peptide masses of all known protein sequences.
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.
Proteomics and its applications in phytopathologyAbhijeet Kashyap
Dear friends, I Abhijeet kashyap presenting the basics of proteomics to you all . Proteomics is the large-scale study of proteins, particularly their structures and functions.Proteomics helps in understanding the structure and function of different proteins as well as protein-protein interactions of an organism.
Proteomics is the study of the proteome, the full protein complement of organisms e.g. plasma, cells and tissue.
Understanding the proteome allows for:
Characterisation of proteins
Understanding protein interactions
Identification of disease biomarkers
Peptide Mass Fingerprinting (PMF) and Isotope Coded Affinity Tags (ICAT)Suresh Antre
Analytical technique for identifying unknown protein. The peptide mass are compared to database containing the theoretical peptide masses of all known protein sequences.
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.
Proteomics and its applications in phytopathologyAbhijeet Kashyap
Dear friends, I Abhijeet kashyap presenting the basics of proteomics to you all . Proteomics is the large-scale study of proteins, particularly their structures and functions.Proteomics helps in understanding the structure and function of different proteins as well as protein-protein interactions of an organism.
Proteomics is the study of the proteome, the full protein complement of organisms e.g. plasma, cells and tissue.
Understanding the proteome allows for:
Characterisation of proteins
Understanding protein interactions
Identification of disease biomarkers
Overview Radboudumc Center for Proteomics, Glycomics and Metabolomics april 2015Alain van Gool
An overview of the proteomics, glycomics and metabolomics expertise and capabilities within the Translational Metabolic Laboratory of the Radboudumc. We're interested in collaboration with academic and industrial partners, either bilateral or as part of multi-partner consortia.
If you want to know more, please visit https://www.creative-proteomics.com/s...
Stable isotope labeling using amino acids in cell culture (SILAC) is a powerful method based on mass spectrometry that identifies and quantifies relative differential changes in protein abundance. First used in quantitative proteomics in 2002, it provides accurate relative quantification without any chemical derivatization or manipulation.
Overview Radboudumc Center for Proteomics, Glycomics and Metabolomics april 2015Alain van Gool
An overview of the proteomics, glycomics and metabolomics expertise and capabilities within the Translational Metabolic Laboratory of the Radboudumc. We're interested in collaboration with academic and industrial partners, either bilateral or as part of multi-partner consortia.
If you want to know more, please visit https://www.creative-proteomics.com/s...
Stable isotope labeling using amino acids in cell culture (SILAC) is a powerful method based on mass spectrometry that identifies and quantifies relative differential changes in protein abundance. First used in quantitative proteomics in 2002, it provides accurate relative quantification without any chemical derivatization or manipulation.
Join Brian Searle on an illustrated tour about interpreting MS/MS peptide spectra. On this tour you will first see how you can relate mass spectra to peptides. Next you see why the SEQUEST software was developed to interpret these spectra as peptides. Next you will see other software approaches have been developed and how combining approaches produces even better results.
Bottom-up workflows have been a staple of mass spectrometry based proteomic approaches. We present in this work a fully automated solution for MALDI-TOF MS based peptide mapping experiments.
At present, strategies for proteomics research can be divided into discovery proteomics and targeted proteomics. Discovery proteomics is more concerned with protein screening and dynamics, while targeted proteomics focuses more on detecting target proteins/peptides to achieve absolute quantification. https://www.creative-proteomics.com/ngpro/targeted-proteomics.html
Nanodroplet processing platform for deep and quantitative proteome profiling ...Gul Muneer
Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.
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
Proteomics, definatio , general concept, signficanceKAUSHAL SAHU
INTRODUCTION
GENERAL CONCEPT
WHY PROTEIOMIC NECESERY?
WHAT PROTEOMIC CAN ANSWER?
PRTEOMICS- ANALYSIS AND IDENTIFICATION OF PROTEIN
TWO-DIMENSIONAL SDS-PAGE
MASS SPECTROMETERS
SIGNIFICANCE OF STUDY AN ITS IMPORTANCE
APPLICATIONS
CHALLENGES
CONCLUSIONS
REFERENCES
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
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Monitor common gases, weather parameters, particulates.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
2. WHY BOTHER WITH PROTEOMICS?
• Proteins are the machines that drive much
of biology
• Genes are merely the recipe
• The direct characterization of a sample’s
proteins en masse.
• What proteins are present?
• How much of each protein is present?
3. WHY NOT MICROARRAYS?
Is Proteomics the New Genomics? Jürgen Cox and Matthias Mann, Cell 130, August 10, 2007
5. AN ANALYTICAL CHALLENGE
Dynamic range
of protein
abundances is
a challenge for
separation
sciences
No equivalent
of PCR for
proteins-deal
with µ- to nmol
concentrations
Alternate
splice forms of
a gene can
make different
proteins
>200 Post
translational
modifications;
cannot be
deduced from
a gene or
mRNA
Edman sequencing cannot provide the solutions !!!
8. MASS SPECTROMETRY
Analytical method to measure the molecular or atomic
weight of samples
Slide adopted from: Dr.. Ahna Skop. Mass Spectrometry: Methods & Theory
9. SOFT IONIZATION METHODS
337 nm UV laser
MALDI
cyano-hydroxy
cinnamic acid
Gold tip needle
Fluid (no salt)
ESI
+
_
Slide adopted from: Nathan Edwards
Center for Bioinformatics and Computational Biology(UMIACS)
14. MS INSTRUMENTS
A Brief Summary of the Different Types of Mass Spectrometers Used in Proteomics
Methods in Molecular Biology, vol. 484: Functional Proteomics: Methods and Protocols
15. IDENTIFICATION STRATEGIES
Experimental
masses
Theoretical
Masses
(database)
1. Peptide mass fingerprinting(PMF)
2. MS/MS spectral matching
Experimental spectrum
Theoretical spectra
3.De novo sequencing*
72.0 129.0 97.0 101.0 113.1 174.1
A E P T I R H2O
*Adopted from: Brian C. Searle, Proteome Software
Inc. Portland, Oregon USA
4. Spectral library search
18. PEPTIDE MASS FINGERPRINT
The proteins from a sample are separated on 2D gels
Protein of interest is digested by trypsin (or any other site
specific cleavage)
Ionization of peptides in a MALDI mass spectrometer
m/z values detected and plotted as mass spectrum
PMF database search to identify the protein
22. 22
MODIFICATIONS
Fixed modifications: will be present on any
occurrence of the affected amino acid.Eg.+57@C
Variable modifications: may be present on some
or all positions of the affected amino acid.
Eg.+16@M
Slide adopted from: Nathan Edwards
Center for Bioinformatics and Computational Biology(UMIACS)
26. 26
FRAGMENTATION
PEPTIDE
MW ion ion MW
98 b1 P EPTIDE y6 703
227 b2 PE PTIDE y5 574
324 b3 PEP TIDE y4 477
425 b4 PEPT IDE y3 376
538 b5 PEPTI DE y2 263
653 b6 PEPTID E y2 148
27. SHOTGUN PROTEOMICS & DATABASE
SEARCH
The pros and cons of peptide-centric proteomics. Mark W. Duncan, Ruedi Aebersold, Richard M. Caprioli
Nature Biotechnology, Vol. 28, No. 7. (01 July 2010), pp. 659-664
30. 30
DE NOVO INTERPRETATION
100
0
250 500 750 1000
m/z
%Intensity
Slide adopted from: Nathan Edwards
Center for Bioinformatics and Computational Biology(UMIACS)
31. 31
DE NOVO INTERPRETATION
100
0
250 500 750 1000
m/z
%Intensity
E L
Slide adopted from: Nathan Edwards
Center for Bioinformatics and Computational Biology(UMIACS)
32. 32
DE NOVO INTERPRETATION
100
0
250 500 750 1000
m/z
%Intensity
E L F
KL
SGF G
E D
E
L E
E D E L
Slide adopted from: Nathan Edwards
Center for Bioinformatics and Computational Biology(UMIACS)
33. 33
SUMMARY
Proteomics is large-scale study (qualitative and
quantitative) study of proteins by mass spec.
Mass spectrometry + sequence databases
represent a huge leap for protein (bio-)chemistry.
ProteinSeparation - 2DGE and HPLC
Ionization - MALDI and ESI
Identification - PMF, MS/MS and de novo
sequencing
Sample prep, instruments and algorithms still
maturing, much work to be done.
