Download Proteomic studies of the environmentally important methanotroph

Proteomic studies of the environmentally important
methanotroph Methylocella silvestris
Konstantinos Thalassinos, Vibhuti Patel, Susan Slade, Nisha Patel, Joanne
Connoly, Andrew Crombie, Colin Murrell, James Scrivens
The Central Dogma of Molecular Biology
Proteome Complexity
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Human Genome 20,000 – 25,000 genes1
A single gene can give rise to many different proteins by the
process of alternative splicing
 In complex genes, alternative splicing can generate dozens or
even hundreds of different mRNA isoforms2
It is estimated that almost 50% of all proteins contain one or
more post-translational modifications3
1International Human
Genome Sequencing Consortium (2004). "Finishing the euchromatic
sequence of the human genome.". Nature 431 (7011): 931-945
2Missler, M. and Sudhof, T. C. (1998). Neurexins: three genes and 1001 products. Trends Genet. 14,
20–26.
3Apweiler, R., Hermjakob, H. and Sharon, N. (1999). On the frequency of protein glycosylation, as
deduced from analysis of the SWISS-PROT database. Biochim.Biophys. Acta 1473, 4–8.
What is Proteomics?
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Proteomics is the global characterisation of protein
products (sequence, post-translational modifications,
protein-protein interactions) expressed by a given
genome at a specific point in time
Unlike the genome, the proteome is a dynamic entity
Challenges and limitations
Biological
 Dynamic range
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4 orders of magnitude in
cells and 10 orders of
magnitude in plasma
Post-translational
modifications
Alternative splicing
Technical
 Sample requirements
 Complex, time-consuming
sample preparation
 Days of experimental time
Pedrioli, P. G., et al., (2004). A common open representation of mass spectrometry data and its application to
proteomics research. Nat. Biotechnol. 22, 1459–1466.
Proteomics Approaches
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Profiling
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Differential
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Identify which proteins are present in a sample
Probe for changes in protein expression levels between a
number of environmental states
Detailed characterisation
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Identify the presence and map the position of all posttranslational modifications present on each protein
Essentials of a Mass Spectrometer
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A mass spectrometer separates ions according to their
mass-to-charge (m/z) ratio
Direct Sample Introduction ESI
Liquid Chromatography MALDI
Quadrupole
TOF
Ion Trap
FT
MS and Tandem MS data
MS/MS fragment ion nomenclature
Limitations of Current Database Search Programs
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Finding a peptide match after a database search is easy, but
knowing whether it is correct is not
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It is almost always possible to match a MS/MS spectrum to a peptide
in the database
Incorrect matches often (but not always) result from use of low
quality peptide MS/MS data to search the database
Even high quality data can produce invalid identifications
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Actual peptide sequence is not in the database searched (under the
search conditions used)
Probability of a false positive assignment is much higher for
proteins identified with only one peptide (known as one-hitwonders)
According to publishing guidelines more than 1 peptide per
protein is required
Methylocella silvestris
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Acidophillic aerobic methanotroph
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Methanotrophs use methane as
their sole carbon and energy
source
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Key position in the global
methane cycle
Effects of multi-carbon substrates
on activity
Soluble methane monooxygenase
(sMMO)
The recently discovered genus of
Methylocella is capable of utilising
certain multi-carbon compounds
as well as methane
Aims
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To measure changes in protein expression of
Methylocella silvestris under varying growth
conditions.
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Relate changes in proteome to important biological
pathways.
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Compare existing methods and new approaches using
the same instrumentation and software without bias.
Proteomes analysed
H3C
CH3
H
H
O
HO
OH
H
OH
H
N
O
H
Propane
Succinate
H
H
H
Methanol
O
H
HO
H
Methane
Acetate
CH3
H
H
Methylamine
Creation of protein database
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M. silvestris genome recently published
Predict all open reading frames
Use custom Perl scripts to create appropriate FASTA
formatted database
Experimental approaches used
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SDS-PAGE gels
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iTRAQ
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Uses 4 isobaric tags for
quantitation
MSE (IdentityE)
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No quantitation
Uses an internal standard
for quantitation
Database search results
saved in MySQL database
Proteins identified by each methodology
Gels
iTRAQ
IdentityE
Overlap of protein identifications
Including single-peptide
identifications
Two peptides or more
iTRAQ reporter ion ratios
Replicate analyses of iTRAQ-labelled samples
IdentityE estimated quantitation
Log(e) ratio plot of common proteins expressed under methane and acetate growth.
Summary
Gels
iTRAQ
IdentityE
Protein loading
14 µg
800 – 1000 µg
0.5 – 0.75 µg
Total experimental time
4 days
6 days
Less than 3 days
30-40 hours
30-40 hours
6 hours per sample
Number of proteins
identified
95
171
399
Average number of
peptides per protein
3.7
2
10
17.2 %
11.5 %
50.4 %
--
3
4
Total instrument time
Average sequence
coverage
Dynamic range covered
by relative quantitation
Conclusions
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All the methodologies employed provided good profiling
coverage of the respective proteome.
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iTRAQ and IdentityE both provide information on protein
identity and changes in expression.
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IdentityE
 More confident protein identifications
 Lower protein requirements
 Significantly less instrument demands
 Significantly reduced sample preparation time
 Provides a stand-alone quantitative estimate of the proteins
present in any given sample
Publication
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A comparison of labelling and label-free mass
spectrometry-based proteomics approaches.
Konstantinos Thalassinos, Vibhuti Patel, Susan Slade,
Nisha Patel, Joanne Connoly, Andrew Crombie, Colin
Murrell, James Scrivens. Journal of Proteome Research
Ongoing studies
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Continue the studies on the effect of growth
substrate on the proteome of M. silvestris.
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Relate results back to M. silvestris cell biochemistry in
particular the pathways of multi-carbon substrate
assimilation
Biological significance of results obtained
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Distinct protein profiles for each substrate:
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Certain proteins only expressed under methane.
Certain proteins only expressed under acetate.
Significantly lower levels of key enzyme soluble
methane monooxygenase (sMMO) when grown
under acetate.
Pathway mapping
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Kyoto Encyclopedia of Genes and Genomes (KEGG)
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KEGG Automatic Annotation Server (KAAS)
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Manually curated database of biological pathways.
Functional annotation of genes by BLAST comparisons
against KEGG database.
Develop a program to map the KAAS results back
onto KEGG pathways
http://www.genome.jp/kegg/
Biological pathways
Acknowledgements
Acknowledgements
Multi-dimensional protein identification
techniques (MudPIT)
Profiling
Quantitation
Proteome
Tryptic
digest
Label with
isobaric tags
Strong cation exchange
chromatography
LC-ESI-MS/MS
Analyse ratios
of tags
115
iTRAQ
117
Database
searches
114
Protein
identification
Relative levels
of identified
proteins
116
Alternative approach to profiling and
quantitative proteomics
Waters IdentityE and ExpressionE
500 ng sample loading plus an internal standard
Approximately 2 hours analysis/sample
New approach to profiling and quantitative
proteomics
Validation of MSE data
IdentityE and ExpressionE
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Quantitation is based on relationship between ESI signal
response and protein concentration
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The average ESI signal response of the 3 most intense tryptic
peptides per mole of protein is constant (CV +/- 10%)$
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Quantify at the protein level (gross changes) or peptide level
(minor fluctuations in protein expression)
$Absolute
Quantification of Proteins by LCMSE Silva et al., MCP vol. 5 issue 1 (2006) 144-156
Protein identifications common to iTRAQ and
IdentityE
Proteins identified in the iTRAQ and IdentityE experiments, including onehit-wonders.