Nucleic Acids Research Advance Access published online on October 9, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp808
© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Dynamic Proteomics: a database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells
Milana Frenkel-Morgenstern1,*,
Ariel A. Cohen1,
Naama Geva-Zatorsky1,
Eran Eden1,
Jaime Prilusky2,
Irina Issaeva1,
Alex Sigal3,
Cellina Cohen-Saidon1,
Yuvalal Liron,
Lydia Cohen1,
Tamar Danon1,
Natalie Perzov1 and
Uri Alon1
1Molecular Cell Biology Department, 2Bioinformatics Unit, Weizmann Institute of Science, Rehovot, 76100, Israel and 3Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA
*To whom correspondence should be addressed. Tel: +972523450459; Fax: +34912246976; Email: milana.frenkel{at}weizmann.ac.il
Received August 15, 2009. Revised December 10, 2009. Accepted September 12, 2009.
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ABSTRACT
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Recent advances allow tracking the levels and locations of a
thousand proteins in individual living human cells over time
using a library of annotated reporter cell clones (LARC). This
library was created by Cohen
et al. to study the proteome dynamics
of a human lung carcinoma cell-line treated with an anti-cancer
drug. Here, we report the Dynamic Proteomics database for the
proteins studied by Cohen
et al. Each cell-line clone in LARC
has a protein tagged with yellow fluorescent protein, expressed
from its endogenous chromosomal location, under its natural
regulation. The Dynamic Proteomics interface facilitates searches
for genes of interest, downloads of protein fluorescent movies
and alignments of dynamics following drug addition. Each protein
in the database is displayed with its annotation, cDNA sequence,
fluorescent images and movies obtained by the time-lapse microscopy.
The protein dynamics in the database represents a quantitative
trace of the protein fluorescence levels in nucleus and cytoplasm
produced by image analysis of movies over time. Furthermore,
a sequence analysis provides a search and comparison of up to
50 input DNA sequences with all cDNAs in the library. The raw
movies may be useful as a benchmark for developing image analysis
tools for individual-cell dynamic-proteomics. The database is
available at
http://www.dynamicproteomics.net/.
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INTRODUCTION
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To study the proteome of living human cells requires quantification
of the levels and localization of thousands of proteins in space
and time (
1–4). Proteome dynamics are crucial for understanding,
for instance, the effects of drugs on cells (
5–7). A recent
advance in molecular cell biology and image analysis, reported
by Cohen
et al. allows measuring the proteome dynamics in individual
living human cancer cells (
1). Cohen
et al. studied the levels
of over a thousand unique proteins in single cells of a human
lung carcinoma line treated with the anti-cancer drug, camptothecin
(CPT) (
1). The study was focused on a library of annotated reporter
cell clones (LARC), in which each clone has a fluorescently
tagged protein expressed form its native chromosomal location.
The LARC library was created using the ‘CD tagging’
approach (
2–4,
8–12), in which a retrovirus inserts
a fluorescent label (for example, enhanced yellow fluorescent
protein, eYFP or Venus) into the intron of a protein-encoding
gene. Protein identity was established by sequencing the mRNA
downstream of the eYFP insertion site (3' RACE). The LARC library
contains about 1200 unique tagged proteins. Cohen
et al. used
the time-lapse fluorescence microscopy to study protein fluorescence
levels and changes in the subcellular localizations for 48 hours
after drug treatment (
1).
We present here the Dynamics Proteomics database, which is a compendium of endogenously tagged human proteins studied by Cohen et al. (1), and their time-lapse microscopy movies that illustrate the protein dynamics in space and in time in individual living human cancer cells in response to an anti-cancer drug CPT (1–4). The database provides the annotation of the tagged proteins, alignment of protein dynamics for proteins of interest, sequence search and comparison of up to 50 input sequences to all the cDNAs in the library. The web interface enables a visual overview of the available proteins in the library, fluorescent and phase images of their intracellular localizations and time-lapse microscopy movies.
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DATABASE CONTENT AND STATISTICS
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The database version 1.0 incorporates the LARC library (
1),
which includes 2189 cell-line clones, 1144 unique characterized
proteins and over 150 uncharacterized proteins. Each clone contains
a different protein fused to a fluorescent protein (eYFP or
Venus), expressed from its endogenous chromosomal location under
its natural regulation (
1).
The Dynamic Proteomics annotation is produced by the similarity search of cDNA sequences against public databases of human DNA sequences using BLAST-Like Alignment Tool (BLAT) (13). For each database entry, all BLAT hits are recorded with database IDs, and information in text is used for the manual QA process. Additional automatic PERL programs produce an extended protein annotation from the Ensembl (14) and Entrez (NCBI) databases for entries selected according to QA standards.
A database entry contains a protein description, cellular process and function, and the chromosomal position of the integrated fluorescent tag. Moreover, the entry page includes phase and fluorescence images of protein localization in the cell, a manual annotation of the observed localization patterns, time-lapse movies, and protein dynamics. The protein dynamics is a quantitative trace of the tagged-protein fluorescence levels in the nucleus and cytoplasm obtained by image analysis of the movies over time (1).
Tagged proteins in the library have different cell localizations, including cytoplasm, cytoskeleton, nucleus, nucleolus, endoplasmic reticulum, Golgi, mitochondrion, plasma membrane and others (Figure 1A). These localizations are distributed among the clones similarly to the distribution of known human proteins annotated in the GO database (Figure 1B). We found that the uncharacterized proteins tagged in the library (proteins annotated as hypothetical, or proteins encoded from regions in the genome denoted as ESTs and mRNAs), have a distribution of localizations similar to that of the characterized proteins in the library (Figure 1C).
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Figure 1. Tagged proteins in the LARC library are found across all cellular localizations. The localization distribution is similar to that of all known proteins. Represented are distributions of cellular localizations for: (A) all proteins in the Dynamic Proteomics database with published localizations; (B) all proteins in the GO database; (C) uncharacterized proteins in the database based on manual inspection. These proteins have no available published localization.
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DYNAMIC PROTEOMICS INTERFACE
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The Dynamic Proteomics interface (based on MySQL) is designed
to make it easy for users to find genes of interest. The database
offers a search for gene names (e.g. LMNA), DNA sequences (e.g.
ATGGGAAAGAAAACCAAGCGGAC), protein description (e.g. ‘synthetases’),
image or published localization (e.g. ‘cytoplasm’),
exon-tag insertion point (e.g. ‘intron 1’). In addition,
it provides an alignment of protein dynamics for user-defined
gene names (e.g. ACTN4 GARS TOP1, separated by ‘space’)
from the ‘
Search Dynamics’ page. When a gene of
interest has been selected, or if a query that entered matches
a certain gene, the user is directed to the database entry page
(for example, LMNA,
Figure 2). This page is the primary interface
for viewing the annotation of tagged proteins in the library,
its fluorescent and phase images, protein dynamics, exon-tag
insertion point, a protein sequence and references to the time-lapse
microscopy movies. In addition, protein movies and dynamics
can be viewed from the ‘
All Movies/Dynamics’ page
linked from the menu. It provides a list of all available movies
for library clones, a search and an alignment of dynamics for
the proteins of interest (
Figure 3). Usually, one to six movies
are presented for each protein in the database. Movies were
selected manually according to QA standards (e.g. sufficient
number of cells per field of view). Quantitative protein dynamics
are displayed for available movies.
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Figure 2. Example of the database entry page with a detailed protein annotation for LMNA (Lamin A/C isoform 2). The protein is localized in nucleus as it can be seen on the fluorescent image (white ‘beans’). This entry includes links to four microscopy movies. In addition, the clone ID, the published and image localizations, the protein description and annotation, the eYFP insertion point, the protein dynamics following drug addition, and links to other public databases are shown on the database entry page.
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Figure 3. The alignment of protein dynamics for ACTN4 (actinin, alpha 4), GARS (glycyl-tRNA synthetase) and TOP1 (DNA topoisomerase I). (A) The dynamics is presented for the individual proteins normalized to the total fluorescence at time t = 0. (B) The alignment of protein dynamics in cytoplasm, nucleus and total protein dynamics are presented for all three proteins together.
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LINKS TO OTHER DATABASES
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Each entry in the Dynamic Proteomics is associated with a cDNA
sequence, a detailed protein annotation obtained from the Ensembl
(
14) and Entrez (NCBI) databases. In additional, each protein
has links to GeneCards (
15), InterPro (
16) and UniProt (
17)
for the complete protein sequence information.
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QUANTITATIVE PROTEIN DYNAMICS
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The presentation and alignment of protein dynamics are produced
by PERL script running online. The protein dynamics alignment
is obtained by placing each profile onto a common time scale
(hours, following drug addition) with zero corresponding to
the drug-addition time point for the corresponding clone. All
fluorescence levels are normalized to the total fluorescence
at time point zero (
t = 0) (
Figure 3). Such normalization is
helpful because fluorescence levels vary between different proteins.
Details on the image analysis methods used for producing protein
dynamics is presented by Cohen
et al. and Sigal
et al. (
1–4).
Figure 3 displays the protein-dynamics alignment results for
proteins: ACTN4 (actinin, alpha 4), GARS (glycyl-tRNA synthetase)
and TOP1 (DNA topoisomerase I).
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SEQUENCE COMPARISON TOOL
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Using the MySQL database and the FASTA sequence comparison tool
(
18), the ‘
Sequence Analysis’ page provides a powerful
search engine for user sequences. Users can enter up to 50 different
DNA sequences and search over all cDNAs in the database. The
query parameters are passed to the search engine using CGI.
Query results are presented with a corresponding query or gene
name. The results refer to the proteins in the Dynamic Proteomics
database, links to their movies and dynamics. The alignment
of proteins dynamics can be obtained from the result page.
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RAW MOVIES DATA
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The Dynamic Proteomics database provides the raw data of the
time-lapse microscopy experiments for 50 proteins at the ‘
Raw Data’ page. For all other proteins, the data are available
from the authors. The data includes three types of movies: cell
background (fluorescently mCherry-colored), the protein fluorescent
(eYFP- or Venus-colored) and phase (
1). The raw movies may be
useful as a benchmark dataset for developing image analysis
tools.
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DATABASE ACCESS AND FEEDBACK
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The Dynamic Proteomics databases can be accessed online (
http://www.dynamicproteomics.net or
http://www.weizmann.ac.il/mcb/UriAlon/DynamProt/). The database
is regularly updated with new clones, images, movies and dynamics.
The ftp access to a bulk download of all images and movies in
the database is provided from the public directory:
ftp://alon-serv.weizmann.ac.il/pub/dynamprot/.
Statistics are available with each update at the ‘Statistics’
page. We consider user feedback as extremely valuable. Please
contact us at
dynamicproteomics{at}gmail.com.
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OUTLOOK
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The Dynamic Proteomics version 1.0 database contains more than
2180 fluorescently tagged proteins in the H1299 non-small lung
cell carcinoma line. We expect this number to increase, and
new cell lines to be tagged. We invite other authors to submit
their measured or calculated protein dynamics using the raw
data provided by the database.
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ACKNOWLEDGEMENTS
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The authors thank the Kahn Family Foundation and the Israel
Science Foundation for the project support. M.F.M. and E.E.
are supported by the Horowitz Center for Complexity Science.
The authors also thank Pierre Choukroun and Michael Green for
the UNIX system administration; Malka Cymbalista and Shlomit
Afgin for a technical help in the website and database construction.
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FUNDING
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Funding for open access charge: The Kahn Family Foundation and
the Israel Science Foundation.
Conflict of interest statement. None declared.
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Footnotes
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Present address: Milana Frenkel-Morgenstern, CNIO, C/Melchor
Fernandez Almagro, 3, Madrid, E-28029 Spain.
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REFERENCES
|
|---|
- Cohen AA, Geva-Zatorsky N, Eden E, Frenkel-Morgenstern M, Issaeva I, Sigal A, Milo R, Cohen-Saidon C, Liron Y, Kam Z, et al. Dynamic proteomics of individual cancer cells in response to a drug. Science (2008) 322:1511–1516.[Abstract/Free Full Text]
- Sigal A, Danon T, Cohen A, Milo R, Geva-Zatorsky N, Lustig G, Liron Y, Alon U, Perzov N. Generation of a fluorescently labeled endogenous protein library in living human cells. Nat. Protoc. (2007) 2:1515–1527.[CrossRef][Web of Science][Medline]
- Sigal A, Milo R, Cohen A, Geva-Zatorsky N, Klein Y, Liron Y, Rosenfeld N, Danon T, Perzov N, Alon U. Variability and memory of protein levels in human cells. Nature (2006) 444:643–656.[CrossRef][Medline]
- Sigal A, Milo R, Cohen A, Geva-Zatorsky N, Klein Y, Alaluf I, Swerdlin N, Perzov N, Danon T, Liron Y, et al. Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins. Nat. Methods (2006) 3:525–531.[CrossRef][Web of Science][Medline]
- Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschuler SJ. Multidimensional drug profiling by automated microscopy. Science (2004) 306:1194–1198.[Abstract/Free Full Text]
- Yeh P, Tschumi AI, Kishony R. Functional classification of drugs by properties of their pairwise interactions. Nat. Genet. (2006) 38:489–494.[CrossRef][Web of Science][Medline]
- Young DW, Bender A, Hoyt J, McWhinnie E, Chirn GW, Tao CY, Tallarico JA, Labow M, Jenkins JL, Mitchison TJ, et al. Integrating high-content screening and ligand-target prediction to identify mechanism of action. Nat. Chem. Biol. (2008) 4:59–68.[CrossRef][Web of Science][Medline]
- Jarvik JW, Telmer CA. Epitope tagging. Annu. Rev. Genet. (1998) 32:601–618.[CrossRef][Web of Science][Medline]
- Jarvik JW, Adler SA, Telmer CA, Subramaniam V, Lopez AJ. CD-tagging: a new approach to gene and protein discovery and analysis. Biotechniques (1996) 20:896–904.[Web of Science][Medline]
- Jarvik JW, Fisher GW, Shi C, Hennen L, Hauser C, Adler S, Berget PB. In vivo functional proteomics: mammalian genome annotation using CD-tagging. Biotechniques (2002) 33:852–854, 856, 858–860 passim.[Web of Science][Medline]
- Clyne PJ, Brotman JS, Sweeney ST, Davis G. Green fluorescent protein tagging Drosophila proteins at their native genomic loci with small P elements. Genetics (2003) 165:1433–1441.[Abstract/Free Full Text]
- Morin X, Daneman R, Zavortink M, Chia W. A protein trap strategy to detect GFP-tagged proteins expressed from their endogenous loci in Drosophila. Proc. Natl Acad. Sci. USA (2001) 98:15050–15055.[Abstract/Free Full Text]
- Kent WJ. BLAT- the BLAST-like alignment tool. Genome Res. (2002) 12:656–664.[Abstract/Free Full Text]
- Birney E, Andrews D, Caccamo M, Chen Y, Clarke L, Coates G, Cox T, Cunningham F, Curwen V, Cutts T, et al. Ensembl 2006. Nucleic Acids Res (2006) 34:D556–D561.[Abstract/Free Full Text]
- Lancet D, Safran M, Olender T, Dalah I, Iny-Stein T, Inger A, Harel A, Stelzer G. GeneCards tools for combinatorial annotation and dissemination of human genome information. In: GIACS Conf. Data Complex Syst (2008).
- Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, et al. InterPro: the integrative protein signature database. Nucleic Acids Res. (2009) 37:D211–D215.[Abstract/Free Full Text]
- The UniProt Consortium. The Universal Protein Resource (UniProt). Nucleic Acids Res. (2009) 37:D169–D174.[Abstract/Free Full Text]
- Pearson WR, Lipman LD. Improved tools for biological sequence comparison. Proc. Natl Acad. Sci. USA (1988) 85:2444–2448.[Abstract/Free Full Text]
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