Transcript National Microbial Pathogen Data Resource

Tools for comparative
genomics and expert
annotations
Goals of this Presentation
• Introduce microbiologists to the power of
NMPDR and SEED
• Enable users to interact with data
• Invite experts to participate in construction
of subsystems
• Capture expert annotations via the
annotation clearinghouse
www.nmpdr.org
What is NMPDR?
• Beautified, read-only version of the SEED
What is the SEED?
• Editable environment for assignment of function in the
context of systems biology
• Intended to clean up legacy of errors created by
similarity-based, automated assignment of function
• Manual assignment of function based on integrated
evidence: sequence similarity, functional clusters,
phylogenetic and metabolic profiles
• Developed for the project to annotate 1000 genomes
www.nmpdr.org
When Will We Have 1000
Complete Genomes?
• Depends on what is meant by “complete”
 Many sequencing projects will stop without “finishing” or “closing”
the genome in one contiguous sequence for each replicon
• A genome is essentially complete when:
 95 - 99% of genome accurately sequenced
 10X coverage by 454 method; 5X coverage by Sanger method
 Assembly places 70% data in contigs at least 20 kbp
www.nmpdr.org
Bacterial Genome Facts
• First two complete genomes in 1995 were
bacterial pathogens
• 2913 genomes started as of Sept., 2007
 63% of total are bacteria; 50% of bacteria are
pathogens
• 4434 genomes started as of January, 2009
 51% bacteria
• Value depends on accuracy of annotation
www.nmpdr.org
Complete Genome Projects
1000
900
Total
800
700
Bacteria
Eukarya
Archaea
600
500
400
300
200
100
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
www.nmpdr.org
What is an Annotation?
• Identification of nucleotide string that could
potentially encode a protein
 Open reading frames (ORFs) computed from stop and
start codons, codon bias, promoters and RBS
• Assignment of a name to that gene
 Usually that of known protein with most similar sequence,
computed from translated BLAST
• Prediction of functional role for that gene
 Function of most similar protein not always established
with experimental evidence
 Most similar protein may not have known function
 Most similar ORF may or may not be expressed
www.nmpdr.org
Problems with Standard Annotations
• 42% of H. influenzae ORFs assigned no function in 1995
 about half of those had no sequence match in GenBank
 the rest matched “hypothetical proteins” in E. coli
• 58% of H. influenzae ORFs assigned function of a
significantly similar sequence
• What was in GenBank to compare with in 1995?
 7% of all GenBank entries were bacterial, 16% of those, E. coli
 many “conserved hypotheticals” added to database
• Paralogous members of protein families may not be properly
discriminated
• Significantly similar enzymes may act on different substrates
• Assignments are transitive, many times removed from
experimental data
www.nmpdr.org
Subsystems Annotations
vs.
Pipelines or Protein Families
• What is subsystems annotation?
 humans integrating evidence within a comparative framework
• What’s wrong with “genome-at-a-time” pipelines?
 automated assignment of archived annotations to new genomes
 propagates uninformative and incorrect annotations
• What’s wrong with annotation based on protein
families?
 emphasizes structural and phylogenetic evidence
 ignores metabolic and chromosomal contexts
 leads to ambiguity for members of large families, e.g. transporters
www.nmpdr.org
What is a Subsystem?
• Subsystem is a generalization of pathway
 Collection of functional roles jointly involved in a biological process
or complex
• metabolic, signaling, regulatory, structural
• Functional role is the abstract biological function of a gene
product
 Atomic or fundamental; examples:
• 6-phosphofructokinase (EC 2.7.1.11)
• LSU ribosomal protein L31p
• cell division protein FtsZ
• Inclusion of gene in subsystem is only by functional role
• Controlled vocabulary …
www.nmpdr.org
Expert-Defined Subsystems
• Curator is researcher with first-hand knowledge of
biological system
• Functional roles defined and grouped into
subsystem and subsets by curator
 universal groups of roles include all organisms
 functional variants are subsets of roles found in a
limited number of organisms
• often represent alternative paths or nonorthologous replacement
• Semi-automated assignment of function based on
manual groundwork, sequence homology, and
functional clustering
www.nmpdr.org
Subsystem Primer
• Describe your subsystem in 150 words or less—why should these
functions be considered together?
 define the emergent properties of the system
• Provide or link to a diagram that illustrates this subsystem
 define the graph or network
• List the reactions or relationships between these functional roles
 define the edges
• List the exact names and abbreviations of these functional roles
 define the nodes
• List the id numbers (GenBank, SwissProt—any identifying alias) of
genes that play these roles in one or more exemplar genomes
 examples of nodes
• Provide one or more references that support the assignment of
function for the exemplar genes
 provide evidence
www.nmpdr.org
Populated Subsystems
• Two-dimensional integration of functional
roles with genomes
• Spreadsheet
 Columns of functional roles
 Rows of organisms
 Cells of annotated genes
• Table of functional roles with GO terms
• Diagram
• Curator notes and citations
www.nmpdr.org
Simple Example:
Histidine Degradation Subsystem
• Conversion of histidine to glutamate is organizing
principle
• Functional roles defined in table:
Subsystem: Histidine Degradation
1
2
3
4
5
6
7
HutH
HutU
HutI
GluF
HutG
NfoD
ForI
Histidine ammonia-lyase (EC 4.3.1.3)
Urocanate hydratase (EC 4.2.1.49)
Imidazolonepropionase (EC 3.5.2.7)
Glutamate formiminotransferase (EC 2.1.2.5)
Formiminoglutamase (EC 3.5.3.8)
N-formylglutamate deformylase (EC 3.5.1.68)
Formiminoglutamic iminohydrolase (EC 3.5.3.13)
www.nmpdr.org
Subsystem Diagram
• Three functional variants
• Universal subset has three roles, followed
by three alternative paths from IV to VI
www.nmpdr.org
Subsystem Spreadsheet
Subsystem Spreadsheet
Organism
Variant
HutH
HutU
HutI
GluF
HutG
NfoD
Bacteroides thetaiotaomicron
1
Q8A4B3
Q8A4A9
Q8A4B1
Q8A4B0
Desulfotela psychrophila
1
gi51246205
gi51246204
gi51246203
gi51246202
Halobacterium sp.
2
Q9HQD5
Q9HQD8
Q9HQD6
Q9HQD7
Deinococcus radiodurans
2
Q9RZ06
Q9RZ02
Q9RZ05
Q9RZ04
Bacillus subtilis
2
P10944
P25503
P42084
P42068
Caulobacter crescentus
3
P58082
Q9A9MI
P58079
Q9A9M0
Pseudomonas putida
3
Q88CZ7
Q88CZ6
Q88CZ9
Q88D00
Xanthomonas campestris
3
Q8PAA7
P58988
Q8PAA6
Q8PAA8
Listeria monocytogenes
-1
•
•
•
•
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Column headers taken from table of functional roles
Rows are selected genomes, or organisms
Cells are populated with specific, annotated genes
Shared background color indicates proximity of genes
Functional variants defined by the annotated roles
Variant code -1 indicates subsystem is not functional
www.nmpdr.org
ForI
Missing Genes Noticed by
Subsystems Annotation
• No genes were annotated “ForI (EC 3.5.3.13)
Formiminoglutamic iminohydrolase” when the
Histidine Degradation subsystem was
populated
• Organisms missing ForI convert His to Glu
• Candidate genes that could perform the role
“ForI” must be identified
• Strategy for finding genes is based on
chromosomal clustering and occurrence
profiling
www.nmpdr.org
Finding Genes that Cluster with NfoD
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•
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•
•
Red gene in graphic and table is NfoD of Xanthomonas
Genes pictured in gray boxes located nearby NfoD in four or more species
Advanced controls expands display of homologous regions in other genomes
Functional Coupling score links to table of homologous pairs in other genomes
Cluster button finds biggest clusters in other species when not clustered in
subject genome
www.nmpdr.org
What are Pinned Regions?
• Focus gene is number 1, colored red
• Most frequently co-localized homolog numbered
2, colored green
• Sets of homologous genes presented in the same
color with the same numerical label; BLASTP cutoff e-val = 1e-20
• Numerical labels correspond to rank-ordered
frequency of co-localization with the focus gene
• Number of regions, size of region, and cut-off can
be re-set by user
www.nmpdr.org
Candidate ForI in Context with NfoD
• Compare Regions
around NfoD, red,
center
• HutC, the regulator,
is green, 2
 HutH, the first
functional role in the
subsystem, is blue,
4
 Candidate ForI is
teal, 6, originally
annotated as
“conserved
hypothetical”
www.nmpdr.org
Annotation of ForI EC 3.5.3.13
• Metabolic context proves need for role
 Organisms missing annotated ForI degrade His to Glu
• Chromosomal context points to candidate
 Clusters with NfoD and other genes in subsystem
• Occurrence context supports candidate
 Organisms containing NfoD lack GluF and HutG,
required for functional variants 1 and 2, respectively
 Organisms containing candidate ForI also contain NfoD,
indicating functional variant 3
• Phylogenetic trees of candidate ForI genes are
coherent
www.nmpdr.org
Subsystems Allow Bioinformatics
to Inform Bench Research
• Subsystems point to missing or alternative
genes
• Bioinformatic predictions need to be tested
at the bench
• ForI candidate now verified experimentally
• Connections forged between bench and
bioinformatics
www.nmpdr.org
How is NMPDR distinct from NCBI?
• Corrected, functional annotations, manually curated in
context of systems biology
• Multiple starting points for accessing data
 gene or protein name, subsystem, organism
• Search results downloadable as names or sequences
• Interactive tools for comparative analysis
 Compare regions—adjust size of region, number of genomes
 Subsystems—browse phylogenetic distribution of biological system;
color spreadsheet and diagram
 Functional clusters—find genes with conserved proximity
 BLASTP Hits—select and align interesting sequences
 Signature genes—find genes in common or that distinguish userselected groups of genomes; groups may contain one or many
www.nmpdr.org
Exploration of physical, genomic context
• Compare Regions graphic
 Focus protein highlighted red
 Color-matched orthlogs allow comparative analysis of functional
clustering and chromosomal rearrangements
 Redraw the display with different number of genomes or different size
region
• Compare Regions table
 Table is sortable and filterable with active column headings
 Genes with conserved proximity shown with functional coupling
scores, fc-sc
• fc-sc (functional coupling score)
 Measures conservation of gene proximity and phylogenetic distance
 Link returns table listing pairs of proximal orthologs
• CL (find best clusters)
 Finds clusters containing the focus protein in other genomes
 Useful for genes without functional coupling scores, fc-sc
www.nmpdr.org
Exploration of functional, biological context
• Populated Subsystem Spreadsheet
 Columns represent functional roles, mouse over header for
definition
 Genomes (rows) shown may be filtered and sorted by
name or taxonomic group
 Cells populated with specific, annotated genes linked to
context pages
 Functional variants defined by the annotated roles
 Variant codes defined in notes tab
 Diagram of subsystem often provided
• Protein families
 FIGfams taken from single column of functional roles
 Links to structures, orthologs, literature
www.nmpdr.org
NMPDR Services
• Essential Genes on Genomic Scale
 Experimentally verified in genome-wide scans of 10 important model
organisms
• Drug targets pipline to in silico screening
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essential in at least one of the NMPDR pathogens
included in subsystems by our curators
orthologs in the Protein Data Bank
orthologs in a substantial number of bacterial priority pathogens
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physical characteristics such as MW, pI
subcellular location
transmembrane regions and signal peptides
subsystem, pathway, reaction
structural motifs, protein families
• Targets search: flexible search forms for discovering
novel targets based on computed attributes
www.nmpdr.org
Related NMPDR Services
• RAST Genome annotation server
 Automated annotation of essentially complete genome sequences in a
small set of long sequence contigs
 View results in comparative context with other genomes
• MG-RAST Metagenome annotation server
 Automated annotation of a very large set of very short DNA
sequences
 View results in comparative context with other data sets
• Annotation Clearinghouse
 Tool to credit experts with annotation of specific genes and to share
annotations with other databases
 Input is a two-column table of gene IDs and annotations vouched for
by expert
www.nmpdr.org
Who is NMPDR?
• Fellowship for Interpretation of Genomes (FIG)
Ross Overbeek, Veronika Vonstein, Gordon Pusch, Bruce Parrello, Rob
Edwards, Andrei Osterman, Michael Fonstein, Svetlana Gerdes, Olga
Zagnitko, Olga Vassieva, Yakov Kogan, Irina Goltsman
• Argonne National Laboratory
Rick Stevens, Terry Disz, Robert Olson, Folker Meyer, Elizabeth Glass,
Chris Henry, Jared Wilkening
• Computation Institute at University of Chicago
Daniela Bartels, Michael Kubal, William Mihalo, Tobias Paczian, Andreas Wilke,
Alex Rodriguez, Mark D'Souza, Rami Aziz
• University of Illinois at Urbana; Hope College
Gary J. Olsen, Claudia Reich, Leslie McNeil; Aaron Best, Matt DeJongh
• National Institute of Allergy and Infectious Diseases
National Institutes of Health, Department of Health and Human
Services, Contract HHSN266200400042C.
www.nmpdr.org