1. PathoLogic Pathway Predictor

2. Inference of Metabolic Pathways
Annotated Genomic
Sequence
Pathway/Genome
Database
Genes/ORFs
Gene Products
DNA Sequences
Pathways
Reactions
PathoLogic Software
Integrates genome and pathway data to identify putative metabolic networks
Compounds
Multi-organism Pathway
Database (MetaCyc)
Gene Products
Reactions
Pathways
Compounds
Genes
Genomic Map

3. PathoLogic Functionality
Initialize schema for new PGDB
Transform existing genome to PGDB form
Infer metabolic pathways and store in PGDB
Infer operons and store in PGDB
Assemble Overview diagram
Assist user with manual tasks
Assign enzymes to reactions they catalyze
Identify false-positive pathway predictions
Build protein complexes from monomers
Infer transport reactions
Fill pathway holes
Note PathoLogic can be run from command line

4. Overview of Metabolic Pathway Inference

5. PathoLogic Step 3: Metabolic Reconstruction
Phase I: Qualitative metabolic reconstruction (PathoLogic)
Inference of the reactome from the annotated genome
Inference of metabolic pathways by selecting from MetaCyc pathways
Karp et al, Stand Genomic Sci, :424
Phase II: Quantitative model construction (MetaFlux)
Infer biomass metabolites, nutrients
Gap fill reaction network
Modify reaction complement until biomass metabolites producible from nutrients
Solve model, assess computed fluxes
Iterate
Karp et al, Briefings in Bioinformatics 2015
Dale et al, BMC Bioinformatics :15

6. MetaCyc: Curated Metabolic Database
MetaCyc v
KEGG
2013
SEED
2015
Citations
45,000
Pathways
2,310
179
Modules
583
Subsystems
Reactions
12,400
8,692
Metabolites
12,000
Mini-reviews: Textbook Pages
6,300
“A Systematic Comparison of the MetaCyc and KEGG Pathway Databases
BMC Bioinformatics (1):112

7. Pathway Prediction Pathway prediction is useful because
Pathways organize the metabolic network into tractable units
Pathways guide us to search for missing enzymes
Pathways can be used for analysis of high-throughput data
Visualization, enrichment analysis
Pathway inference fills gaps in metabolic network
Reduces computational demands of gap filling
Pathway prediction is hard because
Reactome inference is imperfect
Some reactions present in multiple pathways
Pathway variants share many reactions in common
Increasing size of MetaCyc

8. Reactome Inference
For each protein in the organism, infer reaction(s) it catalyzes
Build from existing genome annotation!
Match protein functions to MetaCyc reactions
Enzyme names (uncontrolled vocabulary)
EC numbers
Gene Ontology terms

9. PathoLogic Enzyme Name Matcher
Name matcher generates alternative variants of each name and matches each to MetaCyc
Strips extraneous information found in enzyme names
Putative carbamate kinase, alpha subunit
Flavin subunit of carbamate kinase
Cytoplasmic carbamate kinase
Carbamate kinase (abcD)
Carbamate kinase ( )

10. Algorithm for Inference of Metabolic Pathways
For each pathway in MetaCyc consider
For what fraction of its reactions are enzymes present in the organism?
Are enzymes present for reactions unique to the pathway?
Is a given pathway outside its designated taxonomic range?
Calvin cycle: green plants, green algae, etc
Are enzymes present for designated “key reactions” within MetaCyc pathways?
Calvin cycle / ribulose bisphosphate carboxylase
Standards in Genomic Sciences 5:

11. New Addition: Pathway Score
PS : Pathway Score [0,1]
R : Set of reactions within pathway
Ignore spontaneous reactions
RS : Reaction Score for a given reaction
T : Boost if organism is within taxonomic range of pathway

12. Reaction Score RS = P + U + K P = presence score
0.2 if enzyme catalyzing rxn is present
Else 0
U = uniqueness score
Ranges from 0.6 (rxn present in single pathway) to 0 (many pathways)
K = key reaction score
0.5 if rxn is a key reaction of the pathway

13. Pathway Decision Procedure for Pathway P
REJECT P if P is a transport, signaling, or synthetic (engineered) pathway
REJECT P if P is an electron transport pathway AND P lacks enzymes for any reaction
INCLUDE P if P has all reactions present (meaning an enzyme is present for each reaction) AND if P is outside its taxonomic range, P contains more than 3 reactions
REJECT P if P is outside its taxonomic range
REJECT P if P is missing enzymes for all key reactions of P

14. Decision Procedure
REJECT P if the score of P is significantly less than the score of a variant pathway of P
INCLUDE P if the score of P exceeds the threshold PATHWAY-PREDICTION-SCORE-CUTOFF
Defined in ptools-init.dat
Default decision: REJECT

15. PathoLogic Analysis Phases
Trial parsing of input data files -- fix errors
Initialize schema of new PGDB (automatic)
Create DB objects for replicons, genes, proteins (automatic)
Assign enzymes to reactions they catalyze (part automatic, part manual)
From assigned reactions, infer what pathways are present (automatic, with manual review)

16. PathoLogic Analysis Phases
Define metabolic overview diagram (automatic, redo after changing data)
Define protein complexes (manual)
Define transcription units (automatic)
Infer transport reactions (manual review necessary)
Fill Pathway Holes (manual review necessary)

17. PathoLogic Input/Output
Inputs:
List of all genetic elements
Enter using GUI or provide a file
Files containing annotation for each genetic element
Files containing DNA sequence for each genetic element
MetaCyc database
Output:
Pathway/genome database for the subject organism
Reports that summarize:
Evidence in the input genome for the presence of reference pathways
Reactions missing from inferred pathways

18. File Naming Conventions
One pair of sequence and annotation files for each genetic element
Sequence files: FASTA format
suffix fsa or fna
Annotation file:
Genbank format: suffix .gbk
PathoLogic format: suffix .pf

19. Typical Problems Using Genbank Files With PathoLogic
Wrong qualifier names used: read PathoLogic documentation!
Extraneous information in a given qualifier
Check results of trial parse carefully

20. GenBank File Format Accepted feature types: CDS, tRNA, rRNA, misc_RNA
Accepted qualifiers:
/locus_tag Unique ID [recm]
/gene Gene name [req]
/product [req]
/EC_number [recm]
/product_comment [opt]
/gene_comment [opt]
/alt_name Synonyms [opt]
/pseudo Gene is a pseudogene [opt]
/db_xref DB:AccessionID [opt]
/go_component, /go_function, /go_process GO terms [opt]
For multifunctional proteins, put each function in a separate /product line

21. PathoLogic File Format
Each record starts with line containing an ID attribute
Tab delimited
Each record ends with a line containing //
One attribute-value pair is allowed per line
Use multiple FUNCTION lines for multifunctional proteins
Lines starting with ‘;’ are comment lines
Valid attributes are:
ID, NAME, SYNONYM
STARTBASE, ENDBASE, GENE-COMMENT
FUNCTION, PRODUCT-TYPE, EC, FUNCTION-COMMENT
DBLINK GO
INTRON

22. PathoLogic File Format
ID TP0734
NAME deoD
STARTBASE
ENDBASE
FUNCTION purine nucleoside phosphorylase
DBLINK PID:g
PRODUCT-TYPE P
GENE-COMMENT similar to GP: percent identity: 57.51; identified by sequence similarity; putative //
ID TP0735
NAME gltA
STARTBASE
ENDBASE
FUNCTION glutamate synthase
DBLINK PID:g
GO glutamate synthase (NADPH) activity [goid ] [evidence IDA] [pmid ]

23. Before you start: What to do when an error occurs
Most Navigator errors are automatically trapped – debugging information is saved to error.tmp file.
All other errors (including most PathoLogic errors) will cause software to drop into the Lisp debugger
Unix: error message will show up in the original terminal window from which you started Pathway Tools.
Windows: Error message will show up in the Lisp console. The Lisp console usually starts out iconified – its icon is a blue bust of Franz Liszt
2 goals when an error occurs:
Try to continue working
Obtain enough information for a bug report to send to pathway-tools support team.

24. The Lisp Debugger
Sample error (details and number of restart actions differ for each case)
Error: Received signal number 2 (Keyboard interrupt)
Restart actions (select using :continue):
0: continue computation
1: Return to command level
2: Pathway Tools version 10.0 top level
3: Exit Pathway Tools version 10.0
[1c] EC(2):
To generate debugging information (stack backtrace):
:zoom :count :all
To continue from error, find a restart that takes you to the top level – in this case, number 2
:cont 2
To exit Pathway Tools:
:exit

25. How to report an error
Determine if problem is reproducible, and how to reproduce it (make sure you have all the latest patches installed)
Send to containing:
Pathway Tools version number and platform
Description of exactly what you were doing (which command you invoked, what you typed, etc.) or instructions for how to reproduce the problem
error.tmp file, if one was generated
If software breaks into the lisp debugger, the complete error message and stack backtrace (obtained using the command :zoom :count :all, as described on previous slide)

26. PathoLogic Command Menus
Invoking PathoLogic:
Tools -> PathoLogic
Organism
Select
Create New
Save KB
Revert KB
Reinitialize KB
Convert File KB to Oracle KB
Convert File KB to MySQL KB
Backup KB to File
New Version
Specify Reference PGDB(s)
Exit
Build
Trial Parse
Automated Build
Update Build for Revised Annotation
Refine
Assign Probable Enzymes
Assign Modified Proteins
Create Protein Complexes
Re-run Name Matcher
Rescore Pathways
Predict transcription units
Transport Identification Parser
Update Overview
Pathway Hole Filler

27. Using the PPP GUI to Create a Pathway/Genome Database
Input Project Information
Organism -> Create New
Creates directory structure for new PGDB
Creates and saves empty PGDB, populated only with objects common to all PGDBs (schema classes, elements, etc.) and data you entered in the form.
Offers to invoke Replicon Editor

28. Input Project Information

29. Enter Replicon Information
For each replicon
Name
Type: chromosome, plasmid, etc.
Circular?
Annotation file
Sequence file (optional)
Contigs (optional)
Links to other DBs (optional)
GUI-Based entry
Build->Specify Replicons
File-Based Entry
Create genetic-elements.dat file using template provided

30. GUI-Based Replicon Entry

31. Batch Entry of Replicon Info
File /<orgid>cyc/<version>/input/genetic-elements.dat:
ID TEST-CHROM-1
NAME Chromosome 1
TYPE :CHRSM
CIRCULAR? N
ANNOT-FILE chrom1.pf
SEQ-FILE chrom1.fsa //
ID TEST-CHROM-2
NAME Chromosome 2
ANNOT-FILE /mydata/chrom2.gbk
SEQ-FILE /mydata/chrom2.fna

32. Specify Reference PGDB(s)
This step is optional, and most users will omit it
MetaCyc is always the primary reference PGDB
Specify additional reference PGDB if you have your own curated PGDB which has:
Pathways and/or reactions that are not in MetaCyc
Manual functional assignments, with names similar to current genome
There is no point specifying any of our PGDBs as references, only your own curated PGDBs.

33. Building the PGDB Trial Parse Build -> Trial Parse
Check output to ensure numbers “look right”
Same number of gene start positions, end positions, names
Did my file contain EC numbers? Were they detected?
Did my file contain RNAs? Were they detected?
Fix any errors in input files
Build pathway/genome database
Build -> Automated Build

34. PathoLogic Parser Output

35. Automated Build Parses input files
Creates objects for every gene and gene product
Uses EC numbers, GO annotations and name matcher to match enzymes to reactions in MetaCyc
Imports catalyzed enzymes and compounds from MetaCyc
Generates list of likely enzymes that couldn’t be assigned
Infers pathways likely to be present
Generates Cellular Overview Diagram (first pass)
Generates reports

36. Assign Enzymes to Reactions
Gene product
MetaCyc
UDP-glucose-4-epimerase
Match
yes no
Probable enzyme
-ase
Assign
UDP-D-glucose  UDP-galactose no
yes
Manually search
Not a metabolic enzyme no
yes
Assign
Can’t Assign

37. Enzyme Name Matcher
For names that do not match, software identifies probable metabolic enzymes as those
Containing “ase”
Not containing keywords such as
“sensor kinase”
“topoisomerase”
“protein kinase”
“peptidase”
Etc
User should research unknown enzymes
MetaCyc, Swiss-Prot, PubMed

38. Stored in ORGIDcyc/VERSION/reports/name-matching-report.txt

39. Pathway Evidence Report
On Organism Summary Page in Navigator, button “Generate Pathway Evidence Report”
Report saved as HTML file, view in browser
Hierarchical listing of all inferred pathways
“Pathway Glyph” shows evidence graphically
Steps with/without enzymes (green/black)
Steps that are unique to pathway (orange)
Steps filled by Pathway Hole Filler (blue)
Counts reactions in pathway, with evidence, in other pathways
Lists other pathways that share reactions
Link to pathway in MetaCyc

41. Manual Pruning of Pathways
Use pathway evidence report
Coloring scheme aids in assessing pathway evidence
Phase I: Prune extra variant pathways
Rescore pathways, re-generate pathway evidence report
Phase II: Prune pathways unlikely to be present
No/few unique enzymes
Most pathway steps present because they are used in another pathway
Pathway very unlikely to be present in this organism
Nonspecific enzyme name assigned to a pathway step

42. Caveats Cannot predict pathways not present in MetaCyc
Evidence for short pathways is hard to interpret
Since many reactions occur in multiple pathways, some false positives

43. Output from PPP Pathway/genome database Summary pages
Pathway evidence page
Click “Summary of Organisms”, then click organism name, then click “Pathway Evidence”, then click “Save Pathway Report”
Missing enzymes report
Directory tree containing sequence files, reports, etc.

44. Resulting Directory Structure
ROOT/ptools-local/pgdbs/user/ORGIDcyc/VERSION/
input
organism.dat
organism-init.dat
genetic-elements.dat
annotation files
sequence files
reports
name-matching-report.txt
trial-parse-report.txt kb
ORGIDbase.ocelot
data
overview.graph
released -> VERSION

45. Manual Polishing Refine -> Assign Probable Enzymes  Do this first
Refine -> Rescore Pathways  Redo after assigning enzymes
Refine -> Create Protein Complexes  Can be done at any time
Refine -> Assign Modified Proteins  Can be done at any time
Refine -> Transport Identification Parser  Can be done at any time
Refine -> Pathway Hole Filler
Refine -> Predict Transcription Units
Refine -> Update Overview  Do this last, and repeat after any material changes to PGDB

46. Assign Probable Enzymes

47. How to find reactions for probable enzymes
First, verify that enzyme name describes a specific, metabolic function
Search for fragment of name in MetaCyc – you may be able to find a match that PathoLogic missed
Look up protein in UniProt or other DBs
Search for gene name in PGDB for related organism (bear in mind that gene names are not reliable indicators of function, so check carefully)
Search for function name in PubMed
Other…