Sixing Huang - MGI Neo4j Health Care & Life Sciences Workshop 2021

1. Neo4j for Bacterial Genomes
Sixing Huang
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2. Talk Overview
• How to do Neo4j bioinformatics on a local computer with public data
• Three use cases:
ofor genome analyses
ofor Carbohydrate-active enzymes
ofor antibiotic resistance in CARD
• Conclusions
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Genes
Genomes Phenotypes
Degrade cellulose
Resist cephalosporin
Transport Fe2+

3. About me – Sixing Huang
• Studied biology and bioinformatics in Bremen.
• Worked as a bioinformatic data scientist in DSZM Braunschweig.
• Now as a bioinformatic scientist in MGI Shenzhen.
• First contact with Neo4j in 2019.
• Now use Neo4j for knowledge management, genome browser and
database and write about my Neo4j journey in medium.com.
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4. Genomes have structures
• Genes are more than a bag of words.
• Neo4j can model genome structures.
Gene1 Gene2 Gene3
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5. Neo4j as a genome browser
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EMBL file Neo4j genome browser
Import

6. Gene CAZy clusters and annotations
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MATCH p=(f0:Gene) -[:NEXT*5] -> (f1:Gene) -[:NEXT*5] ->(f2:Gene)
WHERE f1.name =~ '.+GH16[^a-zA-Zds:]*'
Neo4j Commander

7. Bacterial genome data
Data in biological studies
Genome1 3 4 1 0 1 0 1 3 2 1 3 2 1
Genome2 2 1 3 1 3 0 1 3 2 1 4 1 2
Genes
Neo4j can compare core and pan genomes effectively.
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8. Heavy use of orthology
Taxonomy
Phylum
Class1 Class2
Order1 Order2 Order3
Genome1 Genome2 Genome3 Genome4
KEGG Gene annotation
Metabolism
Carbohydrate
metabolism
Glycolysis /
Gluconeogenesis
alcohol
dehydrogenase
K00001
Lipid metabolism
Fatty acid
degradation
acyl-CoA
dehydrogenase
K06445
hexokinase
K00844
Neo4j can model orthology intuitively.
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9. Neo4j for genome analyses
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Taxonomy
Gene
annotation

10. Chromobacterium sp. ATCC 53434
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KO in sisters as filter
KO in 53434 - filter
Unique KO in 53434

11. Unique KO in ATCC 53434
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KO Annotation
K04783 yersiniabactin salicyl-AMP ligase [EC:6.3.2.-]
K04784 yersiniabactin nonribosomal peptide synthetase
K12241 pyochelin biosynthesis protein PchG
K12242 pyochelin biosynthesis protein PchC
K13255 ferric iron reductase protein FhuF
K23227
ferric hydroxamate transport system substrate-
binding protein
K23228
ferric hydroxamate transport system permease
protein
K10829
ferric hydroxamate transport system ATP-binding
protein [EC:7.2.2.16]
siderophore
siderophore
ferric hydroxamate transport
Hypothesis: ATCC 53434 has a unique repertoire of iron related transport proteins.

12. Phylogeny made easy
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Order by numbers of shared KO
Compute the shared KO
Name Shared KO
Chromobacterium vaccinii 1869
Chromobacterium sp. IIBBL 112-1 1867
Chromobacterium rhizoryzae 1777
Chromobacterium haemolyticum 1776
Chromobacterium sp. 257-1 1723

13. Neo4j for Carbohydrate-active EnZYmes:
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Reannotation of Formosa agariphila KMM 3901
CAZy Annotation
PL28 ulvan lyase
PL37 ulvan lyase
GH28 polygalacturonase
GH78 alpha-L-rhamnosidase
GH105 unsaturated rhamnogalacturonyl hydrolase
GH86 beta-agarase
Gh168 endo-alpha-(1,3)-L-fucanase
Unique CAZy not in sister genomes
Visualization
degrade
ulvan
degrade
pectin
degrade sulfated
polysaccharide
unique agarolytic life strategy

14. Node classification: Predict cellulose degradation
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CV: Training: 0.67; Testing: 0.65
CAZy annotated genomes
annotated with cellulose degradability
Holdout
Embedding

15. Deploy on holdout genomes
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Predicted cellulose degrader Confirmed
Micromonospora carbonacea africana ✓
Micromonospora sp. HM134 X
Streptacidiphilus sp. P02-A3a
Streptomyces prasinus ATCC 13879 ?
Streptomyces sp. CB01881
Streptomyces sp. SirexAA-E ✓
Streptomyces venezuelae ATCC 15439
Streptomyces venezuelae ATCC 21113
Xanthomonas citri pv. citri UI7 ✓
Xenorhabdus budapestensis C72
Kitasatospora sp. MMS16-BH015
CAZy annotated genomes
Holdout
Prediction
Results

16. GraphQL for non-Neo4j users
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17. Antibiotic resistance with CARD
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Fluoroquinolone resistance Cephalosporin resistance

18. Conclusions
• Neo4j can serve as an all-in-one genome browser, a biodata
warehouse and a data mining tool.
• It can deliver insights more quickly than relational database + SQL
• Built-in machine learning can predict new connections and properties
• GraphQL serves data for non-Neo4j users
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19. Acknowledgement
• Hanno Teeling (MPI Bremen)
• The Neo4j Community
• MGI (BGI)
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