Human Reference Interactome (HuRI) mapping

PRIMARY OUTCOME

Comprehensive binary protein-protein interaction network

EXPECTED OUTCOMES

- 1. Primary: Generate >50,000 high-confidence binary protein-protein interactions representing 4-fold increase over existing curated datasets - 2. Secondary: Achieve >12,000 proteins covered in the interaction network (>60% of tested human proteome) - 3. Validation rate: >70% of tested high-confidence interactions confirmed by orthogonal biochemical methods - 4. Novel discoveries: >80% of identified interactions not present in existing curated databases (BioGRID, STRING) - 5. Disease relevance: Significant enrichment of disease genes in network hubs and modules (p < 10^-5, hypergeometric test) - 6. Network properties: Scale-free topology with γ exponent 2.0-3.0 and high clustering coefficient (>0.1) - 7. Functional coherence: >60% of interaction partners share at least one Gene Ontology biological process annotation

SUCCESS CRITERIA

- • Interaction quality: >95% of reported interactions pass reciprocal testing and autoactivation controls - • Reproducibility: >90% of interactions detected in ≥2 independent experimental replicates - • Clone validation: >95% sequence accuracy for expression clones with correct ORF representation - • Coverage metrics: Successfully test >85% of planned protein pairs with <15% technical failures - • Database quality: <5% false positive rate estimated through comparison with negative control datasets - • Experimental validation: >65% confirmation rate for selected interactions using co-immunoprecipitation assays - • Network coherence: Significant functional enrichment (FDR < 0.01) in >50% of identified network modules

PROTOCOL

**Phase 1: Human Protein Library Construction and Validation** — Month 1-3 Clone ~17,500 human protein-coding genes into Gateway-compatible entry vectors using high-throughput PCR amplification. Design gene-specific primers with Gateway attB sites flanking full-length ORFs from human cDNA libraries (Mammalian Genome Collection, Harvard Medical School). Perform BP recombination reactions to generate pENTR223 entry clones using Gateway BP Clonase II (Thermo Fisher 11789020). Sequence verify >95% of clones using 96-well format sequencing. Create DB (DNA-binding domain) and AD (activation domain) expression clones by LR recombination into pDEST32 and pDEST22 destination vectors respectively. Transform into electrocompetent E. coli DH5α cells and select on spectinomycin (DB) or ampicillin (AD) plates. Archive clones in 384-well glycerol stock format at -80°C. **Phase 2: Yeast Strain Preparation and Mating Setup** — Month 3-4 Transform DB constructs into MATa yeast strain Y8930 (genotype: MATa trp1-901 leu2-3,112 ura3-52 his3-200 gal4Δ gal80Δ GAL2-ADE2 LYS2::GAL1-HIS3 met2::GAL7-lacZ cyh2R) using lithium acetate protocol. Transform AD constructs into MATα strain Y8800 (genotype: MATα trp1-901 leu2-3,112 ura3-52 his3-200 gal4Δ gal80Δ GAL2-ADE2 LYS2::GAL1-HIS3 met2::GAL7-lacZ) using identical protocol. Select transformants on synthetic defined (SD) medium lacking tryptophan (-Trp) for DB clones and lacking leucine (-Leu) for AD clones. Validate transformation efficiency >70% and maintain individual clone arrays in 1536-well format. Perform systematic mating using robotic pin tools to cross each DB clone with each AD clone, creating ~53,000 unique diploid combinations on SD medium lacking both tryptophan and leucine (-Trp-Leu). **Phase 3: High-throughput Y2H Screening** — Month 4-8 Screen mated diploids for protein-protein interactions using three-step selection process: (1) Growth on SD medium lacking tryptophan, leucine, and histidine (-Trp-Leu-His) supplemented with 1 mM 3-amino-1,2,4-triazole (3-AT) to reduce background; (2) Growth on SD medium lacking tryptophan, leucine, histidine, and adenine (-Trp-Leu-His-Ade); (3) β-galactosidase activity using X-gal overlay assay. Include positive controls (known interacting protein pairs) and negative controls (empty vectors, non-interacting pairs) on each plate. Use automated imaging system to score growth and blue color development after 3-5 days incubation at 30°C. Implement statistical scoring algorithm considering growth intensity, color development, and reproducibility across technical replicates. **Phase 4: Interaction Validation and Quality Assessment** — Month 8-10 Validate initial positive interactions through retransformation and retesting in fresh yeast strains. Perform reciprocal testing by swapping DB and AD fusion orientations for each positive interaction. Test interactions at multiple 3-AT concentrations (0.5, 1, 2.5, 5 mM) to assess interaction strength. Eliminate interactions showing autoactivation by testing individual DB and AD clones against empty vectors. Sequence verify all positive clones to confirm correct gene identity and rule out sequence artifacts. Implement computational filters to remove likely false positives based on protein domain analysis, subcellular localization predictions, and literature curation. Apply additional quality filters: remove interactions involving proteins with >10 interaction partners (potential sticky proteins) and interactions not reproducible in technical triplicates. **Phase 5: Computational Analysis and Network Construction** — Month 10-11 Compile final high-confidence interaction dataset after applying all quality filters. Compare with existing curated interaction databases (BioGRID, STRING, HPRD) to assess overlap and identify novel interactions. Perform network topology analysis calculating degree distribution, clustering coefficient, betweenness centrality, and identification of network modules using community detection algorithms (Louvain method). Annotate interactions with Gene Ontology terms, KEGG pathways, and protein domain information from InterPro. Conduct enrichment analysis to identify overrepresented biological processes, molecular functions, and cellular components among interacting proteins. Generate interaction confidence scores based on experimental evidence strength, literature support, and orthology to known interactions in model organisms. **Phase 6: Disease Gene Analysis and Validation** — Month 11-12 Map Mendelian disease genes from OMIM database onto the interaction network to identify disease modules and pathways. Perform network-based analysis of gene sets associated with specific diseases (cancer, neurological disorders, metabolic diseases) using random walk algorithms and module identification methods. Validate selected high-confidence interactions using orthogonal methods: co-immunoprecipitation in mammalian cells (HEK293T), GST pull-down assays, and bimolecular fluorescence complementation (BiFC). Select 100 representative interactions spanning different confidence levels and functional categories for experimental validation. Calculate network coverage statistics and estimate total number of human protein-protein interactions. Perform comparative analysis with interaction networks from model organisms (yeast, fly, worm) to assess evolutionary conservation of interaction patterns. Create web-accessible database with search functionality and network visualization tools.

HTML iframe

<iframe src="http://scidex.ai/artifact/exp-7f9e8410-a720-4b45-93ff-112f7ee16e46?embed=1" width="100%" height="600" style="border:0;border-radius:8px"></iframe>

Markdown link

[Human Reference Interactome (HuRI) mapping](http://scidex.ai/artifact/exp-7f9e8410-a720-4b45-93ff-112f7ee16e46)

Direct URL

http://scidex.ai/artifact/exp-7f9e8410-a720-4b45-93ff-112f7ee16e46

Preview