Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data.
Xi ChenYuan WangAntonio CappuccioWan-Sze ChengFrederique Ruf ZamojskiVenugopalan D NairClare M MillerAliza B RubensteinGerman NudelmanAlicja TadychChandra L TheesfeldAlexandria VornholtMary-Catherine GeorgeFelicia RuffinMichael DagherDaniel G ChawlaAlessandra Soares-SchanoskiRachel R SpurbeckLishomwa C NdhlovuRobert SebraSteven H KleinsteinAndrew G LetiziaIrene RamosVance G FowlerChristopher W WoodsElena ZaslavskyOlga G TroyanskayaStuart C SealfonPublished in: Nature computational science (2023)
Resolving chromatin-remodeling-linked gene expression changes at cell-type resolution is important for understanding disease states. Here we describe MAGICAL (Multiome Accessibility Gene Integration Calling and Looping), a hierarchical Bayesian approach that leverages paired single-cell RNA sequencing and single-cell transposase-accessible chromatin sequencing from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regulatory circuits. By simultaneously modeling signal variation across cells and conditions in both omics data types, MAGICAL achieved high accuracy on circuit inference. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single-cell data that we generated from subjects with bloodstream infection and uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be activated by bacterial sepsis. We addressed the challenging problem of distinguishing host regulatory circuit responses to methicillin-resistant and methicillin-susceptible S. aureus infections. Although differential expression analysis failed to show predictive value, MAGICAL identified epigenetic circuit biomarkers that distinguished methicillin-resistant from methicillin-susceptible S. aureus infections.
Keyphrases
- single cell
- staphylococcus aureus
- transcription factor
- gene expression
- rna seq
- genome wide identification
- peripheral blood
- genome wide
- high throughput
- methicillin resistant staphylococcus aureus
- acute kidney injury
- dna methylation
- electronic health record
- intensive care unit
- biofilm formation
- septic shock
- dna binding
- dna damage
- high resolution
- hiv infected
- induced apoptosis
- cell cycle arrest
- copy number
- oxidative stress
- klebsiella pneumoniae
- cell proliferation
- cell death
- multidrug resistant
- signaling pathway