Integrating GWAS with bulk and single-cell RNA-sequencing reveals a role for LY86 in the anti-Candida host response.
Dylan H de VriesVasiliki MatzarakiOlivier B BakkerHarm BruggeHarm-Jan WestraMihai G NeteaLude FrankeVinod KumarMonique G P van der WijstPublished in: PLoS pathogens (2020)
Candida bloodstream infection, i.e. candidemia, is the most frequently encountered life-threatening fungal infection worldwide, with mortality rates up to almost 50%. In the majority of candidemia cases, Candida albicans is responsible. Worryingly, a global increase in the number of patients who are susceptible to infection (e.g. immunocompromised patients), has led to a rise in the incidence of candidemia in the last few decades. Therefore, a better understanding of the anti-Candida host response is essential to overcome this poor prognosis and to lower disease incidence. Here, we integrated genome-wide association studies with bulk and single-cell transcriptomic analyses of immune cells stimulated with Candida albicans to further our understanding of the anti-Candida host response. We show that differential expression analysis upon Candida stimulation in single-cell expression data can reveal the important cell types involved in the host response against Candida. This confirmed the known major role of monocytes, but more interestingly, also uncovered an important role for NK cells. Moreover, combining the power of bulk RNA-seq with the high resolution of single-cell RNA-seq data led to the identification of 27 Candida-response QTLs and revealed the cell types potentially involved herein. Integration of these response QTLs with a GWAS on candidemia susceptibility uncovered a potential new role for LY86 in candidemia susceptibility. Finally, experimental follow-up confirmed that LY86 knockdown results in reduced monocyte migration towards the chemokine MCP-1, thereby implying that this reduced migration may underlie the increased susceptibility to candidemia. Altogether, our integrative systems genetics approach identifies previously unknown mechanisms underlying the immune response to Candida infection.
Keyphrases
- single cell
- candida albicans
- rna seq
- biofilm formation
- poor prognosis
- high throughput
- high resolution
- end stage renal disease
- newly diagnosed
- risk factors
- escherichia coli
- ejection fraction
- long non coding rna
- pseudomonas aeruginosa
- intensive care unit
- genome wide
- prognostic factors
- dna methylation
- cystic fibrosis
- mesenchymal stem cells
- cardiovascular disease
- stem cells
- transcription factor
- nk cells
- artificial intelligence
- big data
- immune response
- patient reported
- cell therapy
- liquid chromatography
- light emitting