Shared and organism-specific host responses to childhood diarrheal diseases revealed by whole blood transcript profiling

Abstract

Globally, diarrheal diseases are a leading cause of death in children under five and disproportionately affect children in developing countries. Children who contract diarrheal diseases are rarely screened to identify the etiologic agent due to time and cost considerations associated with pathogen-specific screening and hence pathogen-directed therapy is uncommon. The development of biomarkers to rapidly identify underlying pathogens could improve treatment options and clinical outcomes in childhood diarrheal diseases. Here, we perform RNA sequencing on blood samples collected from children evaluated in an emergency room setting with diarrheal disease where the pathogen(s) present are known. We determine host response gene signatures specific to Salmonella, Shigella and rotavirus, but not E. coli, infections that distinguish them from each other and from healthy controls. Specifically, we observed differential expression of genes related to chemokine receptors or inflammasome signaling in Shigella cases, such as CCR3, CXCR8, and NLRC4, and interferon response genes, such as IFI44 and OASL, in rotavirus cases. Our findings add insight into the host peripheral immune response to these pathogens, and suggest strategies and limitations for the use host response transcript signatures for diagnosing the etiologic agent of childhood diarrheal diseases.

A 2-transcript host cell signature distinguishes viral from bacterial diarrhea and it is influenced by the severity of symptoms

“… 5 ). We have exclusively analyzed cases with a single infecting pathogen, but it would most interesting to further explore the behavior of this 2-biomarker test in scenarios of coinfection 36 – 38 . The translation of this 2-biomarker test into a clinical setup still needs further validation; and this validation would require the analysis of more virus and bacteria scenarios, as well as different time points in the course of the same infection, or the case of parasitic infections.…”

Translation of a Host Blood RNA Signature Distinguishing Bacterial From Viral Infection Into a Platform Suitable for Development as a Point-of-Care Test

“…We identified transcripts suitable for translation to our laboratory-on-chip platform, which uses reverse transcription loop-mediated isothermal amplification (RT-LAMP), by assessing counts of IFI44L and FAM89A in a publicly available blood RNA sequencing data set comprising 255 children with bacterial and viral infections ( GSE69529 ). The average gene counts for IFI44L were sufficient (2281.9) but low for FAM89A (20.2), potentially compromising transferability across platforms. Therefore, using the list of previously identified 38 highly correlated transcripts, we replaced FAM89A with EMR1-ADGRE1 (RefSeq ID: NM_001974 .5 ), which had sufficient average gene counts (511.3), and in combination with IFI44L (RefSeq ID: NM_006820 ) had a similar performance to the original 2 transcript signature (area under the curve [AUC] in the training, test, and validation data sets: 93.4%, 97.4%, and 97.2%, respectively).…”

RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans

“…The Mexican group consists of 255 blood samples of healthy controls (n = 35), and patients with acute diarrhea caused by different bacterial/viral pathogens: RV (n = 60), norovirus (n = 7), adenovirus (n = 13), Salmonella (n = 42) , Shigella (n = 38) and different strains of E. coli (n = 60); Gene Expression Omnibus (GEO) accession number: GSE69529 (more detailed information about the samples is provided in [47]).…”