Publications
Identification of host response signatures of infection
Sinha, Anupama S.; Bent, Zachary B.
Biological weapons of mass destruction and emerging infectious diseases represent a serious and growing threat to our national security. Effective response to a bioattack or disease outbreak critically depends upon efficient and reliable distinguishing between infected vs healthy individuals, to enable rational use of scarce, invasive, and/or costly countermeasures (diagnostics, therapies, quarantine). Screening based on direct detection of the causative pathogen can be problematic, because culture- and probe-based assays are confounded by unanticipated pathogens (e.g., deeply diverged, engineered), and readily-accessible specimens (e.g., blood) often contain little or no pathogen, particularly at pre-symptomatic stages of disease. Thus, in addition to the pathogen itself, one would like to detect infection-specific host response signatures in the specimen, preferably ones comprised of nucleic acids (NA), which can be recovered and amplified from tiny specimens (e.g., fingerstick draws). Proof-of-concept studies have not been definitive, however, largely due to use of sub-optimal sample preparation and detection technologies. For purposes of pathogen detection, Sandia has developed novel molecular biology methods that enable selective isolation of NA unique to, or shared between, complex samples, followed by identification and quantitation via Second Generation Sequencing (SGS). The central hypothesis of the current study is that variations on this approach will support efficient identification and verification of NA-based host response signatures of infectious disease. To test this hypothesis, we re-engineered Sandia's sophisticated sample preparation pipelines, and developed new SGS data analysis tools and strategies, in order to pioneer use of SGS for identification of host NA correlating with infection. Proof-of-concept studies were carried out using specimens drawn from pathogen-infected non-human primates (NHP). This work provides a strong foundation for large-scale, highly-efficient efforts to identify and verify infection-specific host NA signatures in human populations.