A transcriptomic reporter assay employing neutrophils to measure immunogenic activity of septic patients’ plasma

Abstract

BackgroundThere are diverse molecules present in blood plasma that regulate immune functions and also present a potential source of disease biomarkers and therapeutic targets. Genome-wide profiling has become a powerful method for assessing immune responses on a systems scale, but technologies that can measure the plasma proteome still face considerable challenges. An alternative approach to direct proteome assessment is to measure transcriptome responses in reporter cells exposed in vitro to plasma. In this report we describe such a “transcriptomic reporter assay” to assess plasma from patients with sepsis, which is a common and severe systemic infectious process for which physicians lack efficient diagnostic or prognostic markers.MethodsPlasma samples collected from patients with culture-confirmed bacterial sepsis and uninfected healthy controls were used to stimulate three separate cell types – neutrophils, peripheral blood mononuclear cells, and monocyte-derived dendritic cells. Whole genome microarrays were generated from stimulated cells to assess transcriptional responses. Unsupervised analysis and enriched functional networks were evaluated for each cell type. Principal component analyses were used to assess variability in responses. A random K-nearest neighbor – feature selection algorithm was used to identify markers predictive of sepsis severity, which were then validated in an independent data set.ResultsNeutrophils demonstrated the most distinct response to plasma from septic patients with 709 genes showing altered expression profiles, many of which are involved in established immunologic pathways. The amplitude of the neutrophil transcriptomic response was shown to be correlated with sepsis severity in two independent sets of patients comprised of 64 total septic patients. A subset of 30 transcripts selected using one set of patients was demonstrated to have a high degree of accuracy (82-90%) in predicting sepsis severity and outcomes in the other independent set. This subset included several genes previously established in sepsis pathogenesis as well as novel genes.ConclusionsThese results demonstrate both the suitability and potential clinical relevance of a neutrophil reporter assay for studying plasma, in this case from septic patients. The distinctive transcriptional signature we found could potentially help predict severity of disease and guide treatment. Our findings also shed new light on mechanisms of immune dysregulation in sepsis.

Innate inflammation in type 1 diabetes

“…To explore the disease-specificity of the approach, we have applied it to H1N1 influenza, bacterial pneumonia, and cystic fibrosis with airway Pseudomonas aeruginosa colonization (71) as well as multiple sclerosis and Crohn’s disease (unpublished results) and have found specific, mechanistically-informative signatures for each disease state. Other groups have used this approach to identify disease specific signatures associated with systemic onset juvenile idiopathic arthritis and sepsis (78, 79). Importantly, corroborating evidence of an innate inflammatory state associated with T1D has been generated through the application of global serum-based proteomic analysis of diabetes patients and unrelated healthy controls (80).…”

Blood-based signatures in type 1 diabetes

“…Our laboratory has employed an alternative approach to assay the extracellular milieu associated with diabetes susceptibility. This strategy, which was also used to study juvenile idiopathic arthritis and sepsis [73, 74], employs patient serum or plasma to induce transcriptional responses in a ‘reporter’ cell population. While various cell lines, neutrophils or islets [74–76] have been used in this type of assay, because of the breadth of expressed receptors, we have used cryopreserved PBMCs of a single well-controlled healthy blood donor as sensitive biosensors that transcriptionally respond to the dilute disease-associated factors in patient plasma.…”

“…This strategy, which was also used to study juvenile idiopathic arthritis and sepsis [73, 74], employs patient serum or plasma to induce transcriptional responses in a ‘reporter’ cell population. While various cell lines, neutrophils or islets [74–76] have been used in this type of assay, because of the breadth of expressed receptors, we have used cryopreserved PBMCs of a single well-controlled healthy blood donor as sensitive biosensors that transcriptionally respond to the dilute disease-associated factors in patient plasma. After co-culture, induced transcription is comprehensively measured with a genome-scale array and then the data are subjected to ontological analyses for quantitative interpretation in terms of inflammatory and regulatory immune activities [75, 77–81].…”

A One-Nearest-Neighbor Approach to Identify the Original Time of Infection Using Censored Baboon Sepsis Data*

“…A related paper was found to use a variable k-nearest-neighbor approach for the purposes of early diagnosis in neonatal sepsis (15). Another recent paper utilized the nearest-neighbor approach to identify novel genes associated with sepsis severity (16). Nearest-neighbor is a popular nonparametric approach in data mining and was selected here to find similarities among biomarker trajectories.…”