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Epithelial cells of the conducting airways are a pivotal first line of defense against airborne pathogens and allergens that orchestrate inflammatory responses and mucociliary clearance. Nonetheless, the molecular mechanisms responsible for epithelial hyperreactivity associated with allergic asthma are not completely understood. Transcriptomic analysis of human airway epithelial cells (HAECs), differentiated in-vitro at air-liquid interface (ALI), showed 725 differentially expressed immediate-early transcripts, including putative long noncoding RNAs (lncRNAs). A novel lncRNA on the antisense strand of ICAM-1 or LASI was identified, which was induced in LPS-primed HAECs along with mucin MUC5AC and its transcriptional regulator SPDEF. LPS-primed expression of LASI, MUC5AC, and SPDEF transcripts were higher in ex-vivo cultured asthmatic HAECs that were further augmented by LPS treatment. Airway sections from asthmatics with increased mucus load showed higher LASI expression in MUC5AC+ goblet cells following multi-fluorescent in-situ hybridization and immunostaining. LPS- or IL-13-induced LASI transcripts were mostly enriched in the nuclear/perinuclear region and were associated with increased ICAM-1, IL-6, and CXCL-8 expression. Blocking LASI expression reduced the LPS or IL-13-induced epithelial inflammatory factors and MUC5AC expression, suggesting that the novel lncRNA LASI could play a key role in LPS-primed trained airway epithelial responses that are dysregulated in allergic asthma.

Acute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors’ biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition.

OBJECTIVES Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test. DESIGN Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results. SETTING Four U.S. emergency departments. PATIENTS Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis. INTERVENTIONS Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes. MEASUREMENTS AND MAIN RESULTS Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance. CONCLUSIONS The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.

Chronic airway inflammation from recurring exposures to noxious environmental stimuli results in a progressive and irreversible airflow limitation and the lung parenchymal damage that characterizes chronic obstructive pulmonary disease (COPD). The large variability observed in the onset and progression of COPD is primarily driven by complex gene–environment interactions. The transcriptomic and epigenetic memory potential of lung epithelial and innate immune cells drive responses, such as mucus hyperreactivity and airway remodeling, that are tightly regulated by various molecular mechanisms, for which several candidate susceptibility genes have been described. However, the recently described noncoding RNA species, in particular the long noncoding RNAs, may also have an important role in modulating pulmonary responses to chronic inhalation of toxic substances and the development of COPD. This review outlines the features of long noncoding RNAs that have been implicated in regulating the airway inflammatory responses to cigarette smoke exposure and their possible association with COPD pathogenesis. As COPD continues to debilitate the increasingly aging population and contribute to higher morbidity and mortality rates worldwide, the search for better biomarkers and alternative therapeutic options is pivotal.

Background: Distinguishing bacterial and viral respiratory infections is challenging. Novel diagnostics based on differential host gene expression patterns are promising but have not been translated to a clinical platform nor extensively tested. Here, we validate a microarray-derived host response signature and explore performance in microbiology-negative and coinfection cases. Methods: Subjects with acute respiratory illness were enrolled in participating emergency departments. Reference standard was an adjudicated diagnosis of bacterial infection, viral infection, both, or neither. An 87-transcript signature for distinguishing bacterial, viral, and noninfectious illness was measured from peripheral blood using RT-PCR. Performance characteristics were evaluated in subjects with confirmed bacterial, viral, or noninfectious illness. Subjects with bacterial-viral coinfection and microbiologically-negative suspected bacterial infection were also evaluated. Performance was compared to procalcitonin. Findings: 151 subjects with microbiologically confirmed, single-etiology illness were tested, yielding AUROCs 0•85–0•89 for bacterial, viral, and noninfectious illness. Accuracy was similar to procalcitonin (88% vs 83%, p = 0•23) for bacterial vs. non-bacterial infection. Whereas procalcitonin cannot distinguish viral from non-infectious illness, the RT-PCR test had 81% accuracy in making this determination. Bacterial-viral coinfection was subdivided. Among 19 subjects with bacterial superinfection, the RT-PCR test identified 95% as bacterial, compared to 68% with procalcitonin (p = 0•13). Among 12 subjects with bacterial infection superimposed on chronic viral infection, the RT-PCR test identified 83% as bacterial, identical to procalcitonin. 39 subjects had suspected bacterial infection; the RT-PCR test identified bacterial infection more frequently than procalcitonin (82% vs 64%, p = 0•02). Interpretation: The RT-PCR test offered similar diagnostic performance to procalcitonin in some subgroups but offered better discrimination in others such as viral vs. non-infectious illness and bacterial/viral coinfection. Gene expression-based tests could impact decision-making for acute respiratory illness as well as a growing number of other infectious and non-infectious diseases. Keywords: Biomarkers, Gene expression, Respiratory tract infections, Coinfection, Diagnosis, Precision medicine

The presence in plasma of mitochondrial DNA (mtDNA) fragments, a proinflammatory damage-associated molecular pattern (DAMP), is positively associated with outcomes of multiple human disorders. Because mtDNA comprises only a small percentage of the total DNA in plasma, qPCR is typically employed as an analytic strategy. However, this method provides little insight into sequence origins or other characteristics of circulating mtDNA fragments. Here we found that target bait-capture applied to plasma mtDNA derived from severely injured patients enriched recovery by ≈ 1400-fold, thus affording depth sufficient for NextGen sequence analysis. Our method excluded nuclear mitochondrial insertions (NUMTs) using a stringent alignment and filtering strategy which calls and quantifies both NUMT in the reference genome and polymorphic NUMTs. After enrichment, we sequenced 2,000–60,000x mean coverage over the mtDNA genome. Normalization of mtDNA abundance to NUMT coverage reduced batch variability. Two massively-transfused trauma patients and two non-transfused patients displayed time-dependent increases in mtDNA DAMP coverage and decreases in the mean fragment length, which were more pronounced in massively transfused patients. Finally, our approach enabled detection of low-frequency heteroplasmic variants. Collectively, these findings suggest that our target bait-capture, deep sequencing and attendant analytic protocols could provide unprecedented characterization of cell-free plasma mtDNA and NUMTs.

Mammalian antibody switch regions (∼1500 bp) are composed of a series of closely neighboring G4-capable sequences. Whereas numerous structural and genome-wide analyses of roles for minimal G4s in transcriptional regulation have been reported, Long G4-capable regions (LG4s)—like those at antibody switch regions—remain virtually unexplored. Using a novel computational approach we have identified 301 LG4s in the human genome and find LG4s prone to mutation and significantly associated with chromosomal rearrangements in malignancy. Strikingly, 217 LG4s overlap annotated enhancers, and we find the promoters regulated by these enhancers markedly enriched in G4-capable sequences suggesting G4s facilitate promoter-enhancer interactions. Finally, and much to our surprise, we also find single-stranded loops of minimal G4s within individual LG4 loci are frequently highly complementary to one another with 178 LG4 loci averaging >35 internal loop:loop complements of >8 bp. As such, we hypothesized (then experimentally confirmed) that G4 loops within individual LG4 loci directly basepair with one another (similar to characterized stem–loop kissing interactions) forming a hitherto undescribed, higher-order, G4-based secondary structure we term a ‘G4 Kiss or G4K’. In conclusion, LG4s adopt novel, higher-order, composite G4 structures directly contributing to the inherent instability, regulatory capacity, and maintenance of these conspicuous genomic regions.

Embryonic development is highly sensitive to xenobiotic toxicity and in utero exposure to environmental toxins affects physiological responses of the progeny. In the United States, the prevalence of allergic asthma (AA) is inexplicably rising and in utero exposure to cigarette smoke increases the risk of AA and bronchopulmonary dysplasia (BPD) in children and animal models. We reported that gestational exposure to sidestream cigarette smoke (SS), or secondhand smoke, promoted nicotinic acetylcholine receptor–dependent exacerbation of AA and BPD in mice. Recently, perinatal nicotine injections in rats were reported to induce peroxisome proliferator-activated receptor γ–dependent transgenerational transmission of asthma. Herein, we show that first generation and second generation progeny from gestationally SS-exposed mice exhibit exacerbated AA and BPD that is not dependent on the decrease in peroxisome proliferator-activated receptor γ levels. Lungs from these mice show strong eosinophilic infiltration, excessive Th2 polarization, marked airway hyperresponsiveness, alveolar simplification, decreased lung compliance, and decreased lung angiogenesis. At the molecular level, these changes are associated with increased RUNX3 expression, alveolar cell apoptosis, and the antiangiogenic factor GAX, and decreased expression of HIF-1α and proangiogenic factors NF-κB and VEGFR2 in the 7-d first generation and second generation lungs. Moreover, the lungs from these mice exhibit lower levels of microRNA (miR)-130a and increased levels of miR-16 and miR-221. These miRs regulate HIF-1α–regulated apoptotic, angiogenic, and immune pathways. Thus the intergenerational effects of gestational SS involve epigenetic regulation of HIF-1α through specific miRs contributing to increased incidence of AA and BPD in the progenies.

Sepsis is a dysregulated host response that leads to high mortality and death. It is a complicated syndrome that can be difficult to diagnose and predict acute and long-term patient outcomes. Current biomarkers are relatively non-specific and rarely relate to the pathophysiology of the syndrome or the organ dysfunctions. Moreover, there are currently no approved pharmaceutical interventions that can treat the accompanying organ dysfunctions. Utilizing systems biology approaches in clinical samples it is possible to identify new biomarkers as well as determine novel mechanisms of the disease. In this chapter we will review common metabolomic and proteomic biomarkers for sepsis diagnosis and outcome prediction as well as review new biomarkers and pathways that have been identified utilizing metabolomic datasets.

Background Sepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-free DNA (cfDNA), and nucleosomes. Methods The cfDNA and nucleosome levels were assayed in plasma samples acquired in patients admitted from four emergency departments with suspected sepsis. Subjects with non-infectious systemic inflammatory response syndrome (SIRS) served as controls. Samples were acquired at enrollment (T0) and 24 h later (T24). We assessed diagnostic (differentiating SIRS from sepsis) and prognostic (28-day mortality) predictive power. Models incorporating procalcitonin (diagnostic prediction) and APACHE II scores (mortality prediction) were generated. Results Two hundred three subjects were included (107 provided procalcitonin measurements). Four subjects exhibited uncomplicated sepsis, 127 severe sepsis, 35 septic shock, and 24 had non-infectious SIRS. There were 190-survivors and 13 non-survivors. Mortality prediction models using cfDNA, nucleosomes, or APACHEII yielded AUC values of 0.61, 0.75, and 0.81, respectively. A model combining nucleosomes with the APACHE II score improved the AUC to 0.84. Diagnostic models distinguishing sepsis from SIRS using procalcitonin, cfDNA(T0), or nucleosomes(T0) yielded AUC values of 0.64, 0.65, and 0.63, respectively. The three parameter model yielded an AUC of 0.74. Conclusions To our knowledge, this is the first head-to-head comparison of cfDNA and nucleosomes in diagnosing sepsis and predicting sepsis-related mortality. Both cfDNA and nucleosome concentrations demonstrated a modest ability to distinguish sepsis survivors and non-survivors and provided additive diagnostic predictive accuracy in differentiating sepsis from non-infectious SIRS when integrated into a diagnostic prediction model including PCT and APACHE II. A sepsis biomarker strategy incorporating measures of the apoptotic pathway may serve as an important component of a sepsis diagnostic and mortality prediction tool.

OBJECTIVE: To find and validate generalizable sepsis subtypes using data-driven clustering. DESIGN: We used advanced informatics techniques to pool data from 14 bacterial sepsis transcriptomic datasets from 8 different countries (N=700). SETTING: Retrospective analysis. SUBJECTS: Persons admitted to the hospital with bacterial sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A unified clustering analysis across 14 discovery datasets revealed three subtypes, which, based on functional analysis, we termed Inflammopathic, Adaptive, and Coagulopathic. We then validated these subtypes in 9 independent datasets from 5 different countries (N=600). In both discovery and validation data, the Adaptive subtype is associated with a lower clinical severity and lower mortality rate, and the Coagulopathic subtype is associated with higher mortality and clinical coagulopathy. Further, these clusters are statistically associated with clusters derived by others in independent single sepsis cohorts. CONCLUSIONS: The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision-medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.

Sepsis remains one of the leading causes of death in the United States and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug resistant organisms (MDROs). There is a dire need for the development of new antibiotics, improved antibiotic stewardship and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic and proteomic platforms have allowed for a broad spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic data sets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we will highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis.

Rationale: Sepsis is a leading cause of morbidity and mortality. Currently, early diagnosis and the progression of the disease are difficult to make. The integration of metabolomic and transcriptomic data in a primate model of sepsis may provide a novel molecular signature of clinical sepsis. Objectives: To develop a biomarker panel to characterize sepsis in primates and ascertain its relevance to early diagnosis and progression of human sepsis. Methods: Intravenous inoculation of Macaca fascicularis with Escherichia coli produced mild to severe sepsis, lung injury, and death. Plasma samples were obtained before and after 1, 3, and 5 days of E. coli challenge and at the time of killing. At necropsy, blood, lung, kidney, and spleen samples were collected. An integrative analysis of the metabolomic and transcriptomic datasets was performed to identify a panel of sepsis biomarkers. Measurements and Main Results: The extent of E. coli invasion, respiratory distress, lethargy, and mortality was dependent on the bacterial dose. Metabolomic and transcriptomic changes characterized severe infections and death, and indicated impaired mitochondrial, peroxisomal, and liver functions. Analysis of the pulmonary transcriptome and plasma metabolome suggested impaired fatty acid catabolism regulated by peroxisome-proliferator activated receptor signaling. A representative four-metabolite model effectively diagnosed sepsis in primates (area under the curve, 0.966) and in two human sepsis cohorts (area under the curve, 0.78 and 0.82). Conclusions: A model of sepsis based on reciprocal metabolomic and transcriptomic data was developed in primates and validated in two human patient cohorts. It is anticipated that the identified parameters will facilitate early diagnosis and management of sepsis.

The substrate of the methionine salvage pathway, methylthioadenosine, is a predictor of death in sepsis patients., Sepsis is a deleterious inflammatory response to infection with high mortality. Reliable sepsis biomarkers could improve diagnosis, prognosis, and treatment. Integration of human genetics, patient metabolite and cytokine measurements, and testing in a mouse model demonstrate that the methionine salvage pathway is a regulator of sepsis that can accurately predict prognosis in patients. Pathway-based genome-wide association analysis of nontyphoidal Salmonella bacteremia showed a strong enrichment for single-nucleotide polymorphisms near the components of the methionine salvage pathway. Measurement of the pathway’s substrate, methylthioadenosine (MTA), in two cohorts of sepsis patients demonstrated increased plasma MTA in nonsurvivors. Plasma MTA was correlated with levels of inflammatory cytokines, indicating that elevated MTA marks a subset of patients with excessive inflammation. A machine-learning model combining MTA and other variables yielded approximately 80% accuracy (area under the curve) in predicting death. Furthermore, mice infected with Salmonella had prolonged survival when MTA was administered before infection, suggesting that manipulating MTA levels could regulate the severity of the inflammatory response. Our results demonstrate how combining genetic data, biomolecule measurements, and animal models can shape our understanding of disease and lead to new biomarkers for patient stratification and potential therapeutic targeting.

Improved risk stratification and prognosis in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here three scientific groups were invited to independently generate prognostic models for 30-day mortality using 12 discovery cohorts (N=650) containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance was validated in 5 cohorts of community-onset sepsis patients (N=189) in which the models showed summary AUROCs ranging from 0.765-0.89. Similar performance was observed in 4 cohorts of hospital-acquired sepsis (N=282). Combining the new gene-expression-based prognostic models with prior clinical severity scores led to significant improvement in prediction of 30-day mortality (p

Although a number of inflammatory cytokines are increased during sepsis, the clinical trials aimed at down-regulating these mediators have not improved the outcome. These paradoxical results are attributed to loss of the “tolerance” phase that normally follows the proinflammatory response. Chronic nicotine (NT) suppresses both adaptive and innate immune responses, and the effects are partly mediated by the nicotinic acetylcholine receptors in the brain; however, the mechanism of neuroimmune communication is not clear. Here, we present evidence that, in rats and mice, NT initially increases IL-1β in the brain, but the expression is downregulated within 1–2 week of chronic exposure, and the animals become resistant to proinflammatory/pyrogenic stimuli. To examine the relationship between NT, IL-1β, and immunosuppression, we hypothesized that NT induces IL-1β in the brain, and its constant presence produces immunological “tolerance”. Indeed, unlike wild-type C57BL/6 mice, chronic NT failed to induce immunosuppression or downregulation of IL-1β expression in IL-1β-receptor knockout mice. Moreover, while acute intracerebroventricular administration of IL-1β in Lewis (LEW) rats activated Fyn and protein tyrosine kinase activities in the spleen, chronic administration of low levels of IL-1β progressively diminished the pyrogenic and T cell proliferative responses of treated animals. Thus, IL-1β may play a critical role in the perception of inflammation by the CNS and the induction of an immunologic “tolerant” state. Moreover, the immunosuppressive effects of NT might be at least partly mediated through its effects on the brain IL-1β. This represents a novel mechanism for neuroimmune communication.

Smokers are less likely to develop some inflammatory and allergic diseases. In Brown-Norway rats, nicotine inhibits several parameters of allergic asthma, including the production of Th2 cytokines and the cysteinyl leukotriene LTC4. Cysteinyl leukotrienes are primarily produced by mast cells, and these cells play a central role in allergic asthma. Mast cells express a high-affinity receptor for IgE (FcεRI). Following its cross-linking, cells degranulate and release preformed inflammatory mediators (early phase) and synthesize and secrete cytokines/chemokines and leukotrienes (late phase). The mechanism by which nicotine modulates mast cell activation is unclear. Using α-bungarotoxin binding and quantitative PCR and PCR product sequencing, we showed that the rat mast/basophil cell line RBL-2H3 expresses nicotinic acetylcholine receptors (nAChRs) α7, α9, and α10; exposure to exceedingly low concentrations of nicotine (nanomolar), but not the biologically inactive metabolite cotinine, for ≥8 h suppressed the late phase (leukotriene/cytokine production) but not degranulation (histamine and hexosaminidase release). These effects were unrelated to those of nicotine on intracellular free calcium concentration but were causally associated with the inhibition of cytosolic phospholipase A2 activity and the PI3K/ERK/NF-κB pathway, including phosphorylation of Akt and ERK and nuclear translocation of NF-κB. The suppressive effect of nicotine on the late-phase response was blocked by the α7/α9-nAChR antagonists methyllycaconitine and α-bungarotoxin, as well as by small interfering RNA knockdown of α7-, α9-, or α10-nAChRs, suggesting a functional interaction between α7-, α9-, and α10-nAChRs that might explain the response of RBL cells to nanomolar concentrations of nicotine. This “hybrid” receptor might serve as a target for novel antiallergic/antiasthmatic therapies.

Nodulation is the result of a mutualistic interaction between legumes and symbiotic soil bacteria (e.g. soybean [Glycine max] and Bradyrhizobium japonicum) initiated by the infection of plant root hair cells by the symbiont. Fewer than 20 plant genes involved in the nodulation process have been functionally characterized. Considering the complexity of the symbiosis, significantly more genes are likely involved. To identify genes involved in root hair cell infection, we performed a large-scale transcriptome analysis of B. japonicum-inoculated and mock-inoculated soybean root hairs using three different technologies: microarray hybridization, Illumina sequencing, and quantitative real-time reverse transcription-polymerase chain reaction. Together, a total of 1,973 soybean genes were differentially expressed with high significance during root hair infection, including orthologs of previously characterized root hair infection-related genes such as NFR5 and NIN. The regulation of 60 genes was confirmed by quantitative real-time reverse transcription-polymerase chain reaction. Our analysis also highlighted changes in the expression pattern of some homeologous and tandemly duplicated soybean genes, supporting their rapid specialization.

Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational, cohort study determined whether host gene expression patterns discriminate non-infectious from infectious illness, and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or non-infectious illness as well as 44 healthy controls was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a non-infectious cause of illness (26 probes). Overall accuracy was 87% (238/273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, p

Background Chronic obstructive pulmonary disease (COPD) is characterized by an irreversible airflow limitation in response to inhalation of noxious stimuli, such as cigarette smoke. However, only 15–20 % smokers manifest COPD, suggesting a role for genetic predisposition. Although genome-wide association studies have identified common genetic variants that are associated with susceptibility to COPD, effect sizes of the identified variants are modest, as is the total heritability accounted for by these variants. In this study, an extreme phenotype exome sequencing study was combined with in vitro modeling to identify COPD candidate genes. Results We performed whole exome sequencing of 62 highly susceptible smokers and 30 exceptionally resistant smokers to identify rare variants that may contribute to disease risk or resistance to COPD. This was a cross-sectional case-control study without therapeutic intervention or longitudinal follow-up information. We identified candidate genes based on rare variant analyses and evaluated exonic variants to pinpoint individual genes whose function was computationally established to be significantly different between susceptible and resistant smokers. Top scoring candidate genes from these analyses were further filtered by requiring that each gene be expressed in human bronchial epithelial cells (HBECs). A total of 81 candidate genes were thus selected for in vitro functional testing in cigarette smoke extract (CSE)-exposed HBECs. Using small interfering RNA (siRNA)-mediated gene silencing experiments, we showed that silencing of several candidate genes augmented CSE-induced cytotoxicity in vitro. Conclusions Our integrative analysis through both genetic and functional approaches identified two candidate genes (TACC2 and MYO1E) that augment cigarette smoke (CS)-induced cytotoxicity and, potentially, COPD susceptibility.

Annually, approximately two million babies are exposed to cigarette smoke in utero and postnatally through cigarette smoking of their mothers. Exposure to mainstream cigarette smoke is known to impair both innate and adaptive immunities, and it has been hypothesized that the effects of in utero exposure to cigarette smoke on children's health might primarily stem from the adverse effects of cigarette smoke on the immune system. To simulate the environment that babies from smoking mothers encounter, we examined the effects of prenatal mainstream and postnatal sidestream cigarette smoke on spleen cell responses. Results show that postnatal exposure of newborn Balb/c mouse pups to sidestream cigarette smoke through the first 6 weeks of life strongly suppresses the antibody response of spleen cells to the T-cell-dependent antigen, sheep red blood cells. The reduction in the antibody response seen within 6 weeks of postnatal smoke exposure is much quicker than the published data on the time 25 weeks) required to establish reproducible immunosuppression in adult rats and mice. Moreover, the immunosuppression is not associated with significant changes in T-cell numbers or subset distribution. While the postnatal exposure to cigarette smoke did not affect the mitogenic response of T and B cells, the exposure inhibited the T cell receptor-mediated rise in the intracellular calcium concentration. These results suggest that the early postnatal period is highly sensitive to the immunosuppressive effects of environmental tobacco smoke, and the effects are causally associated with impaired antigen-mediated signaling in T cells.

To study the immunological effects of nicotine, there are several rodent models for chronic nicotine administration. These models include subcutaneously implanted miniosmotic pumps, nicotine-spiked drinking water, and self-administration via jugular cannulae. Administration of nicotine via these routes affects the immune system. Smokers frequently use nicotine patches to quit smoking, and the immunological effects of nicotine patches are largely unknown. To determine whether the nicotine patch affects the immune system, nicotine patches were affixed daily onto the backs of Lewis rats for 3 to 4 weeks. The patches efficiently raised the levels of nicotine and cotinine in serum and strongly inhibited the antibody-forming cell response of spleen cells to sheep red blood cells. The nicotine patch also suppressed the concanavalin A-induced T-cell proliferation and mobilization of intracellular Ca2+by spleen cells, as well as the fever response of animals to subcutaneous administration of turpentine. Moreover, immunosuppression was associated with chronic activation of protein tyrosine kinase and phospholipase C-γ1 activities. Thus, in this animal model of nicotine administration, the nicotine patch efficiently raises the levels of nicotine and cotinine in serum and impairs both the immune and inflammatory responses.

IntroductionTwo recent, independent, studies conducted novel metabolomics analyses relevant to human sepsis progression; one was a human model of endotoxin (lipopolysaccharide (LPS)) challenge (experimental endotoxemia) and the other was community acquired pneumonia and sepsis outcome diagnostic study (CAPSOD). The purpose of the present study was to assess the concordance of metabolic responses to LPS and community-acquired sepsis.MethodsWe tested the hypothesis that the patterns of metabolic response elicited by endotoxin would agree with those in clinical sepsis. Alterations in the plasma metabolome of the subjects challenged with LPS were compared with those of sepsis patients who had been stratified into two groups: sepsis patients with confirmed infection and non-infected patients who exhibited systemic inflammatory response syndrome (SIRS) criteria. Common metabolites between endotoxemia and both these groups were individually identified, together with their direction of change and functional classifications.ResultsResponse to endotoxemia at the metabolome level elicited characteristics that agree well with those observed in sepsis patients despite the high degree of variability in the response of these patients. Moreover, some distinct features of SIRS have been identified. Upon stratification of sepsis patients based on 28-day survival, the direction of change in 21 of 23 metabolites was the same in endotoxemia and sepsis survival groups.ConclusionsThe observed concordance in plasma metabolomes of LPS-treated subjects and sepsis survivors strengthens the relevance of endotoxemia to clinical research as a physiological model of community-acquired sepsis, and gives valuable insights into the metabolic changes that constitute a homeostatic response. Furthermore, recapitulation of metabolic differences between sepsis non-survivors and survivors in LPS-treated subjects can enable further research on the development and assessment of rational clinical therapies to prevent sepsis mortality. Compared with earlier studies which focused exclusively on comparing transcriptional dynamics, the distinct metabolomic responses to systemic inflammation with or without confirmed infection, suggest that the metabolome is much better at differentiating these pathophysiologies. Finally, the metabolic changes in the recovering patients shift towards the LPS-induced response pattern strengthening the notion that the metabolic, as well as transcriptional responses, characteristic to the endotoxemia model represent necessary and “healthy” responses to infectious stimuli.

A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on patient response during critical illness. To achieve this, we examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Quantification of plasma metabolites indicated greater change as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular-weight proteins and acute-phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among patients on HD. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and N-acetylaspartate were inversely correlated with the majority of significantly downregulated genes. Thus, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness; changes were not effectively mitigated by hemodialysis. These studies allude to several novel mechanisms whereby renal dysfunction contributes to critical illness.

The nerve gas sarin is a potent cholinergic agent, and exposure to high doses may cause neurotoxicity and death. Subclinical exposures to sarin have been postulated to contribute to the Gulf War syndrome; however, the biological effects of subclinical exposure are largely unknown. In this communication, evidence shows that subclinical doses (0.2 and 0.4 mg/m(3)) of sarin administered by inhalation to F344 rats for 1 h/day for 5 or 10 days inhibited the anti-sheep red blood cell antibody-forming cell response of spleen cells without affecting the distribution of lymphocyte subpopulations in the spleen. Moreover, sarin suppressed T cell responses, including the concanavalin A (Con A) and the anti-alphabeta-T cell receptor (TCR) antibody-induced T cell proliferation and the rise in the intracellular calcium following TCR ligation. These concentrations of sarin altered regional but not total brain acetylcholinesterase activity. Interestingly, serum corticosterone levels of the sarin-treated animals were dramatically lower than the control animals, indicating that sarin-induced immunosuppression did not result from the activation of the hypothalamus-pituitary-adrenal (HPA) axis. Pretreatment of animals with the ganglionic blocker chlorisondamine abrogated the inhibitory effects of sarin on spleen cell proliferation in response to Con A and anti-TCR antibodies. These results suggest that the effects of sarin on T cell responsiveness are mediated via the autonomic nervous system and are independent of the HPA axis.

Background Sepsis, a leading cause of morbidity and mortality, is not a homogeneous disease but rather a syndrome encompassing many heterogeneous pathophysiologies. Patient factors including genetics predispose to poor outcomes, though current clinical characterizations fail to identify those at greatest risk of progression and mortality. Methods The Community Acquired Pneumonia and Sepsis Outcome Diagnostic study enrolled 1,152 subjects with suspected sepsis. We sequenced peripheral blood RNA of 129 representative subjects with systemic inflammatory response syndrome (SIRS) or sepsis (SIRS due to infection), including 78 sepsis survivors and 28 sepsis non-survivors who had previously undergone plasma proteomic and metabolomic profiling. Gene expression differences were identified between sepsis survivors, sepsis non-survivors, and SIRS followed by gene enrichment pathway analysis. Expressed sequence variants were identified followed by testing for association with sepsis outcomes. Results The expression of 338 genes differed between subjects with SIRS and those with sepsis, primarily reflecting immune activation in sepsis. Expression of 1,238 genes differed with sepsis outcome: non-survivors had lower expression of many immune function-related genes. Functional genetic variants associated with sepsis mortality were sought based on a common disease-rare variant hypothesis. VPS9D1, whose expression was increased in sepsis survivors, had a higher burden of missense variants in sepsis survivors. The presence of variants was associated with altered expression of 3,799 genes, primarily reflecting Golgi and endosome biology. Conclusions The activation of immune response-related genes seen in sepsis survivors was muted in sepsis non-survivors. The association of sepsis survival with a robust immune response and the presence of missense variants in VPS9D1 warrants replication and further functional studies. Trial registration ClinicalTrials.gov NCT00258869. Registered on 23 November 2005. Electronic supplementary material The online version of this article (doi:10.1186/s13073-014-0111-5) contains supplementary material, which is available to authorized users.

Subclinical, repeated exposures of F344 rats to sarin resulted in brain alterations in densities of chlonergic receptor subtypes that may be associated with memory loss and cognitive dysfunction. The exposures also depressed the immune system. The rat appears to be a good model for studying the effects of subclinical exposure to a nerve gas.

Cotton rats (Sigmodon hispidusandS. fulviventer) are susceptible to many viruses that infect humans (e.g., poliovirus, respiratory syncytial virus, influenza virus, adenovirus, and parainfluenza virus) and have been influential in developing therapeutic clinical intervention strategies for many viral infections of man. This study set out to determine whether cotton rats are susceptible to infection with HIV type 1 (HIV-1). Results indicate that HIV-1 does infect the cotton rat andS. fulviventeris more susceptible thanS. hispidus. The virus was passaged from animal to animal for a total of three serial passages; but HIV replicated poorlyin vivo, was only detectable as proviral DNA, and never exceeded one provirus per 1.8 × 105cotton rat peripheral blood mononuclear cells. Infection induced a distinct and characteristic anti-HIV antibody response that, in some animals, included neutralizing antibodies, recognized all of the major HIV-1 antigens and the antibodies lasted out to 52 wk post-infection. NeonateS. fulviventerwere not more susceptible to infection than adults.In vitroculture studies produced indirect evidence of viral replication by detection of viral gag gene RNA in reverse transcriptase–PCR assays on viral culture supernatants. Collectively, these results indicate that HIV-1 can replicate in a nontransgenic rodent and that this system may have potential as an animal model for HIV-1 infection if viral replication rates can be improvedin vivo.

Objective To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults. Rationale Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible. Methods We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study. Results We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p

Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would ultimately die differed markedly from those of patients who would survive. The different profiles of proteins and metabolites clustered into the following groups: fatty acid transport and β-oxidation, gluconeogenesis, and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of five metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.

In this podcast, Raymond J. Langley explains how a new molecular signature can help to identify patients with sepsis who are at greatest risk of dying. Length: 8.52 min File size: 5.2 MB File format: Mp3 Listen to Podcast: http://podcasts.aaas.org/science_transl_med/SciTranslMed130724.mp3 Download the Transcript (Adobe PDF format)