Diagnostic Host Gene Expression Analysis by Quantitative Reverse Transcription Loop-Mediated Isothermal Amplification to Discriminate between Bacterial and Viral Infections.

BACKGROUND: Early and accurate diagnosis of acute infections can help minimize the overprescription of antibiotics and improve patient outcomes. Discrimination between bacterial and viral etiologies in acute infection based on changes in host gene expression has been described. Unfortunately, established technologies used for gene expression profiling are typically expensive and slow, confounding integration into clinical workflows. Here we report the development of an ultra-rapid test system for host gene expression profiling from blood based on quantitative reverse transcription followed by loop-mediated isothermal amplification (qRT-LAMP). METHODS: We developed 10 messenger ribonucleic acid-specific assays based on qRT-LAMP targeting 7 informative biomarkers to discriminate viral from bacterial infections and 3 housekeeping reference genes. We optimized qRT-LAMP formulations to achieve a turnaround time of 12 min without sacrificing specificity or precision. The accuracy of the test system was verified utilizing blood samples from 57 patients and comparing qRT-LAMP results to profiles obtained using an orthogonal reference technology. RESULTS: We observed a Pearson coefficient of 0.90 between bacterial/viral metascores generated by qRT-LAMP and the reference technology. CONCLUSIONS: qRT-LAMP assays can provide sufficiently accurate gene expression profiling data to enable discrimination between bacterial and viral etiologies using an established set of biomarkers and a classification algorithm.

Validation of Inflammopathic, Adaptive, and Coagulopathic Sepsis Endotypes in Coronavirus Disease 2019.

OBJECTIVES: Complex critical syndromes like sepsis and coronavirus disease 2019 may be composed of underling "endotypes," which may respond differently to treatment. The aim of this study was to test whether a previously defined bacterial sepsis endotypes classifier recapitulates the same clinical and immunological endotypes in coronavirus disease 2019. DESIGN: Prospective single-center observational cohort study. SETTING: Patients were enrolled in Athens, Greece, and blood was shipped to Inflammatix (Burlingame, CA) for analysis. PATIENTS: Adult patients within 24 hours of hospital admission with coronavirus disease 2019 confirmed by polymerase chain reaction and chest radiography. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We studied 97 patients with coronavirus disease 2019, of which 50 went on to severe respiratory failure (SRF) and 16 died. We applied a previously defined 33-messenger RNA classifier to assign endotype (Inflammopathic, Adaptive, or Coagulopathic) to each patient. We tested endotype status against other clinical parameters including laboratory values, severity scores, and outcomes. Patients were assigned as Inflammopathic (29%), Adaptive (44%), or Coagulopathic (27%), similar to our prior study in bacterial sepsis. Adaptive patients had lower rates of SRF and no deaths. Coagulopathic and Inflammopathic endotypes had 42% and 18% mortality rates, respectively. The Coagulopathic group showed highest d-dimers, and the Inflammopathic group showed highest C-reactive protein and interleukin-6 levels. CONCLUSIONS: Our predefined 33-messenger RNA endotypes classifier recapitulated immune phenotypes in viral sepsis (coronavirus disease 2019) despite its prior training and validation only in bacterial sepsis. Further work should focus on continued validation of the endotypes and their interaction with immunomodulatory therapy.

Selective RNA targeting and regulated signaling by RIG-I is controlled by coordination of RNA and ATP binding.

RIG-I is an innate immune receptor that detects and responds to infection by deadly RNA viruses such as influenza, and Hepatitis C. In the cytoplasm, RIG-I is faced with a difficult challenge: it must sensitively detect viral RNA while ignoring the abundance of host RNA. It has been suggested that RIG-I has a 'proof-reading' mechanism for rejecting host RNA targets, and that disruptions of this selectivity filter give rise to autoimmune diseases. Here, we directly monitor RNA proof-reading by RIG-I and we show that it is controlled by a set of conserved amino acids that couple RNA and ATP binding to the protein (Motif III). Mutations of this motif directly modulate proof-reading by eliminating or enhancing selectivity for viral RNA, with major implications for autoimmune disease and cancer. More broadly, the results provide a physical explanation for the ATP-gated behavior of SF2 RNA helicases and receptor proteins.

The RIG-I ATPase core has evolved a functional requirement for allosteric stabilization by the Pincer domain.

Retinoic acid-inducible gene I (RIG-I) is a pattern recognition receptor expressed in metazoan cells that is responsible for eliciting the production of type I interferons and pro-inflammatory cytokines upon detection of intracellular, non-self RNA. Structural studies of RIG-I have identified a novel Pincer domain composed of two alpha helices that physically tethers the C-terminal domain to the SF2 helicase core. We find that the Pincer plays an important role in mediating the enzymatic and signaling activities of RIG-I. We identify a series of mutations that additively decouple the Pincer motif from the ATPase core and show that this decoupling results in impaired signaling. Through enzymological and biophysical analysis, we further show that the Pincer domain controls coupled enzymatic activity of the protein through allosteric control of the ATPase core. Further, we show that select regions of the HEL1 domain have evolved to potentiate interactions with the Pincer domain, resulting in an adapted ATPase cleft that is now responsive to adjacent domains that selectively bind viral RNA.

Structure of an actin-related subcomplex of the SWI/SNF chromatin remodeler.

The packaging of DNA into nucleosomal structures limits access for templated processes such as transcription and DNA repair. The repositioning or ejection of nucleosomes is therefore critically important for regulated events, including gene expression. This activity is provided by chromatin remodeling complexes, or remodelers, which are typically large, multisubunit complexes that use an ATPase subunit to translocate the DNA. Many remodelers contain pairs or multimers of actin-related proteins (ARPs) that contact the helicase-SANT-associated (HSA) domain within the catalytic ATPase subunit and are thought to regulate ATPase activity. Here, we determined the structure of a four-protein subcomplex within the SWI/SNF remodeler that comprises the Snf2 HSA domain, Arp7, Arp9, and repressor of Ty1 transposition, gene 102 (Rtt102). Surprisingly, unlike characterized actin-actin associations, the two ARPs pack like spoons and straddle the HSA domain, which forms a 92-Å-long helix. The ARP-HSA interactions are reminiscent of contacts between actin and many binding partners and are quite different from those in the Arp2/3 complex. Rtt102 wraps around one side of the complex in a highly extended conformation that contacts both ARPs and therefore stabilizes the complex, yet functions to reduce by ∼2.4-fold the remodeling and ATPase activity of complexes containing the Snf2 ATPase domain. Thus, our structure provides a foundation for developing models of remodeler function, including mechanisms of coupling between ARPs and the ATPase translocation activity.

Defining the functional determinants for RNA surveillance by RIG-I.

Retinoic acid-inducible gene-I (RIG-I) is an intracellular RNA sensor that activates the innate immune machinery in response to infection by RNA viruses. Here, we report the crystal structure of distinct conformations of a RIG-I:dsRNA complex, which shows that HEL2i-mediated scanning allows RIG-I to sense the length of RNA targets. To understand the implications of HEL2i scanning for catalytic activity and signalling by RIG-I, we examined its ATPase activity when stimulated by duplex RNAs of varying lengths and 5' composition. We identified a minimal RNA duplex that binds one RIG-I molecule, stimulates robust ATPase activity, and elicits a RIG-I-mediated interferon response in cells. Our results reveal that the minimal functional unit of the RIG-I:RNA complex is a monomer that binds at the terminus of a duplex RNA substrate. This behaviour is markedly different from the RIG-I paralog melanoma differentiation-associated gene 5 (MDA5), which forms cooperative filaments.

A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections.

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

Prospective validation of an 11-gene mRNA host response score for mortality risk stratification in the intensive care unit.

Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p < 0.01) and within 60 days (40% vs 15%, p = 0.06). The 11-gene score improved prognostication with a categorical Net Reclassification Improvement index of 0.37 (p = 0.03) and an Integrated Discrimination Improvement index of 0.07 (p = 0.02) when combined with Simplified Acute Physiology Score 3 or Acute Physiology and Chronic Health Evaluation II score. The test performed poorly in the 95 independent samples collected > 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.

Transcriptomic similarities and differences in host response between SARS-CoV-2 and other viral infections.

The pandemic 2019 novel coronavirus disease (COVID-19) shares certain clinical characteristics with other acute viral infections. We studied the whole-blood transcriptomic host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using RNAseq from 24 healthy controls and 62 prospectively enrolled patients with COVID-19. We then compared these data to non-COVID-19 viral infections, curated from 23 independent studies profiling 1,855 blood samples covering six viruses (influenza, respiratory syncytial virus (RSV), human rhinovirus (HRV), severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), Ebola, dengue). We show gene expression changes in COVID-19 versus non-COVID-19 viral infections are highly correlated (r = 0.74, p < 0.001). However, we also found 416 genes specific to COVID-19. Inspection of top genes revealed dynamic immune evasion and counter host responses specific to COVID-19. Statistical deconvolution of cell proportions maps many cell type proportions concordantly shifting. Discordantly increased in COVID-19 were CD56bright natural killer cells and M2 macrophages. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of the host response to SARS-CoV-2.

A photosensory two-component system regulates bacterial cell attachment.

Flavin-binding LOV domains are blue-light photosensory modules that are conserved in a number of developmental and circadian regulatory proteins in plants, algae, and fungi. LOV domains are also present in bacterial genomes, and are commonly located at the amino termini of sensor histidine kinases. Genes predicted to encode LOV-histidine kinases are conserved across a broad range of bacterial taxa, from aquatic oligotrophs to plant and mammalian pathogens. However, the function of these putative prokaryotic photoreceptors remains largely undefined. The differentiating bacterium, Caulobacter crescentus, contains an operon encoding a two-component signaling system consisting of a LOV-histidine kinase, LovK, and a single-domain response regulator, LovR. LovK binds a flavin cofactor, undergoes a reversible photocycle, and displays increased ATPase and autophosphorylation activity in response to visible light. Deletion of the response regulator gene, lovR, results in severe attenuation of cell attachment to a glass surface under laminar flow, whereas coordinate, low-level overexpression of lovK and lovR results in a light-independent increase in cell-cell attachment, a response that requires both the conserved histidine phosphorylation site in LovK and aspartate phosphorylation site in LovR. Growing C. crescentus in the presence of blue light dramatically enhances cell-cell attachment in the lovK-lovR overexpression background. A conserved cysteine residue in the LOV domain of LovK, which forms a covalent adduct with the flavin cofactor upon absorption of visible light, is necessary for the light-dependent regulation of LovK enzyme activity and is required for the light-dependent enhancement of intercellular attachment.

Small-Molecule Antagonists of the RIG-I Innate Immune Receptor.

The RIG-I receptor plays a key role in the vertebrate innate immune system, where it functions as a sensor for detecting infection by RNA viruses. Although agonists of RIG-I show great potential as antitumor and antimicrobial therapies, antagonists of RIG-I remain undeveloped, despite the role of RIG-I hyperstimulation in a range of diseases, including COPD and autoimmune disorders. There is now a wealth of information on RIG-I structure, enzymatic function, and signaling mechanism that can drive new drug design strategies. Here, we used the enzymatic activity of RIG-I to develop assays for high-throughput screening, SAR, and downstream optimization of RIG-I antagonists. Using this approach, we have developed potent RIG-I antagonists that interact directly with the receptor and which inhibit RIG-I signaling and interferon response in living cells.

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.

Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.

Inappropriate ICD shocks for inappropriate reasons.

ICD shocks can result from a variety of etiologies; determining the proper etiology of the inappropriate shock is essential for correction of the problem. Electromagnetic interference (EMI) can mimic cardiac signals and cause inappropriate defibrillator shocks. We present two cases of inappropriate ICD shocks due to EMI and reversal of the proximal and distal DF-1 lead terminals of the ICD lead. These are two unusual etiologies for inappropriate defibrillator shocks.

Establishing the role of ATP for the function of the RIG-I innate immune sensor.

Retinoic acid-inducible gene I (RIG-I) initiates a rapid innate immune response upon detection and binding to viral ribonucleic acid (RNA). This signal activation occurs only when pathogenic RNA is identified, despite the ability of RIG-I to bind endogenous RNA while surveying the cytoplasm. Here we show that ATP binding and hydrolysis by RIG-I play a key role in the identification of viral targets and the activation of signaling. Using biochemical and cell-based assays together with mutagenesis, we show that ATP binding, and not hydrolysis, is required for RIG-I signaling on viral RNA. However, we show that ATP hydrolysis does provide an important function by recycling RIG-I and promoting its dissociation from non-pathogenic RNA. This activity provides a valuable proof-reading mechanism that enhances specificity and prevents an antiviral response upon encounter with host RNA molecules.

Parts, assembly and operation of the RIG-I family of motors.

Host cell invasion is monitored by a series of pattern recognition receptors (PRRs) that activate the innate immune machinery upon detection of a cognate pathogen associated molecular pattern (PAMP). The RIG-I like receptor (RLR) family of PRRs includes three proteins--RIG-I, MDA5, and LGP2--responsible for the detection of intracellular pathogenic RNA. All RLR proteins are built around an ATPase core homologous to those found in canonical Superfamily 2 (SF2) RNA helicases, which has been modified through the addition of novel accessory domains to recognize duplex RNA. This review focuses on the structural bases for pathogen-specific dsRNA binding and ATPase activation in RLRs, differential RNA recognition by RLR family members, and implications for other duplex RNA activated ATPases, such as Dicer.

An evolving arsenal: viral RNA detection by RIG-I-like receptors.

RIG-I-like receptors (RLRs) utilize a specialized, multi-domain architecture to detect and respond to invasion by a diverse set of viruses. Structural similarities among these receptors provide a general mechanism for double strand RNA recognition and signal transduction. However, each RLR has developed unique strategies for sensing the specific molecular determinants on subgroups of viral RNAs. As a means to circumvent the antiviral response, viruses escape RLR detection by degrading, or sequestering or modifying their RNA. Patterns of variation in RLR sequence reveal a continuous evolution of the protein domains that contribute to RNA recognition and signaling.

In vivo approaches to dissecting the function of RNA helicases in eukaryotic ribosome assembly.

In eukaryotes, ribosome biogenesis involves the nucleolar transcription and processing of pre-ribosomal RNA molecules (pre-rRNA) in a complex pathway requiring the participation of myriad protein and ribonucleoprotein factors. Through efforts aimed at categorizing and characterizing these factors, at least 20 RNA helicases have been shown to interact with or participate in the activities of the major ribosome biogenesis complexes. Unfortunately, little is known about the enzymatic properties of most of these helicases, and less is known about their roles in ribosome biogenesis and pre-rRNA maturation. This chapter presents approaches for characterizing RNA helicases involved in ribosome biogenesis. Included are methods for depletion of specific protein targets, with standard protocols for assaying the typical ribosome biogenesis defects that may result. Procedures and rationales for mutagenic studies of target proteins are discussed, as well as several approaches for identifying protein-protein interactions in order to determine functional context and potential cofactors of RNA helicases.

The magnitude of sinus cycle length change during ventricular tachycardia is predictive of successful antitachycardia pacing.

BACKGROUND: Despite the wide use of antitachycardia pacing (ATP) in patients with implantable cardioverter defibrillators (ICDs), predictors of ATP success remain poorly understood. We hypothesize that the degree of sympathoexcitation, as measured by the sinus cycle length (SCL) shortening during ventricular tachycardia (VT), is a predictor of ATP success. METHODS AND RESULTS: The charts of 462 patients with dual-chamber ICDs were reviewed. A total of 88 events in 26 patients met the inclusion criteria and were analyzed. The mean SCL during the 4 seconds preceding the VT onset (SCL-baseline), and during the 4 seconds prior to ATP delivery (SCL-VT) was measured. The percent shortening in SCL was calculated as ((SCL-baseline) - (SCL-VT))/(SCL-baseline) x 100. Patients were classified into the ATP-success and ATP-failure groups depending on the VT(s) response to ATP. Using a t-test analogue for clustered data, patients in the ATP-success group exhibited a greater shortening in SCL when compared with the ATP-Failure group (5.8% compared to 4.7%, P = 0.007). The successful ATP events displayed an average SCL shortening of 6.0% compared to 1.8% in the unsuccessful ATP events (P = 0.029). When the events were analyzed, the sensitivity and specificity of a shortening in SCL of >10% in predicting ATP success were 0.29 and 1. CONCLUSION: We have shown that the SCL change during VT, a marker of the autonomic changes that accompany a tachycardia, is useful in predicting ATP success. Our findings suggest that analysis of the SCL during VT might play a role in future programming of ATP in patients with ICDs.