Viral Detection by Reverse Transcriptase Polymerase Chain Reaction in Upper Respiratory Tract and Metagenomic RNA Sequencing in Lower Respiratory Tract in Critically Ill Children With Suspected Lower Respiratory Tract Infection.

OBJECTIVES: Viral lower respiratory tract infection (vLRTI) contributes to substantial morbidity and mortality in children. Diagnosis is typically confirmed by reverse transcriptase polymerase chain reaction (RT-PCR) of nasopharyngeal specimens in hospitalized patients; however, it is unknown whether nasopharyngeal detection accurately reflects presence of virus in the lower respiratory tract (LRT). This study evaluates agreement between viral detection from nasopharyngeal specimens by RT-PCR compared with metagenomic next-generation RNA sequencing (RNA-Seq) from tracheal aspirates (TAs). DESIGN: This is an analysis of of a seven-center prospective cohort study. SETTING: Seven PICUs within academic children's hospitals in the United States. PATIENTS: Critically ill children (from 1 mo to 18 yr) who required mechanical ventilation via endotracheal tube for greater than or equal to 72 hours. INTERVENTIONS: We evaluated agreement in viral detection between paired upper and LRT samples. Results of clinical nasopharyngeal RT-PCR were compared with TA RNA-Seq. Positive and negative predictive agreement and Cohen's Kappa were used to assess agreement. MEASUREMENTS AND MAIN RESULTS: Of 295 subjects with paired testing available, 200 (68%) and 210 (71%) had positive viral testing by RT-PCR from nasopharyngeal and RNA-Seq from TA samples, respectively; 184 (62%) were positive by both nasopharyngeal RT-PCR and TA RNA-Seq for a virus, and 69 (23%) were negative by both methods. Nasopharyngeal RT-PCR detected the most abundant virus identified by RNA-Seq in 92.4% of subjects. Among the most frequent viruses detected, respiratory syncytial virus demonstrated the highest degree of concordance (κ = 0.89; 95% CI, 0.83-0.94), whereas rhinovirus/enterovirus demonstrated lower concordance (κ = 0.55; 95% CI, 0.44-0.66). Nasopharyngeal PCR was more likely to detect multiple viruses than TA RNA-Seq (54 [18.3%] vs 24 [8.1%], p ≤ 0.001). CONCLUSIONS: Viral nucleic acid detection in the upper versus LRT reveals good overall agreement, but concordance depends on the virus. Further studies are indicated to determine the utility of LRT sampling or the use of RNA-Seq to determine LRTI etiology.

FLASH: a next-generation CRISPR diagnostic for multiplexed detection of antimicrobial resistance sequences.

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

Integrating host response and unbiased microbe detection for lower respiratory tract infection diagnosis in critically ill adults.

Lower respiratory tract infections (LRTIs) lead to more deaths each year than any other infectious disease category. Despite this, etiologic LRTI pathogens are infrequently identified due to limitations of existing microbiologic tests. In critically ill patients, noninfectious inflammatory syndromes resembling LRTIs further complicate diagnosis. To address the need for improved LRTI diagnostics, we performed metagenomic next-generation sequencing (mNGS) on tracheal aspirates from 92 adults with acute respiratory failure and simultaneously assessed pathogens, the airway microbiome, and the host transcriptome. To differentiate pathogens from respiratory commensals, we developed a rules-based model (RBM) and logistic regression model (LRM) in a derivation cohort of 20 patients with LRTIs or noninfectious acute respiratory illnesses. When tested in an independent validation cohort of 24 patients, both models achieved accuracies of 95.5%. We next developed pathogen, microbiome diversity, and host gene expression metrics to identify LRTI-positive patients and differentiate them from critically ill controls with noninfectious acute respiratory illnesses. When tested in the validation cohort, the pathogen metric performed with an area under the receiver-operating curve (AUC) of 0.96 (95% CI, 0.86-1.00), the diversity metric with an AUC of 0.80 (95% CI, 0.63-0.98), and the host transcriptional classifier with an AUC of 0.88 (95% CI, 0.75-1.00). Combining these achieved a negative predictive value of 100%. This study suggests that a single streamlined protocol offering an integrated genomic portrait of pathogen, microbiome, and host transcriptome may hold promise as a tool for LRTI diagnosis.

Investigating Transfusion-related Sepsis Using Culture-Independent Metagenomic Sequencing.

BACKGROUND: Transfusion-related sepsis remains an important hospital infection control challenge. Investigation of septic transfusion events is often restricted by the limitations of bacterial culture in terms of time requirements and low yield in the setting of prior antibiotic administration. METHODS: In 3 gram-negative septic transfusion cases, we performed metagenomic next-generation sequencing (mNGS) of direct clinical blood specimens in addition to standard culture-based approaches utilized for infection control investigations. Pathogen detection leveraged IDSeq, a new open-access microbial bioinformatics portal. Phylogenetic analysis was performed to assess microbial genetic relatedness and understand transmission events. RESULTS: mNGS of direct clinical blood specimens afforded precision detection of pathogens responsible for each case of transfusion-related sepsis and enabled discovery of a novel Acinetobacter species in a platelet product that had become contaminated despite photochemical pathogen reduction. In each case, longitudinal assessment of pathogen burden elucidated the temporal sequence of events associated with each transfusion-transmitted infection. We found that informative data could be obtained from culture-independent mNGS of residual platelet products and leftover blood specimens that were either unsuitable or unavailable for culture or that failed to grow due to prior antibiotic administration. We additionally developed methods to enhance accuracy for detecting transfusion-associated pathogens that share taxonomic similarity to contaminants commonly found in mNGS library preparations. CONCLUSIONS: Culture-independent mNGS of blood products afforded rapid and precise assessment of pathogen identity, abundance, and genetic relatedness. Together, these challenging cases demonstrated the potential for metagenomics to advance existing methods for investigating transfusion-transmitted infections.

Metagenomic comparison of tracheal aspirate and mini-bronchial alveolar lavage for assessment of respiratory microbiota.

Accurate and informative microbiological testing is essential for guiding diagnosis and management of pneumonia in patients who are critically ill. Sampling of tracheal aspirate (TA) is less invasive compared with mini-bronchoalveolar lavage (mBAL) and is now recommended as a frontline diagnostic approach in patients who are mechanically ventilated, despite the historical belief that TA was suboptimal due to contamination from oral microbes. Advancements in metagenomic next-generation sequencing (mNGS) now permit assessment of airway microbiota without a need for culture and, as such, provide an opportunity to examine differences between mBAL and TA at a resolution previously unachievable. Here, we engaged shotgun mNGS to assess quantitatively the airway microbiome in matched mBAL and TA specimens from a prospective cohort of critically ill adults. We observed moderate differences between sample types across all subjects; however, we found significant compositional similarity in subjects with bacterial pneumonia, whose microbial communities were characterized by dominant pathogens. In contrast, in patients with noninfectious acute respiratory illnesses, significant differences were observed between sample types. Our findings suggest that TA sampling provides a similar assessment of airway microbiota as more invasive testing by mBAL in patients with pneumonia.

Microbiome and Antimicrobial Resistance Gene Dynamics in International Travelers.

We used metagenomic next-generation sequencing to longitudinally assess the gut microbiota and antimicrobial resistomes of international travelers to clarify global exchange of resistant organisms. Travel resulted in an increase in antimicrobial resistance genes and a greater proportion of Escherichia species within gut microbial communities without impacting diversity.

Aerosolized nicotine from e-cigarettes alters gene expression, increases lung protein permeability, and impairs viral clearance in murine influenza infection.

E-cigarette use has rapidly increased as an alternative means of nicotine delivery by heated aerosolization. Recent studies demonstrate nicotine-containing e-cigarette aerosols can have immunosuppressive and pro-inflammatory effects, but it remains unclear how e-cigarettes and the constituents of e-liquids may impact acute lung injury and the development of acute respiratory distress syndrome caused by viral pneumonia. Therefore, in these studies, mice were exposed one hour per day over nine consecutive days to aerosol generated by the clinically-relevant tank-style Aspire Nautilus aerosolizing e-liquid containing a mixture of vegetable glycerin and propylene glycol (VG/PG) with or without nicotine. Exposure to the nicotine-containing aerosol resulted in clinically-relevant levels of plasma cotinine, a nicotine-derived metabolite, and an increase in the pro-inflammatory cytokines IL-17A, CXCL1, and MCP-1 in the distal airspaces. Following the e-cigarette exposure, mice were intranasally inoculated with influenza A virus (H1N1 PR8 strain). Exposure to aerosols generated from VG/PG with and without nicotine caused greater influenza-induced production in the distal airspaces of the pro-inflammatory cytokines IFN-γ, TNFα, IL-1ß, IL-6, IL-17A, and MCP-1 at 7 days post inoculation (dpi). Compared to the aerosolized carrier VG/PG, in mice exposed to aerosolized nicotine there was a significantly lower amount of Mucin 5 subtype AC (MUC5AC) in the distal airspaces and significantly higher lung permeability to protein and viral load in lungs at 7 dpi with influenza. Additionally, nicotine caused relative downregulation of genes associated with ciliary function and fluid clearance and an increased expression of pro-inflammatory pathways at 7 dpi. These results show that (1) the e-liquid carrier VG/PG increases the pro-inflammatory immune responses to viral pneumonia and that (2) nicotine in an e-cigarette aerosol alters the transcriptomic response to pathogens, blunts host defense mechanisms, increases lung barrier permeability, and reduces viral clearance during influenza infection. In conclusion, acute exposure to aerosolized nicotine can impair clearance of viral infection and exacerbate lung injury, findings that have implications for the regulation of e-cigarette products.

Index cases first identified by nasal-swab rapid COVID-19 tests had more transmission to household contacts than cases identified by other test types.

At-home rapid COVID-19 tests in the U.S. utilize nasal-swab specimens and require high viral loads to reliably give positive results. Longitudinal studies from the onset of infection have found infectious virus can present in oral specimens days before nasal. Detection and initiation of infection-control practices may therefore be delayed when nasal-swab rapid tests are used, resulting in greater transmission to contacts. We assessed whether index cases first identified by rapid nasal-swab COVID-19 tests had more transmission to household contacts than index cases who used other test types (tests with higher analytical sensitivity and/or non-nasal specimen types). In this observational cohort study, 370 individuals from 85 households with a recent COVID-19 case were screened at least daily by RT-qPCR on one or more self-collected upper-respiratory specimen types. A two-level random intercept model was used to assess the association between the infection outcome of household contacts and each covariable (household size, race/ethnicity, age, vaccination status, viral variant, infection-control practices, and whether a rapid nasal-swab test was used to initially identify the household index case). Transmission was quantified by adjusted secondary attack rates (aSAR) and adjusted odds ratios (aOR). An aSAR of 53.6% (95% CI 38.8-68.3%) was observed among households where the index case first tested positive by a rapid nasal-swab COVID-19 test, which was significantly higher than the aSAR for households where the index case utilized another test type (27.2% 95% CI 19.5-35.0%, P = 0.003 pairwise comparisons of predictive margins). We observed an aOR of 4.90 (95% CI 1.65-14.56) for transmission to household contacts when a nasal-swab rapid test was used to identify the index case, compared to other test types. Use of nasal-swab rapid COVID-19 tests for initial detection of infection and initiation of infection control may be less effective at limiting transmission to household contacts than other test types.

Daily SARS-CoV-2 Nasal Antigen Tests Miss Infected and Presumably Infectious People Due to Viral Load Differences among Specimen Types.

In a recent household transmission study of SARS-CoV-2, we found extreme differences in SARS-CoV-2 viral loads among paired saliva, anterior nares swab (ANS), and oropharyngeal swab specimens collected from the same time point. We hypothesized these differences may hinder low-analytical-sensitivity assays (including antigen rapid diagnostic tests [Ag-RDTs]) by using a single specimen type (e.g., ANS) from reliably detecting infected and infectious individuals. We evaluated daily at-home ANS Ag-RDTs (Quidel QuickVue) in a cross-sectional analysis of 228 individuals and a longitudinal analysis (throughout infection) of 17 individuals enrolled early in the course of infection. Ag-RDT results were compared to reverse transcription-quantitative PCR (RT-qPCR) results and high, presumably infectious viral loads (in each, or any, specimen type). The ANS Ag-RDT correctly detected only 44% of time points from infected individuals on cross-sectional analysis, and this population had an inferred limit of detection of 7.6 × 106 copies/mL. From the longitudinal cohort, daily Ag-RDT clinical sensitivity was very low (<3%) during the early, preinfectious period of the infection. Further, the Ag-RDT detected ≤63% of presumably infectious time points. The poor observed clinical sensitivity of the Ag-RDT was similar to what was predicted based on quantitative ANS viral loads and the inferred limit of detection of the ANS Ag-RDT being evaluated, indicating high-quality self-sampling. Nasal Ag-RDTs, even when used daily, can miss individuals infected with the Omicron variant and even those presumably infectious. Evaluations of Ag-RDTs for detection of infected or infectious individuals should be compared with a composite (multispecimen) infection status to correctly assess performance. IMPORTANCE We reveal three findings from a longitudinal study of daily nasal antigen rapid diagnostic test (Ag-RDT) evaluated against SARS-CoV-2 viral load quantification in three specimen types (saliva, nasal swab, and throat swab) in participants enrolled at the incidence of infection. First, the evaluated Ag-RDT showed low (44%) clinical sensitivity for detecting infected persons at all infection stages. Second, the Ag-RDT poorly detected (≤63%) time points that participants had high and presumably infectious viral loads in at least one specimen type. This poor clinical sensitivity to detect infectious individuals is inconsistent with the commonly held view that daily Ag-RDTs have near-perfect detection of infectious individuals. Third, use of a combination nasal-throat specimen type was inferred by viral loads to significantly improve Ag-RDT performance to detect infectious individuals.

Extreme differences in SARS-CoV-2 viral loads among respiratory specimen types during presumed pre-infectious and infectious periods.

SARS-CoV-2 viral-load measurements from a single-specimen type are used to establish diagnostic strategies, interpret clinical-trial results for vaccines and therapeutics, model viral transmission, and understand virus-host interactions. However, measurements from a single-specimen type are implicitly assumed to be representative of other specimen types. We quantified viral-load timecourses from individuals who began daily self-sampling of saliva, anterior-nares (nasal), and oropharyngeal (throat) swabs before or at the incidence of infection with the Omicron variant. Viral loads in different specimen types from the same person at the same timepoint exhibited extreme differences, up to 109 copies/mL. These differences were not due to variation in sample self-collection, which was consistent. For most individuals, longitudinal viral-load timecourses in different specimen types did not correlate. Throat-swab and saliva viral loads began to rise as many as 7 days earlier than nasal-swab viral loads in most individuals, leading to very low clinical sensitivity of nasal swabs during the first days of infection. Individuals frequently exhibited presumably infectious viral loads in one specimen type while viral loads were low or undetectable in other specimen types. Therefore, defining an individual as infectious based on assessment of a single-specimen type underestimates the infectious period, and overestimates the ability of that specimen type to detect infectious individuals. For diagnostic COVID-19 testing, these three single-specimen types have low clinical sensitivity, whereas a combined throat-nasal swab, and assays with high analytical sensitivity, was inferred to have significantly better clinical sensitivity to detect presumed pre-infectious and infectious individuals.

Integrated host/microbe metagenomics enables accurate lower respiratory tract infection diagnosis in critically ill children.

BACKGROUNDLower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging because noninfectious respiratory illnesses appear clinically similar and because existing microbiologic tests are often falsely negative or detect incidentally carried microbes, resulting in antimicrobial overuse and adverse outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and treatment remains unclear.METHODSWe used tracheal aspirate RNA-Seq to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n = 117) or of noninfectious respiratory failure (n = 50). We then developed a classifier that integrates the host LRTI probability, abundance of respiratory viruses, and dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm.RESULTSThe host classifier achieved a median AUC of 0.967 by cross-validation, driven by activation markers of T cells, alveolar macrophages, and the interferon response. The integrated classifier achieved a median AUC of 0.986 and increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n = 94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those.CONCLUSIONLower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.FUNDINGSupport for this study was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Heart, Lung, and Blood Institute (UG1HD083171, 1R01HL124103, UG1HD049983, UG01HD049934, UG1HD083170, UG1HD050096, UG1HD63108, UG1HD083116, UG1HD083166, UG1HD049981, K23HL138461, and 5R01HL155418) as well as by the Chan Zuckerberg Biohub.

Functional Transcriptomic Studies of Immune Responses and Endotoxin Tolerance in Early Human Sepsis.

BACKGROUND: Limited studies have functionally evaluated the heterogeneity in early ex vivo immune responses during sepsis. Our aim was to characterize early sepsis ex vivo functional immune response heterogeneity by studying whole blood endotoxin responses and derive a transcriptional metric of ex vivo endotoxin response. METHODS: Blood collected within 24 h of hospital presentation from 40 septic patients was divided into two fractions and incubated with media (unstimulated) or endotoxin. Supernatants and cells were isolated, and responses measured using: supernatant cytokines, lung endothelial permeability after supernatant exposure, and RNA expression. A transcriptomic signature was derived in unstimulated cells to predict the ex vivo endotoxin response. The signature was tested in a separate cohort of 191 septic patients to evaluate for association with clinical outcome. Plasma biomarkers were quantified to measure in vivo host inflammation. RESULTS: Ex vivo response to endotoxin varied and was unrelated to immunosuppression, white blood cell count, or the causative pathogen. Thirty-five percent of patients demonstrated a minimal response to endotoxin, suggesting early immunosuppression. High ex vivo cytokine production by stimulated blood cells correlated with increased in vitro pulmonary endothelial cell permeability and was associated with attenuated in vivo host inflammation. A four-gene signature of endotoxin response detectable without the need for a functional assay was identified. When tested in a separate cohort of septic patients, its expression was inversely associated with hospital mortality. CONCLUSIONS: An attenuated ex vivo endotoxin response in early sepsis is associated with greater host in vivo inflammation and a worse clinical outcome.

Metagenomic prediction of antimicrobial resistance in critically ill patients with lower respiratory tract infections.

BACKGROUND: Antimicrobial resistance (AMR) is rising at an alarming rate and complicating the management of infectious diseases including lower respiratory tract infections (LRTI). Metagenomic next-generation sequencing (mNGS) is a recently established method for culture-independent LRTI diagnosis, but its utility for predicting AMR has remained unclear. We aimed to assess the performance of mNGS for AMR prediction in bacterial LRTI and demonstrate proof of concept for epidemiological AMR surveillance and rapid AMR gene detection using Cas9 enrichment and nanopore sequencing. METHODS: We studied 88 patients with acute respiratory failure between 07/2013 and 9/2018, enrolled through a previous observational study of LRTI. Inclusion criteria were age ≥ 18, need for mechanical ventilation, and respiratory specimen collection within 72 h of intubation. Exclusion criteria were decline of study participation, unclear LRTI status, or no matched RNA and DNA mNGS data from a respiratory specimen. Patients with LRTI were identified by clinical adjudication. mNGS was performed on lower respiratory tract specimens. The primary outcome was mNGS performance for predicting phenotypic antimicrobial susceptibility and was assessed in patients with LRTI from culture-confirmed bacterial pathogens with clinical antimicrobial susceptibility testing (n = 27 patients, n = 32 pathogens). Secondary outcomes included the association between hospital exposure and AMR gene burden in the respiratory microbiome (n = 88 patients), and AMR gene detection using Cas9 targeted enrichment and nanopore sequencing (n = 10 patients). RESULTS: Compared to clinical antimicrobial susceptibility testing, the performance of respiratory mNGS for predicting AMR varied by pathogen, antimicrobial, and nucleic acid type sequenced. For gram-positive bacteria, a combination of RNA + DNA mNGS achieved a sensitivity of 70% (95% confidence interval (CI) 47-87%) and specificity of 95% (CI 85-99%). For gram-negative bacteria, sensitivity was 100% (CI 87-100%) and specificity 64% (CI 48-78%). Patients with hospital-onset LRTI had a greater AMR gene burden in their respiratory microbiome versus those with community-onset LRTI (p = 0.00030), or those without LRTI (p = 0.0024). We found that Cas9 targeted sequencing could enrich for low abundance AMR genes by > 2500-fold and enabled their rapid detection using a nanopore platform. CONCLUSIONS: mNGS has utility for the detection and surveillance of resistant bacterial LRTI pathogens.

Pneumonia surveillance with culture-independent metatranscriptomics in HIV-positive adults in Uganda: a cross-sectional study.

BACKGROUND: Pneumonia is a leading cause of death worldwide and is a major health-care challenge in people living with HIV. Despite this, the causes of pneumonia in this population remain poorly understood. We aimed to assess the feasibility of metatranscriptomics for epidemiological surveillance of pneumonia in patients with HIV in Uganda. METHODS: We performed a retrospective observational study in patients with HIV who were admitted to Mulago Hospital, Kampala, Uganda between Oct 1, 2009, and Dec 31, 2011. Inclusion criteria were age 18 years or older, HIV-positivity, and clinically diagnosed pneumonia. Exclusion criteria were contraindication to bronchoscopy or an existing diagnosis of tuberculosis. Bronchoalveolar lavage fluid was collected within 72 h of admission and a combination of RNA sequencing and Mycobacterium tuberculosis culture plus PCR were performed. The primary outcome was detection of an established or possible respiratory pathogen in the total study population. FINDINGS: We consecutively enrolled 217 patients during the study period. A potential microbial cause for pneumonia was identified in 211 (97%) patients. At least one microorganism of established respiratory pathogenicity was identified in 113 (52%) patients, and a microbe of possible pathogenicity was identified in an additional 98 (45%). M tuberculosis was the most commonly identified established pathogen (35 [16%] patients; in whom bacterial or viral co-infections were identified in 13 [37%]). Streptococcus mitis, although not previously reported as a cause of pneumonia in patients with HIV, was the most commonly identified bacterial organism (37 [17%] patients). Haemophilus influenzae was the most commonly identified established bacterial pathogen (20 [9%] patients). Pneumocystis jirovecii was only identified in patients with a CD4 count of less than 200 cells per mL. INTERPRETATION: We show the feasibility of using metatranscriptomics for epidemiologic surveillance of pneumonia by describing the spectrum of respiratory pathogens in adults with HIV in Uganda. Applying these methods to a contemporary cohort could enable broad assessment of changes in pneumonia aetiology following the emergence of SARS-CoV-2. FUNDING: US National Institutes of Health, Chan Zuckerberg Biohub.

Upper airway gene expression shows a more robust adaptive immune response to SARS-CoV-2 in children.

Unlike other respiratory viruses, SARS-CoV-2 disproportionately causes severe disease in older adults whereas disease burden in children is lower. To investigate whether differences in the upper airway immune response may contribute to this disparity, we compare nasopharyngeal gene expression in 83 children (<19-years-old; 38 with SARS-CoV-2, 11 with other respiratory viruses, 34 with no virus) and 154 older adults (>40-years-old; 45 with SARS-CoV-2, 28 with other respiratory viruses, 81 with no virus). Expression of interferon-stimulated genes is robustly activated in both children and adults with SARS-CoV-2 infection compared to the respective non-viral groups, with only subtle distinctions. Children, however, demonstrate markedly greater upregulation of pathways related to B cell and T cell activation and proinflammatory cytokine signaling, including response to TNF and production of IFNγ, IL-2 and IL-4. Cell type deconvolution confirms greater recruitment of B cells, and to a lesser degree macrophages, to the upper airway of children. Only children exhibit a decrease in proportions of ciliated cells, among the primary targets of SARS-CoV-2, upon infection. These findings demonstrate that children elicit a more robust innate and especially adaptive immune response to SARS-CoV-2 in the upper airway that likely contributes to their protection from severe disease in the lower airway.

Integrated host-microbe plasma metagenomics for sepsis diagnosis in a prospective cohort of critically ill adults.

We carried out integrated host and pathogen metagenomic RNA and DNA next generation sequencing (mNGS) of whole blood (n = 221) and plasma (n = 138) from critically ill patients following hospital admission. We assigned patients into sepsis groups on the basis of clinical and microbiological criteria. From whole-blood gene expression data, we distinguished patients with sepsis from patients with non-infectious systemic inflammatory conditions using a trained bagged support vector machine (bSVM) classifier (area under the receiver operating characteristic curve (AUC) = 0.81 in the training set; AUC = 0.82 in a held-out validation set). Plasma RNA also yielded a transcriptional signature of sepsis with several genes previously reported as sepsis biomarkers, and a bSVM sepsis diagnostic classifier (AUC = 0.97 training set; AUC = 0.77 validation set). Pathogen detection performance of plasma mNGS varied on the basis of pathogen and site of infection. To improve detection of virus, we developed a secondary transcriptomic classifier (AUC = 0.94 training set; AUC = 0.96 validation set). We combined host and microbial features to develop an integrated sepsis diagnostic model that identified 99% of microbiologically confirmed sepsis cases, and predicted sepsis in 74% of suspected and 89% of indeterminate sepsis cases. In summary, we suggest that integrating host transcriptional profiling and broad-range metagenomic pathogen detection from nucleic acid is a promising tool for sepsis diagnosis.

Lower respiratory tract infections in children requiring mechanical ventilation: a multicentre prospective surveillance study incorporating airway metagenomics.

BACKGROUND: Lower respiratory tract infections (LRTI) are a leading cause of critical illness and mortality in mechanically ventilated children; however, the pathogenic microbes frequently remain unknown. We combined traditional diagnostics with metagenomic next generation sequencing (mNGS) to evaluate the cause of LRTI in critically ill children. METHODS: We conducted a prospective, multicentre cohort study of critically ill children aged 31 days to 17 years with respiratory failure requiring mechanical ventilation (>72 h) in the USA. By combining bacterial culture and upper respiratory viral PCR testing with mNGS of tracheal aspirate collected from all patients within 24 h of intubation, we determined the prevalence, age distribution, and seasonal variation of viral and bacterial respiratory pathogens detected by either method in children with or without LRTI. FINDINGS: Between Feb 26, 2015, and Dec 31, 2017, of the 514 enrolled patients, 397 were eligible and included in the study (276 children with LRTI and 121 with no evidence of LRTI). A presumptive microbiological cause was identified in 255 (92%) children with LRTI, with respiratory syncytial virus (127 [46%]), Haemophilus influenzae (70 [25%]), and Moraxella catarrhalis (65 [24%]) being most prevalent. mNGS identified uncommon pathogens including Ureaplasma parvum and Bocavirus. Co-detection of viral and bacterial pathogens occurred in 144 (52%) patients. Incidental carriage of potentially pathogenic microbes occurred in 82 (68%) children without LRTI, with rhinovirus (30 [25%]) being most prevalent. Respiratory syncytial virus (p<0·0001), H influenzae (p=0·0006), and M catarrhalis (p=0·0002) were most common in children younger than 5 years. Viral and bacterial LRTI occurred predominantly during winter months. INTERPRETATION: These findings demonstrate that respiratory syncytial virus, H influenzae, and M catarrhalis contribute disproportionately to severe paediatric LRTI, co-infections are common, and incidental carriage of potentially pathogenic microbes occurs frequently. Further, we provide a framework for future epidemiological and emerging pathogen surveillance studies, highlighting the potential for metagenomics to enhance clinical diagnosis. FUNDING: US National Institutes of Health and CZ Biohub.

The sputum transcriptome better predicts COPD exacerbations after the withdrawal of inhaled corticosteroids than sputum eosinophils.

INTRODUCTION: Continuing inhaled corticosteroid (ICS) use does not benefit all patients with COPD, yet it is difficult to determine which patients may safely sustain ICS withdrawal. Although eosinophil levels can facilitate this decision, better biomarkers could improve personalised treatment decisions. METHODS: We performed transcriptional profiling of sputum to explore the molecular biology and compared the predictive value of an unbiased gene signature versus sputum eosinophils for exacerbations after ICS withdrawal in COPD patients. RNA-sequencing data of induced sputum samples from 43 COPD patients were associated with the time to exacerbation after ICS withdrawal. Expression profiles of differentially expressed genes were summarised to create gene signatures. In addition, we built a Bayesian network model to determine coregulatory networks related to the onset of COPD exacerbations after ICS withdrawal. RESULTS: In multivariate analyses, we identified a gene signature (LGALS12, ALOX15, CLC, IL1RL1, CD24, EMR4P) associated with the time to first exacerbation after ICS withdrawal. The addition of this gene signature to a multiple Cox regression model explained more variance of time to exacerbations compared to a model using sputum eosinophils. The gene signature correlated with sputum eosinophil as well as macrophage cell counts. The Bayesian network model identified three coregulatory gene networks as well as sex to be related to an early versus late/nonexacerbation phenotype. CONCLUSION: We identified a sputum gene expression signature that exhibited a higher predictive value for predicting COPD exacerbations after ICS withdrawal than sputum eosinophilia. Future studies should investigate the utility of this signature, which might enhance personalised ICS treatment in COPD patients.