Human SARS-CoV-2 challenge uncovers local and systemic response dynamics.

The COVID-19 pandemic is an ongoing global health threat, yet our understanding of the dynamics of early cellular responses to this disease remains limited1. Here in our SARS-CoV-2 human challenge study, we used single-cell multi-omics profiling of nasopharyngeal swabs and blood to temporally resolve abortive, transient and sustained infections in seronegative individuals challenged with pre-Alpha SARS-CoV-2. Our analyses revealed rapid changes in cell-type proportions and dozens of highly dynamic cellular response states in epithelial and immune cells associated with specific time points and infection status. We observed that the interferon response in blood preceded the nasopharyngeal response. Moreover, nasopharyngeal immune infiltration occurred early in samples from individuals with only transient infection and later in samples from individuals with sustained infection. High expression of HLA-DQA2 before inoculation was associated with preventing sustained infection. Ciliated cells showed multiple immune responses and were most permissive for viral replication, whereas nasopharyngeal T cells and macrophages were infected non-productively. We resolved 54 T cell states, including acutely activated T cells that clonally expanded while carrying convergent SARS-CoV-2 motifs. Our new computational pipeline Cell2TCR identifies activated antigen-responding T cells based on a gene expression signature and clusters these into clonotype groups and motifs. Overall, our detailed time series data can serve as a Rosetta stone for epithelial and immune cell responses and reveals early dynamic responses associated with protection against infection.

Tissue CD14+CD8+ T cells reprogrammed by myeloid cells and modulated by LPS.

The liver is bathed in bacterial products, including lipopolysaccharide transported from the intestinal portal vasculature, but maintains a state of tolerance that is exploited by persistent pathogens and tumours1-4. The cellular basis mediating this tolerance, yet allowing a switch to immunity or immunopathology, needs to be better understood for successful immunotherapy of liver diseases. Here we show that a variable proportion of CD8+ T cells compartmentalized in the human liver co-stain for CD14 and other prototypic myeloid membrane proteins and are enriched in close proximity to CD14high myeloid cells in hepatic zone 2. CD14+CD8+ T cells preferentially accumulate within the donor pool in liver allografts, among hepatic virus-specific and tumour-infiltrating responses, and in cirrhotic ascites. CD14+CD8+ T cells exhibit increased turnover, activation and constitutive immunomodulatory features with high homeostatic IL-10 and IL-2 production ex vivo, and enhanced antiviral/anti-tumour effector function after TCR engagement. This CD14+CD8+ T cell profile can be recapitulated by the acquisition of membrane proteins-including the lipopolysaccharide receptor complex-from mononuclear phagocytes, resulting in augmented tumour killing by TCR-redirected T cells in vitro. CD14+CD8+ T cells express integrins and chemokine receptors that favour interactions with the local stroma, which can promote their induction through CXCL12. Lipopolysaccharide can also increase the frequency of CD14+CD8+ T cells in vitro and in vivo, and skew their function towards the production of chemotactic and regenerative cytokines. Thus, bacterial products in the gut-liver axis and tissue stromal factors can tune liver immunity by driving myeloid instruction of CD8+ T cells with immunomodulatory ability.

Pre-existing polymerase-specific T cells expand in abortive seronegative SARS-CoV-2.

Individuals with potential exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) do not necessarily develop PCR or antibody positivity, suggesting that some individuals may clear subclinical infection before seroconversion. T cells can contribute to the rapid clearance of SARS-CoV-2 and other coronavirus infections1-3. Here we hypothesize that pre-existing memory T cell responses, with cross-protective potential against SARS-CoV-2 (refs. 4-11), would expand in vivo to support rapid viral control, aborting infection. We measured SARS-CoV-2-reactive T cells, including those against the early transcribed replication-transcription complex (RTC)12,13, in intensively monitored healthcare workers (HCWs) who tested repeatedly negative according to PCR, antibody binding and neutralization assays (seronegative HCWs (SN-HCWs)). SN-HCWs had stronger, more multispecific memory T cells compared with a cohort of unexposed individuals from before the pandemic (prepandemic cohort), and these cells were more frequently directed against the RTC than the structural-protein-dominated responses observed after detectable infection (matched concurrent cohort). SN-HCWs with the strongest RTC-specific T cells had an increase in IFI27, a robust early innate signature of SARS-CoV-2 (ref. 14), suggesting abortive infection. RNA polymerase within RTC was the largest region of high sequence conservation across human seasonal coronaviruses (HCoV) and SARS-CoV-2 clades. RNA polymerase was preferentially targeted (among the regions tested) by T cells from prepandemic cohorts and SN-HCWs. RTC-epitope-specific T cells that cross-recognized HCoV variants were identified in SN-HCWs. Enriched pre-existing RNA-polymerase-specific T cells expanded in vivo to preferentially accumulate in the memory response after putative abortive compared to overt SARS-CoV-2 infection. Our data highlight RTC-specific T cells as targets for vaccines against endemic and emerging Coronaviridae.

Evolution of enhanced innate immune evasion by SARS-CoV-2.

The emergence of SARS-CoV-2 variants of concern suggests viral adaptation to enhance human-to-human transmission1,2. Although much effort has focused on the characterization of changes in the spike protein in variants of concern, mutations outside of spike are likely to contribute to adaptation. Here, using unbiased abundance proteomics, phosphoproteomics, RNA sequencing and viral replication assays, we show that isolates of the Alpha (B.1.1.7) variant3 suppress innate immune responses in airway epithelial cells more effectively than first-wave isolates. We found that the Alpha variant has markedly increased subgenomic RNA and protein levels of the nucleocapsid protein (N), Orf9b and Orf6-all known innate immune antagonists. Expression of Orf9b alone suppressed the innate immune response through interaction with TOM70, a mitochondrial protein that is required for activation of the RNA-sensing adaptor MAVS. Moreover, the activity of Orf9b and its association with TOM70 was regulated by phosphorylation. We propose that more effective innate immune suppression, through enhanced expression of specific viral antagonist proteins, increases the likelihood of successful transmission of the Alpha variant, and may increase in vivo replication and duration of infection4. The importance of mutations outside the spike coding region in the adaptation of SARS-CoV-2 to humans is underscored by the observation that similar mutations exist in the N and Orf9b regulatory regions of the Delta and Omicron variants.

SARS-CoV-2 sensing by RIG-I and MDA5 links epithelial infection to macrophage inflammation.

SARS-CoV-2 infection causes broad-spectrum immunopathological disease, exacerbated by inflammatory co-morbidities. A better understanding of mechanisms underpinning virus-associated inflammation is required to develop effective therapeutics. Here, we discover that SARS-CoV-2 replicates rapidly in lung epithelial cells despite triggering a robust innate immune response through the activation of cytoplasmic RNA sensors RIG-I and MDA5. The inflammatory mediators produced during epithelial cell infection can stimulate primary human macrophages to enhance cytokine production and drive cellular activation. Critically, this can be limited by abrogating RNA sensing or by inhibiting downstream signalling pathways. SARS-CoV-2 further exacerbates the local inflammatory environment when macrophages or epithelial cells are primed with exogenous inflammatory stimuli. We propose that RNA sensing of SARS-CoV-2 in lung epithelium is a key driver of inflammation, the extent of which is influenced by the inflammatory state of the local environment, and that specific inhibition of innate immune pathways may beneficially mitigate inflammation-associated COVID-19.

Pneumolysin suppresses the initial macrophage pro-inflammatory response to Streptococcus pneumoniae.

Published data for the Streptococcus pneumoniae virulence factor Pneumolysin (Ply) show contradictory effects on the host inflammatory response to infection. Ply has been shown to activate the inflammasome, but also can bind to MRC-1 resulting in suppression of dendritic cell inflammatory responses. We have used an in vitro infection model of human monocyte-derived macrophages (MDM), and a mouse model of pneumonia to clarify whether pro- or anti-inflammatory effects dominate the effects of Ply on the initial macrophage inflammatory response to S. pneumoniae, and the consequences during early lung infection. We found that infection with S. pneumoniae expressing Ply suppressed tumour necrosis factor (TNF) and interleukin-6 production by MDMs compared to cells infected with ply-deficient S. pneumoniae. This effect was independent of bacterial effects on cell death. Transcriptional analysis demonstrated S. pneumoniae expressing Ply caused a qualitatively similar but quantitatively lower MDM transcriptional response to S. pneumoniae compared to ply-deficient S. pneumoniae, with reduced expression of TNF and type I IFN inducible genes. Reduction of the MDM inflammatory response was prevented by inhibition of SOCS1. In the early lung infection mouse model, the TNF response to ply-deficient S. pneumoniae was enhanced and bacterial clearance increased compared to infection with wild-type S. pneumoniae. Overall, these data show Ply inhibits the initial macrophage inflammatory response to S. pneumoniae, probably mediated through SOCS1, and this was associated with improved immune evasion during early lung infection.

HLA-DR polymorphism in SARS-CoV-2 infection and susceptibility to symptomatic COVID-19.

SARS-CoV-2 infection results in different outcomes ranging from asymptomatic infection to mild or severe disease and death. Reasons for this diversity of outcome include differences in challenge dose, age, gender, comorbidity and host genomic variation. Human leukocyte antigen (HLA) polymorphisms may influence immune response and disease outcome. We investigated the association of HLAII alleles with case definition symptomatic COVID-19, virus-specific antibody and T-cell immunity. A total of 1364 UK healthcare workers (HCWs) were recruited during the first UK SARS-CoV-2 wave and analysed longitudinally, encompassing regular PCR screening for infection, symptom reporting, imputation of HLAII genotype and analysis for antibody and T-cell responses to nucleoprotein (N) and spike (S). Of 272 (20%) HCW who seroconverted, the presence of HLA-DRB1*13:02 was associated with a 6·7-fold increased risk of case definition symptomatic COVID-19. In terms of immune responsiveness, HLA-DRB1*15:02 was associated with lower nucleocapsid T-cell responses. There was no association between DRB1 alleles and anti-spike antibody titres after two COVID vaccine doses. However, HLA DRB1*15:01 was associated with increased spike T-cell responses following both first and second dose vaccination. Trial registration: NCT04318314 and ISRCTN15677965.

Prospective validation of the 4C prognostic models for adults hospitalised with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol.

PURPOSE: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19. METHODS: Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups. RESULTS: 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, -0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions. CONCLUSION: Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making. TRIAL REGISTRATION NUMBER: ISRCTN66726260.

Viral infection triggers interferon-induced expulsion of live Cryptococcus neoformans by macrophages.

Cryptococcus neoformans is an opportunistic human pathogen, which causes serious disease in immunocompromised hosts. Infection with this pathogen is particularly relevant in HIV+ patients, where it leads to around 200,000 deaths per annum. A key feature of cryptococcal pathogenesis is the ability of the fungus to survive and replicate within the phagosome of macrophages, as well as its ability to be expelled from host cells via a novel non-lytic mechanism known as vomocytosis. Here we show that cryptococcal vomocytosis from macrophages is strongly enhanced by viral coinfection, without altering phagocytosis or intracellular proliferation of the fungus. This effect occurs with distinct, unrelated human viral pathogens and is recapitulated when macrophages are stimulated with the anti-viral cytokines interferon alpha or beta (IFNα or IFNß). Importantly, the effect is abrogated when type-I interferon signalling is blocked, thus underscoring the importance of type-I interferons in this phenomenon. Lastly, our data help resolve previous, contradictory animal studies on the impact of type I interferons on cryptococcal pathogenesis and suggest that secondary viral stimuli may alter patterns of cryptococcal dissemination in the host.

A G1-like state allows HIV-1 to bypass SAMHD1 restriction in macrophages.

An unresolved question is how HIV-1 achieves efficient replication in terminally differentiated macrophages despite the restriction factor SAMHD1. We reveal inducible changes in expression of cell cycle-associated proteins including MCM2 and cyclins A, E, D1/D3 in macrophages, without evidence for DNA synthesis or mitosis. These changes are induced by activation of the Raf/MEK/ERK kinase cascade, culminating in upregulation of CDK1 with subsequent SAMHD1 T592 phosphorylation and deactivation of its antiviral activity. HIV infection is limited to these G1-like phase macrophages at the single-cell level. Depletion of SAMHD1 in macrophages decouples the association between infection and expression of cell cycle-associated proteins, with terminally differentiated macrophages becoming highly susceptible to HIV-1. We observe both embryo-derived and monocyte-derived tissue-resident macrophages in a G1-like phase at frequencies approaching 20%, suggesting how macrophages sustain HIV-1 replication in vivo Finally, we reveal a SAMHD1-dependent antiretroviral activity of histone deacetylase inhibitors acting via p53 activation. These data provide a basis for host-directed therapeutic approaches aimed at limiting HIV-1 burden in macrophages that may contribute to curative interventions.

Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study.

BACKGROUND: The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. METHODS: In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. FINDINGS: We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41-4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. INTERPRETATION: We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. FUNDING: National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.

Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study.

BACKGROUND: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. METHODS: Training cohorts comprised 1276 patients admitted to King's College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy's and St Thomas' Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. RESULTS: A baseline model of 'NEWS2 + age' had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. CONCLUSIONS: NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.

Quantitative IFN-γ Release Assay and Tuberculin Skin Test Results to Predict Incident Tuberculosis. A Prospective Cohort Study.

Rationale: Development of diagnostic tools with improved predictive value for tuberculosis (TB) is a global research priority.Objectives: We evaluated whether implementing higher diagnostic thresholds than currently recommended for QuantiFERON Gold-in-Tube (QFT-GIT), T-SPOT.TB, and the tuberculin skin test (TST) might improve prediction of incident TB.Methods: Follow-up of a UK cohort of 9,610 adult TB contacts and recent migrants was extended by relinkage to national TB surveillance records (median follow-up 4.7 yr). Incidence rates and rate ratios, sensitivities, specificities, and predictive values for incident TB were calculated according to ordinal strata for quantitative results of QFT-GIT, T-SPOT.TB, and TST (with adjustment for prior bacillus Calmette-Guérin [BCG] vaccination).Measurements and Main Results: For all tests, incidence rates and rate ratios increased with the magnitude of the test result (P < 0.0001). Over 3 years' follow-up, there was a modest increase in positive predictive value with the higher thresholds (3.0% for QFT-GIT ≥0.35 IU/ml vs. 3.6% for ≥4.00 IU/ml; 3.4% for T-SPOT.TB ≥5 spots vs. 5.0% for ≥50 spots; and 3.1% for BCG-adjusted TST ≥5 mm vs. 4.3% for ≥15 mm). As thresholds increased, sensitivity to detect incident TB waned for all tests (61.0% for QFT-GIT ≥0.35 IU/ml vs. 23.2% for ≥4.00 IU/ml; 65.4% for T-SPOT.TB ≥5 spots vs. 27.2% for ≥50 spots; 69.7% for BCG-adjusted TST ≥5 mm vs. 28.1% for ≥15 mm).Conclusions: Implementation of higher thresholds for QFT-GIT, T-SPOT.TB, and TST modestly increases positive predictive value for incident TB, but markedly reduces sensitivity. Novel biomarkers or validated multivariable risk algorithms are required to improve prediction of incident TB.

Blood Transcriptomic Stratification of Short-term Risk in Contacts of Tuberculosis.

BACKGROUND: The highest risk of tuberculosis arises in the first few months after exposure. We reasoned that this risk reflects incipient disease among tuberculosis contacts. Blood transcriptional biomarkers of tuberculosis may predate clinical diagnosis, suggesting they offer improved sensitivity to detect subclinical incipient disease. Therefore, we sought to test the hypothesis that refined blood transcriptional biomarkers of active tuberculosis will improve stratification of short-term disease risk in tuberculosis contacts. METHODS: We combined analysis of previously published blood transcriptomic data with new data from a prospective human immunodeficiency virus (HIV)-negative UK cohort of 333 tuberculosis contacts. We used stability selection as an alternative computational approach to identify an optimal signature for short-term risk of active tuberculosis and evaluated its predictive value in independent cohorts. RESULTS: In a previously published HIV-negative South African case-control study of patients with asymptomatic Mycobacterium tuberculosis infection, a novel 3-gene transcriptional signature comprising BATF2, GBP5, and SCARF1 achieved a positive predictive value (PPV) of 23% for progression to active tuberculosis within 90 days. In a new UK cohort of 333 HIV-negative tuberculosis contacts with a median follow-up of 346 days, this signature achieved a PPV of 50% (95% confidence interval [CI], 15.7-84.3) and negative predictive value of 99.3% (95% CI, 97.5-99.9). By comparison, peripheral blood interferon gamma release assays in the same cohort achieved a PPV of 5.6% (95% CI, 2.1-11.8). CONCLUSIONS: This blood transcriptional signature provides unprecedented opportunities to target therapy among tuberculosis contacts with greatest risk of incident disease.

Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: an observational cohort study.

The number of proposed prognostic models for coronavirus disease 2019 (COVID-19) is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation.We independently externally validated the performance of candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at the time of admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictors in univariable analyses.We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78, 95% CI 0.73-0.83), and a novel model for prediction of deterioration <14 days from admission (0.78, 95% CI 0.74-0.82). The most discriminating univariable predictors were admission oxygen saturation on room air for in-hospital deterioration (AUROC 0.76, 95% CI 0.71-0.81), and age for in-hospital mortality (AUROC 0.76, 95% CI 0.71-0.81). No prognostic model demonstrated consistently higher net benefit than these univariable predictors, across a range of threshold probabilities.Admission oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated here offered incremental value for patient stratification to these univariable predictors.

Blood transcriptomic discrimination of bacterial and viral infections in the emergency department: a multi-cohort observational validation study.

BACKGROUND: There is an urgent need to develop biomarkers that stratify risk of bacterial infection in order to support antimicrobial stewardship in emergency hospital admissions. METHODS: We used computational machine learning to derive a rule-out blood transcriptomic signature of bacterial infection (SeptiCyte™ TRIAGE) from eight published case-control studies. We then validated this signature by itself in independent case-control data from more than 1500 samples in total, and in combination with our previously published signature for viral infections (SeptiCyte™ VIRUS) using pooled data from a further 1088 samples. Finally, we tested the performance of these signatures in a prospective observational cohort of emergency department (ED) patients with fever, and we used the combined SeptiCyte™ signature in a mixture modelling approach to estimate the prevalence of bacterial and viral infections in febrile ED patients without microbiological diagnoses. RESULTS: The combination of SeptiCyte™ TRIAGE with our published signature for viral infections (SeptiCyte™ VIRUS) discriminated bacterial and viral infections in febrile ED patients, with a receiver operating characteristic area under the curve of 0.95 (95% confidence interval 0.90-1), compared to 0.79 (0.68-0.91) for WCC and 0.73 (0.61-0.86) for CRP. At pre-test probabilities 0.35 and 0.72, the combined SeptiCyte™ score achieved a negative predictive value for bacterial infection of 0.97 (0.90-0.99) and 0.86 (0.64-0.96), compared to 0.90 (0.80-0.94) and 0.66 (0.48-0.79) for WCC and 0.88 (0.69-0.95) and 0.60 (0.31-0.72) for CRP. In a mixture modelling approach, the combined SeptiCyte™ score estimated that 24% of febrile ED cases receiving antibacterials without a microbiological diagnosis were due to viral infections. Our analysis also suggested that a proportion of patients with bacterial infection recovered without antibacterials. CONCLUSIONS: Blood transcriptional biomarkers offer exciting opportunities to support precision antibacterial prescribing in ED and improve diagnostic classification of patients without microbiologically confirmed infections.

Correction to: Blood transcriptomic discrimination of bacterial and viral infections in the emergency department: a multi-cohort observational validation study.

An amendment to this paper has been published and can be accessed via the original article.

Spatial Network Mapping of Pulmonary Multidrug-Resistant Tuberculosis Cavities Using RNA Sequencing.

Rationale: There is poor understanding about protective immunity and the pathogenesis of cavitation in patients with tuberculosis.Objectives: To map pathophysiological pathways at anatomically distinct positions within the human tuberculosis cavity.Methods: Biopsies were obtained from eight predetermined locations within lung cavities of patients with multidrug-resistant tuberculosis undergoing therapeutic surgical resection (n = 14) and healthy lung tissue from control subjects without tuberculosis (n = 10). RNA sequencing, immunohistochemistry, and bacterial load determination were performed at each cavity position. Differentially expressed genes were normalized to control subjects without tuberculosis, and ontologically mapped to identify a spatially compartmentalized pathophysiological map of the cavity. In silico perturbation using a novel distance-dependent dynamical sink model was used to investigate interactions between immune networks and bacterial burden, and to integrate these identified pathways.Measurements and Main Results: The median (range) lung cavity volume on positron emission tomography/computed tomography scans was 50 cm3 (15-389 cm3). RNA sequence reads (31% splice variants) mapped to 19,049 annotated human genes. Multiple proinflammatory pathways were upregulated in the cavity wall, whereas a downregulation "sink" in the central caseum-fluid interface characterized 53% of pathways including neuroendocrine signaling, calcium signaling, triggering receptor expressed on myeloid cells-1, reactive oxygen and nitrogen species production, retinoic acid-mediated apoptosis, and RIG-I-like receptor signaling. The mathematical model demonstrated that neuroendocrine, protein kinase C-θ, and triggering receptor expressed on myeloid cells-1 pathways, and macrophage and neutrophil numbers, had the highest correlation with bacterial burden (r > 0.6), whereas T-helper effector systems did not.Conclusions: These data provide novel insights into host immunity to Mycobacterium tuberculosis-related cavitation. The pathways defined may serve as useful targets for the design of host-directed therapies, and transmission prevention interventions.

HIV-1 evades innate immune recognition through specific cofactor recruitment.

Human immunodeficiency virus (HIV)-1 is able to replicate in primary human macrophages without stimulating innate immunity despite reverse transcription of genomic RNA into double-stranded DNA, an activity that might be expected to trigger innate pattern recognition receptors. We reasoned that if correctly orchestrated HIV-1 uncoating and nuclear entry is important for evasion of innate sensors then manipulation of specific interactions between HIV-1 capsid and host factors that putatively regulate these processes should trigger pattern recognition receptors and stimulate type 1 interferon (IFN) secretion. Here we show that HIV-1 capsid mutants N74D and P90A, which are impaired for interaction with cofactors cleavage and polyadenylation specificity factor subunit 6 (CPSF6) and cyclophilins (Nup358 and CypA), respectively, cannot replicate in primary human monocyte-derived macrophages because they trigger innate sensors leading to nuclear translocation of NF-κB and IRF3, the production of soluble type 1 IFN and induction of an antiviral state. Depletion of CPSF6 with short hairpin RNA expression allows wild-type virus to trigger innate sensors and IFN production. In each case, suppressed replication is rescued by IFN-receptor blockade, demonstrating a role for IFN in restriction. IFN production is dependent on viral reverse transcription but not integration, indicating that a viral reverse transcription product comprises the HIV-1 pathogen-associated molecular pattern. Finally, we show that we can pharmacologically induce wild-type HIV-1 infection to stimulate IFN secretion and an antiviral state using a non-immunosuppressive cyclosporine analogue. We conclude that HIV-1 has evolved to use CPSF6 and cyclophilins to cloak its replication, allowing evasion of innate immune sensors and induction of a cell-autonomous innate immune response in primary human macrophages.