The combined effect of oseltamivir and favipiravir on influenza A virus evolution in patients hospitalized with severe influenza.

Our previous study shows favipiravir and oseltamivir combination therapy may accelerate clinical recovery compared to oseltamivir monotherapy in severe influenza, but its effect on virological evolution and resistance mutation against oseltamivir is still unknown. In this study, we collected longitudinal respiratory samples from influenza patients who underwent combination therapy and applied them to next generation sequencing of the whole genome of the influenza A virus (IAV). We also included a cohort untreated with any antivirals to serve as the control. In total, 62 samples from 19 patients treated with combination therapy and 20 samples from 20 patients untreated were successfully sequenced. The nucleotide diversity in the whole genome of IAV in the combination group showed no difference compared to that in the control group (P > 0.05). Moreover, we observed 174 kinds of nonsynonymous nucleotide substitutions in patients with combination therapy, mostly in NA (n = 44) and HA (n = 43). Of them, the G→A transition was the dominant variant type (27%) and 46/174 (26%) was reported to have biological effects, such as increased pathogenicity and polymerase activity. Among the 29 mutations conferring reduction in oseltamivir sensitivity we investigated, H275Y was the only mutation detected in the 4 samples from 1 of 19 patients and demonstrated increasing frequency during the treatment. Mutations conferring favipiravir resistance were not observed. Our studies showed combination therapy of favipiravir and oseltamivir has little effect on virus nucleotide diversity, nor prevents the increase of oseltamivir-resistant variants.

Azithromycin Exposure Induces Transient Microbial Composition Shifts and Decreases the Airway Microbiota Resilience from Outdoor PM2.5 Stress in Healthy Adults: a Randomized, Double-Blind, Placebo-Controlled Trial.

Inappropriate antibiotic prescriptions are common for patients with upper respiratory tract infections (URTIs). Few data exist regarding the effects of antibiotic administration on airway microbiota among healthy adults. We conducted a randomized, double-blind, placebo-controlled trial to characterize the airway microbiota longitudinally in healthy adults using 16S rRNA gene sequencing and quantification. Both the induced sputum and oral wash samples were collected over a 60-day period following a 3-day intervention with 500 mg azithromycin or placebo. Environmental information, including air quality data (particulate matter [PM2.5] and PM10, air quality index [AQI] values), were also collected during the study. A total of 48 healthy volunteers were enrolled and randomly assigned into two groups. Azithromycin did not alter bacterial load but significantly reduced species richness and Shannon index. Azithromycin exposure resulted in a decrease in the detection rate and relative abundance of different genera belonging to Veillonellaceae, Leptotrichia, Fusobacterium, Neisseria, and Haemophilus. In contrast, the relative abundance of taxa belonging to Streptococcus increased immediately after azithromycin intervention. The shifts in the diversity of the microbiology composition took between 14 and 60 days to recover, depending on the measure used: either UniFrac phylogenetic distance or α-diversity. Outdoor environmental perturbations, especially the high concentration of PM2.5, contributed to novel variability in microbial community composition of the azithromycin group at D30 (30 days after baseline). The network analysis found that azithromycin altered the microbial interactions within airway microbiota. The influence was still obvious at D14 when the relative abundance of most taxa had returned to the baseline level. Compared to the sputum microbiota, oral cavity microbiota had a different pattern of change over time. The induced sputum microbial data can represent the airway microbiota composition in healthy adults. Azithromycin may have transient effects in the airway microbiota of healthy adults and decrease the airway microbiota resilience against outdoor environmental stress. The influence of azithromycin on microbial interactions is noteworthy, although the airway microbiota has returned to a near-baseline level. IMPORTANCE The influence of antibiotic administration on the airway microbiota of healthy adults remains unknown. This study is a randomized, double-blind, placebo-controlled trial aiming to investigate the microbial shifts in airways after exposure to azithromycin among heathy adults. We find that azithromycin changes the airway microbial community composition of healthy adults and decreases the airway microbiota resilience against outdoor environmental stress. This study depicts the longitudinal recovery trajectory of airway microbiota after the antibiotic perturbation and may provide reference for appropriate antibiotic prescription.

Rheumatic Symptoms Following Coronavirus Disease 2019 (COVID-19): A Chronic Post-COVID-19 Condition.

Background: Detailed characteristics of rheumatic symptoms of coronavirus disease 2019 (COVID-19) were still unknown. We aim to investigate the proportions, characteristics, and risk factors of this condition. Methods: In this prospective, longitudinal cohort study, discharged patients with COVID-19 were interviewed face-to-face at 12 months after symptom onset. Rheumatic symptoms following COVID-19 included newly occurring joint pain and/or joint swelling. The risk factors of developing rheumatic symptoms were identified by multivariable logistic regression analysis. Results: In total, 1296 of 2469 discharged patients with COVID-19 were enrolled in this study. Among them, 160 (12.3% [95% confidence interval {CI}, 10.6%-14.3%]) suffered from rheumatic symptoms following COVID-19 at 12-month follow-up. The most frequently involved joints were the knee joints (38%), followed by hand (25%) and shoulder (19%). Rheumatic symptoms were independent of the severity of illness and corticosteroid treatment during the acute phase, while elderly age (odds ratio [OR], 1.22 [95% CI, 1.06-1.40]) and female sex (OR, 1.58 [95% CI, 1.12-2.23]) were identified as the risk factors for this condition. Conclusions: Our investigation showed a considerable proportion of rheumatic symptoms following COVID-19 in discharged patients, which highlights the need for continuing attention. Notably, rheumatic symptoms following COVID-19 were independent of the severity of illness and corticosteroid treatment during the acute phase.

Pandemic influenza A (H1N1) virus causes abortive infection of primary human T cells.

Influenza A virus still represents a noticeable epidemic risk to international public health at present, despite the extensive use of vaccines and anti-viral drugs. In the fight against pathogens, the immune defence lines consisting of diverse lymphocytes are indispensable for humans. However, the role of virus infection of lymphocytes and subsequent abnormal immune cell death remains to be explored. Different T cell subpopulations have distinct characterizations and functions, and we reveal the high heterogeneity of susceptibility to viral infection and biological responses such as apoptosis in various CD4+ T and CD8+ T cell subsets through single-cell transcriptome analyses. Effector memory CD8+ T cells (CD8+ TEM) that mediate protective memory are identified as the most susceptible subset to pandemic influenza A virus infection among primary human T cells. Non-productive infection is established in CD8+ TEM and naïve CD8+ T cells, which indicate the mechanism of intracellular antiviral activities for inhibition of virus replication such as abnormal viral splicing efficiency, incomplete life cycles and up-regulation of interferon-stimulated genes in human T cells. These findings provide insights into understanding lymphopenia and the infectious mechanisms of pandemic influenza A virus and broad immune host-pathogen interactional atlas in primary human T cells.

Characterization of two SARS-CoV-2 subgenomic RNA dynamics in severe COVID-19 patients.

Little is known about Subgenomic RNA (sgRNA) dynamics in patients with Coronavirus diseases 2019 (COVID-19). We collected 147 throat swabs, 74 gut swabs and 46 plasma samples from 117 COVID-19 patients recruited in the LOTUS China trial (ChiCTR2000029308) and compared E and orf7a sgRNA load in patients with different illness duration, outcome, and comorbidities. Both sgRNAs were detected in all the three types of samples, with longest duration of 25, 13, and 17 days for E sgRNA, and 32, 28, and 17 days for orf7a sgRNA in throat, gut, and plasma, respectively. A total of 95% (57/60) of patients had no E sgRNA detected after 10 days post treatment, though 86% of them were still E RNA positive. High correlation on titer was observed between sgRNA encoding E and orf7a gene. sgRNA showed similar variation in the standard care and Lopinavir-Ritonavir group. Patients with diabetes and heart diseases showed higher pharyngeal E sgRNA at the first day (P â€‹= â€‹0.016 and 0.013, respectively) but no difference at five days after treatment, compared with patients without such commodities. Patients with hypertension and cerebrovascular diseases showed no difference in the pharyngeal sgRNA levels at both one and five days after treatment, compared with patients without these two commodities. E sgRNA levels in the initial infection showed no correlation with the serum antibody against spike, nucleoprotein, and receptor binding domains at ten days later. sgRNA lasted a long period in COVID-19 patients and might have little effect on humoral response.

Concurrent pigeon paramyxovirus-1 and Acinetobacter baumannii infection in a fatal case of pneumonia.

Pigeon paramyxovirus type 1 (PPMV-1), an antigenic variant of avian paramyxovirus type 1 (APMV-1), mainly infects pigeons. PPMV-1 genotype VI is the dominant genotype infecting pigeons in China. Human infection of avian paramyxovirus was rarely reported, and usually developed mild symptoms, such as conjunctivitis. We detected PPMV-1 in the lower respiratory sample from a fatal case with severe pneumonia; this patient aged 64 years presented cough, fever, and haemoptysis for 8 days and was admitted to hospital on Dec 26, 2020. He developed acute respiratory distress syndrome and sepsis in the following days and died of multiple organ failure on Jan 7, 2021. Sputum and blood culture reported multidrug-resistant Acinetobacter baumannii (ABA) for samples collected on days 22 and 19 post-illness, respectively. However, clinical metagenomic sequencing further reported PPMV-1 besides ABA in the bronchoalveolar lavage fluid. The PPMV-1 genome showed 99.21% identity with a Chinese strain and belonged to VI genotype by BLAST analysis. Multiple basic amino acids were observed at the cleavage site of F protein (113RKKRF117), which indicated high virulence of this PPMV-1 strain to poultry. The patient had close contact with pigeons before his illness, and PPMV-1 nucleic acid was detected from the pigeon feather. PPMV antibody was also detected in the patient serum 20 days after illness. In conclusion, concurrent PPMV-1 genotype VI.2.1.1.2.2 and ABA infection were identified in a fatal pneumonia case, and cross-species transmission of PPMV-1 may occur between infected pigeons and the human being.

Prospective Evaluation of a Rapid Clinical Metagenomics Test for Bacterial Pneumonia.

Background: The diagnosis of bacterial pathogens in lower respiratory tract infections (LRI) using conventional culture methods remains challenging and time-consuming. Objectives: To evaluate the clinical performance of a rapid nanopore-sequencing based metagenomics test for diagnosis of bacterial pathogens in common LRIs through a large-scale prospective study. Methods: We enrolled 292 hospitalized patients suspected to have LRIs between November 2018 and June 2019 in a single-center, prospective cohort study. Rapid clinical metagenomics test was performed on-site, and the results were compared with those of routine microbiology tests. Results: 171 bronchoalveolar lavage fluid (BAL) and 121 sputum samples were collected from patients with six kinds of LRIs. The turnaround time (from sample registration to result) for the rapid metagenomics test was 6.4 ± 1.4 hours, compared to 94.8 ± 34.9 hours for routine culture. Compared with culture and real-time PCR validation tests, rapid metagenomics achieved 96.6% sensitivity and 88.0% specificity and identified pathogens in 63 out of 161 (39.1%) culture-negative samples. Correlation between enriched anaerobes and lung abscess was observed by Gene Set Enrichment Analysis. Moreover, 38 anaerobic species failed in culture was identified by metagenomics sequencing. The hypothetical impact of metagenomics test proposed antibiotic de-escalation in 34 patients compared to 1 using routine culture. Conclusions: Rapid clinical metagenomics test improved pathogen detection yield in the diagnosis of LRI. Empirical antimicrobial therapy could be de-escalated if rapid metagenomics test results were hypothetically applied to clinical management.

Identification of key candidate biomarkers for severe influenza infection by integrated bioinformatical analysis and initial clinical validation.

One of the key barriers for early identification and intervention of severe influenza cases is a lack of reliable immunologic indicators. In this study, we utilized differentially expressed genes screening incorporating weighted gene co-expression network analysis in one eligible influenza GEO data set (GSE111368) to identify hub genes associated with clinical severity. A total of 10 genes (PBI, MMP8, TCN1, RETN, OLFM4, ELANE, LTF, LCN2, DEFA4 and HP) were identified. Gene set enrichment analysis (GSEA) for single hub gene revealed that these genes had a close association with antimicrobial response and neutrophils activity. To further evaluate these genes' ability for diagnosis/prognosis of disease developments, we adopted double validation with (a) another new independent data set (GSE101702); and (b) plasma samples collected from hospitalized influenza patients. We found that 10 hub genes presented highly correlation with disease severity. In particular, BPI and MMP8 encoding proteins in plasma achieved higher expression in severe and dead cases, which indicated an adverse disease development and suggested a frustrating prognosis. These findings provide new insight into severe influenza pathogenesis and identify two significant candidate genes that were superior to the conventional clinical indicators. These candidate genes or encoding proteins could be biomarker for clinical diagnosis and therapeutic targets for severe influenza infection.