BackgroundThe novel coronavirus (SARS-CoV-2) infected over 3,300 health-care-workers (HCWs) in early 2020 in China. Little information is known about nosocomial infections of HCWs in the initial period. We analyzed data from HCWs with nosocomial infections in Wuhan Union Hospital and their family members. MethodsWe collected and analyzed data on exposure history, illness timelines, and epidemiologic characteristics of 25 laboratory-confirmed and two highly suspected HCWs as well as ten of their family members with COVID-19 from Jan 5 to Feb 12, 2020. Among them, demographics and clinical features of the 35 laboratory-confirmed cases were investigated and viral RNA of 12 cases was sequenced and analyzed. ResultsNine clusters were found among the patients. All patients showed mild to moderate clinical manifestation and recovered without deterioration. The average periods of incubation, clinical onset serial interval (COSI), and virus shedding were 4.5 days, 5.2 ± 3.2 days, and 18.5 days, respectively. Complete genomic sequences of 12 different coronavirus strains demonstrated that the viral structure with small, irrelevant mutations was stable in the transmission chains and showed remarkable traits of infectious traceability. ConclusionsSARS-CoV-2 can be rapidly transmitted person-to-person regardless of whether they have symptoms in both hospital settings and social activities based on the short period of incubation and COSI. The public health service should take practical measures to curb the spread, including isolation of cases, tracing close-contacts, and containment of severe epidemic areas. Besides, the HCWs should be alert during the epidemic, and make self-quarantine if self-suspected. Nosocomial Outbreak of 2019 Novel

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Background Metagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential. Methods We performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses. Results An optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%. Conclusions A complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

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Background: Infiltration of the lower respiratory tract (LRT) microenvironment could be significantly associated with respiratory diseases. However, alterations in the LRT microbiome and metabolome in infectious and inflammatory respiratory diseases and their correlation with inflammation still need to be explored. Methods: Bronchoalveolar lavage samples from 44 community-acquired pneumonia (CAP) patients, 29 connective tissue disease-associated interstitial disease (CTD-ILD) patients, and 30 healthy volunteers were used to detect microbiota and metabolites through 16S rRNA gene sequencing and untargeted high-performance liquid chromatography with mass spectrometry. Results: The composition of the LRT microbial communities and metabolites differed in disease states. CAP patients showed a significantly low abundance and both diseases presented a depletion of some genera of the phylum Bacteroidetes, including Prevotella, Porphyromonas, and health-associated metabolites, such as sphingosine (d16:1), which were negatively correlated with infectious indicators. In contrast, Bacillus and Mycoplasma were both enriched in the disease groups. Streptococcus was specifically increased in CTD-ILD. In addition, co-elevated metabolites such as FA (22:4) and pyruvic acid represented hypoxia and inflammation in the diseases. Significantly increased levels of amino acids and succinate, as well as decreased itaconic acid levels, were observed in CAP patients, whereas CTD-ILD patients showed only a handful of specific metabolic alterations. Functions related to microbial lipid and amino acid metabolism were significantly altered, indicating the possible contributions of microbial metabolism. Dual omics analysis showed a moderate positive correlation between the microbiome and metabolome. The levels of L-isoleucine and L-arginine were negatively correlated with Streptococcus, and itaconic acid positively correlated with Streptococcus. Conclusion: In the LRT microenvironment, shared and specific alterations occurred in CAP and CTD-ILD patients, which were associated with inflammatory and immune reactions, which may provide a new direction for future studies aiming to elucidate the mechanism, improve the diagnosis, and develop therapies for different respiratory diseases.

Background: Community-acquired pneumonia (CAP) is often accompanied by changes in lipid metabolism. This study aimed to examine the changes in serum phospholipids (PLs) that may be useful for early disease stratification and as potential therapeutic targets in patients with CAP.Methods: Serum samples from 58 patients hospitalized with CAP and 11 control samples were collected during admission between January 2017 and October 2018. Targeted lipidomic analysis was used to determine the concentrations of phosphatidylcholine (PC), lysophosphatidylcholine (LPC), phosphatidylethanolamine (PE), and lysophosphatidylethanolamine (LPE). The Gene Expression Omnibus (GEO) database was used to evaluate the gene expression levels of key enzymes in the Lands cycle, and quantitative real-time polymerase chain reaction (qRT-PCR) was used for further verification.Results: A significant decrease in LPC levels and an increase in PE levels, PC/LPC and PE/LPE ratios were observed in patients with CAP (P<0.05). The area under the curve (AUC) of PE serum concentrations combined with CURB-65 scores (confusion, uremia, respiratory rate, blood pressure, and age ≥65 years) was 0.848 for discriminating disease severity, which was significantly higher than the discriminating disease severity of CURB-65 (P<0.05). The efficiency of predicting 30-day mortality using PC, LPC, or PC/LPC ratio combined with CURB-65 scores (AUC =0.811, AUC =0.854, AUC =0.838, respectively) was better than CURB-65 alone (P<0.05). Gene expression analysis revealed the upregulation of LPC acyltransferase 2.Conclusions: LPC or PE serum levels as well as PC/LPC ratios combined with CURB-65 are effective biomarkers for predicting the disease severity and 30-day mortality of patients with CAP. Further investigations of phospholipid metabolism will improve our understanding and treatment of CAP.

BackgroundPneumonia is a leading cause of non-relapse mortality after hematopoietic stem cell transplantation (HSCT), and the lower respiratory tract (LRT) microbiome has been proven to be associated with various respiratory diseases. However, little is known about the characteristics of the LRT microbiome in patients with post-HSCT compared to healthy controls (HC) and community-acquired pneumonia (CAP).MethodsBronchoalveolar lavage samples from 55 patients with post-HSCT pneumonia, 44 patients with CAP, and 30 healthy volunteers were used to detect microbiota using 16S rRNA gene sequencing.ResultsThe diversity of the LRT microbiome significantly decreased in patients with post-HSCT pneumonia, and the overall community was different from the CAP and HC groups. At the phylum level, post-HSCT pneumonia samples had a high abundance of Actinobacteria and a relatively low abundance of Bacteroidetes. The same is true for non-survivors compared with survivors in patients with post-HSCT pneumonia. At the genus level, the abundances of Pseudomonas, Acinetobacter, Burkholderia, and Mycobacterium were prominent in the pneumonia group after HSCT. On the other hand, gut-associated bacteria, Enterococcus were more abundant in the non-survivors. Some pathways concerning amino acid and lipid metabolism were predicted to be altered in patients with post-HSCT pneumonia.ConclusionsOur results reveal that the LRT microbiome in patients with post-HSCT pneumonia differs from CAP patients and healthy controls, which could be associated with the outcome. The LRT microbiota could be a target for intervention during post-HSCT pneumonia.

BackgroundOral microbiota is closely related to the homeostasis of the oral cavity and lungs. To provide potential information for the prediction, screening, and treatment strategies of individuals, this study compared and investigated the bacterial signatures in periodontitis and chronic obstructive pulmonary disease (COPD).Materials and methodsWe collected subgingival plaque and gingival crevicular fluid samples from 112 individuals (31 healthy controls, 24 patients with periodontitis, 28 patients with COPD, and 29 patients with both periodontitis and COPD). The oral microbiota was analyzed using 16S rRNA gene sequencing and diversity and functional prediction analysis were performed.ResultsWe observed higher bacterial richness in individuals with periodontitis in both types of oral samples. Using LEfSe and DESeq2 analyses, we found differentially abundant genera that may be potential biomarkers for each group. Mogibacterium is the predominant genus in COPD. Ten genera, including Desulfovibrio, Filifactor, Fretibacterium, Moraxella, Odoribacter, Pseudoramibacter Pyramidobacter, Scardovia, Shuttleworthia and Treponema were predominant in periodontitis. Bergeyella, Lautropia, Rothia, Propionibacterium and Cardiobacterium were the signature of the healthy controls. The significantly different pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) between healthy controls and other groups were concentrated in genetic information processing, translation, replication and repair, and metabolism of cofactors and vitamins.ConclusionsWe found the significant differences in the bacterial community and functional characterization of oral microbiota in periodontitis, COPD and comorbid diseases. Compared to gingival crevicular fluid, subgingival plaque may be more appropriate for reflecting the difference of subgingival microbiota in periodontitis patients with COPD. These results may provide potentials for predicting, screening, and treatment strategies for individuals with periodontitis and COPD.