BACKGROUND The recent identification of a novel coronavirus, also known as SARS-CoV-2, has caused a global outbreak of respiratory illnesses. The rapidly developing pandemic has posed great challenges to diagnosis of this novel infection. However, little is known about the metatranscriptomic characteristics of patients with Coronavirus Disease 2019 (COVID-19). METHODS We analyzed metatranscriptomics in 187 patients (62 cases with COVID-19 and 125 with non-COVID-19 pneumonia). Transcriptional aspects of three core elements – pathogens, the microbiome, and host responses – were interrogated. Based on the host transcriptional signature, we built a host gene classifier and examined its potential for diagnosing COVID-19 and indicating disease severity. RESULTS The airway microbiome in COVID-19 patients had reduced alpha diversity, with 18 taxa of differential abundance. Potentially pathogenic microbes were also detected in 47% of the COVID-19 cases, 58% of which were respiratory viruses. Host gene analysis revealed a transcriptional signature of 36 differentially expressed genes significantly associated with immune pathways such as cytokine signaling. The host gene classifier built on such a signature exhibited potential for diagnosing COVID-19 (AUC of 0.75-0.89) and indicating disease severity. CONCLUSIONS Compared to those with non-COVID-19 pneumonias, COVID-19 patients appeared to have a more disrupted airway microbiome with frequent potential concurrent infections, and a special trigger host immune response in certain pathways such as interferon gamma signaling. The immune-associated host transcriptional signatures of COVID-19 hold promise as a tool for improving COVID-19 diagnosis and indicating disease severity.

Background Identifying the causes of community-acquired pneumonia (CAP) is challenging due to the disease’s complex etiology and the limitations of traditional microbiological diagnostic methods. Recent advances in next generation sequencing (NGS)-based metagenomics allow pan-pathogen detection in a single assay, and may have significant advantages over culture-based techniques. Results We conducted a cohort study of 159 CAP patients to assess the diagnostic performance of a clinical metagenomics assay and its impact on clinical management and patient outcomes. When compared to other techniques, clinical metagenomics detected more pathogens in more CAP cases, and identified a substantial number of polymicrobial infections. Moreover, metagenomics results led to changes in or confirmation of clinical management in 35 of 59 cases; these 35 cases also had significantly improved patient outcomes. Conclusions Clinical metagenomics could be a valuable tool for the diagnosis and treatment of CAP. Trial registration Trial registration number with the Chinese Clinical Trial Registry: ChiCTR2100043628.

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The razor clam Sinonovacula constricta is an important commercial species. The deficiency of developmental transcriptomic data is becoming the bottleneck of further researches on the mechanisms underlying settlement and metamorphosis in early development. In this study, de novo transcriptome sequencing was performed for S. constricta at different early developmental stages by using Illumina HiSeq 2000 paired-end (PE) sequencing technology. A total of 112,209,077 PE clean reads were generated. De novo assembly generated 249,795 contigs with an average length of 585 bp. Gene annotation resulted in the identification of 22,870 unigene hits against the NCBI database. Eight unique sequences related to metamorphosis were identified and analyzed using real-time PCR. The razor clam reference transcriptome would provide useful information on early developmental and metamorphosis mechanisms and could be used in the genetic breeding of shellfish.

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