Non-SARS-CoV-2 genome sequences identified in clinical samples from COVID-19 infected patients: Evidence for co-infections

Abstract

Background In December 2019, an ongoing outbreak of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/ 2019-nCoV) infection was initially reported in Wuhan, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be a Public Health Emergency of International Concern (PHEIC). Cellular co-infection is a critical determinant of viral fitness and infection outcomes and plays a crucial role in shaping the host immune response to infections. Methods In this study, 68 public next-generation sequencing data from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Data screening was performed using an alignment-free method based on k-mer mapping and extension, fastv. Taxonomic classification was performed using Kraken 2 on all reads containing one or more virus sequences other than SARS-CoV-2. Results SARS-CoV-2 was identified in all except three patients. Influenza type A (H7N9) virus, human immunodeficiency virus, rhabdovirus, human metapneumovirus, Human adenovirus, Human herpesvirus 1, coronavirus NL63, parvovirus, simian virus 40, and hepatitis virus genomes sequences were detected in SARS-CoV-2 infected patients. Besides, a very diverse group of bacterial populations were observed in the samples.

Viral coinfections in COVID‐19

“…Coinfections, compared with single infections, may lead to changes in transmission of the pathogen, progression of clinical symptoms, and the adverse effects associated with any given infection, which ultimately determines the management of infectious diseases 182‐185 . The inability of conventional methods to detect coinfection, in the absence of sufficient evidence, in turn, can result in underdiagnosis of coinfections 186 . Coinfections or mixed infections have been reported to negatively affect the efficiency of diagnostic methods used for detection of SARS‐CoV‐2; for instance, RT‐PCR may not be the optimal diagnostic test for diagnosis of COVID‐19 in patients with influenza A virus coinfection 18 .…”

“…[182][183][184][185] The inability of conventional methods to detect coinfection, in the absence of sufficient evidence, in turn, can result in underdiagnosis of coinfections. 186 Coinfections or mixed infections have been reported to negatively affect the efficiency of diagnostic methods used for detection of SARS-CoV-2; for instance, RT-PCR may not be the optimal diagnostic test for diagnosis of COVID-19 in patients with influenza A virus coinfection. 18 In contrast, nucleic acid amplification test would be a suitable method for detection of influenza virus RNA in the case of coinfection with SARS-CoV-2.…”

Using RNA-Sequencing Data to Examine Tissue-Specific Garlic Microbiomes

“…As previously described, Kraken2 generated accurate taxonomic identification for bacteria with very fast speed [37,38]. However, only a few studies have used Kraken2 for fungal and viral microbiome studies [39,40]. In this study, we have shown that Kraken2 is a powerful tool for identifying bacteria, fungi, and viruses.…”

Warm Autoimmune Hemolytic Anemia and Pure Red Cell Aplasia during a Severe COVID-19 B.1.1.7 Infection

“…COVID-19-associated AIHA has been previously described [ 1 , 2 ], Furthermore, this patient had evidence of recent parvovirus B19-mediated pure red cell aplasia, which significantly worsened his anemia in the setting of ongoing hemolysis. Co-infection with SARS-CoV-2 and parvovirus B19 has been found to cause severe cardiac, neurologic, and hematologic manifestations [ 3 , 4 , 5 , 6 , 7 ].…”