ABSTRACT
AIM: The aim of the present study is to compare the performance of 16S rRNA Nanopore sequencing and conventional culture in detecting infectious pathogens in patients with suspected meningitis in a resource-limited setting without extensive bioinformatics expertise. METHODS: DNA was isolated from the cerebrospinal fluid (CSF) of 30 patients with suspected bacterial meningitis. The isolated DNA was subjected to 16S sequencing using MinION™. The data were analysed in real time via the EPI2ME cloud platform. The Nanopore sequencing was done in parallel to routine microbiological diagnostics. RESULTS: Nanopore sequencing detected bacterial pathogens to species level in 13 of 30 (43%) samples. CSF culture showed 40% (12/30) positivity. In 21 of 30 patients (70%) with suspected bacterial meningitis, both methods yielded concordant results. About nine of 30 samples showed discordant results, of these five were false positive and four were false negative. In five of the culture negative results, nanopore sequencing was able to detect pathogen genome, due to the higher sensitivity of the molecular diagnostics. In two other samples, the CSF culture revealed Cryptococcus neoformans and Streptococcus pneumoniae, which were not detected by Nanopore sequencing. Overall, using both the cultures and 16S Nanopore sequencing, positivity rate increased from 40% (12/30) to 57% (17/30). CONCLUSION: Next-generation sequencing could detect pathogens within six hours and could become an important tool for both pathogen screening and surveillance in low- and middle-income countries (LMICs) that do not have direct access to extensive bioinformatics expertise.
Subject(s)
Meningitis, Bacterial , Nanopore Sequencing , Bacteria/genetics , Humans , Meningitis, Bacterial/cerebrospinal fluid , RNA, Ribosomal, 16S/genetics , Streptococcus pneumoniae/geneticsABSTRACT
SARS-CoV-2 is the virus causing the major pandemic facing the world today. Although, SARS-CoV-2 primarily causes lung infection, a variety of symptoms have proven a systemic impact on the body. SARS-CoV-2 has spread in the community quickly infecting humans from all age, ethnicities and gender. However, fatal outcomes have been linked to specific host factors and co-morbidities such as age, hypertension, immuno-deficiencies, chronic lung diseases or metabolic disorders. A major shift in the microbiome of patients suffering of the coronavirus disease 2019 (COVID-19) have also been observed and is linked to a worst outcome of the disease. As many co-morbidities are already known to be associated with a dysbiosis of the microbiome such as hypertension, diabetes and metabolic disorders. Host factors and microbiome changes are believed to be involved as a network in the acquisition of the infection and the development of the diseases. We will review in detail in this manuscript, the immune response toward SARS-CoV-2 infection as well as the host factors involved in the facilitation and worsening of the infection. We will also address the impact of COVID-19 on the host's microbiome and secondary infection which also worsen the disease.
Subject(s)
COVID-19/immunology , COVID-19/virology , Lung/immunology , Lung/virology , SARS-CoV-2/immunology , Virus Replication/immunology , Animals , Dysbiosis/immunology , Dysbiosis/virology , Humans , Immunity/immunology , Microbiota/immunology , PandemicsABSTRACT
OBJECTIVES: Host genetic factors contribute to the variable severity of COVID-19. We examined genetic variants from genome-wide association studies and candidate gene association studies in a cohort of patients with COVID-19 and investigated the role of early SARS-CoV-2 strains in COVID-19 severity. METHODS: This case-control study included 123 COVID-19 cases (hospitalized or ambulatory) and healthy controls from the state of Baden-Wuerttemberg, Germany. We genotyped 30 single nucleotide polymorphisms, using a custom-designed panel. Cases were also compared with the 1000 genomes project. Polygenic risk scores were constructed. SARS-CoV-2 genomes from 26 patients with COVID-19 were sequenced and compared between ambulatory and hospitalized cases, and phylogeny was reconstructed. RESULTS: Eight variants reached nominal significance and two were significantly associated with at least one of the phenotypes "susceptibility to infection", "hospitalization", or "severity": rs73064425 in LZTFL1 (hospitalization and severity, P <0.001) and rs1024611 near CCL2 (susceptibility, including 1000 genomes project, P = 0.001). The polygenic risk score could predict hospitalization. Most (23/26, 89%) of the SARS-CoV-2 genomes were classified as B.1 lineage. No associations of SARS-CoV-2 mutations or lineages with severity were observed. CONCLUSION: These host genetic markers provide insights into pathogenesis and enable risk classification. Variants which reached nominal significance should be included in larger studies.
Subject(s)
COVID-19 , Chemokine CCL2 , Transcription Factors , COVID-19/genetics , Case-Control Studies , Chemokine CCL2/genetics , Genetic Loci , Genome-Wide Association Study , Humans , SARS-CoV-2 , Transcription Factors/geneticsABSTRACT
The COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) poses an unprecedented challenge to humanity. SARS-CoV-2 infections range from asymptomatic to severe courses of COVID-19 with acute respiratory distress syndrome (ARDS), multiorgan involvement and death. Risk factors for disease severity include older age, male sex, increased BMI and pre-existing comorbidities. Ethnicity is also relevant to COVID-19 susceptibility and severity. Host genetic predisposition to COVID-19 is now increasingly recognized and whole genome and candidate gene association studies regarding COVID-19 susceptibility have been performed. Several common and rare variants in genes related to inflammation or immune responses have been identified. We summarize research on COVID-19 host genetics and compile genetic variants associated with susceptibility to COVID-19 and disease severity. We discuss candidate genes that should be investigated further to understand such associations and provide insights relevant to pathogenesis, risk classification, therapy response, precision medicine, and drug repurposing.