Viral genomic, metagenomic and human transcriptomic characterization and prediction of the clinical forms of COVID-19

Multicenter benchmarking of short and long read wet lab protocols for clinical viral metagenomics

Metagenomics is gradually being implemented for diagnosing infectious diseases. However, in-depth protocol comparisons for viral detection have been limited to individual sets of experimental workflows and laboratories. In this study, we present a benchmark of metagenomics protocols used in clinical diagnostic laboratories initiated by the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS). A mock viral reference panel was designed to mimic low biomass clinical specimens. The panel was used to assess the performance of twelve metagenomic wet lab protocols currently in use in the diagnostic laboratories of participating ENNGS member institutions. Both Illumina and Nanopore, shotgun and targeted capture probe protocols were included. Performance metrics sensitivity, specificity, and quantitative potential were assessed using a central bioinformatics pipeline. Overall, viral pathogens with loads down to 104 copies/ml (corresponding to CT values of 31 in our PCR assays) were detected by all the evaluated metagenomic wet lab protocols. In contrast, lower abundant mixed viruses of CT values of 35 and higher were detected only by a minority of the protocols. Considering the reference panel as the gold standard, optimal thresholds to define a positive result were determined per protocol, based on the horizontal genome coverage. Implementing these thresholds, sensitivity and specificity of the protocols ranged from 67 to 100 % and 87 to 100 %, respectively. A variety of metagenomic protocols are currently in use in clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implying the need for standardization of metagenomic analysis for use in clinical settings.

Early Metabolomic and Immunologic Biomarkers as Prognostic Indicators for COVID-19

This prospective study in Hong Kong aimed at identifying prognostic metabolomic and immunologic biomarkers for Coronavirus Disease 2019 (COVID-19). We examined 327 patients, mean age 55 (19-89) years, in whom 33.6% were infected with Omicron and 66.4% were infected with earlier variants. The effect size of disease severity on metabolome outweighed others including age, gender, peak C-reactive protein (CRP), vitamin D and peak viral levels. Sixty-five metabolites demonstrated strong associations and the majority (54, 83.1%) were downregulated in severe disease (z score: -3.30 to -8.61). Ten cytokines/chemokines demonstrated strong associations (p < 0.001), and all were upregulated in severe disease. Multiple pairs of metabolomic/immunologic biomarkers showed significant correlations. Fourteen metabolites had the area under the receiver operating characteristic curve (AUC) > 0.8, suggesting a high predictive value. Three metabolites carried high sensitivity for severe disease: triglycerides in medium high-density lipoprotein (MHDL) (sensitivity: 0.94), free cholesterol-to-total lipids ratio in very small very-low-density lipoprotein (VLDL) (0.93), cholesteryl esters-to-total lipids ratio in chylomicrons and extremely large VLDL (0.92);whereas metabolites with the highest specificity were creatinine (specificity: 0.94), phospholipids in large VLDL (0.94) and triglycerides-to-total lipids ratio in large VLDL (0.93). Five cytokines/chemokines, namely, interleukin (IL)-6, IL-18, IL-10, macrophage inflammatory protein (MIP)-1b and tumour necrosis factor (TNF)-a, had AUC > 0.8. In conclusion, we demonstrated a tight interaction and prognostic potential of metabolomic and immunologic biomarkers enabling an outcome-based patient stratification.

Respiratory support with standard low-flow oxygen therapy, high-flow oxygen therapy or continuous positive airway pressure in adults with acute hypoxaemic respiratory failure in a resource-limited setting: protocol for a randomised, open-label, clinical trial - the Acute Respiratory Intervention StudiEs in Africa (ARISE-AFRICA) study

RATIONALE

Acute hypoxaemic respiratory failure (AHRF) is associated with high mortality in sub-Saharan Africa. This is at least in part due to critical care-related resource constraints including limited access to invasive mechanical ventilation and/or highly skilled acute care workers. Continuous positive airway pressure (CPAP) and high-flow oxygen by nasal cannula (HFNC) may prove useful to reduce intubation, and therefore, improve survival outcomes among critically ill patients, particularly in resource-limited settings, but data in such settings are lacking. The aim of this study is to determine whether CPAP or HFNC as compared with standard oxygen therapy, could reduce mortality among adults presenting with AHRF in a resource-limited setting.

METHODS

This is a prospective, multicentre, randomised, controlled, stepped wedge trial, in which patients presenting with AHRF in Uganda will be randomly assigned to standard oxygen therapy delivered through a face mask, HFNC oxygen or CPAP. The primary outcome is all-cause mortality at 28 days. Secondary outcomes include the number of patients with criteria for intubation at day 7, the number of patients intubated at day 28, ventilator-free days at day 28 and tolerance of each respiratory support.

ETHICS AND DISSEMINATION

The study has obtained ethical approval from the Research and Ethics Committee, School of Biomedical Sciences, College of Health Sciences, Makerere University as well as the Uganda National Council for Science and Technology. Patients will be included after informed consent. The results will be submitted for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04693403.

PROTOCOL VERSION

8 September 2023; version 5.

Integrated analysis of RNA-seq datasets reveals novel targets and regulators of COVID-19 severity

During the COVID-19 pandemic, RNA-seq datasets were produced to investigate the virus-host relationship. However, much of these data remains underexplored. To improve the search for molecular targets and biomarkers, we performed an integrated analysis of multiple RNA-seq datasets, expanding the cohort and including patients from different countries, encompassing severe and mild COVID-19 patients. Our analysis revealed that severe COVID-19 patients exhibit overexpression of genes coding for proteins of extracellular exosomes, endomembrane system, and neutrophil granules (e.g., S100A9, LY96, and RAB1B), which may play an essential role in the cellular response to infection. Concurrently, these patients exhibit down-regulation of genes encoding components of the T cell receptor complex and nucleolus, including TP53, IL2RB, and NCL Finally, SPI1 may emerge as a central transcriptional factor associated with the up-regulated genes, whereas TP53, MYC, and MAX were associated with the down-regulated genes during COVID-19. This study identified targets and transcriptional factors, lighting on the molecular pathophysiology of syndrome coronavirus 2 infection.

Clinical Phenotypes and Molecular Characteristics of Respiratory Syncytial Virus in Adults: A Monocentric Prospective Study Between 2019 and 2022

Respiratory syncytial virus (RSV) infection is a major cause of pneumonia in adults. Little is known on the viral genetic diversity and the associated clinical phenotypes in this population. This single-center prospective cohort study included RSV-infected patients hospitalized between January 2019 and December 2022. Of 100 patients, including 41 with severe infection, 72 were infected with RSV-B. RSV genome sequencing showed no clustering according to severity. Patients infected with RSV-B with risk factors for severe pneumonia had significantly higher fusion protein diversity scores. No amino acid substitutions conferring resistance to nirsevimab were detected.

[High-throughput sequencing for infectious disease diagnoses: Example of shotgun metagenomics in central nervous system infections]

The advent of high-throughput sequencing in clinical microbiology is opening the way to new diagnostic and prognostic approaches in infectious diseases. Detection, identification and characterisation of pathogenic microorganisms are essential steps in diagnosis and implementation of appropriate antimicrobial therapy. However, standard methods of microbiological diagnosis are failing in some cases. In addition, the emergence of new infections, facilitated by international travel and global warming, requires the implementation of innovative diagnostic methods. Among the different strategies used in clinical microbiology and reviewed in this article, shotgun metagenomics is the only technique that allows today a panpathogenic and unbiased detection of all microorganisms potentially responsible for an infectious disease, including those still unknown. The aims of this article are to present the different possible strategies of high-throughput sequencing used in the microbiological diagnosis of infectious diseases and to highlight the diagnostic contribution of shotgun metagenomics in the field of central nervous system infections.

CCR5/CXCR3 antagonist TAK-779 prevents diffuse alveolar damage of the lung in the murine model of the acute respiratory distress syndrome

Introduction: The acute respiratory distress syndrome (ARDS), secondary to viral pneumonitis, is one of the main causes of high mortality in patients with COVID-19 (novel coronavirus disease 2019)-ongoing SARS-CoV-2 infection- reached more than 0.7 billion registered cases. Methods: Recently, we elaborated a non-surgical and reproducible method of the unilateral total diffuse alveolar damage (DAD) of the left lung in ICR mice-a publicly available imitation of the ARDS caused by SARS-CoV-2. Our data read that two C-C chemokine receptor 5 (CCR5) ligands, macrophage inflammatory proteins (MIPs) MIP-1α/CCL3 and MIP-1β/CCL4, are upregulated in this DAD model up to three orders of magnitude compared to the background level. Results: Here, we showed that a nonpeptide compound TAK-779, an antagonist of CCR5/CXCR3, readily prevents DAD in the lung with a single injection of 2.5 mg/kg. Histological analysis revealed reduced peribronchial and perivascular mononuclear infiltration in the lung and mononuclear infiltration of the wall and lumen of the alveoli in the TAK-779-treated animals. Administration of TAK-779 decreased the 3-5-fold level of serum cytokines and chemokines in animals with DAD, including CCR5 ligands MIP-1α/β, MCP-1, and CCL5. Computed tomography revealed rapid recovery of the density and volume of the affected lung in TAK-779-treated animals. Discussion: Our pre-clinical data suggest that TAK-779 is more effective than the administration of dexamethasone or the anti-IL6R therapeutic antibody tocilizumab, which brings novel therapeutic modality to TAK-779 and other CCR5 inhibitors for the treatment of virus-induced hyperinflammation syndromes, including COVID-19.

Metagenomic and Molecular Detection of Novel Fecal Viruses in Free-Ranging Agile Wallabies

The agile wallaby (Notamacropus agilis) is one of the most abundant marsupial species in northern Queensland and a competent host for the zoonotic Ross River virus. Despite their increased proximity and interactions with humans, little is known about the viruses carried by these animals, and whether any are of conservation or zoonotic importance. Metagenomics and molecular techniques were used in a complementary manner to identify and characterize novel viruses in the fecal samples of free-ranging agile wallabies. We detected a variety of novel marsupial-related viral species including agile wallaby atadenovirus 1, agile wallaby chaphamaparvovirus 1-2, agile wallaby polyomavirus 1-2, agile wallaby associated picobirnavirus 1-9, and a known macropod gammaherpesvirus 3. Phylogenetic analyses indicate that most of these novel viruses would have co-evolved with their hosts (agile wallabies). Additionally, non-marsupial viruses that infect bacteria (phages), plants, insects, and other eukaryotes were identified. This study highlighted the utility of non-invasive sampling as well as the integration of broad-based molecular assays (consensus PCR and next generation sequencing) for monitoring the emergence of potential pathogenic viruses in wildlife species. Furthermore, the novel marsupial viruses identified in this study will enrich the diversity of knowledge about marsupial viruses, and may be useful for developing diagnostics and vaccines.

Omicron induced distinct immune respiratory transcriptomics signatures compared to pre-existing variants in critically ill COVID-19 patients

Severe coronavirus disease 2019 (COVID-19) is related to dysregulated immune responses. We aimed to explore the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on the immune response by nasopharyngeal transcriptomic in critically-ill patients. This prospective monocentric study included COVID-19 patients requiring intensive care unit (ICU) admission between March 2020 and 2022. Patients were classified according to VOC (ancestral, Alpha, Delta, and Omicron). Eighty-eight patients with severe COVID-19 were included after matching (on prespecified clinical criteria). Profiling of gene expression markers of innate and adaptive immune responses were investigated by respiratory transcriptomics at ICU admission. Eighty-eight patients were included in the study after matching (ancestral [n = 24], Alpha [n = 24], Delta [n = 22], and Omicron [n = 18] variants). Respiratory transcriptomic analysis revealed distinct innate and adaptive immune profiling between variants. In comparison with the ancestral variant, there was a reduced expression of neutrophil degranulation, T cell activation, cytokines signalling pathways in patients infected with Alpha and Delta variants. In contrast, there was a higher expression of neutrophil degranulation, T and B cells activation, and inflammatory interleukins pathways in patients infected with Omicron. To conclude, Omicron induced distinct immune respiratory transcriptomics signatures compared to pre-existing variants in patients with severe COVID-19, pointing to an evolving pathophysiology of severe COVID-19 in the Omicron era.

Recent Advances in Metagenomic Approaches, Applications, and Challenge

Advances in metagenomics analysis with the advent of next-generation sequencing have extended our knowledge of microbial communities as compared to conventional techniques providing advanced approach to identify novel and uncultivable microorganisms based on their genetic information derived from a particular environment. Shotgun metagenomics involves investigating the DNA of the entire community without the requirement of PCR amplification. It provides access to study all genes present in the sample. On the other hand, amplicon sequencing targets taxonomically important marker genes, the analysis of which is restricted to previously known DNA sequences. While sequence-based metagenomics is used to analyze DNA sequences directly from the environment without the requirement of library construction and with limited identification of novel genes and products that can be complemented by functional genomics, function-based metagenomics requires fragmentation and cloning of extracted metagenome DNA in a suitable host with subsequent functional screening and sequencing clone for detection of a novel gene. Although advances were made in metagenomics, different challenges arise. This review provides insight into advances in the metagenomic approaches combined with next-generation sequencing, their recent applications highlighting the emerging ones, such as in astrobiology, forensic sciences, and SARS-CoV-2 infection diagnosis, and the challenges associated. This review further discusses the different types of metagenomics and outlines advancements in bioinformatics tools and their significance in the analysis of metagenomic datasets.

Coot-Lion optimized deep learning algorithm for COVID-19 point mutation rate prediction using genome sequences

In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed using the Bray-Curtis distance and the deep belief network (DBN). Lastly, a deep quantum neural network (Deep QNN) is used to predict COVID-19. The LBCA is obtained by integrating Coot algorithm and LOA. The COVID-19 predictions are done with mutation points. The LBCA-based Deep QNN outperformed with testing accuracy of 0.941, true positive rate of 0.931, and false positive rate of 0.869.

A deficient immune response to SARS-CoV-2 in the nasopharynx is associated with severe COVID-19 pneumonia

OBJECTIVES

We analyzed the expression of inflammatory and antiviral genes in the nasopharynx of SARS-CoV-2 infected patients and their association with the severity of COVID-19 pneumonia.

METHODS

We conducted a cross-sectional study on 223 SARS-CoV-2 infected patients. Clinical data were collected from medical records, and nasopharyngeal samples were collected in the first 24 hours after admission to the emergency room. The gene expression of eight proinflammatory/antiviral genes (plasminogen activator urokinase receptor [PLAUR], interleukin [IL]-6, IL-8, interferon [IFN]-β, IFN-stimulated gene 15 [ISG15], retinoic acid-inducible gene I [RIG-I], C-C motif ligand 5 [CCL5], and chemokine C-X-C motif ligand 10 [CXCL10]) were quantified by real-time polymerase chain reaction. Outcome variables were: (i) pneumonia; (ii) severe pneumonia or acute respiratory distress syndrome. Statistical analysis was performed using multivariate logistic regression analyses.

RESULTS

We enrolled 84 mild, 88 moderate, and 51 severe/critical cases. High expression of PLAUR (adjusted odds ratio [aOR] = 1.25; P = 0.032, risk factor) and low expression of CXCL10 (aOR = 0.89; P = 0.048, protective factor) were associated with pneumonia. Furthermore, lower values of ISG15 (aOR = 0.88, P = 0.021), RIG-I (aOR = 0.87, P = 0.034), CCL5 (aOR = 0.73, P <0.001), and CXCL10 (aOR = 0.84, P = 0.002) were risk factors for severe pneumonia/acute respiratory distress syndrome.

CONCLUSION

An unbalanced early innate immune response to SARS-CoV-2 in the nasopharynx, characterized by high expression of PLAUR and low expression of antiviral genes (ISG15 and RIG-I), and chemokines (CCL5 and CXCL10), was associated with COVID-19 severity.

A CRISPR-enhanced metagenomic NGS test to improve pandemic preparedness

The lack of preparedness for detecting and responding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen (i.e., COVID-19) has caused enormous harm to public health and the economy. Testing strategies deployed on a population scale at day zero, i.e., the time of the first reported case, would be of significant value. Next-generation sequencing (NGS) has such capabilities; however, it has limited detection sensitivity for low-copy-number pathogens. Here, we leverage the CRISPR-Cas9 system to effectively remove abundant sequences not contributing to pathogen detection and show that NGS detection sensitivity of SARS-CoV-2 approaches that of RT-qPCR. The resulting sequence data can also be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single molecular and analysis workflow. This NGS work flow is pathogen agnostic and, therefore, has the potential to transform how large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.

Unknown Circovirus in Immunosuppressed Patient with Hepatitis, France, 2022

Hepatitis of undetermined origin can be caused by a wide variety of pathogens, sometimes emerging pathogens. We report the discovery, by means of routine shotgun metagenomics, of a new virus belonging to the family Circoviridae, genus Circovirus, in a patient in France who had acute hepatitis of unknown origin.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

COVID-19 in elderly: Correlations of viral load, clinical course, laboratory parameters, among patients vaccinated with CoronaVac

SARS-CoV-2 virus was initially identified in Wuhan, China, in December 2019 and a global pandemic was declared in March 2020 by World Health Organization. COVID-19 disease is characterized with severe pneumonia and hypoxemia, especially in the elderly population. The elderly population was primarily vaccinated with CoronaVac, which is a whole virion inactivated vaccine (Sinovac Biotech, China) in Turkey. This study aimed to investigate the association of viral load and laboratory parameters with the severity of the disease and vaccination status in elderly (older than 60 years old) COVID-19 patients. The age range of the patients was 61-97 years old with a mean of 71.80. Vaccinated patients had a lower viral load (P = 0.253) in nasopharyngeal swabs during breakthrough COVID-19 infection compared to unvaccinated ones and were hospitalized for a shorter period of time in hospital wards (P = 0.035). A lower number of patients were vaccinated in both moderate (n = 33, 29.20%) and severe/critical group (n = 46, 34.07%) (P = 0.412). Only 17 (32.08%) vaccinated patients were hospitalized in an intensive care unit (ICU), whereas 36 (67.92%) of the ICU patients were unvaccinated (P = 0.931). Severe/critical patients had higher c-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), fibrinogen, ferritin, and lactate dehydrogenase (LDH) levels compared to the moderate group on the admission day (P < 0.05). Our study suggested that elderly patients vaccinated with CoronaVac had a shorter stay in hospitals and according to our results CRP, PLR, fibrinogen, ferritin, and LDH levels could be used to determine the severity of the infections.

Plasma Metabolome Alterations Discriminate between COVID-19 and Non-COVID-19 Pneumonia

Pneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the plasma metabolome of 43 cases of COVID-19 pneumonia, 23 cases of non-COVID-19 pneumonia, and 26 controls using a non-targeted approach. Metabolic alterations differentiating the three groups were detected, with specific metabolic changes distinguishing the two types of pneumonia groups. A comparison of venous and arterial blood plasma samples from the same subjects revealed the distinct metabolic effects of pulmonary pneumonia. In addition, a machine learning signature of four metabolites was predictive of the disease outcome of COVID-19 subjects with an area under the curve (AUC) of 86 ± 10 %. Overall, the results of this study uncover systemic metabolic changes that could be linked to the etiology of COVID-19 pneumonia and non-COVID-19 pneumonia.

Effect of asthma, COPD, and ACO on COVID-19: A systematic review and meta-analysis

Introduction

The prevalence of asthma, chronic obstructive pulmonary disease (COPD), and asthma-COPD overlap (ACO) in patients with COVID-19 varies, as well as their risks of mortality. The present study aimed to assess the prevalence of asthma, COPD, and ACO as comorbidities, and to determine their risks of mortality in patients with COVID-19 using a systematic review and meta-analysis.

Methods

We systematically reviewed clinical studies that reported the comorbidities of asthma, COPD, and ACO in patients with COVID-19. We searched various databases including PubMed (from inception to 27 September 2021) for eligible studies written in English. A meta-analysis was performed using the random-effect model for measuring the prevalence of asthma, COPD, and ACO as comorbidities, and the mortality risk of asthma, COPD, and ACO in patients with COVID-19 was estimated. A stratified analysis was conducted according to country.

Results

One hundred one studies were eligible, and 1,229,434 patients with COVID-19 were identified. Among them, the estimated prevalence of asthma, COPD, and ACO using a meta-analysis was 10.04% (95% confidence interval [CI], 8.79–11.30), 8.18% (95% CI, 7.01–9.35), and 3.70% (95% CI, 2.40–5.00), respectively. The odds ratio for mortality of pre-existing asthma in COVID-19 patients was 0.89 (95% CI, 0.55–1.4; p = 0.630), while that in pre-existing COPD in COVID-19 patients was 3.79 (95% CI, 2.74–5.24; p<0.001). France showed the highest prevalence of asthma followed by the UK, while that of COPD was highest in the Netherlands followed by India.

Conclusion

Pre-existing asthma and COPD are associated with the incidence of COVID-19. Having COPD significantly increases the risk of mortality in patients with COVID-19. These differences appear to be influenced by the difference of locations of disease pathophysiology and by the daily diagnosis and treatment policy of each country.

CXCL8, CCL2, and CMV Seropositivity as New Prognostic Factors for a Severe COVID-19 Course

The exact pathophysiology of severe COVID-19 is not entirely elucidated, but it has been established that hyperinflammatory responses and cytokine storms play important roles. The aim of this study was to examine CMV status, select chemokines, and complement components in COVID-19, and how concentrations of given molecules differ over time at both molecular and proteomic levels. A total of 210 COVID-19 patients (50 ICU and 160 non-ICU patients) and 80 healthy controls were enrolled in this study. Concentrations of select chemokines (CXCL8, CXCL10, CCL2, CCL3, CCR1) and complement factors (C2, C9, CFD, C4BPA, C5AR1, CR1) were examined at mRNA and protein levels with regard to a COVID-19 course (ICU vs. non-ICU group) and CMV status at different time intervals. We detected several significant differences in chemokines and complement profiles between ICU and non-ICU groups. Pro-inflammatory chemokines and the complement system appeared to greatly contribute to the pathogenesis and development of severe COVID-19. Higher concentrations of CXCL8 and CCL2 in the plasma, with reduced mRNA expression presumably through negative feedback mechanisms, as well as CMV-positive status, correlated with more severe courses of COVID-19. Therefore, CXCL8, CCL2, and CMV seropositivity should be considered as new prognostic factors for severe COVID-19 courses. However, more in-depth research is needed.

Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality

To elucidate the molecular mechanisms that manifest lung abnormalities during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, we performed whole-transcriptome sequencing of lung autopsies from 31 patients with severe COVID-19 and ten uninfected controls. Using metatranscriptomics, we identified the existence of two distinct molecular signatures of lethal COVID-19. The dominant 'classical' signature (n=23) showed upregulation of the unfolded protein response, steroid biosynthesis and complement activation, supported by massive metabolic reprogramming leading to characteristic lung damage. The rarer signature (n=8) that potentially represents 'cytokine release syndrome' (CRS) showed upregulation of cytokines such as IL1 and CCL19, but absence of complement activation. We found that a majority of patients cleared SARS-CoV-2 infection, but they suffered from acute dysbiosis with characteristic enrichment of opportunistic pathogens such as Staphylococcus cohnii in 'classical' patients and Pasteurella multocida in CRS patients. Our results suggest two distinct models of lung pathology in severe COVID-19 patients, which can be identified through complement activation, presence of specific cytokines and characteristic microbiome. These findings can be used to design personalized therapy using in silico identified drug molecules or in mitigating specific secondary infections.

Genomic characterization of the dominating Beta variant carrying vaccinated (Oxford-AstraZeneca) and non-vaccinated COVID-19 patient samples in Bangladesh: A metagenomics and whole genome approach

Bangladesh experiences a second wave of COVID-19 since March 2021, despite the nationwide vaccination drive with ChAdOx1 (Oxford-AstraZeneca) vaccine from early February 2021. Here, we characterized 19 nasopharyngeal swab (NPS) samples from COVID-19 suspect patients using genomic and metagenomic approach. Screening for SARS-CoV-2 by RT-PCR and metagenomic sequencing revealed 17 samples of COVID-19 positive (vaccinated=10, non-vaccinated=7) and 2 samples of COVID-19 negative. We did not find any significant correlation between associated factors including vaccination status, age or sex of the patients, diversity or abundance of the co-infected organisms/pathogens, and the abundance of SARS-CoV-2. Though the first wave of the pandemic was dominated by clade 20B, Beta,V2 (South African variant) dominated the second wave (January 2021 to May 2021), while the third wave (May 2021 to September 2021) was responsible for Delta variants of the epidemic in Bangladesh including both vaccinated and unvaccinated infections. Noteworthy, the RBD region of S protein of all the isolates harbored similar substitutions including K417N, E484K and N501Y that signify the Beta, while D614G, D215G, D80A, A67V, L18F and A701V substitutions were commonly found in the non-RBD region of Spike proteins. ORF7b and ORF3a genes underwent a positive selection (dN/dS ratio 1.77 and 1.24, respectively), while the overall S protein of the Bangladeshi SARS-CoV-2 isolates underwent negative selection pressure (dN/dS=0.621). Furthermore, we found different bacterial co-infection like Streptococcus agalactiae, Neisseria meningitidis, Elizabethkingia anophelis, Stenotrophomonas maltophilia, Klebsiella pneumoni and Pseudomonas plecoglossicida, expressing a number of antibiotic resistance genes such as tetA and tetM. Overall, this approach provides valuable insights on the SARS-CoV-2 genomes and microbiome composition from both vaccinated and non-vaccinated patients in Bangladesh. This article is protected by copyright. All rights reserved.

High SARS-CoV-2 viral load and low CCL5 expression levels in the upper respiratory tract are associated with COVID-19 severity

Mucosal immune response in the upper respiratory tract is crucial for the initial control of viral replication, the clearance of SARS-CoV-2, and the progression of the coronavirus disease 2019 (COVID-19). We analyzed the SARS-CoV-2 RNA load and the expression of selected immune genes in the upper respiratory tract (nasopharynx) of 255 SARS-CoV-2 infected patients and evaluated their association with severe COVID-19. SARS-CoV-2 replication in the nasopharyngeal mucosa induces the expression of several innate immune genes. High SARS-CoV-2 viral load and low CCL5 expression levels were associated with ICU admission or death, although CCL5 was the best predictor of COVID-19 severity.

Viral metagenomic sequencing in the diagnosis of meningoencephalitis: a review of technical advances and diagnostic yield

INTRODUCTION

Meningoencephalitis patients are often severely impaired and benefit from early etiological diagnosis, though many cases remain without identified cause. Metagenomics as pathogen agnostic approach can result in additional etiological findings; however, the exact diagnostic yield when used as a secondary test remains unknown.

AREAS COVERED

This review aims to highlight recent advances with regard to wet and dry lab methodologies of metagenomic testing and technical milestones that have been achieved. A selection of procedures currently applied in accredited diagnostic laboratories is described in more detail to illustrate best practices. Furthermore, a meta-analysis was performed to assess the additional diagnostic yield utilizing metagenomic sequencing in meningoencephalitis patients. Finally, the remaining challenges for successful widespread implementation of metagenomic sequencing for the diagnosis of meningoencephalitis are addressed in a future perspective.

EXPERT OPINION

The last decade has shown major advances in technical possibilities for using mNGS in diagnostic settings including cloud-based analysis. An additional advance may be the current established infrastructure of platforms for bioinformatic analysis of SARS-CoV-2, which may assist to pave the way for global use of clinical metagenomics.