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.

Application of CRISPR-Based Human and Bacterial Ribosomal RNA Depletion for SARS-CoV-2 Shotgun Metagenomic Sequencing.

OBJECTIVES: The aim of this study is to evaluate the effectiveness of a CRISPR-based human and bacterial ribosomal RNA (rRNA) depletion kit (JUMPCODE Genomics) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shotgun metagenomic sequencing in weakly positive respiratory samples. METHODS: Shotgun metagenomics was performed on 40 respiratory specimens collected from solid organ transplant patients and deceased intensive care unit patients at UCLA Medical Center in late 2020 to early 2021. Human and bacterial rRNA depletion was performed on remnant library pools prior to sequencing by Illumina MiSeq. Data quality was analyzed using Geneious Prime, whereas the identification of SARS-CoV-2 variants and lineages was determined by Pangolin. RESULTS: The average genome coverage of the rRNA-depleted respiratory specimens increased from 72.55% to 93.71% in overall samples and from 29.3% to 83.3% in 15 samples that failed to achieve sufficient genome coverage using the standard method. Moreover, rRNA depletion enhanced genome coverage to over 85% in 11 (73.3%) of 15 low viral load samples with cycle threshold values up to 35, resulting in the identification of genotypes. CONCLUSION: The CRISPR-based human and bacterial rRNA depletion enhanced the sensitivity of SARS-CoV-2 shotgun metagenomic sequencing, especially in low viral load samples.

Proteome2virus: Shotgun mass spectrometry data analysis pipeline for virus identification

Objectives: Shotgun proteomics is a generic method enabling detection of multiple viral species in one assay. The reliable and accurate identification of these viral species by analyzing peptides from MS-spectra is a challenging task. The aim of this study was to develop an easy accessible proteome analysis approach for the identification of viruses that cause respiratory and gastrointestinal infections. Method(s): For this purpose, a shotgun proteomics based method and a web application, 'proteome2virus', were developed. Identified peptides were searched in a database comprising proteomic data of 46 viruses known to be infectious to humans. Result(s): The method was successfully tested for cultured viruses and eight fecal samples consisting of ten different viral species from seven different virus families, including SARS-CoV-2. The samples were prepared with two different sample preparation methods and were measured with two different mass spectrometers. Conclusion(s): The results demonstrate that the developed web application is applicable to different MS data sets, generated from two different instruments, and that with this approach a high variety of clinically relevant viral species can be identified. This emphasizes the potential and feasibility for the diagnosis of a wide range of viruses in clinical samples with a single shotgun proteomics analysis.Copyright © 2023

Microrna Profiles in Saliva of Children with and Without Severe Disease Due to Severe Acute Respiratory Syndrome Corona Virus 2 Infection

Background: The majority of children with exposure to SARSCoV-2 virus have mild disease. However severe diseases such as Multisystem inflammatory syndrome (MISC) and pneumonia do occur in children. Currently, there are no established biomarkers that can predict progression to severe disease in children exposed to the virus. MicroRNAs (miRNAs) are non-coding RNAs that can be found in saliva and are thought to play a role in the regulation of inflammation following an infection. Our objective was to compare the miRNA profile in saliva of children with or without severe disease due to SARS-CoV-2 infection. Methods: This prospective observational study was supported by the National Institutes of Health (NIH) RADx Program. Children ≤ 18 years of age presenting to two tertiary care children's hospitals with symptoms of SARS-CoV-2 infection (confirmed by PCR test, serology or epidemiological link) were enrolled between 03/29/2021 and 04/30/2021. Severe infection was defined as any of the following within 30 days of testing: MISC or Kawasaki disease diagnosis, requirement for oxygen > 2L, inotropes, mechanical ventilation or ECMO, or the occurrence of death. Informed consent and a saliva swab were obtained at the time of SARS-CoV-2 diagnosis (DNA Genotek, Ottowa Canada), and RNA was extracted (Qiagen, Germantown, MD). Small RNA species (<50 base pairs) were interrogated via shotgun sequencing (HiSeq 2500, Illumina, San Diego, CA) and miRNAs were quantified through alignment to the human genome (GRCh38). RNA features with sparse counts (<10 in 90% of samples) were filtered, and the data was quantile normalized and mean-center scaled. Salivary miRNA levels were compared between those with severe and non-severe SARS-CoV-2 infection using Wilcoxon tests with Benjamini Hochberg multiple testing corrections. In addition, a logistic regression analysis was used to identify miRNA pairs that could best discriminate severe cases based on a Monte Carlo 100-fold cross-validated area under receiver operating characteristic curve (AUROC). Results: Samples from 33 children were analyzed. Median age was 3 (3, 10) years and 54.5% were males. Of the total, 29 were RT PCR positive, 4 had a positive serology and 6 children had severe infection. Seven miRNAs displayed significant differences (Fold change >2, FDR adjusted p < 0.1) among children with severe SARS-CoV-2 infection (Table). All seven miRNAs were up-regulated in severe SARS-CoV-2 cases. A logistic regression using a single ratio of miR-296-5p/miR-378j yielded 1.0 AUROC for differentiating children with severe infection (Figure). Conclusion: In this interim analysis of salivary miRNA in childhood SARS-CoV-2 infection, we found a differential expression of 7 salivary miRNAs in children with severe infection. Ongoing work will seek to validate these findings and explore the role of miRNA in predicting severe SARS-CoV-2 infection in children. Receiver operating characteristic curve and box plot displaying the complete differentiation of severe and non- severe SARSCoV-2 cases using a ratio of miR-296-5p and miR-378j levels in saliva.

Microbiome Analysis for Wastewater Surveillance during COVID-19.

Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases.

Metagenomic Sequencing and Reverse Transcriptase PCR Reveal That Mobile Phones and Environmental Surfaces Are Reservoirs of Multidrug-Resistant Superbugs and SARS-CoV-2.

Background: Mobile phones of healthcare workers (HCWs) can act as fomites in the dissemination of microbes. This study was carried out to investigate microbial contamination of mobile phones of HCWs and environmental samples from the hospital unit using a combination of phenotypic and molecular methods. Methods: This point prevalence survey was carried out at the Emergency unit of a tertiary care facility. The emergency unit has two zones, a general zone for non-COVID-19 patients and a dedicated COVID-19 zone for confirmed or suspected COVID-19 patients. Swabs were obtained from the mobile phones of HCWs in both zones for bacterial culture and shotgun metagenomic analysis. Metagenomic sequencing of pooled environmental swabs was conducted. RT-PCR for SARS-CoV-2 detection was carried out. Results: Bacteria contamination on culture was detected from 33 (94.2%) mobile phones with a preponderance of Staphylococcus epidermidis (n/N = 18/35), Staphylococcus hominis (n/N = 13/35), and Staphylococcus haemolyticus (n/N = 7/35). Two methicillin-sensitive and three methicillin-resistant Staphylococcus aureus, and one pan-drug-resistant carbapenemase producer Acinetobacter baumannii were detected. Shotgun metagenomic analysis showed high signature of Pseudomonas aeruginosa in mobile phone and environmental samples with preponderance of P. aeruginosa bacteriophages. Malassezia and Aspergillus spp. were the predominant fungi detected. Fourteen mobile phones and one environmental sample harbored protists. P. aeruginosa antimicrobial resistance genes mostly encoding for efflux pump systems were detected. The P. aeruginosa virulent factor genes detected were related to motility, adherence, aggregation, and biofilms. One mobile phone from the COVID-19 zone (n/N = 1/5; 20%) had positive SARS-CoV-2 detection while all other phone and environmental samples were negative. Conclusion: The findings demonstrate that mobile phones of HCWs are fomites for potentially pathogenic and highly drug-resistant microbes. The presence of these microbes on the mobile phones and hospital environmental surfaces is a concern as it poses a risk of pathogen transfer to patients and dissemination into the community.

GUT MICROBIOTA ALTERATIONS AND THEIR RELATIONSHIP TO THE DISEASE SEVERITY AND SOME CYTOKINE PROFILE INDICATORS IN PATIENTS WITH COVID-19

Gut microbiota is an essential element of maintaining the immune homeostasis, including in individuals with COVID-19. The study was aimed to assess taxonomic changes in the gut microbiota and their relationship with the disease severity and the levels of IL6, IL10, IL17, and TNFα in patients with COVID-19. A total of 110 patients with COVID-19 (index group) and 98 individuals with no COVID-19 (control group) were enrolled to the comparative cross-sectional study. The gut micribiota composition was determined by shotgun sequencing. Blood serum levels of IL6, IL10, IL17, and TNFα were assessed by enzyme-linked immunosorbent assay. The following significant changes in the gut microbiota composition were observed in patients with COVID-19 in contrast to controls: decreased abundance of B. adolescentis (p = 0.048), E. rectale (p = 0.036), F. prausnitzi (p = 0.0002), B. dorei (p < 0.001), and increased abundance of R. gnavus (p = 0.012), Сl. hathewayi (p = 0.003), E. faecium (p = 0.0003). Correlations were established between the abundance of B. dorei and the IL6 levels (r = 0.49;p = 0.034), the abundance of F. prausnitzii and the levels of IL10, IL17 (r = 0.44;p = 0.001 and r = –0.52;p < 0.001, respectively). The abundance of R. gnavus correlated with the TNFα levels, and the abundance of E. faecium was related to the levels of IL6 (r = 0.47;p = 0.002) and TNFα (r = 0.56;p = 0.001). The relationship between the abundance of B. dorei, F. prausnitzii, E. faecium and the higher SHOKS-COVID clinical assessment scale scores was also revealed (r = –0.54;p = 0.001, r = –0.60;p < 0.001 and r = 0.67;p = 0.005, respectively). Targeted correction of gut microbiota may improve the COVID-19 treatment efficacy.

Gut Microbiota Dysbiosis Correlates with Abnormal Immune Response in Moderate COVID-19 Patients with Fever.

BACKGROUND: Most COVID-19 patients are moderate, and fever is the most common clinical manifestation and associated with poorer prognosis. Gut microbiota may also play important roles in COVID-19 pathogenesis. However, the association between gut microbiota and fever in individuals with moderate COVID-19 remains unclear. METHODS: We compared the clinical features and laboratory results of 187 moderate COVID-19 patients with fever and without fever and identified several inflammatory markers in patients with fever. Then, we performed gut metagenome-wide association study for 31 individuals to identify the microbes and their epitopes which have potential role in fever and hyperinflammation. RESULTS: Among 187 moderate COVID-19 patients, 127 (67.9%) patients presented with fever. Lymphocytes, CD3+ T cells, CD4+ T cells and the ratio of CD4+ T cells to CD8+ T cells were significantly reduced, while AST, LDH, CRP, IL-6 and IL-10 were significantly elevated in patients with fever. Gut microbiome composition was significantly altered in patients with fever compared with those with non-fever. Opportunistic pathogens such as Enterococcus faecalis and Saccharomyces cerevisiae were enriched in patients with fever. E. faecalis was positively correlated with LDH and D-dimer and negatively correlated with CD8+T cells and IL-4, while S. cerevisiae was positively correlated with diarrhea symptom. Furthermore, several species with anti-inflammatory and protective effects, such as Bacteroides fragilis and Eubacterium ramulus, were enriched in patients with non-fever. B. fragilis was positively correlated with lymphocytes, and E. ramulus was negatively correlated with LDH, AST and IL-6. Finally, we found that several bacterial epitopes of GroEL, a homolog of human HSP60, were enriched in patients with fever and positively correlated with IL-6, IL-10, WBC, neutrophils, D-dimer, LDH, CRP, and E. faecalis. CONCLUSION: Gut microbiota dysbiosis correlates with abnormal immune response in moderate COVID-19 patients with fever.

An Algorithm for Gene Fragment Reconstruction.

Gene sequencing technology has been playing an important role in many aspects, such as life science, disease medicine and health medicine, particularly in the extremely tough process of fighting against 2019-novel coronavirus. Drawing DNA restriction map is a particularly important technology in genetic biology. The simplified partial digestion method (SPDP), a biological method, has been widely used to cut DNA molecules into DNA fragments and obtain the biological information of each fragment. In this work, we propose an algorithm based on 0-1 planning for the location of restriction sites on a DNA molecule, which is able to solve the problem of DNA fragment reconstruction just based on data of fragments' length. Two specific examples are presented in detail. Furthermore, based on 1000 groups of original DNA sequences randomly generated, we define the coincidence rate and unique coincidence rate between the reconstructed DNA sequence and the original DNA sequence, and then analyze separately the effect of the number of fragments and the maximum length of DNA fragments on the coincidence rate and unique coincidence rate as defined. The effectiveness of the algorithm is proved. Besides, based on the existing optimization solution obtained, we simulate and discuss the influence of the error by computation method. It turns out that the error of position of one restriction site does not affect other restriction sites and errors of most restriction sites may lead to the failure of sequence reconstruction. Matlab 7.1 program is used to solve feasible solutions of the location of restriction sites, derive DNA fragment sequence and carry out the statistical analysis and error analysis. This paper focuses on basic computer algorithm implementation of rearrangement and sequencing rather than biochemical technology. The innovative application of the mathematical idea of 0-1 planning to DNA sequence mapping construction, to a certain extent, greatly simplifies the difficulty and complexity of calculation and accelerates the process of 'jigsaw' of DNA fragments.

A comparison of DNA/RNA extraction protocols for high-throughput sequencing of microbial communities.

One goal of microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods the authors previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, the authors compared the relative performance of two total nucleic acid extraction protocols with the authors' previously benchmarked protocol. The authors included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here the authors present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection and well-to-well contamination between these protocols.

Quantitative proteomic dataset from oro- and naso-pharyngeal swabs used for COVID-19 diagnosis: Detection of viral proteins and host's biological processes altered by the infection.

Since January 2020, the world is facing the COVID-19 pandemic caused by SARS-CoV-2. In a big effort to cope with this outbreak, two Uruguayan institutions, Institut Pasteur de Montevideo and Universidad de la República, have developed and implemented a diagnosis pipeline based on qRT-PCR using entirely local resources. In this context, we performed comparative quantitative proteomic analysis from oro- and naso-pharyngeal swabs used for diagnosis. Tryptic peptides obtained from five positive and five negative samples were analysed by nano-LC-MS/MS using a Q-Exactive Plus mass spectrometer. Data analysis was performed using PatternLab for Proteomics software. From all SARS-CoV-2 positive swabs we were able to detect peptides of the SARS-CoV-2 nucleoprotein that encapsulates and protect the RNA genome. Additionally, we detected an average of 1100 human proteins from each sample. The most abundant proteins exclusively detected in positive swabs were "Guanylate-binding protein 1", "Tapasin" and "HLA class II histocompatibility antigen DR beta chain". The biological processes overrepresented in infected host cells were "SRP-dependent cotranslational protein targeting to membrane", "nuclear-transcribed mRNA catabolic process, nonsense-mediated decay", "viral transcription" and "translational initiation". Data is available via ProteomeXchange with identifier PXD020394. We expect that this data can contribute to the future development of mass spectrometry based approaches for COVID-19 diagnosis. Also, we share this preliminary proteomic characterization concerning the host response to infection for its reuse in basic investigation.