GPMeta: a GPU-accelerated method for ultrarapid pathogen identification from metagenomic sequences.

Metagenomic sequencing (mNGS) is a powerful diagnostic tool to detect causative pathogens in clinical microbiological testing owing to its unbiasedness and substantially reduced costs. Rapid and accurate classification of metagenomic sequences is a critical procedure for pathogen identification in dry-lab step of mNGS test. However, clinical practices of the testing technology are hampered by the challenge of classifying sequences within a clinically relevant timeframe. Here, we present GPMeta, a novel GPU-accelerated approach to ultrarapid pathogen identification from complex mNGS data, allowing users to bypass this limitation. Using mock microbial community datasets and public real metagenomic sequencing datasets from clinical samples, we show that GPMeta has not only higher accuracy but also significantly higher speed than existing state-of-the-art tools such as Bowtie2, Bwa, Kraken2 and Centrifuge. Furthermore, GPMeta offers GPMetaC clustering algorithm, a statistical model for clustering and rescoring ambiguous alignments to improve the discrimination of highly homologous sequences from microbial genomes with average nucleotide identity >95%. GPMetaC exhibits higher precision and recall rate than others. GPMeta underlines its key role in the development of the mNGS test in infectious diseases that require rapid turnaround times. Further study will discern how to best and easily integrate GPMeta into routine clinical practices. GPMeta is freely accessible to non-commercial users at https://github.com/Bgi-LUSH/GPMeta.

Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.

BACKGROUND: In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. METHODS: We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. FINDINGS: The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. INTERPRETATION: 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. FUNDING: National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.

FRMC: a fast and robust method for the imputation of scRNA-seq data.

The high-resolution feature of single-cell transcriptome sequencing technology allows researchers to observe cellular gene expression profiles at the single-cell level, offering numerous possibilities for subsequent biomedical investigation. However, the unavoidable technical impact of high missing values in the gene-cell expression matrices generated by insufficient RNA input severely hampers the accuracy of downstream analysis. To address this problem, it is essential to develop a more rapid and stable imputation method with greater accuracy, which should not only be able to recover the missing data, but also effectively facilitate the following biological mechanism analysis. The existing imputation methods all have their drawbacks and limitations, some require pre-assumed data distribution, some cannot distinguish between technical and biological zeros, and some have poor computational performance. In this paper, we presented a novel imputation software FRMC for single-cell RNA-Seq data, which innovates a fast and accurate singular value thresholding approximation method. The experiments demonstrated that FRMC can not only precisely distinguish 'true zeros' from dropout events and correctly impute missing values attributed to technical noises, but also effectively enhance intracellular and intergenic connections and achieve accurate clustering of cells in biological applications. In summary, FRMC can be a powerful tool for analysing single-cell data because it ensures biological significance, accuracy, and rapidity simultaneously. FRMC is implemented in Python and is freely accessible to non-commercial users on GitHub: https://github.com/HUST-DataMan/FRMC.

Clinical application and evaluation of metagenomic next-generation sequencing in suspected adult central nervous system infection.

BACKGROUND: Accurate etiology diagnosis is crucial for central nervous system infections (CNS infections). The diagnostic value of metagenomic next-generation sequencing (mNGS), an emerging powerful platform, remains to be studied in CNS infections. METHODS: We conducted a single-center prospective cohort study to compare mNGS with conventional methods including culture, smear and etc. 248 suspected CNS infectious patients were enrolled and clinical data were recorded. RESULTS: mNGS reported a 90.00% (9/10) sensitivity in culture-positive patients without empirical treatment and 66.67% (6/9) in empirically-treated patients. Detected an extra of 48 bacteria and fungi in culture-negative patients, mNGS provided a higher detection rate compared to culture in patients with (34.45% vs. 7.56%, McNemar test, p < 0.0083) or without empirical therapy (50.00% vs. 25.00%, McNemar test, p > 0.0083). Compared to conventional methods, positive percent agreement and negative percent agreement was 75.00% and 69.11% separately. mNGS detection rate was significantly higher in patients with cerebrospinal fluid (CSF) WBC > 300 * 106/L, CSF protein > 500 mg/L or glucose ratio ≤ 0.3. mNGS sequencing read is correlated with CSF WBC, glucose ratio levels and clinical disease progression. CONCLUSION: mNGS showed a satisfying diagnostic performance in CNS infections and had an overall superior detection rate to culture. mNGS may held diagnostic advantages especially in empirically treated patients. CSF laboratory results were statistically relevant to mNGS detection rate, and mNGS could dynamically monitor disease progression.

Pseudorabies virus encephalitis in humans: a case series study.

Pseudorabies virus (PRV) is known to cause severe encephalitis in juvenile pigs and various non-native hosts; recent evidences suggest that PRV might cause encephalitis in humans. In a multicenter cohort study in China, next-generation sequencing of cerebrospinal fluid (CSF) was performed to detect pathogens in all patients with clinically suspected central nervous system infections. This study involved all the patients whose CSF samples were positive for PRV-DNA; their clinical features were evaluated, and species-specific PCR and serological tests were sequentially applied for validation. Among the 472 patients tested from June 1, 2016, to December 1, 2018, six were positive for PRV-DNA, which were partially validated by PCR and serological tests. Additionally, we retrospectively examined another case with similar clinical and neuroimaging appearance and detected the presence of PRV-DNA. These patients had similar clinical manifestations, including a rapid progression of panencephalitis, and similar neuroimaging features of symmetric lesions in the basal ganglia and bilateral hemispheres. Six of the patients were engaged in occupations connected with swine production. PRV infection should be suspected in patients with rapidly progressive panencephalitis and characteristic neuroimaging features, especially with exposure to swine.

Human Endophthalmitis Caused By Pseudorabies Virus Infection, China, 2017.

We report human endophthalmitis caused by pseudorabies virus infection after exposure to sewage on a hog farm in China. High-throughput sequencing and real-time PCR of vitreous humor showed pseudorabies virus sequences. This case showed that pseudorabies virus might infect humans after direct contact with contaminants.

Next generation sequencing based pathogen analysis in a patient with neurocysticercosis: a case report.

BACKGROUND: Accurate and early diagnosis of neurocysticercosis (NCC) remains a challenge due to the heterogeneity of its clinical, immunological and imaging characteristics. The presence of cysticercus DNA in cerebrospinal fluid (CSF) of NCC patients has been previously detected via conventional PCR assays. To the best of our knowledge, the use of CSF Next-Generation Sequencing (NGS) based pathogen analysis in patients with NCC infection has never been reported. CASE PRESENTATION: This study reports the clinical, imaging, and immunological features of a patient initially presenting with several months of headache who further developed a pure sensory stroke. NGS was used to detect the pathogen, and her CSF demonstrated the presence of Taenia solium-DNA. This finding was confirmed by a positive reaction to CSF cysticercosis antibodies. After antiparasitic treatment, secondary CSF NGS revealed the DNA index have dropped considerably compared to the initial NGS readings. CONCLUSIONS: NGS is a promising tool for the early and accurate diagnosis of central nervous system (CNS) infection, especially in the setting of atypical clinical manifestations. Further studies are required to evaluate the persistence of DNA in the CSF of patients.

Rapid and precise diagnosis of disseminated T.marneffei infection assisted by high-throughput sequencing of multifarious specimens in a HIV-negative patient: a case report.

BACKGROUND: Talaromyces marneffei, is an opportunistic pathogenic fungus that is most commonly reported in Southeast Asia and disseminated T.marneffei infection predominantly occurs in patients with immunodeficiency. With a potential to invade multiple organs, it can be fatal for patients if diagnosis and treatment are delayed. In current clinical practice, the diagnosis of T.marneffei infection relies heavily on tissue culture and histologic analysis, which may suffer from limited positive rate and is sometimes time consuming. The rapid and accurate diagnosis of disseminated T.marneffei infection remains challenging. CASE PRESENTATION: A 22-year-old man gradually developed fever, cough, lower extremities weakness, jaundice and rash, for which a 3-month extensive investigation failed to reach a diagnosis. After admitted into our hospital, laboratory and radiological tests revealed multiple lesions in the patient's brain, spinal cord, and lungs. We performed next generation sequencing on the patient's skin tissue, bone marrow, blood and cerebrospinal fluid, which all identified numerous Talaromyces marneffei nucleotide sequences and leaded to the rapid diagnosis and treatment of disseminated T.marneffei infection. CONCLUSIONS: This case underline the clinical significance of T.marneffei as a possible pathogen in immune-competent patients. This successful application of the next generation sequencing assisting the rapid diagnosis of disseminated T.marneffei infection provides a new perspective in the clinical approach to the systematic fungi infections and highlights the potential of this technique in rapid etiological diagnosis.

Exiguobacterium sp. A1b/GX59 isolated from a patient with community-acquired pneumonia and bacteremia: genomic characterization and literature review.

BACKGROUND: Bacterial species belonging to the genus Exiguobacterium are facultative anaerobic, non-spore-forming, Gram-positive bacilli, and rarely associated with human infections. Herein, we reported the first case of community-acquired pneumonia (CAP) and bacteremia due to Exiguobacterium spp. in China. CASE PRESENTATION: An adult male with severe CAP was hospitalized. The pathogen was isolated from his bloodstream and broncho-alveolar lavage fluid. The correct identification of the micro-organism was achieved using 16S rRNA sequencing, and its antibiotic susceptibility test was performed by microdilution method. The Whole Genome Sequencing (WGS) was used to characterize its genetic features and to elucidate its potential pathogenic mechanisms. Furthermore, its genome sequence was also compared with those of 3 publicly-available Exiguobacterium strains. A PubMed search was performed for further understanding the features of Exiguobacterium infections. Phylogenetic analysis of the 16S rRNA gene sequence showed that the strain GX59 was most closely related to Exiguobacterium AT1b (99.7%). The genome of GX59 was 2,727,929 bp in size, harbouring 2855 putative protein-coding genes, 5 rRNA operons, 37 tRNA genes and 1 tmRNA. The multiple genome comparison of 4 Exiguobacterium strains demonstrated that Exiguobacterium contained 37 genes of secretion systems, including sec, tat, FEA, Type IV Pili and competence-related DNA transformation transporter (Com). Virulence factors of the micro-organism included tlyC, NprR, MCP, Dam, which might play a critical role in causing lethal infection. CONCLUSIONS: The study highlighted the potential pathogenicity of the genus Exiguobacterium for its unique genes encoding various virulence factors and those associated with antibiotic resistance, therefore, its clinical significance should be valued.

Detection of virus in CSF from the cases with meningoencephalitis by next-generation sequencing.

We screened for viral DNA in cerebrospinal fluid samples using next-generation sequencing (NGS) technology to diagnose CNS viral infections. We collected CSF samples from four cases with clinically suspected viral meningoencephalitis. DNA extracted from the samples was analyzed with NGS, and the results were further validated using PCR. Herpes simplex virus 1 (HSV-1) was detected in the CSF of two patients, HSV-2 and human herpes virus type 3 (HHV-3, VZV) in the CSF of two other patients separately. The number of unique reads of the identified viral genes ranged from 144 to 44205 (93.51 to 99.57%). The coverage of identified viral genes ranged from 12 to 98% with a depth value of 1.1 to 35, respectively. The results were further confirmed using PCR in three cases. The clinical presentation and outcomes of these four cases were consistent with the diagnostic results of NGS. NGS of CSF samples can be used as a diagnostic assay for CNS viral infection. Its further application for "pan-viral" or even "pan-microbial" screening of CSF might influence the diagnosis of CNS infectious diseases.

Historical variations in mutation rate in an epidemic pathogen, Yersinia pestis.

The genetic diversity of Yersinia pestis, the etiologic agent of plague, is extremely limited because of its recent origin coupled with a slow clock rate. Here we identified 2,326 SNPs from 133 genomes of Y. pestis strains that were isolated in China and elsewhere. These SNPs define the genealogy of Y. pestis since its most recent common ancestor. All but 28 of these SNPs represented mutations that happened only once within the genealogy, and they were distributed essentially at random among individual genes. Only seven genes contained a significant excess of nonsynonymous SNP, suggesting that the fixation of SNPs mainly arises via neutral processes, such as genetic drift, rather than Darwinian selection. However, the rate of fixation varies dramatically over the genealogy: the number of SNPs accumulated by different lineages was highly variable and the genealogy contains multiple polytomies, one of which resulted in four branches near the time of the Black Death. We suggest that demographic changes can affect the speed of evolution in epidemic pathogens even in the absence of natural selection, and hypothesize that neutral SNPs are fixed rapidly during intermittent epidemics and outbreaks.

DNA methylation and mRNA and microRNA expression of SLE CD4+ T cells correlate with disease phenotype.

Systemic lupus erythematosus (SLE) is an autoimmune disease well known for its clinical heterogeneity, and its etiology secondary to a cross-talk involving genetic predisposition and environmental stimuli. Although genome-wide analysis has contributed greatly to our understanding of the genetic basis of SLE, there is increasing evidence for a role of epigenetics. Indeed, recent data have demonstrated that in patients with SLE, there are striking alterations of DNA methylation, histone modifications, and deregulated microRNA expression, the sum of which contribute to over-expression of select autoimmune-related genes and loss of tolerance. To address this issue at the level of clinical phenotype, we performed DNA methylation, mRNA and microRNA expression screening using high-throughput sequencing of purified CD4+ T cells from patients with SLE, compared to age and sex matched controls. In particular, we studied 42 patients with SLE and divided this group into three clinical phenotypes: a) the presence of skin lesions without signs of systemic pathology; b) skin lesions but also chronic renal pathology; and c) skin lesions, chronic renal pathology and polyarticular disease. Interestingly, and as expected, sequencing data revealed changes in DNA methylation in SLE compared to controls. However, and more importantly, although there were common methylation changes found in all groups of SLE compared to controls, there was specific DNA methylation changes that correlated with clinical phenotype. These included changes in the novel key target genes NLRP2, CD300LB and S1PR3, as well as changes in the critical pathways, including the adherens junction and leukocyte transendothelial migration. We also noted that a significant proportion of genes undergoing DNA methylation changes were inversely correlated with gene expression and that miRNA screening revealed the existence of subsets with changes in expression. Integrated analysis of this data highlights specific sets of miRNAs controlled by DNA methylation, and genes that are altered by methylation and targeted by miRNAs. In conclusion, our findings suggest select epigenetic mechanisms that contribute to clinical phenotypes and further shed light on a new venue for basic SLE research.

Single-base-resolution methylomes of Populus trichocarpa reveal the association between DNA methylation and drought stress.

BACKGROUND: DNA methylation is an important biological form of epigenetic modification, playing key roles in plant development and environmental responses. RESULTS: In this study, we examined single-base resolution methylomes of Populus under control and drought stress conditions using high-throughput bisulfite sequencing for the first time. Our data showed methylation levels of methylated cytosines, upstream 2 kp, downstream 2kb, and repeatitive sequences significantly increased after drought treatment in Populus. Interestingly, methylation in 100 bp upstream of the transcriptional start site (TSS) repressed gene expression, while methylations in 100-2000 bp upstream of TSS and within the gene body were positively associated with gene expression. Integrated with the transcriptomic data, we found that all cis-splicing genes were non-methylated, suggesting that DNA methylation may not associate with cis-splicing. However, our results showed that 80% of trans-splicing genes were methylated. Moreover, we found 1156 transcription factors (TFs) with reduced methylation and expression levels and 690 TFs with increased methylation and expression levels after drought treatment. These TFs may play important roles in Populus drought stress responses through the changes of DNA methylation. CONCLUSIONS: These findings may provide valuable new insight into our understanding of the interaction between gene expression and methylation of drought responses in Populus.

Double restriction-enzyme digestion improves the coverage and accuracy of genome-wide CpG methylation profiling by reduced representation bisulfite sequencing.

BACKGROUND: Reduced representation bisulfite sequencing (RRBS) was developed to measure DNA methylation of high-CG regions at single base-pair resolution, and has been widely used because of its minimal DNA requirements and cost efficacy; however, the CpG coverage of genomic regions is restricted and important regions with low-CG will be ignored in DNA methylation profiling. This method could be improved to generate a more comprehensive representation. RESULTS: Based on in silico simulation of enzyme digestion of human and mouse genomes, we have optimized the current single-enzyme RRBS by applying double enzyme digestion in the library construction to interrogate more representative regions. CpG coverage of genomic regions was considerably increased in both high-CG and low-CG regions using the double-enzyme RRBS method, leading to more accurate detection of their average methylation levels and identification of differential methylation regions between samples. We also applied this double-enzyme RRBS method to comprehensively analyze the CpG methylation profiles of two colorectal cancer cell lines. CONCLUSION: The double-enzyme RRBS increases the CpG coverage of genomic regions considerably over the previous single-enzyme RRBS method, leading to more accurate detection of their average methylation levels. It will facilitate genome-wide DNA methylation studies in multiple and complex clinical samples.

The DNA methylome of human peripheral blood mononuclear cells.

DNA methylation plays an important role in biological processes in human health and disease. Recent technological advances allow unbiased whole-genome DNA methylation (methylome) analysis to be carried out on human cells. Using whole-genome bisulfite sequencing at 24.7-fold coverage (12.3-fold per strand), we report a comprehensive (92.62%) methylome and analysis of the unique sequences in human peripheral blood mononuclear cells (PBMC) from the same Asian individual whose genome was deciphered in the YH project. PBMC constitute an important source for clinical blood tests world-wide. We found that 68.4% of CpG sites and <0.2% of non-CpG sites were methylated, demonstrating that non-CpG cytosine methylation is minor in human PBMC. Analysis of the PBMC methylome revealed a rich epigenomic landscape for 20 distinct genomic features, including regulatory, protein-coding, non-coding, RNA-coding, and repeat sequences. Integration of our methylome data with the YH genome sequence enabled a first comprehensive assessment of allele-specific methylation (ASM) between the two haploid methylomes of any individual and allowed the identification of 599 haploid differentially methylated regions (hDMRs) covering 287 genes. Of these, 76 genes had hDMRs within 2 kb of their transcriptional start sites of which >80% displayed allele-specific expression (ASE). These data demonstrate that ASM is a recurrent phenomenon and is highly correlated with ASE in human PBMCs. Together with recently reported similar studies, our study provides a comprehensive resource for future epigenomic research and confirms new sequencing technology as a paradigm for large-scale epigenomics studies.

Pathogen quantitative efficacy of different spike-in internal controls and clinical application in central nervous system infection with metagenomic sequencing.

IMPORTANCE: Metagenomic next-generation sequencing (mNGS) has been used broadly for pathogens detection of infectious diseases. However, there is a lack of method for the absolute quantitation of pathogens by mNGS. We compared the quantitative efficiency of three mNGS internal controls (ICs) Thermus thermophilus, T1 phages, and artificial DNA sequence and developed the most applicable strategies for pathogen quantitation via mNGS in central nervous system infection. The IC application strategy we developed will enable mNGS analysis to assess the pathogen load simultaneously with the detection of pathogens, which should provide critical information for quick decision-making of treatment as well as clinical prognosis.

Genome-wide DNA methylation changes between the superficial and deep backfat tissues of the pig.

Adipose tissue is not only a storage organ involved in fuel metabolism, but also an endocrine organ involved in the regulation of insulin sensitivity, thermogenesis, immunity, and inflammation. There are anatomical, cellular, molecular and physiological differences among adipose tissues deposited in different body sites. However, current understanding of the intrinsic differences between the sub-compartments of the subcutaneous adipose tissue remains rudimentary. Here, we analyzed the genome-wide DNA methylation differences between the porcine superficial and deep backfat tissues using methylated DNA immunoprecipitation combined with high-throughput sequencing. We show that the genes with differentially methylated regions in their promoter are mainly involved in the processes of "lipid metabolism" and "regulation of immune-related cytokines". Compared with the deep backfat tissue, the promoters of genes related to the 'positive regulation of cytokine production' were significantly hypermethylated in the superficial backfat tissue, which reflects the intrinsic functional and metabolic differences between the sub-compartments of the subcutaneous adipose tissue. This study provides epigenetic evidence for functionally relevant methylation differences between different layers of porcine backfat tissues.

Improved cancer biomarkers identification using network-constrained infinite latent feature selection.

Identifying biomarkers that are associated with different types of cancer is an important goal in the field of bioinformatics. Different researcher groups have analyzed the expression profiles of many genes and found some certain genetic patterns that can promote the improvement of targeted therapies, but the significance of some genes is still ambiguous. More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes. In this paper, we proposed a novel method that combines the infinite latent feature selection (ILFS) method with the functional interaction (FIs) network to rank the biomarkers. We applied the proposed method to the expression data of five cancer types. The experiments indicated that our network-constrained ILFS (NCILFS) provides an improved prediction of the diagnosis of the samples and locates many more known oncogenes than the original ILFS and some other existing methods. We also performed functional enrichment analysis by inspecting the over-represented gene ontology (GO) biological process (BP) terms and applying the gene set enrichment analysis (GSEA) method on selected biomarkers for each feature selection method. The enrichments analysis reports show that our network-constraint ILFS can produce more biologically significant gene sets than other methods. The results suggest that network-constrained ILFS can identify cancer-related genes with a higher discriminative power and biological significance.

HCMB: A stable and efficient algorithm for processing the normalization of highly sparse Hi-C contact data.

The high-throughput genome-wide chromosome conformation capture (Hi-C) method has recently become an important tool to study chromosomal interactions where one can extract meaningful biological information including P(s) curve, topologically associated domains, A/B compartments, and other biologically relevant signals. Normalization is a critical pre-processing step of downstream analyses for the elimination of systematic and technical biases from chromatin contact matrices due to different mappability, GC content, and restriction fragment lengths. Especially, the problem of high sparsity puts forward a huge challenge on the correction, indicating the urgent need for a stable and efficient method for Hi-C data normalization. Recently, some matrix balancing methods have been developed to normalize Hi-C data, such as the Knight-Ruiz (KR) algorithm, but it failed to normalize contact matrices with high sparsity. Here, we presented an algorithm, Hi-C Matrix Balancing (HCMB), based on an iterative solution of equations, combining with linear search and projection strategy to normalize the Hi-C original interaction data. Both the simulated and experimental data demonstrated that HCMB is robust and efficient in normalizing Hi-C data and preserving the biologically relevant Hi-C features even facing very high sparsity. HCMB is implemented in Python and is freely accessible to non-commercial users at GitHub: https://github.com/HUST-DataMan/HCMB.

Evaluation of superinfection, antimicrobial usage, and airway microbiome with metagenomic sequencing in COVID-19 patients: A cohort study in Shanghai.

BACKGROUND: In COVID-19 patients, information regarding superinfection, antimicrobial assessment, and the value of metagenomic sequencing (MS) could help develop antimicrobial stewardship. METHOD: This retrospective study analyzed 323 laboratory-confirmed COVID-19 patients for co-infection rate and antimicrobial usage in the Shanghai Public Health Clinical Center (SPHCC) from January 23rd to March 14th 2020. The microbiota composition was also investigated in patients with critically severe COVID-19. RESULTS: The total population co-infection rate was 17/323 (5.3%) and 0/229 (0), 4/78 (5.1%), and 13/16 (81.3%) for the mild, severe, and critically severe subgroups, respectively. Proven fungal infection was significantly associated with a higher mortality rate (p = 0.029). In critically severe patients, the rate of antimicrobials and carbapenem usage were 16/16 (100%) and 13/16 (81.3%), respectively, in which the preemptive and empiric antimicrobial days accounted for 51.6% and 30.1%, respectively. Targeted therapy only accounted for 18.3%. MS was implemented to detect non-COVID-19 virus co-existence and the semi-quantitative surveillance of bacteremia, with clear clinical benefit seen in cases with MS-based precision antimicrobial management. Airway microbiome analysis suggested that the microbiota compositions in critically severe COVID-19 patients were likely due to intubation and mechanical ventilation. CONCLUSIONS: In the SPHCC cohort, we observed a non-negligible rate of super-infection, especially for the critically ill COVID-19 patients. Fungal co-infection requires intensive attention due to the high risk of mortality, and the clinical benefit of MS in guiding antimicrobial management warrants further investigation.