Host transcriptomics and machine learning for secondary bacterial infections in patients with COVID-19: a prospective, observational cohort study.

BACKGROUND: Viral respiratory tract infections are frequently complicated by secondary bacterial infections. This study aimed to use machine learning to predict the risk of bacterial superinfection in SARS-CoV-2-positive individuals. METHODS: In this prospective, multicentre, observational cohort study done in nine centres in six countries (Australia, Indonesia, Singapore, Italy, Czechia, and France) blood samples and RNA sequencing were used to develop a robust model of predicting secondary bacterial infections in the respiratory tract of patients with COVID-19. Eligible participants were older than 18 years, had known or suspected COVID-19, and symptoms of a recent respiratory infection. A control cohort of participants without COVID-19 who were older than 18 years and with no infection symptoms was also recruited from one Australian centre. In the pre-analysis phase, data were filtered to include only individuals with complete blood transcriptomics and patient data (ie, age, sex, location, and WHO severity score at the time of sample collection). The dataset was then divided randomly (4:1) into a training set (80%) and a test set (20%). Gene expression data in the training set and control cohort were used for differential expression analysis. Differentially expressed genes, along with WHO severity score, location, age, and sex, were used for feature selection with least absolute shrinkage and selection operator (LASSO) in the training set. For LASSO analysis, samples were excluded if gene expression data were not obtained at study admission, no longitudinal clinical information was available, a bacterial infection at the time of study admission was present, or a fungal infection in the absence of a bacterial infection was detected. LASSO regression was performed using three subsets of predictor variables: patient data alone, gene expression data alone, or a combination of patient data and gene expression data. The accuracy of the resultant models was tested on data from the test set. FINDINGS: Between March, 2020, and October, 2021, we recruited 536 SARS-CoV-2-positive individuals and between June, 2013, and January, 2020, we recruited 74 participants into the control cohort. After prefiltering analysis and other exclusions, samples from 158 individuals were analysed in the training set and 47 in the test set. The expression of seven host genes (DAPP1, CST3, FGL2, GCH1, CIITA, UPP1, and RN7SL1) in the blood at the time of study admission was identified by LASSO as predictive of the risk of developing a secondary bacterial infection of the respiratory tract more than 24 h after study admission. Specifically, the expression of these genes in combination with a patient's WHO severity score at the time of study enrolment resulted in an area under the curve of 0·98 (95% CI 0·89-1·00), a true positive rate (sensitivity) of 1·00 (95% CI 1·00-1·00), and a true negative rate (specificity) of 0·94 (95% CI 0·89-1·00) in the test cohort. The combination of patient data and host transcriptomics at hospital admission identified all seven individuals in the training and test sets who developed a bacterial infection of the respiratory tract 5-9 days after hospital admission. INTERPRETATION: These data raise the possibility that host transcriptomics at the time of clinical presentation, together with machine learning, can forward predict the risk of secondary bacterial infections and allow for the more targeted use of antibiotics in viral infection. FUNDING: Snow Medical Research Foundation, the National Health and Medical Research Council, the Jack Ma Foundation, the Helmholtz-Association, the A2 Milk Company, National Institute of Allergy and Infectious Disease, and the Fondazione AIRC Associazione Italiana per la Ricerca contro il Cancro.

RAPIDprep: A Simple, Fast Protocol for RNA Metagenomic Sequencing of Clinical Samples.

Emerging infectious disease threats require rapid response tools to inform diagnostics, treatment, and outbreak control. RNA-based metagenomics offers this; however, most approaches are time-consuming and laborious. Here, we present a simple and fast protocol, the RAPIDprep assay, with the aim of providing a cause-agnostic laboratory diagnosis of infection within 24 h of sample collection by sequencing ribosomal RNA-depleted total RNA. The method is based on the synthesis and amplification of double-stranded cDNA followed by short-read sequencing, with minimal handling and clean-up steps to improve processing time. The approach was optimized and applied to a range of clinical respiratory samples to demonstrate diagnostic and quantitative performance. Our results showed robust depletion of both human and microbial rRNA, and library amplification across different sample types, qualities, and extraction kits using a single workflow without input nucleic-acid quantification or quality assessment. Furthermore, we demonstrated the genomic yield of both known and undiagnosed pathogens with complete genomes recovered in most cases to inform molecular epidemiological investigations and vaccine design. The RAPIDprep assay is a simple and effective tool, and representative of an important shift toward the integration of modern genomic techniques with infectious disease investigations.

Pathway and Network Analyses Identify Growth Factor Signaling and MMP9 as Potential Mediators of Mitochondrial Dysfunction in Severe COVID-19.

Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 (MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.

Novel Hendra Virus Variant Detected by Sentinel Surveillance of Horses in Australia.

We identified and isolated a novel Hendra virus (HeV) variant not detected by routine testing from a horse in Queensland, Australia, that died from acute illness with signs consistent with HeV infection. Using whole-genome sequencing and phylogenetic analysis, we determined the variant had ≈83% nt identity with prototypic HeV. In silico and in vitro comparisons of the receptor-binding protein with prototypic HeV support that the human monoclonal antibody m102.4 used for postexposure prophylaxis and current equine vaccine will be effective against this variant. An updated quantitative PCR developed for routine surveillance resulted in subsequent case detection. Genetic sequence consistency with virus detected in grey-headed flying foxes suggests the variant circulates at least among this species. Studies are needed to determine infection kinetics, pathogenicity, reservoir-species associations, viral-host coevolution, and spillover dynamics for this virus. Surveillance and biosecurity practices should be updated to acknowledge HeV spillover risk across all regions frequented by flying foxes.

Blood transcriptome responses in patients correlate with severity of COVID-19 disease.

Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state. Aim: Our current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants. Results: All WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways. Conclusions: Our data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study.

Purpose: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. Methods: We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients. Results: We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients. Conclusion: These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Prevalence of Possible Depression and Post-traumatic Stress Disorder among Community Dwelling Adult Refugees and Refugee Applicants in South Korea.

BACKGROUND: Because there has been a recent increase in refugee applications in Korea, the mental health of these refugees merits greater study. METHODS: We surveyed 129 refugees (including those in process of refugee application) and 121 migrant workers living in urban communities, using: the Patient Health Questionnaire-9 for depressive symptoms, the Impact Event Scale-Revised for post-traumatic stress disorder (PTSD) symptoms, and the health questionnaires used in 2016 Korean National Health and Nutrition Examination Survey (KNHANES). The majority of refugee subjects were from sub-Saharan Africa and Middle East. We compared the prevalence of possible depression and possible PTSD between refugees and migrant workers and refugees and age-gender matched samples from the KNHANES 2016. RESULTS: Frequency of suicidal planning during the last year was higher in the refugee group than Korean nationals, but frequency of suicidal attempt was not. High risk drinking was found in 0.8% of refugees, 6.6% of migrant workers and 27.2% of Korean nationals. Possible depression was present in 42.9% of refugee subjects, 33.3% of migrant workers, and 4.2% of Korean controls. Possible PTSD was present in 38.9% of refugees compared to 12.5% of migrant workers. Only major risk factor for depression among refugees was a traumatic event before entering Korea. CONCLUSION: Possible depression and PTSD are significantly more prevalent in refugees, compared to both migrant workers and Korean nationals. Prevalence rates are commensurate with refugee studies worldwide. Appropriate early screening and intervention schemes need to be developed for refugees entering Korea.

The tandem repeats enabling reversible switching between the two phases of ß-lactamase substrate spectrum.

Expansion or shrinkage of existing tandem repeats (TRs) associated with various biological processes has been actively studied in both prokaryotic and eukaryotic genomes, while their origin and biological implications remain mostly unknown. Here we describe various duplications (de novo TRs) that occurred in the coding region of a ß-lactamase gene, where a conserved structure called the omega loop is encoded. These duplications that occurred under selection using ceftazidime conferred substrate spectrum extension to include the antibiotic. Under selective pressure with one of the original substrates (amoxicillin), a high level of reversion occurred in the mutant ß-lactamase genes completing a cycle back to the original substrate spectrum. The de novo TRs coupled with reversion makes a genetic toggling mechanism enabling reversible switching between the two phases of the substrate spectrum of ß-lactamases. This toggle exemplifies the effective adaptation of de novo TRs for enhanced bacterial survival. We found pairs of direct repeats that mediated the DNA duplication (TR formation). In addition, we found different duos of sequences that mediated the DNA duplication. These novel elements-that we named SCSs (same-strand complementary sequences)-were also found associated with ß-lactamase TR mutations from clinical isolates. Both direct repeats and SCSs had a high correlation with TRs in diverse bacterial genomes throughout the major phylogenetic lineages, suggesting that they comprise a fundamental mechanism shaping the bacterial evolution.

Twelve positions in a ß-lactamase that can expand its substrate spectrum with a single amino acid substitution.

The continuous evolution of ß-lactamases resulting in bacterial resistance to ß-lactam antibiotics is a major concern in public health, and yet the underlying molecular basis or the pattern of such evolution is largely unknown. We investigated the mechanics of the substrate fspectrum expansion of the class A ß-lactamase using PenA of Burkholderia thailandensis as a model. By analyzing 516 mutated enzymes that acquired the ceftazidime-hydrolyzing activity, we found twelve positions with single amino acid substitutions (altogether twenty-nine different substitutions), co-localized at the active-site pocket area. The ceftazidime MIC (minimum inhibitory concentration) levels and the relative frequency in the occurrence of substitutions did not correlate well with each other, and the latter appeared be largely influenced by the intrinsic mutational biases present in bacteria. Simulation studies suggested that all substitutions caused a congruent effect, expanding the space in a conserved structure called the omega loop, which in turn increased flexibility at the active site. A second phase of selection, in which the mutants were placed under increased antibiotic pressure, did not result in a second mutation in the coding region, but a mutation that increased gene expression arose in the promoter. This result suggests that the twelve amino acid positions and their specific substitutions in PenA may represent a comprehensive repertoire of the enzyme's adaptability to a new substrate. These mapped substitutions represent a comprehensive set of general mechanical paths to substrate spectrum expansion in class A ß-lactamases that all share a functional evolutionary mechanism using common conserved residues.

Substrate spectrum extension of PenA in Burkholderia thailandensis with a single amino acid deletion, Glu168del.

We describe a deletion mutation in a class A ß-lactamase, PenA, of Burkholderia thailandensis that extended the substrate spectrum of the enzyme to include ceftazidime. Glu168del was located in a functional domain called the omega loop causing expansion of the space in the loop, which in turn increased flexibility at the active site. This deletion mutation represents a rare but significant alternative mechanical path to substrate spectrum extension in PenA besides more common substitution mutations.