A high-risk gut microbiota configuration associates with fatal hyperinflammatory immune and metabolic responses to SARS-CoV-2.

Protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and associated clinical sequelae requires well-coordinated metabolic and immune responses that limit viral spread and promote recovery of damaged systems. However, the role of the gut microbiota in regulating these responses has not been thoroughly investigated. In order to identify mechanisms underpinning microbiota interactions with host immune and metabolic systems that influence coronavirus disease 2019 (COVID-19) outcomes, we performed a multi-omics analysis on hospitalized COVID-19 patients and compared those with the most severe outcome (i.e. death, n = 41) to those with severe non-fatal disease (n = 89), or mild/moderate disease (n = 42), that recovered. A distinct subset of 8 cytokines (e.g. TSLP) and 140 metabolites (e.g. quinolinate) in sera identified those with a fatal outcome to infection. In addition, elevated levels of multiple pathobionts and lower levels of protective or anti-inflammatory microbes were observed in the fecal microbiome of those with the poorest clinical outcomes. Weighted gene correlation network analysis (WGCNA) identified modules that associated severity-associated cytokines with tryptophan metabolism, coagulation-linked fibrinopeptides, and bile acids with multiple pathobionts, such as Enterococcus. In contrast, less severe clinical outcomes are associated with clusters of anti-inflammatory microbes such as Bifidobacterium or Ruminococcus, short chain fatty acids (SCFAs) and IL-17A. Our study uncovered distinct mechanistic modules that link host and microbiome processes with fatal outcomes to SARS-CoV-2 infection. These features may be useful to identify at risk individuals, but also highlight a role for the microbiome in modifying hyperinflammatory responses to SARS-CoV-2 and other infectious agents

Molecular epidemiology of methicillin-resistant Staphylococcus aureus isolated from Australian veterinarians

This work investigated the molecular epidemiology and antimicrobial resistance of methicillinresistant Staphylococcus aureus (MRSA) isolated from veterinarians in Australia in 2009. The collection (n = 44) was subjected to extensive molecular typing (MLST, spa, SCCmec, dru, PFGE, virulence and antimicrobial resistance genotyping) and antimicrobial resistance phenotyping by disk diffusion. MRSA was isolated from Australian veterinarians representing various occupational emphases. The isolate collection was dominated by MRSA strains belonging to clonal complex (CC) 8 and multilocus sequence type (ST) 22. CC8 MRSA (ST8-IV [2B], spa t064; and ST612-IV [2B] , spa variable,) were strongly associated with equine practice veterinarians (OR = 17.5, 95% CI = 3.3-92.5, P < 0.001) and were often resistant to gentamicin and rifampicin. ST22-IV [2B], spa variable, were strongly associated with companion animal practice veterinarians (OR = 52.5, 95% CI = 5.2-532.7, P < 0.001) and were resistant to ciprofloxacin. A single pig practice veterinarian carried ST398-V [5C2], spa t1451. Equine practice and companion animal practice veterinarians frequently carried multiresistant-CC8 and ST22 MRSA, respectively, whereas only a single swine specialist carried MRSA ST398. The presence of these strains in veterinarians may be associated with specific antimicrobial administration practices in each animal species

The appropriateness of prescribing antibiotics in the community in Europe: study design

Contains fulltext : 97417.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: Over 90% of all antibiotics in Europe are prescribed in primary care. It is important that antibiotics are prescribed that are likely to be effective; however, information about antibiotic resistance in the community is incomplete. The aim of our study is to investigate the appropriateness of antibiotic prescribing in primary care in Europe by collecting and combining patterns of antibiotic resistance patterns and antibiotic prescription patterns in primary care. We will also evaluate the appropriateness of national antibiotic prescription guidelines in relation to resistance patterns. METHODS/DESIGN: Antibiotic resistance will be studied in an opportunistic sample from the community in nine European countries. Resistance data will be collected by taking a nose swab of persons (N = 4,000 per country) visiting a primary care practice for a non-infectious disease. Staphylococcus aureus and Streptococcus pneumoniae will be isolated and tested for resistance to a range of antibiotics in one central laboratory. Data on antibiotic prescriptions over the past 5 years will be extracted from the electronic medical records of General Practitioners (GPs). The results of the study will include the prevalence and resistance data of the two species and 5 years of antibiotic prescription data in nine European countries.The odds of receiving an effective antibiotic in each country will be calculated as a measure for the appropriateness of prescribing. Multilevel analysis will be used to assess the appropriateness of prescribing. Relevant treatment guidelines of the nine participating countries will be evaluated using a standardized instrument and related to the resistance patterns in that country. DISCUSSION: This study will provide valuable and unique data concerning resistance patterns and prescription behaviour in primary care in nine European countries. It will provide evidence-based recommendations for antibiotic treatment guidelines that take resistance patterns into account which will be useful for both clinicians and policy makers. By improving antibiotic use we can move towards controlling the resistance problem globally

Procalcitonin for diagnosis of infection and guide to antibiotic decisions: past, present and future

There are a number of limitations to using conventional diagnostic markers for patients with clinical suspicion of infection. As a consequence, unnecessary and prolonged exposure to antimicrobial agents adversely affect patient outcomes, while inappropriate antibiotic therapy increases antibiotic resistance. A growing body of evidence supports the use of procalcitonin (PCT) to improve diagnosis of bacterial infections and to guide antibiotic therapy. For patients with upper and lower respiratory tract infection, post-operative infections and for severe sepsis patients in the intensive care unit, randomized-controlled trials have shown a benefit of using PCT algorithms to guide decisions about initiation and/or discontinuation of antibiotic therapy. For some other types of infections, observational studies have shown promising first results, but further intervention studies are needed before use of PCT in clinical routine can be recommended. The aim of this review is to summarize the current evidence for PCT in different infections and clinical settings, and discuss the reliability of this marker when used with validated diagnostic algorithms

MRSA prevalence in european healthcare settings: a review

<p>Abstract</p> <p>Background</p> <p>During the past two decades, methicillin-resistant <it>Staphylococcus aureus </it>(MRSA) has become increasingly common as a source of nosocomial infections. Most studies of MRSA surveillance were performed during outbreaks, so that results are not applicable to settings in which MRSA is endemic. This paper gives an overview of MRSA prevalence in hospitals and other healthcare institutions in non-outbreak situations in Western Europe.</p> <p>Methods</p> <p>A keyword search was conducted in the Medline database (2000 through June 2010). Titles and abstracts were screened to identify studies on MRSA prevalence in patients in non-outbreak situations in European healthcare facilities. Each study was assessed using seven quality criteria (outcome definition, time unit, target population, participants, observer bias, screening procedure, swabbing sites) and categorized as 'good', 'fair', or 'poor'.</p> <p>Results</p> <p>31 observational studies were included in the review. Four of the studies were of good quality. Surveillance screening of MRSA was performed in long-term care (11 studies) and acute care (20 studies). Prevalence rates varied over a wide range, from less than 1% to greater than 20%. Prevalence in the acute care and long-term care settings was comparable. The prevalence of MRSA was expressed in various ways - the percentage of MRSA among patients (range between 1% and 24%), the percentage of MRSA among <it>S. aureus </it>isolates (range between 5% and 54%), and as the prevalence density (range between 0.4 and 4 MRSA cases per 1,000 patient days). The screening policy differed with respect to time points (on admission or during hospital stay), selection criteria (all admissions or patients at high risk for MRSA) and anatomical sampling sites.</p> <p>Conclusions</p> <p>This review underlines the methodological differences between studies of MRSA surveillance. For comparisons between different healthcare settings, surveillance methods and outcome calculations should be standardized.</p

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease