Characterization of gram-negative bloodstream infections in hospitalised Australian children and their clinical outcomes.

BACKGROUND: Gram-negative bloodstream infections (GNBSI) more commonly occur in children with comorbidities and are increasingly associated with antimicrobial resistance. There are few large studies of GNBSI in children that relate the clinical presentation, pathogen characteristics and outcomes. METHODS: A 3-year prospective study of GNBSI in children aged <18 years was conducted in five Australian children's hospitals between 2019-2021. The clinical characteristics, disease severity and outcomes were recorded. Causative pathogens underwent antibiotic susceptibility testing and whole genome sequencing. RESULTS: There were 931 GNBSI episodes involving 818 children. Median age was 3 years (IQR 0.6-8.5). 576/931 episodes (62%) were community onset though 661/931 (71%) occurred in children with comorbidities and a central venous catheter (CVC) was present in 558/931 (60%). CVC (145/931) and urinary tract (149/931) were the most common sources (16% each). 100/931 (11%) children required Intensive Care Unit (ICU) admission and a further 11% (105/931) developed GNBSI in ICU. 659/927 (71%) isolates were Enterobacterales of which 22% (138/630) were third generation cephalosporin resistant (3GCR). Extended spectrum beta-lactamase genes (ESBL) were confirmed in 65/138 (47%) 3GCR-Enterobacterales. Most common ESBL genes were blaCTX-M-15 (34/94, 36%) and blaSHV-12 (10/94, 11%). There were 48 deaths overall and 30-day in-hospital mortality was 3% (32/931). Infections with 3GCR Enterobacterales were independently associated with higher mortality (adjusted OR 3.2, 95%CI 1.6-6.4). CONCLUSION: GNBSI in children are frequently healthcare-associated and affect children under 5 years. Infections with 3GCR Enterobacterales were associated with worse outcomes. These findings will inform optimal management guidelines and help prioritise future antimicrobial clinical trials.

High-risk Escherichia coli clones that cause neonatal meningitis and association with recrudescent infection.

Neonatal meningitis is a devastating disease associated with high mortality and neurological sequelae. Escherichia coli is the second most common cause of neonatal meningitis in full-term infants (herein NMEC) and the most common cause of meningitis in preterm neonates. Here, we investigated the genomic relatedness of a collection of 58 NMEC isolates spanning 1974-2020 and isolated from seven different geographic regions. We show NMEC are comprised of diverse sequence types (STs), with ST95 (34.5%) and ST1193 (15.5%) the most common. No single virulence gene profile was conserved in all isolates; however, genes encoding fimbrial adhesins, iron acquisition systems, the K1 capsule, and O antigen types O18, O75, and O2 were most prevalent. Antibiotic resistance genes occurred infrequently in our collection. We also monitored the infection dynamics in three patients that suffered recrudescent invasive infection caused by the original infecting isolate despite appropriate antibiotic treatment based on antibiogram profile and resistance genotype. These patients exhibited severe gut dysbiosis. In one patient, the causative NMEC isolate was also detected in the fecal flora at the time of the second infection episode and after treatment. Thus, although antibiotics are the standard of care for NMEC treatment, our data suggest that failure to eliminate the causative NMEC that resides intestinally can lead to the existence of a refractory reservoir that may seed recrudescent infection.

Emergence and clonal expansion of a qacA-harbouring sequence type 45 lineage of methicillin-resistant Staphylococcus aureus.

The past decade has seen an increase in the prevalence of sequence type (ST) 45 methicillin-resistant Staphylococcus aureus (MRSA), yet the underlying drivers for its emergence and spread remain unclear. To better understand the worldwide dissemination of ST45 S. aureus, we performed phylogenetic analyses of Australian isolates, supplemented with a global population of ST45 S. aureus genomes. Our analyses revealed a distinct lineage of multidrug-resistant ST45 MRSA harbouring qacA, predominantly found in Australia and Singapore. Bayesian inference predicted that the acquisition of qacA occurred in the late 1990s. qacA was integrated into a structurally variable region of the chromosome containing Tn552 (carrying blaZ) and Tn4001 (carrying aac(6')-aph(2")) transposable elements. Using mutagenesis and in vitro assays, we provide phenotypic evidence that qacA confers tolerance to chlorhexidine. These findings collectively suggest both antimicrobial resistance and the carriage of qacA may play a role in the successful establishment of ST45 MRSA.

Achievement of therapeutic antibiotic exposures using Bayesian dosing software in critically unwell children and adults with sepsis.

PURPOSE: Early recognition and effective treatment of sepsis improves outcomes in critically ill patients. However, antibiotic exposures are frequently suboptimal in the intensive care unit (ICU) setting. We describe the feasibility of the Bayesian dosing software Individually Designed Optimum Dosing Strategies (ID-ODS™), to reduce time to effective antibiotic exposure in children and adults with sepsis in ICU. METHODS: A multi-centre prospective, non-randomised interventional trial in three adult ICUs and one paediatric ICU. In a pre-intervention Phase 1, we measured the time to target antibiotic exposure in participants. In Phase 2, antibiotic dosing recommendations were made using ID-ODS™, and time to target antibiotic concentrations were compared to patients in Phase 1 (a pre-post-design). RESULTS: 175 antibiotic courses (Phase 1 = 123, Phase 2 = 52) were analysed from 156 participants. Across all patients, there was no difference in the time to achieve target exposures (8.7 h vs 14.3 h in Phase 1 and Phase 2, respectively, p = 0.45). Sixty-one courses in 54 participants failed to achieve target exposures within 24 h of antibiotic commencement (n = 36 in Phase 1, n = 18 in Phase 2). In these participants, ID-ODS™ was associated with a reduction in time to target antibiotic exposure (96 vs 36.4 h in Phase 1 and Phase 2, respectively, p < 0.01). These patients were less likely to exhibit subtherapeutic antibiotic exposures at 96 h (hazard ratio (HR) 0.02, 95% confidence interval (CI) 0.01-0.05, p < 0.01). There was no difference observed in in-hospital mortality. CONCLUSIONS: Dosing software may reduce the time to achieve target antibiotic exposures. It should be evaluated further in trials to establish its impact on clinical outcomes.

HAIviz: an interactive dashboard for visualising and integrating healthcare-associated genomic epidemiological data.

Existing tools for phylogeographic and epidemiological visualisation primarily provide a macro-geographic view of epidemic and pandemic transmission events but offer little support for detailed investigation of outbreaks in healthcare settings. Here, we present HAIviz, an interactive web-based application designed for integrating and visualising genomic epidemiological information to improve the tracking of healthcare-associated infections (HAIs). HAIviz displays and links the outbreak timeline, building map, phylogenetic tree, patient bed movements, and transmission network on a single interactive dashboard. HAIviz has been developed for bacterial outbreak investigations but can be utilised for general epidemiological investigations focused on built environments for which visualisation to customised maps is required. This paper describes and demonstrates the application of HAIviz for HAI outbreak investigations.

TcrXY is an acid-sensing two-component transcriptional regulator of Mycobacterium tuberculosis required for persistent infection.

The ability of Mycobacterium tuberculosis (Mtb) to persist in the host complicates and prolongs tuberculosis (TB) patient chemotherapy. Here we demonstrate that a neglected two-component system (TCS) of Mtb, TcrXY, is an autoregulated acid-sensing TCS that controls a functionally diverse 70-gene regulon required for bacterial persistence. Characterisation of two representatives of this regulon, Rv3706c and Rv3705A, implicate these genes as key determinants for the survival of Mtb in vivo by serving as important effectors to mitigate redox stress at acidic pH. We show that genetic silencing of the response regulator tcrX using CRISPR interference attenuates the persistence of Mtb during chronic mouse infection and improves treatment with the two front-line anti-TB drugs, rifampicin and isoniazid. We propose that targeting TcrXY signal transduction blocks the ability of Mtb to sense and respond to acid stress, resulting in a disordered program of persistence to render the organism vulnerable to existing TB chemotherapy.

Genomic epidemiology reveals geographical clustering of multidrug-resistant Escherichia coli ST131 associated with bacteraemia in Wales.

Antibiotic resistance is a significant global public health concern. Uropathogenic Escherichia coli sequence type (ST)131, a widely prevalent multidrug-resistant clone, is frequently associated with bacteraemia. This study investigates third-generation cephalosporin resistance in bloodstream infections caused by E. coli ST131. From 2013-2014 blood culture surveillance in Wales, 142 E. coli ST131 genomes were studied alongside global data. All three major ST131 clades were represented across Wales, with clade C/H30 predominant (n = 102/142, 71.8%). Consistent with global findings, Welsh strains of clade C/H30 contain ß-lactamase genes from the blaCTX-M-1 group (n = 65/102, 63.7%), which confer resistance to third-generation cephalosporins. Most Welsh clade C/H30 genomes belonged to sub-clade C2/H30Rx (58.3%). A Wales-specific sub-lineage, named GB-WLS.C2, diverged around 1996-2000. An introduction to North Wales around 2002 led to a localised cluster by 2009, depicting limited genomic diversity within North Wales. This investigation emphasises the value of genomic epidemiology, allowing the detection of genetically similar strains in local areas, enabling targeted and timely public health interventions.

Association between gut microbiota development and allergy in infants born during pandemic-related social distancing restrictions.

BACKGROUND: Several hypotheses link reduced microbial exposure to increased prevalence of allergies. Here we capitalize on the opportunity to study a cohort of infants (CORAL), raised during COVID-19 associated social distancing measures, to identify the environmental exposures and dietary factors that contribute to early life microbiota development and to examine their associations with allergic outcomes. METHODS: Fecal samples were sequenced from infants at 6 (n = 351) and repeated at 12 (n = 343) months, using 16S sequencing. Published 16S data from pre-pandemic cohorts were included for microbiota comparisons. Online questionnaires collected epidemiological information on home environment, healthcare utilization, infant health, allergic diseases, and diet. Skin prick testing (SPT) was performed at 12 (n = 343) and 24 (n = 320) months of age, accompanied by atopic dermatitis and food allergy assessments. RESULTS: The relative abundance of bifidobacteria was higher, while environmentally transmitted bacteria such as Clostridia was lower in CORAL infants compared to previous cohorts. The abundance of multiple Clostridia taxa correlated with a microbial exposure index. Plant based foods during weaning positively impacted microbiota development. Bifidobacteria levels at 6 months of age, and relative abundance of butyrate producers at 12 months of age, were negatively associated with AD and SPT positivity. The prevalence of allergen sensitization, food allergy, and AD did not increase over pre-pandemic levels. CONCLUSIONS: Environmental exposures and dietary components significantly impact microbiota community assembly. Our results also suggest that vertically transmitted bacteria and appropriate dietary supports may be more important than exposure to environmental microbes alone for protection against allergic diseases in infancy.

Rapid nanopore sequencing and predictive susceptibility testing of positive blood cultures from intensive care patients with sepsis.

We aimed to evaluate the performance of Oxford Nanopore Technologies (ONT) sequencing from positive blood culture (BC) broths for bacterial identification and antimicrobial susceptibility prediction. Patients with suspected sepsis in four intensive care units were prospectively enrolled. Human-depleted DNA was extracted from positive BC broths and sequenced using ONT (MinION). Species abundance was estimated using Kraken2, and a cloud-based system (AREScloud) provided in silico predictive antimicrobial susceptibility testing (AST) from assembled contigs. Results were compared to conventional identification and phenotypic AST. Species-level agreement between conventional methods and AST predicted from sequencing was 94.2% (49/52), increasing to 100% in monomicrobial infections. In 262 high-quality AREScloud AST predictions across 24 samples, categorical agreement (CA) was 89.3%, with major error (ME) and very major error (VME) rates of 10.5% and 12.1%, respectively. Over 90% CA was achieved for some taxa (e.g., Staphylococcus aureus) but was suboptimal for Pseudomonas aeruginosa. In 470 AST predictions across 42 samples, with both high quality and exploratory-only predictions, overall CA, ME, and VME rates were 87.7%, 8.3%, and 28.4%. VME rates were inflated by false susceptibility calls in a small number of species/antibiotic combinations with few representative resistant isolates. Time to reporting from sequencing could be achieved within 8-16 h from BC positivity. Direct sequencing from positive BC broths is feasible and can provide accurate predictive AST for some species. ONT-based approaches may be faster but significant improvements in accuracy are required before it can be considered for clinical use.IMPORTANCESepsis and bloodstream infections carry a high risk of morbidity and mortality. Rapid identification and susceptibility prediction of causative pathogens, using Nanopore sequencing direct from blood cultures, may offer clinical benefit. We assessed this approach in comparison to conventional phenotypic methods and determined the accuracy of species identification and susceptibility prediction from genomic data. While this workflow holds promise, and performed well for some common bacterial species, improvements in sequencing accuracy and more robust predictive algorithms across a diverse range of organisms are required before this can be considered for clinical use. However, results could be achieved in timeframes that are faster than conventional phenotypic methods.

Melioidosis Queensland: An analysis of clinical outcomes and genomic factors.

BACKGROUND: The clinical and genomic epidemiology of melioidosis varies across regions. AIM: To describe the clinical and genetic diversity of B. pseudomallei across Queensland, Australia. METHODS: Whole genome sequencing of clinical isolates stored at the melioidosis reference lab from 1996-2020 was performed and analysed in conjunction with available clinical data. RESULTS: Isolates from 292 patients were analysed. Bacteraemia was present in 71% and pneumonia in 65%. The case-fatality rate was 25%. Novel sequence types (ST) accounted for 51% of all isolates. No association was identified between the variable virulence factors assessed and patient outcome. Over time, the proportion of First Nation's patients declined from 59% to 26%, and the proportion of patients aged >70 years rose from 13% to 38%. CONCLUSION: This study describes a genomically diverse and comparatively distinct collection of B. pseudomallei clinical isolates from across Queensland, Australia. An increasing incidence of melioidosis in elderly patients may be an important factor in the persistently high case-fatality in this region and warrants further investigation and directed intervention.

Higher rates of cefiderocol resistance among NDM producing Klebsiella bloodstream isolates applying EUCAST over CLSI breakpoints.

BACKGROUND: Cefiderocol is generally active against carbapenem-resistant Klebsiella spp. (CRK) with higher MICs against metallo-beta-lactamase producers. There is a variation in cefiderocol interpretive criteria determined by EUCAST and CLSI. Our objective was to test CRK isolates against cefiderocol and compare cefiderocol susceptibilities using EUCAST and CLSI interpretive criteria. METHODS: A unique collection (n = 254) of mainly OXA-48-like- or NDM-producing CRK bloodstream isolates were tested against cefiderocol with disc diffusion (Mast Diagnostics, UK). Beta-lactam resistance genes and multilocus sequence types were identified using bioinformatics analyses on complete bacterial genomes. RESULTS: Median cefiderocol inhibition zone diameter was 24 mm (interquartile range [IQR] 24-26 mm) for all isolates and 18 mm (IQR 15-21 mm) for NDM producers. We observed significant variability between cefiderocol susceptibilities using EUCAST and CLSI breakpoints, such that 26% and 2% of all isolates, and 81% and 12% of the NDM producers were resistant to cefiderocol using EUCAST and CLSI interpretive criteria, respectively. CONCLUSIONS: Cefiderocol resistance rates among NDM producers are high using EUCAST criteria. Breakpoint variability may have significant implications on patient outcomes. Until more clinical outcome data are available, we suggest using EUCAST interpretive criteria for cefiderocol susceptibility testing.

GraphSNP: an interactive distance viewer for investigating outbreaks and transmission networks using a graph approach.

BACKGROUND: Cluster and transmission analysis utilising pairwise SNP distance are increasingly used in genomic epidemiological studies. However, current methods are often challenging to install and use, and lack interactive functionalities for easy data exploration. RESULTS: GraphSNP is an interactive visualisation tool running in a web browser that allows users to rapidly generate pairwise SNP distance networks, investigate SNP distance distributions, identify clusters of related organisms, and reconstruct transmission routes. The functionality of GraphSNP is demonstrated using examples from recent multi-drug resistant bacterial outbreaks in healthcare settings. CONCLUSIONS: GraphSNP is freely available at https://github.com/nalarbp/graphsnp . An online version of GraphSNP, including demonstration datasets, input templates, and quick start guide is available for use at https://graphsnp.fordelab.com .

Using Genomics To Investigate an Outbreak of Vancomycin-Resistant Enterococcus faecium ST78 at a Large Tertiary Hospital in Queensland.

To investigate an outbreak of vancomycin-resistant Enterococcus faecium (VREfm) sequence type 78 (ST78) in a large tertiary Australian hospital. A collection of 63 VREfm ST78 isolates, identified during a routine genomic surveillance program, were subjected to genomic epidemiological analysis based on whole-genome sequencing (WGS) data. The population structure was reconstructed using phylogenetic analysis, and a collection of publicly available VREfm ST78 genomes were used to provide global context. Core genome single nucleotide polymorphism (SNP) distances and available clinical metadata were used to characterize outbreak clusters and reconstruct transmission events. In silico genotyping confirmed that all study isolates were vanB-type VREfm carrying virulence characteristics of the hospital-associated E. faecium. Phylogenetic analysis identified two distinct phylogenetic clades, only one of which was responsible for a hospital outbreak. Four outbreak subtypes could be defined with examples of recent transmissions. Inference on transmission trees suggested complex transmission routes with unknown environmental reservoirs mediating the outbreak. WGS-based cluster analysis with publicly available genomes identified closely related Australian ST78 and ST203 isolates, highlighting the capacity for WGS to resolve complex clonal relationships between the VREfm lineages. Whole genome-based analysis has provided a high-resolution description of an outbreak of vanB-type VREfm ST78 in a Queensland hospital. Combined routine genomic surveillance and epidemiological analysis have facilitated better understanding of the local epidemiology of this endemic strain, providing valuable insight for better targeted control of VREfm. IMPORTANCE Vancomycin-resistant Enterococcus faecium (VREfm) is a leading cause of health care-associated infections (HAIs) globally. In Australia, the spread of hospital-adapted VREfm is largely driven by a single clonal group (clonal complex [CC]), CC17, to which the lineage ST78 belongs. While implementing a genomic surveillance program in Queensland, we observed increased incidence of ST78 colonizations and infections among patients. Here, we demonstrate the use of real-time genomic surveillance as a tool to support and enhance infection control (IC) practices. Our results show that real-time whole-genome sequencing (WGS) can efficiently disrupt outbreaks by identifying transmission routes that in turn can be targeted using resource-limited interventions. Additionally, we demonstrate that by placing local outbreaks in a global context, high-risk clones can be identified and targeted prior to them becoming established within clinical environments. Finally, the persistence of these organism within the hospital highlights the need for routine genomic surveillance as a management tool to control VRE transmission.

Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria.

Even in the setting of optimal resuscitation in high-income countries severe sepsis and septic shock have a mortality of 20-40%, with antibiotic resistance dramatically increasing this mortality risk. To develop a reference dataset enabling the identification of common bacterial targets for therapeutic intervention, we applied a standardized genomic, transcriptomic, proteomic and metabolomic technological framework to multiple clinical isolates of four sepsis-causing pathogens: Escherichia coli, Klebsiella pneumoniae species complex, Staphylococcus aureus and Streptococcus pyogenes. Exposure to human serum generated a sepsis molecular signature containing global increases in fatty acid and lipid biosynthesis and metabolism, consistent with cell envelope remodelling and nutrient adaptation for osmoprotection. In addition, acquisition of cholesterol was identified across the bacterial species. This detailed reference dataset has been established as an open resource to support discovery and translational research.

Treatment Failure Due to Adaptive Resistance Mechanisms in a Severe and Complicated Bloodstream Infection Due to Elizabethkingia meningoseptica.

Elizabethkingia meningoseptica is an uncommonly encountered multidrug-resistant gram-negative bacterium that causes infections primarily among vulnerable hosts. A true opportunistic pathogen, its ability to cause severe sepsis and complicated infection in selected patients has been noted. Very limited preclinical and clinical data exist with regard to suitable therapeutic options. In this study, we present the case of prolonged bloodstream and central nervous system infection due to E. meningoseptica treated with dose-optimized combination antibiotic therapy, with evidence of microbiological (including development of adaptive resistance mechanisms) and clinical failure.

Clinical Implementation of Routine Whole-genome Sequencing for Hospital Infection Control of Multi-drug Resistant Pathogens.

BACKGROUND: Prospective whole-genome sequencing (WGS)-based surveillance may be the optimal approach to rapidly identify transmission of multi-drug resistant (MDR) bacteria in the healthcare setting. METHODS: We prospectively collected methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), carbapenem-resistant Acinetobacter baumannii (CRAB), extended-spectrum beta-lactamase (ESBL-E), and carbapenemase-producing Enterobacterales (CPE) isolated from blood cultures, sterile sites, or screening specimens across three large tertiary referral hospitals (2 adult, 1 paediatric) in Brisbane, Australia. WGS was used to determine in silico multi-locus sequence typing (MLST) and resistance gene profiling via a bespoke genomic analysis pipeline. Putative transmission events were identified by comparison of core genome single nucleotide polymorphisms (SNPs). Relevant clinical meta-data were combined with genomic analyses via customised automation, collated into hospital-specific reports regularly distributed to infection control teams. RESULTS: Over 4 years (April 2017 to July 2021) 2660 isolates were sequenced. This included MDR gram-negative bacilli (n = 293 CPE, n = 1309 ESBL), MRSA (n = 620), and VRE (n = 433). A total of 379 clinical reports were issued. Core genome SNP data identified that 33% of isolates formed 76 distinct clusters. Of the 76 clusters, 43 were contained to the 3 target hospitals, suggesting ongoing transmission within the clinical environment. The remaining 33 clusters represented possible inter-hospital transmission events or strains circulating in the community. In 1 hospital, proven negligible transmission of non-multi-resistant MRSA enabled changes to infection control policy. CONCLUSIONS: Implementation of routine WGS for MDR pathogens in clinical laboratories is feasible and can enable targeted infection prevention and control interventions.

Optimized Method for Bacterial Nucleic Acid Extraction from Positive Blood Culture Broth for Whole-Genome Sequencing, Resistance Phenotype Prediction, and Downstream Molecular Applications.

The application of direct metagenomic sequencing from positive blood culture broth may solve the challenges of sequencing from low-bacterial-load blood samples in patients with sepsis. Forty prospectively collected blood culture broth samples growing Gram-negative bacteria were extracted using commercially available kits to achieve high-quality DNA. Species identification via metagenomic sequencing and susceptibility prediction via a machine-learning algorithm (AREScloud) were compared to conventional methods and other rapid diagnostic platforms (Accelerate Pheno and blood culture identification [BCID] panel). A two-kit method (using MolYsis Basic and Qiagen DNeasy UltraClean kits) resulted in optimal extractions. Taxonomic profiling by direct metagenomic sequencing matched conventional identification in 38/40 (95%) samples. In two polymicrobial samples, a second organism was missed by sequencing. Prediction models were able to accurately infer susceptibility profiles for 6 common pathogens against 17 antibiotics, with an overall categorical agreement (CA) of 95% (increasing to >95% for 5/6 of the most common pathogens, if Klebsiella oxytoca was excluded). The performance of whole-genome sequencing (WGS)-antimicrobial susceptibility testing (AST) was suboptimal for uncommon pathogens (e.g., Elizabethkingia) and some ß-lactamase inhibitor antibiotics (e.g., ticarcillin-clavulanate). The time to pathogen identification was the fastest with BCID (1 h from blood culture positivity). Accelerate Pheno provided a susceptibility result in approximately 8 h. Illumina-based direct sequencing methods provided results in time frames similar to those of conventional culture-based methods. Direct metagenomic sequencing from blood cultures for pathogen detection and susceptibility prediction is feasible. Additional work is required to optimize algorithms for uncommon species and complex resistance genotypes as well as to streamline methods to provide more rapid results.

Impact of Long COVID on health and quality of life.

Background: The aim of this study was to measure the impact of post-acute sequelae of COVID-19 (PASC) on quality of life, mental health, ability to work and return to baseline health in an Irish cohort. Methods: We invited individuals with symptoms of COVID-19 lasting more than 14 days to participate in an anonymous online questionnaire. Basic demographic data and self-reported symptoms were recorded. Internationally validated instruments including the patient health questionnaire somatic, anxiety and depressive symptom scales (PHQ-SADS), the Patient Health Questionnaire-15 (PHQ-15) and Chadler fatigue scale (CFQ) were used. Results: We analysed responses from 988 participants with self-reported confirmed (diagnostic/antibody positive; 81%) or suspected (diagnostic/antibody negative or untested; 9%) COVID-19. The majority of respondents were female (88%), white (98%), with a median age of 43.0 (range 15 - 88 years old) and a median BMI of 26.0 (range 16 - 60). At the time of completing this survey, 89% of respondents reported that they have not returned to their pre-COVID-19 level of health. The median number of symptoms reported was 8 (range 0 to 33 symptoms), with a median duration of 12 months (range 1 to 20 months) since time of acute infection. A high proportion of PASC patients reported that they have a moderate or severe limitation in their ability to carry out their usual activities, 38% report their ability to work is severely limited and 33% report a moderate, or higher, level of anxiety or depression. Conclusion: The results of this survey of an Irish cohort with PASC are in line with reports from other settings, and we confirm that patients with PASC reported prolonged, multi-system symptoms which can significantly impact quality of life, affect ability to work and cause significant disability. Dedicated multidisciplinary, cross specialty supports are required to improve outcomes of this patient group.

Immunomodulation by foods and microbes: Unravelling the molecular tango.

Metabolic health and immune function are intimately connected via diet and the microbiota. Nearly 90% of all immune cells in the body are associated with the gastrointestinal tract and these immune cells are continuously exposed to a wide range of microbes and microbial-derived compounds, with important systemic ramifications. Microbial dysbiosis has consistently been observed in patients with atopic dermatitis, food allergy and asthma and the molecular mechanisms linking changes in microbial populations with disease risk and disease endotypes are being intensively investigated. The discovery of novel bacterial metabolites that impact immune function is at the forefront of host-microbe research. Co-evolution of microbial communities within their hosts has resulted in intertwined metabolic pathways that affect physiological and pathological processes. However, recent dietary and lifestyle changes are thought to negatively influence interactions between microbes and their host. This review provides an overview of some of the critical metabolite-receptor interactions that have been recently described, which may underpin the immunomodulatory effects of the microbiota, and are of relevance for allergy, asthma and infectious diseases.