Development and proof-of-concept demonstration of a clinical metagenomics method for the rapid detection of bloodstream infection.

BACKGROUND: The timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood. METHODS: Blood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol-SepsiPURE. RESULTS: After first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 106 and < 103 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (SepsiPURE; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50-100 colony forming units (CFU)/mL to 1-5 CFU/mL. CONCLUSION: In this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

Hybrid metagenome assemblies link carbohydrate structure with function in the human gut microbiome.

Complex carbohydrates that escape small intestinal digestion, are broken down in the large intestine by enzymes encoded by the gut microbiome. This is a symbiotic relationship between microbes and host, resulting in metabolic products that influence host health and are exploited by other microbes. However, the role of carbohydrate structure in directing microbiota community composition and the succession of carbohydrate-degrading microbes, is not fully understood. In this study we evaluate species-level compositional variation within a single microbiome in response to six structurally distinct carbohydrates in a controlled model gut using hybrid metagenome assemblies. We identified 509 high-quality metagenome-assembled genomes (MAGs) belonging to ten bacterial classes and 28 bacterial families. Bacterial species identified as carrying genes encoding starch binding modules increased in abundance in response to starches. The use of hybrid metagenomics has allowed identification of several uncultured species with the functional potential to degrade starch substrates for future study.

Antimicrobial Resistance Genes, Virulence Genes, and Associated Mobile Genetic Elements of Eight Multidrug-Resistant Enterobacterales Isolated from Hospital-Acquired Urinary Tract Infections in Sri Lanka.

The study describes the first isolation of multidrug-resistant (MDR) Klebsiella pneumoniae ST16, Escherichia coli ST131 (Esc), and Enterobacter hormaechei subsp. steigerwaltii ST93 (Enterobacter cloacae complex [ECC]) in Sri Lanka. Eight MDR strains of uropathogenic Enterobacterales isolated from hospital acquired urinary tract infections (UTIs) were analyzed using genomic sequencing and comparative genomics. Isolates carried multiple carbapenemase, AmpC, and ESBL (extended-spectrum ß-lactamase) genes. ECC manifested both blaNDM-4 and blaOXA-181. The K. pneumoniae strains harbored fimbrial genes that facilitate pathogenesis of UTI. Several extraintestinal pathogenic E. coli associated virulence genes were identified in Esc. The efflux pump gene, acrA, and the T6SS gene cluster were detected in ECC. Many antimicrobial resistance (AMR) and virulence genes were identified associated with mobile genetic elements. ISEcp1 flanked upstream of blaCTX-M-15. The carbapenemase genes were carried on ColKP3 plasmids and were associated with ISEcp1. In Esc, the AMR gene blaTEM-1B and virulence gene traT were found on an IncF plasmid replicon. In K. pneumoniae the AMR genes sul1 and tetB present on IncR plasmid replicons and were associated with the insertion sequence IS6100. In Kp5, blaLAP-2 and qnrS1 coexisted and were flanked by ISEcl. AMR gene clusters, conferring resistance to multiple antimicrobial classes, flanked by mobile elements were identified in seven isolates.

Phenotypic and genotypic distribution of ESBL, AmpC ß-lactamase and carbapenemase-producing Enterobacteriaceae in community-acquired and hospital-acquired urinary tract infections in Sri Lanka.

OBJECTIVES: Although Sri Lanka belongs to a region with a high prevalence of extended-spectrum ß-lactamase (ESBL), AmpC ß-lactamase and carbapenemase-producing Enterobacteriaceae, data regarding antimicrobial resistance (AMR) is limited. We studied the prevalence and diversity of ß-lactamases produced by Enterobacteriaceae urinary pathogens from two hospitals in the Western Province of Sri Lanka. METHODS: ESBL, AmpC ß-lactamase and carbapenemase production was detected by phenotypic testing followed by genotyping. RESULTS: The species responsible for urinary tract infections (UTI) were Escherichia coli (69%), Klebsiella pneumoniae (16%) and Enterobacter sp (6%). The prevalence of ESBL (50%), AmpC ß-lactamase (19%) and carbapenemase (11%) phenotypes was high, and greater in hospital-acquired (HA-UTI) (75%) than in community-acquired UTI (CA-UTI) (42%). Identification of CA-UTI caused by carbapenemase-producing Enterobacteriaceae (5%) is alarming. Only one ESBL gene, blaCTX- M-15, was detected. AmpC ß-lactamase genes found in E. coli and K. pneumoniae were blaCMY-2, blaCMY-42 and blaDHA-1, while Enterobacter sp. carried blaACT-1. Carbapenemase genes were blaNDM-1, blaNDM-4, blaOXA-181 and blaOXA-232, while blaKPC, blaIMP and blaVIM were absent. Co-occurrence of multiple bla genes, with some isolates harbouring six different bla genes, was common. Carbapenem-resistant isolates without carbapenemase genes displayed mutations in the outer membrane porin genes, ompF of E. coli and ompK36 of K. pneumoniae. Factors associated with UTI with ß-lactamase-producing Enterobacteriaceae were age ≥50 years, previous hospitalization, presence of an indwelling urinary catheter, history of diabetes mellitus or other chronic illness and recurrent urinary tract infections. CONCLUSION: This study adds to the currently scarce data on AMR in Sri Lanka.

Multicentre evaluation of two multiplex PCR platforms for the rapid microbiological investigation of nosocomial pneumonia in UK ICUs: the INHALE WP1 study.

BACKGROUND: Culture-based microbiological investigation of hospital-acquired or ventilator-associated pneumonia (HAP or VAP) is insensitive, with aetiological agents often unidentified. This can lead to excess antimicrobial treatment of patients with susceptible pathogens, while those with resistant bacteria are treated inadequately for prolonged periods. Using PCR to seek pathogens and their resistance genes directly from clinical samples may improve therapy and stewardship. METHODS: Surplus routine lower respiratory tract samples were collected from intensive care unit patients about to receive new or changed antibiotics for hospital-onset lower respiratory tract infections at 15 UK hospitals. Testing was performed using the BioFire FilmArray Pneumonia Panel (bioMérieux) and Unyvero Pneumonia Panel (Curetis). Concordance analysis compared machine and routine microbiology results, while Bayesian latent class (BLC) analysis estimated the sensitivity and specificity of each test, incorporating information from both PCR panels and routine microbiology. FINDINGS: In 652 eligible samples; PCR identified pathogens in considerably more samples compared with routine microbiology: 60.4% and 74.2% for Unyvero and FilmArray respectively vs 44.2% by routine microbiology. PCR tests also detected more pathogens per sample than routine microbiology. For common HAP/VAP pathogens, FilmArray had sensitivity of 91.7%-100.0% and specificity of 87.5%-99.5%; Unyvero had sensitivity of 50.0%-100.0%%, and specificity of 89.4%-99.0%. BLC analysis indicated that, compared with PCR, routine microbiology had low sensitivity, ranging from 27.0% to 69.4%. INTERPRETATION: Conventional and BLC analysis demonstrated that both platforms performed similarly and were considerably more sensitive than routine microbiology, detecting potential pathogens in patient samples reported as culture negative. The increased sensitivity of detection realised by PCR offers potential for improved antimicrobial prescribing.

An optimised protocol for detection of SARS-CoV-2 in stool.

BACKGROUND: SARS-CoV-2 has been detected in stool samples of COVID-19 patients, with potential implications for faecal-oral transmission. Compared to nasopharyngeal swab samples, the complexity of the stool matrix poses a challenge in the detection of the virus that has not yet been solved. However, robust and reliable methods are needed to estimate the prevalence and persistence of SARS-CoV-2 in the gut and to ensure the safety of microbiome-based procedures such as faecal microbiota transplant (FMT). The aim of this study was to establish a sensitive and reliable method for detecting SARS-CoV-2 in stool samples. RESULTS: Stool samples from individuals free of SARS-CoV-2 were homogenised in saline buffer and spiked with a known titre of inactivated virus ranging from 50 to 750 viral particles per 100 mg stool. Viral particles were concentrated by ultrafiltration, RNA was extracted, and SARS-CoV-2 was detected via real-time reverse-transcription polymerase chain reaction (RT-qPCR) using the CDC primers and probes. The RNA extraction procedure we used allowed for the detection of SARS-CoV-2 via RT-qPCR in most of the stool samples tested. We could detect as few as 50 viral particles per 100 mg of stool. However, high variability was observed across samples at low viral titres. The primer set targeting the N1 region provided more reliable and precise results and for this primer set our method had a limit of detection of 1 viral particle per mg of stool. CONCLUSIONS: Here we describe a sensitive method for detecting SARS-CoV-2 in stool samples. This method can be used to establish the persistence of SARS-CoV-2 in stool and ensure the safety of clinical practices such as FMT.

Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management.

The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organizations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1565 positive samples (172 per 100 000 population) from 1376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6 % of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. In total, 1035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a discrete sublineage associated with six care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients, indicating infection control measures were effective; and found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves.

CoronaHiT: high-throughput sequencing of SARS-CoV-2 genomes.

We present CoronaHiT, a platform and throughput flexible method for sequencing SARS-CoV-2 genomes (≤ 96 on MinION or > 96 on Illumina NextSeq) depending on changing requirements experienced during the pandemic. CoronaHiT uses transposase-based library preparation of ARTIC PCR products. Method performance was demonstrated by sequencing 2 plates containing 95 and 59 SARS-CoV-2 genomes on nanopore and Illumina platforms and comparing to the ARTIC LoCost nanopore method. Of the 154 samples sequenced using all 3 methods, ≥ 90% genome coverage was obtained for 64.3% using ARTIC LoCost, 71.4% using CoronaHiT-ONT and 76.6% using CoronaHiT-Illumina, with almost identical clustering on a maximum likelihood tree. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally.

Identification of a Type IV-A CRISPR-Cas System Located Exclusively on IncHI1B/IncFIB Plasmids in Enterobacteriaceae.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) are diverse immune systems found in many prokaryotic genomes that target invading foreign DNA such as bacteriophages and plasmids. There are multiple types of CRISPR with arguably the most enigmatic being Type IV. During an investigation of CRISPR carriage in clinical, multi-drug resistant, Klebsiella pneumoniae, a Type IV-A3 CRISPR-Cas system was detected on plasmids from two K. pneumoniae isolates from Egypt (isolated in 2002-2003) and a single K. pneumoniae isolate from the United Kingdom (isolated in 2017). Sequence analysis of all other genomes available in GenBank revealed that this CRISPR-Cas system was present on 28 other plasmids from various Enterobacteriaceae hosts and was never found on a bacterial chromosome. This system is exclusively located on IncHI1B/IncFIB plasmids and is associated with multiple putative transposable elements. Expression of the cas loci was confirmed in the available clinical isolates by RT-PCR. In all cases, the CRISPR-Cas system has a single CRISPR array (CRISPR1) upstream of the cas loci which has several, conserved, spacers which, amongst things, match regions within conjugal transfer genes of IncFIIK/IncFIB(K) plasmids. Our results reveal a Type IV-A3 CRISPR-Cas system exclusively located on IncHI1B/IncFIB plasmids in Enterobacteriaceae that is likely to be able to target IncFIIK/IncFIB(K) plasmids presumably facilitating intracellular, inter-plasmid competition.

Nanopore metagenomics enables rapid clinical diagnosis of bacterial lower respiratory infection.

The gold standard for clinical diagnosis of bacterial lower respiratory infections (LRIs) is culture, which has poor sensitivity and is too slow to guide early, targeted antimicrobial therapy. Metagenomic sequencing could identify LRI pathogens much faster than culture, but methods are needed to remove the large amount of human DNA present in these samples for this approach to be feasible. We developed a metagenomics method for bacterial LRI diagnosis that features efficient saponin-based host DNA depletion and nanopore sequencing. Our pilot method was tested on 40 samples, then optimized and tested on a further 41 samples. Our optimized method (6 h from sample to result) was 96.6% sensitive and 41.7% specific for pathogen detection compared with culture and we could accurately detect antibiotic resistance genes. After confirmatory quantitative PCR and pathobiont-specific gene analyses, specificity and sensitivity increased to 100%. Nanopore metagenomics can rapidly and accurately characterize bacterial LRIs and might contribute to a reduction in broad-spectrum antibiotic use.

Recent and emerging technologies for the rapid diagnosis of infection and antimicrobial resistance.

The rise in antimicrobial resistance (AMR) is predicted to cause 10 million deaths per year by 2050 unless steps are taken to prevent this looming crisis. Microbiological culture is the gold standard for the diagnosis of bacterial/fungal pathogens and antimicrobial resistance and takes 48 hours or longer. Hence, antibiotic prescriptions are rarely based on a definitive diagnosis and patients often receive inappropriate treatment. Rapid diagnostic tools are urgently required to guide appropriate antimicrobial therapy, thereby improving patient outcomes and slowing AMR development. We discuss new technologies for rapid infection diagnosis including: sample-in-answer-out PCR-based tests, BioFire FilmArray and Curetis Unyvero; rapid susceptibility tests, Accelerate Pheno and microfluidic tests; and sequencing-based approaches, focusing on targeted and clinical metagenomic nanopore sequencing.

Utility of HAPS for predicting prognosis in acute pancreatitis.

BACKGROUND: Acute pancreatitis (AP) is a common abdominal disorder, which requires early diagnosis and treatment. Several prognostic scoring systems introduced to clinical practice are not suitable in emergency department (ED) because these require much time and complex parameters. Recently, the harmless acute pancreatitis score (HAPS) has been introduced to identify AP with a nonsevere course. The aim of this study was to determine the utility of HAPS in predicting the severity of AP. METHODS: All patients aged >16 years who were diagnosed as AP in ED were enrolled in this retrospective study. The study included 144 patients with a mean age of 58.7±15.4 years, and 69 (47.9%) of them were males and 75 (52.1%) were females. Patient data were collected from hospital database. The utility of HAPS was analyzed and compared using the Ranson's score. RESULTS: HAPS was statistically significant for predicting mild disease (p=0.008) and has demonstrated a specificity of 81%, a positive predictive value (PPV) of 96%, and an odds ratio of 5.57 (1.51-20.50). The predictability of Ranson's scores was not significant. The measure of agreement (κ) between the two scores was 0.15, indicating a low agreement. CONCLUSION: HAPS is a simple and useful scoring algorithm to predict the non-severe course of AP in ED. HAPS-0 patients did not require early aggressive treatments and advanced radiological screening tools during the early stages of the disease.

Prognosis of Critically ill patients in the ED and value of perfusion index measurement: a cross-sectional study.

OBJECTIVE: Critically ill patients have high mortality and admission rates requiring early recognition and a rapid management. In the present study, we evaluated the prognostic parameters in these patients and the value of perfusion index measurement as a novel tool for accomplishing emergency department (ED) triage. METHODS: Seven hundred seventy patients admitted to the critical care area of the ED in a month composed the study population. Perfusion index and vital signs (blood pressure, pulse rate, body temperature, pulse oximeter, and respiration rate) of the study patients were recorded to the study form. The communication data, admitting time, comorbidities, capillary refilling time, and blood gas analysis findings if obtained were recorded. Outcome of patients at the end of the ED period such as discharge, admission to the hospital, and death were also recorded. Outcome of patients at 15th and 30th days was identified by telephone call follow-up or from hospital records. RESULTS: Two hundred seventy-eight patients (36.1%) were admitted to the hospital, 454 patients (59%) were discharged, 3 patients (0.4%) died in the ED, 25 patients (3.2%) were transferred to another hospital, and 10 patients (1.3%) refused treatment and left the ED. Sixty patients (7.8%), 39 (5.1%) of whom had died in 15 days' period, were dead at the end of 30-day follow-up period. Respiratory rate and pulse oximetry were significant parameters in hospital admission. Systolic blood pressure, diastolic blood pressure, pulse rate, respiratory rate, pulse oximetry, lactate levels in blood gas analysis, and ED length of stay were significant variables in 30-day mortality rate. Patients who were admitted to the hospital had higher rates of fever and diabetes. Patients who had died in the 30-day follow-up period had higher rates of diabetes and malignancy. In logistic regression analysis, the predictors of hospital admission were hypotension, fever, and pulse oximetry, whereas the predictors of 30-day mortality were systolic blood pressure, respiratory rate, pulse oximetry, and presence of malignancy. CONCLUSIONS: Perfusion index as a novel triage instrument was found to be an insignificant tool in predicting hospital admission and mortality of critically ill patients in the ED. However, diabetes and malignancy were found to be independent factors in determining the prognosis of these patients in addition to vital signs and should be considered by ED physicians either in triage field or inside the ED.