Routine use of microbial whole genome sequencing in diagnostic and public health microbiology

A genome-based investigation of the Priestia species isolated from anthrax endemic regions in Kruger National Park

Priestia is a genus that was renamed from the genus Bacillus based on the conserved signature indels (CSIs) in protein sequences that separate Priestia species from Bacillus, with the latter only including species closely related to B. subtilis and B. cereus. Diagnosis of anthrax, a zoonotic disease, is implicated by tripartite anthrax virulence genes (lef, pagA, and cya) and poly-γ-D-glutamic acid capsular genes cap-ABCDE of Bacillus anthracis. Due to the amplification of anthrax virulence genes in Priestia isolates, the search for homologous anthrax virulence genes within the Priestia genomes (n = 9) isolated from animal blood smears was embarked upon through whole genome sequencing. In silico taxonomic identification of the isolates was conducted using genome taxonomy database (GTDB), average nucleotide identity (ANI), and multi-locus sequence typing (MLST), which identified the genomes as P. aryabhattai (n = 5), P. endophytica (n = 2) and P. megaterium (n = 2). A pan-genome analysis was further conducted on the Priestia genomes, including the screening of virulence, antibiotic resistance genes and mobile genetic elements on the sequenced genomes. The oligoribonuclease NrnB protein sequences showed that Priestia spp. possess a unique CSI that is absent in other Bacillus species. Furthermore, the CSI in P. endophytica is unique from other Priestia spp. Pan-genomic analysis indicates that P. endophytica clusters separately from P. aryabhattai and P. megaterium. In silico BLASTn genome analysis using the SYBR primers, Taqman probes and primers that target the chromosomal marker (Ba-1), protective antigen (pagA), and lethal factor (lef) on B. anthracis, showed partial binding to Priestia regions encoding for hypothetical proteins, pyridoxine biosynthesis, hydrolase, and inhibitory proteins. The antibiotic resistance genes (ARG) profile of Priestia spp. showed that the genomes contained no more than two ARGs. This included genes conferring resistance to rifamycin and fosfomycin on P. endophytica, as well as clindamycin on P. aryabhattai and P. megaterium. Priestia genomes lacked B. anthracis plasmids and consisted of plasmid replicon types with unknown functions. Furthermore, the amplification of Priestia strains may result in false positives when qPCR is used to detect the virulence genes of B. anthracis in soil, blood smears, and/or environmental samples.

From Species to Genes: A New Diagnostic Paradigm

Molecular diagnostics has the potential to revolutionise the field of clinical microbiology. Microbial identification and nomenclature have, for too long, been restricted to phenotypic characterisation. However, this species-level view fails to wholly account for genetic heterogeneity, a result of lateral gene transfer, mediated primarily by mobile genetic elements. This genetic promiscuity has helped to drive virulence development, stress adaptation, and antimicrobial resistance in several important bacterial pathogens, complicating their detection and frustrating our ability to control them. We argue that, as clinical microbiologists at the front line, we must embrace the molecular technologies that allow us to focus specifically on the genetic elements that cause disease rather than the bacterial species that express them. This review focuses on the evolution of microbial taxonomy since the introduction of molecular sequencing, the role of mobile genetic elements in antimicrobial resistance, the current and emerging assays in clinical laboratories, and the comparison of phenotypic versus genotypic analyses. In essence, it is time now to refocus from species to genes as part of a new diagnostic paradigm.

Development of an automated amplicon-based next-generation sequencing pipeline for rapid detection of bacteria and fungi directly from clinical specimens

The timely identification of microbial pathogens is essential to guide targeted antimicrobial therapy and ultimately, successful treatment of an infection. However, the yield of standard microbiology testing (SMT) is directly related to the duration of antecedent antimicrobial therapy as SMT culture methods are dependent on the recovery of viable organisms, the fastidious nature of certain pathogens, and other pre-analytic factors. In the last decade, metagenomic next-generation sequencing (mNGS) has been successfully utilized as a diagnostic tool for various applications within the clinical laboratory. However, mNGS is resource, time, and labor-intensive-requiring extensive laborious preliminary benchwork, followed by complex bioinformatic analysis. We aimed to address these shortcomings by developing a largely Automated targeted Metagenomic next-generation sequencing (tmNGS) PipeLine for rapId inFectIous disEase Diagnosis (AMPLIFIED) to detect bacteria and fungi directly from clinical specimens. Therefore, AMPLIFIED may serve as an adjunctive approach to complement SMT. This tmNGS pipeline requires less than 1 hour of hands-on time before sequencing and less than 2 hours of total processing time, including bioinformatic analysis. We performed tmNGS on 50 clinical specimens with concomitant cultures to assess feasibility and performance in the hospital laboratory. Of the 50 specimens, 34 (68%) were from true clinical infections. Specimens from cases of true infection were more often tmNGS positive compared to those from the non-infected group (82.4% vs 43.8%, respectively, P = 0.0087). Overall, the clinical sensitivity of AMPLIFIED was 54.6% with 85.7% specificity, equating to 70.6% and 75% negative and positive predictive values, respectively. AMPLIFIED represents a rapid supplementary approach to SMT; the typical time from specimen receipt to identification of potential pathogens by AMPLIFIED is roughly 24 hours which is markedly faster than the days, weeks, and months required to recover bacterial, fungal, and mycobacterial pathogens by culture, respectively.

IMPORTANCE

To our knowledge, this represents the first application of an automated sequencing and bioinformatics pipeline in an exclusively pediatric population. Next-generation sequencing is time-consuming, labor-intensive, and requires experienced personnel; perhaps contributing to hesitancy among clinical laboratories to adopt such a test. Here, we report a strong case for use by removing these barriers through near-total automation of our sequencing pipeline.

TYG Index as a Novel Predictor of Clinical Outcomes in Advanced Chronic Heart Failure with Renal Dysfunction Patients

Background

The triglyceride-glucose (TYG) index is a novel and reliable marker reflecting insulin resistance. Its predictive ability for cardiovascular disease onset and prognosis has been confirmed. However, for advanced chronic heart failure (acHF) patients, the prognostic value of TYG is challenged due to the often accompanying renal dysfunction (RD). Therefore, this study focuses on patients with aHF accompanied by RD to investigate the predictive value of the TYG index for their prognosis.

Methods and Results

717 acHF with RD patients were included. The acHF diagnosis was based on the 2021 ESC criteria for acHF. RD was defined as the eGFR < 90 mL/(min/1.73 m2). Patients were divided into two groups based on their TYG index values. The primary endpoint was major adverse cardiovascular events (MACEs), and the secondary endpoints is all-cause mortality (ACM). The follow-up duration was 21.58 (17.98-25.39) months. The optimal cutoff values for predicting MACEs and ACM were determined using ROC curves. Hazard factors for MACEs and ACM were revealed through univariate and multivariate COX regression analyses. According to the univariate COX regression analysis, high TyG index was identified as a risk factor for MACEs (hazard ratio = 5.198; 95% confidence interval [CI], 3.702-7.298; P < 0.001) and ACM (hazard ratio = 4.461; 95% CI, 2.962-6.718; P < 0.001). The multivariate COX regression analysis showed that patients in the high TyG group experienced 440.2% MACEs risk increase (95% CI, 3.771-7.739; P < 0.001) and 406.2% ACM risk increase (95% CI, 3.268-7.839; P < 0.001). Kaplan-Meier survival analysis revealed that patients with high TyG index levels had an elevated risk of experiencing MACEs and ACM within 30 months.

Conclusion

This study found that patients with high TYG index had an increased risk of MACEs and ACM, and the TYG index can serve as an independent predictor for prognosis.

Hybrid Illumina-Nanopore assembly improves identification of multilocus sequence types and antimicrobial resistance genes of Staphylococcus aureus isolated from Vermont dairy farms: comparison to Illumina-only and R9.4.1 nanopore-only assemblies

Antimicrobial resistance (AMR) in Staphylococcus aureus is a pressing public health challenge with significant implications for the dairy industry, encompassing bovine mastitis concerns and potential zoonotic threats. To delve deeper into the resistance mechanisms of S. aureus, this study employed a hybrid whole genome assembly approach that synergized the precision of Illumina with the continuity of Oxford Nanopore. A total of 62 isolates, collected from multiple sources from Vermont dairy farms, were sequenced using the GridION Oxford Nanopore R9.4.1 platform and the Illumina platform, and subsequently processed through our long-read first bioinformatics pipeline. Our analyses showcased the hybrid-assembled genome's superior completeness compared to Oxford Nanopore (R9.4.1)-only or Illumina-only assembled genomes. Furthermore, the hybrid assembly accurately determined multilocus sequence typing (MLST) strain types across all isolates. The comprehensive probe for antibiotic resistance genes (ARGs) using databases like CARD, Resfinder, and MEGARES 2.0 characterized AMR in S. aureus isolates from Vermont dairy farms, and revealed the presence of notable resistance genes, including beta-lactam genes blaZ, blaI, and blaR. In conclusion, the hybrid assembly approach emerged as a tool for uncovering the genomic nuances of S. aureus isolates collected from multiple sources on dairy farms. Our findings offer a pathway for detecting AMR gene prevalence and shaping AMR management strategies crucial for safeguarding human and animal health.

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.

Active surveillance of carbapenemase-producing Enterobacterales using genomic sequencing for hospital-based infection control interventions

BACKGROUND

Whole-genome sequencing (WGS) is increasingly used to characterize hospital outbreaks of carbapenemase-producing Enterobacterales (CPE). However, access to WGS is variable and testing is often centralized, leading to delays in reporting of results.

OBJECTIVE

We describe the utility of a local sequencing service to promptly respond to facility needs over an 8-year period.

METHODS

The study was conducted at Royal Prince Alfred Hospital in Sydney, Australia. All CPE isolated from patient (screening and clinical) and environmental samples from 2015 onward underwent prospective WGS. Results were notified to the infection control unit in real time. When outbreaks were identified, WGS reports were also provided to senior clinicians and the hospital executive administration. Enhanced infection control interventions were refined based on the genomic data.

RESULTS

In total, 141 CPE isolates were detected from 123 patients and 5 environmental samples. We identified 9 outbreaks, 4 of which occurred in high-risk wards (intensive care unit and/or solid-organ transplant ward). The largest outbreak involved Enterobacterales containing an NDM gene. WGS detected unexpected links among patients, which led to further investigation of epidemiological data that uncovered the outpatient setting and contaminated equipment as reservoirs for ongoing transmission. Targeted interventions as part of outbreak management halted further transmission.

CONCLUSIONS

WGS has transitioned from an emerging technology to an integral part of local CPE control strategies. Our results show the value of embedding this technology in routine surveillance, with timely reports generated in clinically relevant timeframes to inform and optimize local control measures for greatest impact.

Rapid Drug Susceptibility Testing to Preserve Antibiotics

Antibiotic resistance is a global challenge likely to cost trillions of dollars in excess costs in the health system and more importantly, millions of lives every year. A major driver of resistance is the absence of susceptibility testing at the time a healthcare worker needs to prescribe an antimicrobial. The effect is that many prescriptions are unintentionally wasted and expose mutable organisms to antibiotics increasing the risk of resistance emerging. Often simplistic solutions are applied to this growing issue, such as a naïve drive to increase the speed of drug susceptibility testing. This puts a spotlight on a technological solution and there is a multiplicity of such candidate DST tests in development. Yet, if we do not define the necessary information and the speed at which it needs to be available in the clinical decision-making progress as well as the necessary integration into clinical pathways, then little progress will be made. In this chapter, we place the technological challenge in a clinical and systems context. Further, we will review the landscape of some promising technologies that are emerging and attempt to place them in the clinic where they will have to succeed.

Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review

Whole-genome sequencing (WGS) has resulted in improvements to pathogen characterisation for the rapid investigation and management of disease outbreaks and surveillance. We conducted a systematic review to synthesise the economic evidence of WGS implementation for pathogen identification and surveillance. Of the 2285 unique publications identified through online database searches, 19 studies met the inclusion criteria. The economic evidence to support the broader application of WGS as a front-line pathogen characterisation and surveillance tool is insufficient and of low quality. WGS has been evaluated in various clinical settings, but these evaluations are predominantly investigations of a single pathogen. There are also considerable variations in the evaluation approach. Economic evaluations of costs, effectiveness, and cost-effectiveness are needed to support the implementation of WGS in public health settings.

A hybridization target enrichment approach for pathogen genomics

IMPORTANCE

Emerging infectious diseases require continuous pathogen monitoring. Rapid clinical diagnosis by nucleic acid amplification is limited to a small number of targets and may miss target detection due to new mutations in clinical isolates. Whole-genome sequencing (WGS) identifies genome-wide variations that may be used to determine a pathogen's drug resistance patterns and phylogenetically characterize isolates to track disease origin and transmission. WGS is typically performed using DNA isolated from cultured clinical isolates. Culturing clinical specimens increases turn-around time and may not be possible for fastidious bacteria. To overcome some of these limitations, direct sequencing of clinical specimens has been attempted using expensive capture probes to enrich the entire genomes of target pathogens. We present a method to produce a cost-effective, time-efficient, and large-scale synthesis of probes for whole-genome enrichment. We envision that our method can be used for direct clinical sequencing of a wide range of microbial pathogens for genomic epidemiology.

An Overview of Antimicrobial Resistance Profiles of Publicly Available Salmonella Genomes with Sufficient Quality and Metadata

Salmonella enterica (S. enterica) is a commensal organism or pathogen causing diseases in animals and humans, as well as widespread in the environment. Antimicrobial resistance (AMR) has increasingly affected both animal and human health and continues to raise public health concerns. A decade ago, it was estimated that the increased use of whole genome sequencing (WGS) combined with sharing of public data would drastically change and improve the surveillance and understanding of Salmonella epidemiology and AMR. This study aimed to evaluate the current usefulness of public WGS data for Salmonella surveillance and to investigate the associations between serovars, antibiotic resistance genes (ARGs), and metadata. Out of 191,306 Salmonella genomes deposited in European Nucleotide Archive and NCBI databases, 47,452 WGS with sufficient minimum metadata (country, year, and source) of S. enterica were retrieved from 116 countries and isolated between 1905 and 2020. For in silico analysis of the WGS data, KmerFinder, SISTR, and ResFinder were used for species, serovars, and AMR identification, respectively. The results showed that the five common isolation sources of S. enterica are human (29.10%), avian (22.50%), environment (11.89%), water (9.33%), and swine (6.62%). The most common ARG profiles for each class of antimicrobials are β-lactam (blaTEM-1B; 6.78%), fluoroquinolone [(parC[T57S], qnrB19); 0.87%], folate pathway antagonist (sul2; 8.35%), macrolide [mph(A); 0.39%], phenicol (floR; 5.94%), polymyxin B (mcr-1.1; 0.09%), and tetracycline [tet(A); 12.95%]. Our study reports the first overview of ARG profiles in publicly available Salmonella genomes from online databases. All data sets from this study can be searched at Microreact.

A Phylogeographic Description of Histoplasma capsulatum in the United States

Histoplasmosis is one of the most under-diagnosed and under-reported endemic mycoses in the United States. Histoplasma capsulatum is the causative agent of this disease. To date, molecular epidemiologic studies detailing the phylogeographic structure of H. capsulatum in the United States have been limited. We conducted genomic sequencing using isolates from histoplasmosis cases reported in the United States. We identified North American Clade 2 (NAm2) as the most prevalent clade in the country. Despite high intra-clade diversity, isolates from Minnesota and Michigan cases were predominately clustered by state. Future work incorporating environmental sampling and veterinary surveillance may further elucidate the molecular epidemiology of H. capsulatum in the United States and how genomic sequencing can be applied to the surveillance and outbreak investigation of histoplasmosis.

Results of the 2020 Genomic Proficiency Test for the network of European Union Reference Laboratory for Antimicrobial Resistance assessing whole-genome-sequencing capacities

The global surveillance and outbreak investigation of antimicrobial resistance (AMR) is amidst a paradigm shift from traditional biology to bioinformatics. This is due to developments in whole-genome-sequencing (WGS) technologies, bioinformatics tools, and reduced costs. The increased use of WGS is accompanied by challenges such as standardization, quality control (QC), and data sharing. Thus, there is global need for inter-laboratory WGS proficiency test (PT) schemes to evaluate laboratories' capacity to produce reliable genomic data. Here, we present the results of the first iteration of the Genomic PT (GPT) organized by the Global Capacity Building Group at the Technical University of Denmark in 2020. Participating laboratories sequenced two isolates and corresponding DNA of Salmonella enterica, Escherichia coli and Campylobacter coli, using WGS methodologies routinely employed at their laboratories. The participants' ability to obtain consistently good-quality WGS data was assessed based on several QC WGS metrics. A total of 21 laboratories from 21 European countries submitted WGS and meta-data. Most delivered high-quality sequence data with only two laboratories identified as overall underperforming. The QC metrics, N50 and number of contigs, were identified as good indicators for high-sequencing quality. We propose QC thresholds for N50 greater than 20 000 and 25 000 for Campylobacter coli and Escherichia coli, respectively, and number of contigs >200 bp greater than 225, 265 and 100 for Salmonella enterica, Escherichia coli and Campylobacter coli, respectively. The GPT2020 results confirm the importance of systematic QC procedures, ensuring the submission of reliable WGS data for surveillance and outbreak investigation to meet the requirements of the paradigm shift in methodology.

Accelerating bioinformatics implementation in public health

We have adopted an open bioinformatics ecosystem to address the challenges of bioinformatics implementation in public health laboratories (PHLs). Bioinformatics implementation for public health requires practitioners to undertake standardized bioinformatic analyses and generate reproducible, validated and auditable results. It is essential that data storage and analysis are scalable, portable and secure, and that implementation of bioinformatics fits within the operational constraints of the laboratory. We address these requirements using Terra, a web-based data analysis platform with a graphical user interface connecting users to bioinformatics analyses without the use of code. We have developed bioinformatics workflows for use with Terra that specifically meet the needs of public health practitioners. These Theiagen workflows perform genome assembly, quality control, and characterization, as well as construction of phylogeny for insights into genomic epidemiology. Additonally, these workflows use open-source containerized software and the WDL workflow language to ensure standardization and interoperability with other bioinformatics solutions, whilst being adaptable by the user. They are all open source and publicly available in Dockstore with the version-controlled code available in public GitHub repositories. They have been written to generate outputs in standardized file formats to allow for further downstream analysis and visualization with separate genomic epidemiology software. Testament to this solution meeting the requirements for bioinformatic implementation in public health, Theiagen workflows have collectively been used for over 5 million sample analyses in the last 2 years by over 90 public health laboratories in at least 40 different countries. Continued adoption of technological innovations and development of further workflows will ensure that this ecosystem continues to benefit PHLs.

Whole-genome sequencing of multidrug resistance Salmonella Typhi clinical strains isolated from Balochistan, Pakistan

Introduction

Salmonella enterica serovar Typhi (S. Typhi) is a major cause of morbidity and mortality in developing countries, contributing significantly to the global disease burden.

Methods

In this study, S. Typhi strains were isolated from 100 patients exhibiting symptoms of typhoid fever at a tertiary care hospital in Pakistan. Antimicrobial testing of all isolates was performed to determine the sensitivity and resistance pattern. Three MDR strains, namely QS194, QS430, and QS468, were subjected to whole genome sequencing for genomic characterization.

Results and Discussion

MLST analysis showed that QS194, belonged to ST19, which is commonly associated with Salmonella enterica serovar typhimurium. In contrast, QS430 and QS468, belonged to ST1, a sequence type frequently associated with S. Typhi. PlasmidFinder identified the presence of IncFIB(S) and IncFII(S) plasmids in QS194, while IncQ1 was found in QS468. No plasmid was detected in QS430. CARD-based analysis showed that the strains were largely resistant to a variety of antibiotics and disinfecting agents/antiseptics, including fluoroquinolones, cephalosporins, monobactams, cephamycins, penams, phenicols, tetracyclines, rifamycins, aminoglycosides, etc. The S. Typhi strains possessed various virulence factors, such as Vi antigen, Agf/Csg, Bcf, Fim, Pef, etc. The sequencing data indicated that the strains had antibiotic resistance determinants and shared common virulence factors. Pangenome analysis of the selected S. Typhi strains identified 13,237 genes, with 3,611 being core genes, 2,093 shell genes, and 7,533 cloud genes. Genome-based typing and horizontal gene transfer analysis revealed that the strains had different evolutionary origins and may have adapted to distinct environments or host organisms. These findings provide important insights into the genetic characteristics of S. Typhi strains and their potential association with various ecological niches and host organisms.

A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis

Background

Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen guided by drug susceptibility test (DST) results. In most settings, DST information is not available or is limited to isoniazid and fluoroquinolones. Whole genome sequencing could more accurately guide individualized treatment as the full drug resistance profile is obtained with a single test. Whole genome sequencing has not reached its full potential for patient care, in part due to the complexity of translating a resistance profile into the most effective individualized regimen.

Methods

We developed a treatment recommender clinical decision support system (CDSS) and an accompanying web application for user-friendly recommendation of the optimal individualized treatment regimen to a clinician.

Results

Following expert stakeholder meetings and literature review, nine drug features and 14 treatment regimen features were identified and quantified. Using machine learning, a model was developed to predict the optimal treatment regimen based on a training set of 3895 treatment regimen-expert feedback pairs. The acceptability of the treatment recommender CDSS was assessed as part of a clinical trial and in a routine care setting. Within the clinical trial setting, all patients received the CDSS recommended treatment. In 8 of 20 cases, the initial recommendation was recomputed because of stock out, clinical contra-indication or toxicity. In routine care setting, physicians rejected the treatment recommendation in 7 out of 15 cases because it deviated from the national TB treatment guidelines. A survey indicated that the treatment recommender CDSS is easy to use and useful in clinical practice but requires digital infrastructure support and training.

Conclusions

Our findings suggest that global implementation of the novel treatment recommender CDSS holds the potential to improve treatment outcomes of rifampicin resistant tuberculosis.

What Whole Genome Sequencing Has Told Us About Pathogenic Vibrios

When the first microbial genome sequences were published just 20 years ago, our understanding regarding the microbial world changed dramatically. The genomes of the first pathogenic vibrios sequenced, including Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio vulnificus revealed a functional and phylogenetic diversity previously unimagined as well as a genome structure indelibly shaped by horizontal gene transfer. The initial glimpses into these organisms also revealed a genomic plasticity that allowed these bacteria to thrive in challenging and varied aquatic and marine environments, but critically also a suite of pathogenicity attributes. In this review we outline how our understanding of vibrios has changed over the last two decades with the advent of genomics and advances in bioinformatic and data analysis techniques, it has become possible to provide a more cohesive understanding regarding these bacteria: how these pathogens have evolved and emerged from environmental sources, their evolutionary routes through time and space, how they interact with other bacteria and the human host, as well as initiate disease. We outline novel approaches to the use of whole genome sequencing for this important group of bacteria and how new sequencing technologies may be applied to study these organisms in future studies.

Epidemiological Investigation of Hospital Transmission of Corynebacterium striatum Infection by Core Genome Multilocus Sequence Typing Approach

Corynebacterium striatum has recently received increasing attention due to its multiple antimicrobial resistances and its role as an invasive infection/outbreak agent. Recently, whole-genome sequencing (WGS)-based core genome multilocus sequence typing (cgMLST) has been used in epidemiological studies of specific human pathogens. However, this method has not been reported in studies of C. striatum. In this work, we aim to propose a cgMLST scheme for C. striatum. All publicly available C. striatum genomes, 30 C. striatum strains isolated from the same hospital, and 1 epidemiologically unrelated outgroup C. striatum strain were used to establish a cgMLST scheme targeting 1,795 genes (hereinafter referred to as 1,795-cgMLST). The genotyping results of cgMLST showed good congruence with core genome-based single-nucleotide polymorphism typing in terms of tree topology. In addition, the cgMLST provided a greater discrimination than the MLST method based on 6 housekeeping genes (gyrA, gyrB, hsp65, rpoB, secA1, and sodA). We established a clonal group (CG) threshold based on 104 allelic differences; a total of 56 CGs were identified from among 263 C. striatum strains. We also defined an outbreak threshold based on seven allelic differences that is capable of identifying closely related isolates that could give clues on hospital transmission. According to the results of analysis of drug-resistant genes and virulence genes, we identified CG4, CG5, CG26, CG28, and CG55 as potentially hypervirulent and multidrug-resistant CGs of C. striatum. This study provides valuable genomic epidemiological data on the diversity, resistance, and virulence profiles of this potentially pathogenic microorganism. IMPORTANCE Recently, WGS of many human and animal pathogens has been successfully used to investigate microbial outbreaks. The cgMLST schema are powerful genotyping tools that can be used to investigate potential epidemics and provide classification of the strains precise and reliable. In this study, we proposed the development of a cgMLST typing scheme for C. striatum, and then we evaluated this scheme for its applicability to hospital transmission investigations. This report describes the first cgMLST schema for C. striatum. The analysis of hospital transmission of C. striatum based on cgMLST methods has important clinical epidemiological significance for improving nosocomial infection monitoring of C. striatum and in-depth understanding of its nosocomial transmission routes.

Application of metagenomic next-generation sequencing in the detection of pathogens in spinal infections

BACKGROUND CONTEXT

The precise diagnosis and treatment of spinal infections (SI) remains challenging for spine surgeons. Identifying the pathogens of SI through metagenomic next-generation sequencing (mNGS) may be a key approach to addressing this challenge.

PURPOSE

To evaluate the accuracy and applicability of mNGS in determining the etiology of SI.

STUDY DESIGN

Diagnostic test study.

PATIENT SAMPLE

Twenty-five patients who had a clinical suspicion of SI and underwent mNGS testing.

OUTCOME MEASURES

The specificity, sensitivity, and time cost of mNGS and bacterial culture were compared. Clinical outcomes were assessed using the numeric rating scale (NRS) score, Oswestry Disability Index (ODI), and the Japanese Orthopedic Association (JOA) score. Demographic data and laboratory results (blood cell count (WBC), erythrocyte sedimentation rate (ESR), neutrophil percentage (NEUT%), and C-reactive protein level (CRP) were also evaluated.

METHODS

In this retrospective study, samples were obtained from 25 eligible patients via surgery or CT-guided puncture and subjected to histopathological examination, bacterial culture, and mNGS. The sensitivity and specificity of the bacterial cultures and mNGS were calculated with respect to the histopathological results as a reference. Postoperative antibiotics or antituberculosis drugs were administered on the basis of mNGS results, combined with clinical manifestations, imaging examination, and histopathology. The changes of clinical outcomes and laboratory results after treatment were observed.

RESULTS

Of the 25 patients, 21 had a positive pathology, of which 10 showed a tuberculous pathology, and the remaining 11 showed a nontuberculous inflammatory pathology. The sensitivity of mNGS was higher than that of the bacterial culture. However, the difference in specificity between bacterial culture and mNGS was not significant. Moreover, the time needed to perform mNGS was significantly lower than that of bacterial culture and pathology. All patients were followed up for more than three months, and CRP and NEUT% significantly decreased by three months after treatment. There was no significant difference in WBC and ESR. The ODI, NRS and JOA scores were significantly improved after treatment.

CONCLUSION

Metagenomic next-generation sequencing technology can play an important role in the detection of pathogens in SI and should be further investigated and applied in future studies.

Highly sensitive quantitative phase microscopy and deep learning aided with whole genome sequencing for rapid detection of infection and antimicrobial resistance

Current state-of-the-art infection and antimicrobial resistance (AMR) diagnostics are based on culture-based methods with a detection time of 48-96 h. Therefore, it is essential to develop novel methods that can do real-time diagnoses. Here, we demonstrate that the complimentary use of label-free optical assay with whole-genome sequencing (WGS) can enable rapid diagnosis of infection and AMR. Our assay is based on microscopy methods exploiting label-free, highly sensitive quantitative phase microscopy (QPM) followed by deep convolutional neural networks-based classification. The workflow was benchmarked on 21 clinical isolates from four WHO priority pathogens that were antibiotic susceptibility tested, and their AMR profile was determined by WGS. The proposed optical assay was in good agreement with the WGS characterization. Accurate classification based on the gram staining (100% recall for gram-negative and 83.4% for gram-positive), species (98.6%), and resistant/susceptible type (96.4%), as well as at the individual strain level (100% sensitivity in predicting 19 out of the 21 strains, with an overall accuracy of 95.45%). The results from this initial proof-of-concept study demonstrate the potential of the QPM assay as a rapid and first-stage tool for species, strain-level classification, and the presence or absence of AMR, which WGS can follow up for confirmation. Overall, a combined workflow with QPM and WGS complemented with deep learning data analyses could, in the future, be transformative for detecting and identifying pathogens and characterization of the AMR profile and antibiotic susceptibility.

Phylogenetic Analysis of Bacterial Pathogen Genomes

The development of high-throughput sequencing technology has led to a significant reduction in the time and cost of sequencing whole genomes of bacterial pathogens. Studies can sequence and compare hundreds or even thousands of genomes within a given bacterial population. A phylogenetic tree is the most frequently used method of depicting the relationships between these bacterial pathogen genomes. However, the presence of homologous recombination in most bacterial pathogen species can invalidate the application of standard phylogenetic tools. Here we describe a method to produce phylogenetic analyses that accounts for the disruptive effect of recombination. This allows users to investigate the recombination events that have occurred, as well as to produce more meaningful phylogenetic analyses which recover the clonal genealogy representing the clonal relationships between genomes.

Genomic insight into Campylobacter jejuni isolated from commercial turkey flocks in Germany using whole-genome sequencing analysis

Campylobacter (C.) jejuni is a zoonotic bacterium of public health significance. The present investigation was designed to assess the epidemiology and genetic heterogeneity of C. jejuni recovered from commercial turkey farms in Germany using whole-genome sequencing. The Illumina MiSeq^® technology was used to sequence 66 C. jejuni isolates obtained between 2010 and 2011 from commercial meat turkey flocks located in ten German federal states. Phenotypic antimicrobial resistance was determined. Phylogeny, resistome, plasmidome and virulome profiles were analyzed using whole-genome sequencing data. Genetic resistance markers were identified with bioinformatics tools (AMRFinder, ResFinder, NCBI and ABRicate) and compared with the phenotypic antimicrobial resistance. The isolates were assigned to 28 different sequence types and 11 clonal complexes. The average pairwise single nucleotide-polymorphisms distance of 14,585 SNPs (range: 0-26,540 SNPs) revealed a high genetic distinction between the isolates. Thirteen virulence-associated genes were identified in C. jejuni isolates. Most of the isolates harbored the genes flaA (83.3%) and flaB (78.8%). The wlaN gene associated with the Guillain-Barré syndrome was detected in nine (13.6%) isolates. The genes for resistance to ampicillin (bla _OXA), tetracycline [tet(O)], neomycin [aph(3')-IIIa], streptomycin (aadE) and streptothricin (sat4) were detected in isolated C. jejuni using WGS. A gene cluster comprising the genes sat4, aph(3')-IIIa and aadE was present in six isolates. The single point mutation T86I in the housekeeping gene gyrA conferring resistance to quinolones was retrieved in 93.6% of phenotypically fluoroquinolone-resistant isolates. Five phenotypically erythromycin-susceptible isolates carried the mutation A103V in the gene for the ribosomal protein L22 inferring macrolide resistance. An assortment of 13 β-lactam resistance genes (bla _OXA variants) was detected in 58 C. jejuni isolates. Out of 66 sequenced isolates, 28 (42.4%) carried plasmid-borne contigs. Six isolates harbored a pTet-like plasmid-borne contig which carries the tet(O) gene. This study emphasized the potential of whole-genome sequencing to ameliorate the routine surveillance of C. jejuni. Whole-genome sequencing can predict antimicrobial resistance with a high degree of accuracy. However, resistance gene databases need curation and updates to revoke inaccuracy when using WGS-based analysis pipelines for AMR detection.

Investigating the Origin of Mycobacterium chimaera Contamination in Heater-Cooler Units: Integrated Analysis with Fourier Transform Infrared Spectroscopy and Whole-Genome Sequencing

Mycobacterium chimaera is ubiquitously spread in the environment, including factory and hospital water systems. Invasive cases of M. chimaera infection have been associated with aerosols produced by the use of heater-cooler units (HCU) during cardiac surgery. The aim of this study was to evaluate for the first time the performance of IR-Biotyper system on a large number of M. chimaera isolates collected from longitudinal environmental HCUs samples and water sources from hospitals located in three Italian provinces. In addition, IR-Biotyper results were compared with whole-genome sequencing (WGS) analysis, the reference method for molecular epidemiology, to investigate the origin of M. chimaera contamination of HCUs. From November 2018 to May 2021, 417 water samples from 52 HCUs (Stockert 3T, n = 41 and HCU40, n = 11) and 23 hospital taps (used to fill the HCU tanks) were concentrated, decontaminated, and cultured for M. chimaera. Positive cultures (n = 53) were purified by agar plate subcultures and analyzed by IR-Biotyper platform and Ion Torrent sequencing system. IR-Biotyper spectra results were analyzed using a statistical approach of dimensionality reduction by linear discriminant analysis (LDA), generating three separate clusters of M. chimaera, ascribable to each hospital. Furthermore, the only M. chimaera-positive sample from tap water clustered with the isolates from the HCUs of the same hospital, confirming that the plumbing system could represent the source of HCU contamination and, potentially, of patient infection. According to the genome-based phylogenies and following the classification proposed by van Ingen and collaborators in 2017, three distinct M. chimaera groups appear to have contaminated the HCU water systems: subgroups 1.1, 2.1, and branch 2. Most of the strains isolated from HCUs at the same hospital share a highly similar genetic profile. The nonrandom distribution obtained with WGS and IR-Biotyper leads to the hypothesis that M. chimaera subtypes circulating in the local plumbing colonize HCUs through the absolute filter, in addition with the current hypothesis that contamination occurs at the HCU production site. This opens the possibility that other medical equipment, such as endoscope reprocessing device or hemodialysis systems, could be contaminated by M. chimaera. IMPORTANCE Our manuscript focuses on interventions to reduce waterborne disease transmission, improve sanitation, and control infection. Sanitary water can be contaminated by nontuberculous Mycobacteria, including M. chimaera, a causative agent of invasive infections in immunocompromised patients. We found highly similar genetic and phenotypic profiles of M. chimaera isolated from heater-cooler units (HCU) used during surgery to thermo-regulate patients' body temperature, and from the same hospital tap water. These results lead to the hypothesis that M. chimaera subtypes circulating in the local plumbing colonize HCUs through the absolute filter, adding to the current hypothesis that contamination occurs at the HCU production site. In addition, this opens the possibility that other medical equipment using sanitized water, such as endoscope reprocessing devices or hemodialysis systems, could be contaminated by nontuberculous Mycobacteria, suggesting the need for environmental surveillance and associated control measures.

Diagnostic Yield and Impact on Antimicrobial Management of 16S rRNA Testing of Clinical Specimens

16S rRNA gene sequencing is increasingly used in clinical practice for bacterial identification of clinical specimens. However, studies on its applicability to direct clinical specimens are limited. Here, we studied the diagnostic yield and impact of 16S rRNA gene sequencing from direct clinical specimens on antimicrobial management. Adult inpatients whose attending physician requested 16S rRNA gene sequencing and corresponding bacterial culture from a direct clinical specimen between January and December 2021 in a university hospital were prospectively included in this study. A total of 434 specimens from 374 patients were requested. Of these, 253 (58.3%) specimens were collected from patients whose final diagnosis indicated a bacterial infection, whereas 181 (41.7%) specimens were from nonbacterial infections. Using the final diagnosis as a "gold standard," the sensitivity and specificity of 16S rRNA gene sequencing were 38.3% and 93.9%, respectively. Among the bacterial infection cases, the proportion of 16S rRNA gene sequencing-positive and culture-positive cases was 32.4%, and the proportion of sequencing-positive and culture-negative cases was 5.9%. The impact on antimicrobial management was evident in 10 (2.3%) specimens, which all resulted in the continuation of antibiotics. The impact on antimicrobial management was highest in skin and soft tissue infections, followed by bone and joint infections. In this study, the long turnaround time of 16S rRNA gene sequencing of clinical specimens was a limiting factor. In conclusion, the overall diagnostic yield of 16S rRNA gene sequencing in bacterial infection cases was fair, being useful in selected cases. Restrictions on test requests may improve test utilization in this setting. IMPORTANCE 16S rRNA gene sequencing has been increasingly used in clinical practice. Using the final diagnosis as a gold standard, the sensitivity of 16S rRNA gene sequencing was fair. In the setting with no 16S rRNA gene sequencing test ordering restrictions, only small percentages of the test results had an impact on antimicrobial management. Restrictions on test requests should be developed to maximize the benefit of the test.

Genomic insights into zoonotic transmission and antimicrobial resistance in Campylobacter jejuni from farm to fork: a one health perspective

BACKGROUND

Campylobacteriosis represents a global public health threat with various socio-economic impacts. Among different Campylobacter species, Campylobacter jejuni (C. jejuni) is considered to be the foremost Campylobacter species responsible for most of gastrointestinal-related infections. Although these species are reported to primarily inhabit birds, its high genetic and phenotypic diversity allowed their adaptation to other animal reservoirs and to the environment that may impact on human infection.

MAIN BODY

A stringent and consistent surveillance program based on high resolution subtyping is crucial. Recently, different epidemiological investigations have implemented high-throughput sequencing technologies and analytical pipelines for higher resolution subtyping, accurate source attribution, and detection of antimicrobial resistance determinants among these species. In this review, we aim to present a comprehensive overview on the epidemiology, clinical presentation, antibiotic resistance, and transmission dynamics of Campylobacter, with specific focus on C. jejuni. This review also summarizes recent attempts of applying whole-genome sequencing (WGS) coupled with bioinformatic algorithms to identify and provide deeper insights into evolutionary and epidemiological dynamics of C. jejuni precisely along the farm-to-fork continuum.

CONCLUSION

WGS is a valuable addition to traditional surveillance methods for Campylobacter. It enables accurate typing of this pathogen and allows tracking of its transmission sources. It is also advantageous for in silico characterization of antibiotic resistance and virulence determinants, and hence implementation of control measures for containment of infection.

Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases

Next-generation sequencing (NGS) technologies have become increasingly available for use in the clinical microbiology diagnostic environment. There are three main applications of these technologies in the clinical microbiology laboratory: whole genome sequencing (WGS), targeted metagenomics sequencing and shotgun metagenomics sequencing. These applications are being utilized for initial identification of pathogenic organisms, the detection of antimicrobial resistance mechanisms and for epidemiologic tracking of organisms within and outside hospital systems. In this review, we analyze these three applications and provide a comprehensive summary of how these applications are currently being used in public health, basic research, and clinical microbiology laboratory environments. In the public health arena, WGS is being used to identify and epidemiologically track food borne outbreaks and disease surveillance. In clinical hospital systems, WGS is used to identify multi-drug-resistant nosocomial infections and track the transmission of these organisms. In addition, we examine how metagenomics sequencing approaches (targeted and shotgun) are being used to circumvent the traditional and biased microbiology culture methods to identify potential pathogens directly from specimens. We also expand on the important factors to consider when implementing these technologies, and what is possible for these technologies in infectious disease diagnosis in the next 5 years.

Molecular characterization and phylogeny of Shiga toxin-producing Escherichia coli derived from cattle farm

Shiga toxin-producing Escherichia coli (STEC) is an important food-borne pathogen, which can cause diseases such as diarrhea, hemorrhagic enteritis, and hemolytic uremic syndrome in humans. Twelve STEC isolates were collected from beeves and feces of commercial animals in China between 2019 and 2020 for this study. In addition to the determination of serotype and Shiga toxin subtype, whole-genome sequencing (WGS) was used for determining phylogenetic relationships, antimicrobial resistance (AMR), virulence genes, and sequence type (ST) of isolates. A total of 27 AMR genes were detected, and each STEC isolate carried more than 10 AMR genes. Eight STEC isolates from ground beef and four STEC isolated from feces were screened. A total of seven serotypes were identified, and one isolate ONT:H10 was undetermined by SeroTypeFinder. Three O157:H7 strains were confirmed and the remaining five serogroups were confirmed as O26:H11, O81:H31, O105:H8, O178:H19, and O136:H12. The phylogenetic analysis showed that STEC isolates of the same serotype or ST were clustered together based on cgMLST. The comparison of the genomes of 157 STEC reference isolates worldwide with our local STEC isolates showed that STEC isolates screened in China represented various collections and could not form a separate cluster but were interspersed among the STEC reference collection, which suggested that several STEC isolates shared a common ancestor irrespective of STEC serotype isolates. cgMLST revealed that isolates of the same O serotype clustered irrespective of their H type. Further investigation is required to determine the pathogenic potential of other serotypes of STEC, particularly in regard to these rare serotypes.

The role of the microbiology laboratory in the diagnosis of multidrug-resistant Gram-negative bacilli infections. The importance of the determination of resistance mechanisms

Early diagnosis and treatment has an important impact on the morbidity and mortality of infections caused by multidrug-resistant bacteria. Multidrug-resistant gram-negative bacilli (MR-GNB) constitute the main current threat in hospitals and especially in intensive care units (ICU). The role of the microbiology laboratory is essential in providing a rapid and effective response. This review updates the microbiology laboratory procedures for the rapid detection of BGN-MR and its resistance determinants. The role of the laboratory in the surveillance and control of outbreaks caused by these bacteria, including typing techniques, is also studied. The importance of providing standardized resistance maps that allow knowing the epidemiological situation of the different units is emphasized. Finally, the importance of effective communication systems for the transmission of results and decision making in the management of patients infected by BGN-MR is reviewed.

A Review of Next Generation Sequencing Methods and its Applications in Laboratory Diagnosis

Next-generation sequencing (NGS) is a new technology used to detect the sequence of DNA and RNA and to detect mutations or variations of significance. NGS generates large quantities of sequence data within a short time duration. The various types of sequencing includes Sanger Sequencing, Pyrosequencing, Sequencing by Synthesis (Illumina), Ligation (SoLID), Single molecule Fluorescent Sequencing (Helicos), Single molecule Real time Sequencing (Pacbio), Semiconductor sequencing (Ion torrent technology), Nanopore sequencing and fourth generation sequencing. These methods of sequencing have been modified and improved over the years such that it has become cost effective and accessible to diagnostic laboratories. Management of Outbreaks, rapid identification of bacteria, molecular case finding, taxonomy, detection of the zoonotic agents and guiding prevention strategies in HIV outbreaks are just a few of the many applications of Next Generation sequencing in clinical microbiology.

Exploiting genomics to mitigate the public health impact of antimicrobial resistance

Antimicrobial resistance (AMR) is a major global public health threat, which has been largely driven by the excessive use of antimicrobials. Control measures are urgently needed to slow the trajectory of AMR but are hampered by an incomplete understanding of the interplay between pathogens, AMR encoding genes, and mobile genetic elements at a microbial level. These factors, combined with the human, animal, and environmental interactions that underlie AMR dissemination at a population level, make for a highly complex landscape. Whole-genome sequencing (WGS) and, more recently, metagenomic analyses have greatly enhanced our understanding of these processes, and these approaches are informing mitigation strategies for how we better understand and control AMR. This review explores how WGS techniques have advanced global, national, and local AMR surveillance, and how this improved understanding is being applied to inform solutions, such as novel diagnostic methods that allow antimicrobial use to be optimised and vaccination strategies for better controlling AMR. We highlight some future opportunities for AMR control informed by genomic sequencing, along with the remaining challenges that must be overcome to fully realise the potential of WGS approaches for international AMR control.

A high-throughput multiplexing and selection strategy to complete bacterial genomes

BACKGROUND

Bacterial whole-genome sequencing based on short-read technologies often results in a draft assembly formed by contiguous sequences. The introduction of long-read sequencing technologies permits those contiguous sequences to be unambiguously bridged into complete genomes. However, the elevated costs associated with long-read sequencing frequently limit the number of bacterial isolates that can be long-read sequenced. Here we evaluated the recently released 96 barcoding kit from Oxford Nanopore Technologies (ONT) to generate complete genomes on a high-throughput basis. In addition, we propose an isolate selection strategy that optimizes a representative selection of isolates for long-read sequencing considering as input large-scale bacterial collections.

RESULTS

Despite an uneven distribution of long reads per barcode, near-complete chromosomal sequences (assembly contiguity = 0.89) were generated for 96 Escherichia coli isolates with associated short-read sequencing data. The assembly contiguity of the plasmid replicons was even higher (0.98), which indicated the suitability of the multiplexing strategy for studies focused on resolving plasmid sequences. We benchmarked hybrid and ONT-only assemblies and showed that the combination of ONT sequencing data with short-read sequencing data is still highly desirable (i) to perform an unbiased selection of isolates for long-read sequencing, (ii) to achieve an optimal genome accuracy and completeness, and (iii) to include small plasmids underrepresented in the ONT library.

CONCLUSIONS

The proposed long-read isolate selection ensures the completion of bacterial genomes that span the genome diversity inherent in large collections of bacterial isolates. We show the potential of using this multiplexing approach to close bacterial genomes on a high-throughput basis.

Genomic Analysis of Multidrug-Resistant Mycobacterium tuberculosis Strains From Patients in Kazakhstan

Tuberculosis (TB) is an infectious disease that remains an essential public health problem in many countries. Despite decreasing numbers of new cases worldwide, the incidence of antibiotic-resistant forms (multidrug resistant and extensively drug-resistant) of TB is increasing. Next-generation sequencing technologies provide a high-throughput approach to identify known and novel potential genetic variants that are associated with drug resistance in Mycobacterium tuberculosis (Mtb). There are limited reports and data related to whole-genome characteristics of drug-resistant Mtb strains circulating in Kazakhstan. Here, we report whole-genome sequencing and analysis results of eight multidrug-resistant strains collected from TB patients in Kazakhstan. Genotyping and validation of all strains by MIRU-VNTR and spoligotyping methodologies revealed that these strains belong to the Beijing family. The spectrum of specific and potentially novel genomic variants (single-nucleotide polymorphisms, insertions, and deletions) related to drug resistance was identified and annotated. ResFinder, CARD, and CASTB antibiotic resistance databases were used for the characterization of genetic variants in genes associated with drug resistance. Our results provide reference data and genomic profiles of multidrug-resistant isolates for further comparative studies and investigations of genetic patterns in drug-resistant Mtb strains.

Paradox of complex diversity: Challenges in the diagnosis and management of bacterial keratitis

Bacterial keratitis continues to be one of the leading causes of corneal blindness in the developed as well as the developing world, despite swift progress since the dawn of the "anti-biotic era". Although, we are expeditiously developing our understanding about the different causative organisms and associated pathology leading to keratitis, extensive gaps in knowledge continue to dampen the efforts for early and accurate diagnosis, and management in these patients, resulting in poor clinical outcomes. The ability of the causative bacteria to subdue the therapeutic challenge stems from their large genome encoding complex regulatory networks, variety of unique virulence factors, and rapid secretion of tissue damaging proteases and toxins. In this review article, we have provided an overview of the established classical diagnostic techniques and therapeutics for keratitis caused by various bacteria. We have extensively reported our recent in-roads through novel tools for accurate diagnosis of mono- and poly-bacterial corneal infections. Furthermore, we outlined the recent progress by our group and others in understanding the sub-cellular genomic changes that lead to antibiotic resistance in these organisms. Finally, we discussed in detail, the novel therapies and drug delivery systems in development for the efficacious management of bacterial keratitis.

Panproteome Analysis of the Human Antibody Response to Bacterial Vaccines and Challenge

High-density protein microarray is an established technology for characterizing host antibody profiles against entire pathogen proteomes. As one of the highest throughput technologies for antigen discovery, proteome microarrays are a translational research tool for identification of vaccine candidates and biomarkers of susceptibility or protection from microbial challenge. The application has been expanded in recent years due to increased availability of bacterial genomic sequences for a broader range of species and strain diversity. Panproteome microarrays now allow for fine characterization of antibody specificity and cross-reactivity that may be relevant to vaccine design and biomarker discovery, as well as a fuller understanding of factors underlying themes of bacterial evolution and host-pathogen interactions. In this chapter, we present a workflow for design of panproteome microarrays and demonstrate statistical analysis of panproteomic human antibody responses to bacterial vaccination and challenge. Focus is particularly drawn to the bioinformatics and statistical tools and providing nontrivial, real examples that may help foster hypotheses and rational design of panproteomic studies.

Genetic support of carbapenemases: a One Health systematic review and meta-analysis of current trends in Africa

Antimicrobial resistance (AMR) is a public health threat globally. Carbapenems are β-lactam antibiotics used as last-resort agents for treating antibiotic-resistant infections. Mobile genetic elements (MGEs) play an important role in the dissemination and expression of antimicrobial resistance genes (ARGs), including the mobilization of ARGs within and between species. The presence of MGEs around carbapenem-hydrolyzing enzymes, called carbapenemases, in bacterial isolates in Africa is concerning. The association between MGEs and carbapenemases is described herein. Specific plasmid replicons, integrons, transposons, and insertion sequences were found flanking specific and different carbapenemases across the same and different clones and species isolated from humans, animals, and the environment. Notably, similar genetic contexts have been reported in non-African countries, supporting the importance of MGEs in driving the intra- and interclonal and species transmission of carbapenemases in Africa and globally. Technical and budgetary limitations remain challenges for epidemiological analysis of carbapenemases in Africa, as studies undertaken with whole-genome sequencing remained relatively few. Characterization of MGEs in antibiotic-resistant infections can deepen our understanding of carbapenemase epidemiology and facilitate the control of AMR in Africa. Investment in genomic epidemiology will facilitate faster clinical interventions and containment of outbreaks.

Multiple introductions of multidrug-resistant typhoid associated with acute infection and asymptomatic carriage, Kenya

Background:

Understanding the dynamics of infection and carriage of typhoid in endemic settings is critical to finding solutions to prevention and control.

Methods:

In a 3-year case-control study, we investigated typhoid among children aged <16 years (4670 febrile cases and 8549 age matched controls) living in an informal settlement, Nairobi, Kenya.

Results:

148 S. Typhi isolates from cases and 95 from controls (stool culture) were identified; a carriage frequency of 1 %. Whole-genome sequencing showed 97% of cases and 88% of controls were genotype 4.3.1 (Haplotype 58), with the majority of each (76% and 88%) being multidrug-resistant strains in three sublineages of the H58 genotype (East Africa 1 (EA1), EA2, and EA3), with sequences from cases and carriers intermingled.

Conclusions:

The high rate of multidrug-resistant H58 S. Typhi, and the close phylogenetic relationships between cases and controls, provides evidence for the role of carriers as a reservoir for the community spread of typhoid in this setting.

Funding:

National Institutes of Health (R01AI099525); Wellcome Trust (106158/Z/14/Z); European Commission (TyphiNET No 845681); National Institute for Health Research (NIHR); Bill and Melinda Gates Foundation (OPP1175797).

Characterization of antibiotic resistance and virulence genes of ocular methicillin-resistant Staphylococcus aureus strains through complete genome analysis

Virulence-factor encoding genes (VFGs) and antimicrobial resistance genes (ARGs) of ocular Methicillin-Resistant Staphylococcus aureus (MRSA), are the reason behind the common cause of severe and untreatable ocular infection and are largely unknown. The unavailability of the complete genome sequence of ocular MRSA strains hinders the unambiguous determination of ARGs and VRGs role in disease pathogenesis and their genomic location. To fulfill this critical need, we achieved the high-quality complete genome of four ocular MRSA strains (AMRF3 - AMRF6) by combining MinION nanopore sequencing technology, followed by polishing with Illumina sequence reads. We obtained a single chromosome and a plasmid in each strain. Sequence typing revealed that AMRF3 and AMRF5 strains harbored ST772, whereas AMRF4 and AMRF6 harbored ST 2066. All plasmids carried heavy metal cadmium resistance genes cadC and cadD, while cadA was detected only in the plasmid pSaa6159 of AMRF4 and AMRF6 strains. Further, pSaa6159 contains a complete Tn552 transposon with beta-lactamase genes, blaI, blaR1, and blaZ. Interestingly, pSaa6159 in AMRF6 carried five copies of Tn552 transposon. Several exotoxins and enterotoxins were identified across ocular MRSA strains and ST2066 strains found to be not carried any enterotoxins; this finding suggests that these two strains are exotoxigenic. Besides, ST2066 strains carried serine proteases (splA, splB, splD, splE and spIF) and exotoxin (seb and set 21) for their virulence, while ST772 carried antimicrobial resistance genes (blaZ, dfrG, msrA, mphC and fosB) and enterotoxin sec for virulence, suggesting sequence type-specific resistance and virulence. Also, we identified many VFGs and ARGs, that provided multi-drug resistance, enterotoxigenic, exotoxigenic, biofilm-forming, host tissue adhesion and immune response evasion in ocular MRSA strains. Thus, our study provides a better insight into the genomes of ocular MRSA strains that would provide more effective treatment strategies for ocular MRSA infection.

Nosocomial or not? A combined epidemiological and genomic investigation to understand hospital-acquired COVID-19 infection on an elderly care ward

Background

COVID-19 has the potential to cause outbreaks in hospitals. Given the comorbid and elderly cohort of patients hospitalized, hospital-acquired COVID-19 infection is often fatal. Pathogen genome sequencing is becoming increasingly important in infection prevention and control (IPC).

Aim

To inform the understanding of in-hospital SARS-CoV-2 transmission in order to improve IPC practices and to inform the future development of virological testing for IPC.

Methods

Patients detected COVID-19 positive by polymerase chain reaction on Ward A in April and May 2020 were included with contact tracing to identify other potential cases. Genome sequencing was undertaken for a subgroup of cases. Epidemiological, genomic, and cluster analyses were performed to describe the epidemiology and to identify factors contributing to the outbreak.

Findings

Fourteen cases were identified on Ward A. Contact tracing identified 16 further patient cases; in addition, eight healthcare workers (HCWs) were identified as being COVID-19 positive through a round of asymptomatic testing. Genome sequencing of 16 of these cases identified viral genomes differing by two single nucleotide polymorphisms or fewer, with further cluster analysis identifying two groups of infection (a five-person group and a six-person group).

Conclusion

Despite the temporal relationship of cases, genome sequencing identified that not all cases shared transmission events. However, 11 samples were found to be closely related and these likely represented in-hospital transmission. This included three HCWs, thereby confirming transmission between patients and HCWs.

Are neighbourhoods of tuberculosis cases a high-risk population for active intervention? A protocol for tuberculosis active case finding

BACKGROUND

Indonesia has the second largest tuberculosis (TB) burden globally. Attempts to scale-up TB control efforts have focused on TB households. However, in most high burden settings, considerable Mycobacterium tuberculosis (Mtb) transmission occurs outside TB households. A better understanding of transmission dynamics in an urban setting in Indonesia will be crucial for the TB Control Program in scaling up efforts towards elimination of TB in a more targeted way. Therefore, the study aims to measure TB prevalence and incidence in household contacts and neighbourhoods in the vicinity of known TB cases and to assess their genomic and epidemiological relatedness.

METHODS AND ANALYSIS

Individuals (~1000) living in the same household as a case diagnosed with pulmonary TB (n = 250) or in a neighbouring household (~4500 individuals) will be screened for TB symptoms and by chest x-ray. Two sputum samples will be collected for microbiological analysis from anyone with a productive cough. Any person found to have TB will be treated by the National TB Control Program. All those with no evidence of TB disease will have a repeat screen at 12 months. Whole-genome sequencing (WGS) and social network analysis (SNA) will be conducted on Index cases and contacts diagnosed with TB.

Validation, Implementation, and Clinical Utility of Whole Genome Sequence-Based Bacterial Identification in the Clinical Microbiology Laboratory

The application of next-generation sequencing extends from microbial identification to epidemiologic insight and antimicrobial resistance prediction. Despite this potential, the roadblock for clinical laboratories lies in implementation and validation of such complex technology and data analysis. Here, we describe a validation study using whole-genome sequencing (WGS) for pan-bacterial identification (ID) in a clinical laboratory setting, and discuss the clinical relevance. A diverse set of 125 bacterial isolates, including a subset of isolates without genus (25) and/or species (10) ID, were analyzed by de novo assembly and reference genome mapping. The 16S rRNA, rpoB, and groEL genes were used for ID. Using WGS, 100% (89 of 89) and 89% (79 of 89) of isolates were identified to the genus and species levels, respectively. WGS also provided improved results for the majority of isolates (25 of 35) that were reported originally with genus-only or descriptive IDs. Chart review identified cases in which improved genus and/or species level ID by WGS may have had a positive impact on patient care. Reasons included the use of an ineffective antibiotic owing to unclear ID, use of antibiotics when not clinically indicated, and help with an outbreak investigation. The implementation of next-generation sequencing in a clinical microbiology setting is a challenging but necessary task. Our study provides a model for the validation and implementation of bacterial ID by WGS in such a setting.

Use of next generation sequencing technologies for the diagnosis and epidemiology of infectious diseases

For the first time, next generation sequencing technologies provide access to genomic information at a price and scale that allow their implementation in routine clinical practice and epidemiology. While there are still many obstacles to their implementation, there are also multiple examples of their major advantages compared with previous methods. Their main advantage is that a single determination allows epidemiological information on the causative microorganism to be obtained simultaneously, as well as its resistance profile, although these advantages vary according to the pathogen under study. This review discusses several examples of the clinical and epidemiological use of next generation sequencing applied to complete genomes and microbiomes and reflects on its future in clinical practice.

Predominance of CTX-M-15-producing ST131 strains among ESBL-producing Escherichia coli isolated from asylum seekers in the Netherlands

Objectives

Numerous studies show increased prevalence of MDR bacteria amongst asylum seekers, but data on the molecular profiles of such strains are limited. We aimed to evaluate the molecular profiles of ESBL-producing Escherichia coli (ESBL-E. coli) strains isolated from asylum seekers and investigate their phylogenetic relatedness.

Methods

WGS data of ESBL-E. coli isolates from asylum seekers, retrieved from 1 January to 31 December 2016, were analysed to assess MLST STs, fim types, phylogroups and resistance genes. Fifty-two ESBL-E. coli isolates from the Dutch–German border region were used for genome comparison purposes as a control group.

Results

Among 112 ESBL-E. coli isolates from asylum seekers, originating mostly from Syria (n = 40) and Iraq (n = 15), the majority belonged to ST131 (21.4%) and ST10 (17.0%). The predominant gene for β-lactam resistance was bla_CTX-M-15 (67.9%), followed by the often co-detected bla_TEM-1B (39.3%). No mcr or carbapenemase genes were detected. The majority of the strains belonged to phylogroups B2 (38.4%) and A (32.1%), carrying fimH27 (25%) and fimH30 (19.6%). A core genome MLST minimum spanning tree did not reveal clusters containing strains from the asylum seekers and the control group. Five clusters were formed within the asylum seeker group, by strains isolated from people originating from different countries.

Conclusions

The most frequently isolated clones in this study were isolated on a regular basis within the Dutch population before the increase in the asylum seeker population. No mcr- or carbapenemase-producing clones were detected among the asylum seeker population. Minor clustering was observed amongst the asylum seeker strains.

Leapfrogging laboratories: the promise and pitfalls of high-tech solutions for antimicrobial resistance surveillance in low-income settings

The scope and trajectory of today’s escalating antimicrobial resistance (AMR) crisis is inadequately captured by existing surveillance systems, particularly those of lower income settings. AMR surveillance systems typically collate data from routine culture and susceptibility testing performed in diagnostic bacteriology laboratories to support healthcare. Limited access to high quality culture and susceptibility testing results in the dearth of AMR surveillance data, typical of many parts of the world where the infectious disease burden and antimicrobial need are high. Culture and susceptibility testing by traditional techniques is also slow, which limits its value in infection management. Here, we outline hurdles to effective resistance surveillance in many low-income settings and encourage an open attitude towards new and evolving technologies that, if adopted, could close resistance surveillance gaps. Emerging advancements in point-of-care testing, laboratory detection of resistance through or without culture, and in data handling, have the potential to generate resistance data from previously unrepresented locales while simultaneously supporting healthcare. Among them are microfluidic, nucleic acid amplification technology and next-generation sequencing approaches. Other low tech or as yet unidentified innovations could also rapidly accelerate AMR surveillance. Parallel advances in data handling further promise to significantly improve AMR surveillance, and new frameworks that can capture, collate and use alternate data formats may need to be developed. We outline the promise and limitations of such technologies, their potential to leapfrog surveillance over currently available, conventional technologies in use today and early steps that health systems could take towards preparing to adopt them.

Evaluation of the BD Phoenix CPO detect panel for prediction of Ambler class carbapenemases

Rapid detection of carbapenemases as a cause of resistance is beneficial for infection control and antimicrobial therapy. The BD Phoenix NMIC-502 panel and CPO detect test identifies presence of carbapenemases in Enterobacterales such as Klebsiella pneumoniae and assigns them to Ambler classes. To evaluate the performance of the CPO detect panel, we employed a European collection of 1222 K. pneumoniae including carbapenem non-susceptible and susceptible clinical isolates from 26 countries, for which draft genomes were available after Illumina sequencing and the presence of carbapenemase genes had been identified by ARIBA gene calling. The CPO panel detected 488 out of 494 carbapenemase-encoding isolates as positive and six as negative. One-hundred and two isolates were tested positive for carbapenemase in the absence of any carbapenemase gene. The CPO panel identified 229 out of 230 KPC-positive isolates as carbapenemase producing and classified 62 of these as class A enzyme. Similarly, the CPO panel correctly specified 167 of 182 as class D. Regarding metallo-beta-lactamases, the CPO panel assigned 78 of 90 MBL positive isolates to class B enzymes. The sensitivity of the CPO panel in detecting carbapenemase activity was 99.5%, 97.7% and 98.3% for class A, B and D enzymes, respectively. The sensitivity in assignation to Ambler class A, B and D was 27%, 86% and 91%, respectively. An overall sensitivity of 98.8% and specificity of 86% in unclassified detection of carbapenemases was observed, with frequent false positive detection of carbapenemase producing organisms, thus rendering further confirmatory tests necessary.

Molecular and Anti-Microbial Resistance (AMR) Profiling of Methicillin-Resistant Staphylococcus aureus (MRSA) from Hospital and Long-Term Care Facilities (LTCF) Environment

To provide evidence of the cross-contamination of emerging pathogenic microbes in a local network between long-term care facilities (LTCFs) and hospitals, this study emphasizes the molecular typing, the prevalence of virulence genes, and the antibiotic resistance pattern of methicillin-resistant Staphylococcus aureus. MRSA isolates were characterized from 246 samples collected from LTCFs, medical tubes of LTCF residents, and hospital environments of two cities, Chiayi and Changhua. Species identification, molecular characterization, and drug resistance analysis were performed. Hospital environments had a higher MRSA detection rate than that of LTCF environments, where moist samples are a hotspot of MRSA habitats, including tube samples from LTCF residents. All MRSA isolates in this study carried the exfoliative toxin eta gene (100%). The majority of MRSA isolates were resistant to erythromycin (76.7%), gentamicin (60%), and ciprofloxacin (55%). The percentage of multidrug-resistant MRSA isolates was approximately 50%. The enterobacterial repetitive intergenic consensus polymerase chain reaction results showed that 18 MRSA isolates belonged to a specific cluster. This implied that genetically similar isolates were spread between hospitals and LTCFs in Changhua city. This study highlights the threat to the health of LTCFs’ residents posed by hospital contact with MRSA.

Navigating Clinical Utilization of Direct-from-Specimen Metagenomic Pathogen Detection: Clinical Applications, Limitations, and Testing Recommendations

BACKGROUND

Metagenomic next generation sequencing (mNGS) is becoming increasingly available for pathogen detection directly from clinical specimens. These tests use target-independent, shotgun sequencing to detect potentially unlimited organisms. The promise of this methodology to aid infection diagnosis is demonstrated through early case reports and clinical studies. However, the optimal role of mNGS in clinical microbiology remains uncertain.

CONTENT

We reviewed studies reporting clinical use of mNGS for pathogen detection from various specimen types, including cerebrospinal fluid, plasma, lower respiratory specimens, and others. Published clinical study data were critically evaluated and summarized to identify promising clinical indications for mNGS-based testing, to assess the clinical impact of mNGS for each indication, and to recognize test limitations. Based on these clinical studies, early testing recommendations are made to guide clinical utilization of mNGS for pathogen detection. Finally, current barriers to routine clinical laboratory implementation of mNGS tests are highlighted.

SUMMARY

The promise of direct-from-specimen mNGS to enable challenging infection diagnoses has been demonstrated through early clinical studies of patients with meningitis or encephalitis, invasive fungal infections, community acquired pneumonia, and other clinical indications. However, the proportion of patient cases with positive clinical impact due to mNGS testing is low in published studies and the cost of testing is high, emphasizing the importance of improving our understanding of 'when to test' and for which patients mNGS testing is appropriate.

Rapid metagenomics for diagnosis of bloodstream and respiratory tract nosocomial infections: current status and future prospects

Introduction: Nosocomial infections represent a major problem for the health-care systems worldwide. Currently, diagnosis relies on microbiological culture, which is slow and has poor sensitivity. While waiting for a diagnosis, patients are treated with empiric broad spectrum antimicrobials, which are often inappropriate for the infecting pathogen. This results in poor patient outcomes, poor antimicrobial stewardship and increased costs for health-care systems.Areas covered: Clinical metagenomics (CMg), the application of metagenomic sequencing for the diagnosis of infection, has the potential to become a viable alternative to culture that can offer rapid results with high accuracy. In this article, we review current CMg methods for the diagnosis of nosocomial bloodstream (BSI) and lower respiratory-tract infections (LRTI).Expert opinion: CMg approaches are more accurate in LRTI compared to BSI. This is because BSIs are caused by low pathogen numbers in a high background of human cells. To overcome this, most approaches focus on cell-free DNA, but, to date, these tests are not accurate enough yet to replace blood culture. The higher pathogen numbers in LRTI samples make this a more suitable for CMg and accurate approaches have been developed, which are likely to be implemented in hospitals within the next 2-5 years.