Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Identifying SARS-CoV-2 Variants of Concern through saliva-based RT-qPCR by targeting recurrent mutation sites

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to compliment whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60% and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20%, 96.40%, 99.60%, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from December 7-22, 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs.

Importance

SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our real-time RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between VOCs and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

One Day in Denmark: Nationwide point-prevalence survey of human bacterial isolates and comparison of classical and whole-genome sequence-based species identification methods

Objectives

Implementing whole-genome sequencing (WGS) technologies in clinical microbiology laboratories can increase the amount and quality of information available for healthcare practitioners. In this study, we analysed the applicability of this method and determined the distribution of bacterial species processed in clinical settings in Denmark.

Methods

We performed a point-prevalence study of all bacterial isolates (n = 2,009) processed and reported in the Clinical Microbiology Laboratories in Denmark in one day in January 2018. We compared species identification as performed by classical methods (MALDI-TOF) and by bioinformatics analysis (KmerFinder and rMLST) of WGS (Illumina NextSeq) data. We compared the national point-prevalence of bacterial isolates observed in clinical settings with the research attention given to those same genera in scientific literature.

Results

The most prevalent bacterium was Escherichia coli isolated from urine (n = 646), followed by Staphylococcus spp. from skin or soft tissues (n = 197). The distribution of bacterial species throughout the country was not homogeneous. We observed concordance of species identification for all methods in 95.7% (n = 1,919) of isolates, furthermore obtaining concordance for 99.7% (n = 1,999) at genus level. The number of scientific publications in the country did not correlate with the number of bacterial isolates of each genera analysed in this study.

Conclusions

WGS technologies have the potential to be applied in clinical settings for routine diagnostics purposes. This study also showed that bioinformatics databases should be continuously improved and results from local point-prevalence surveys should not be applied at national levels without previously determining possible regional variations.

Metagenomic Next-Generation Sequencing for the Microbiological Diagnosis of Abdominal Sepsis Patients

Objectives

For patients with intra-abdominal infection (IAI), the rapid and accurate identification of pathogens remains a challenge. Metagenomic next-generation sequencing (mNGS) is a novel technique for infectious diseases, but its application in IAI is limited. In this study, we compared the microbiological diagnostic ability of plasma mNGS with that of conventional peritoneal drainage (PD) culture in critical care settings.

Methods

From January 2018 to December 2020, a prospective observational study was performed at a tertiary teaching hospital in China and data on 109 abdominal sepsis patients were collected. The pathogen detection performance of plasma mNGS and PD culture method were compared.

Measurements and Results

Ninety-two positive cases detected on PD culture, while plasma mNGS detected 61 positive cases. Forty-five patients (44.0%) had at least one matched pair of plasma mNGS and PD culture results. Compared with PD culture, the plasma mNGS was more rapid (27.1 ± 4.0 vs. 68.9 ± 22.3 h, p < 0.05). The patients received initial antibiotic treatment matched with mNGS detection showed better clinical outcomes.

Conclusion

For abdominal sepsis patients, plasma mNGS can provide early, noninvasive, and rapid microbiological diagnosis. Compared with conventional PD smear, culture, and blood culture methods, plasma mNGS promote the rapid detection of pathogenic bacteria.

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.

Multi-laboratory evaluation of the Illumina iSeq platform for whole genome sequencing of Salmonella, Escherichia coli and Listeria

There is a growing need for public health and veterinary laboratories to perform whole genome sequencing (WGS) for monitoring antimicrobial resistance (AMR) and protecting the safety of people and animals. With the availability of smaller and more affordable sequencing platforms coupled with well-defined bioinformatic protocols, the technological capability to incorporate this technique for real-time surveillance and genomic epidemiology has greatly expanded. There is a need, however, to ensure that data are of high quality. The goal of this study was to assess the utility of a small benchtop sequencing platform using a multi-laboratory verification approach. Thirteen laboratories were provided the same equipment, reagents, protocols and bacterial reference strains. The Illumina DNA Prep and Nextera XT library preparation kits were compared, and 2×150 bp iSeq i100 chemistry was used for sequencing. Analyses comparing the sequences produced from this study with closed genomes from the provided strains were performed using open-source programs. A detailed, step-by-step protocol is publicly available via protocols.io (https://www.protocols.io/view/iseq-bacterial-wgs-protocol-bij8kcrw). The throughput for this method is approximately 4-6 bacterial isolates per sequencing run (20-26 Mb total load). The Illumina DNA Prep library preparation kit produced high-quality assemblies and nearly complete AMR gene annotations. The Prep method produced more consistent coverage compared to XT, and when coverage benchmarks were met, nearly all AMR, virulence and subtyping gene targets were correctly identified. Because it reduces the technical and financial barriers to generating WGS data, the iSeq platform is a viable option for small laboratories interested in genomic surveillance of microbial pathogens.

A novel and improved selective media for the isolation and enumeration of Klebsiella species

Bacterial pathogens are fostered in and transmitted through wastewater. Hence, monitoring their impact on sanitation and hygiene is imperative. As part of the monitoring process, culture-based methodologies are primarily used, which centre on the use of selective and differential media. Media available today are, at best, difficult to formulate and, at worst, prohibitively expensive. To address this lacuna, the study proposes a selective and differential medium for Klebsiella spp. Klebsiella blue agar (KBA) is completely selective against selected gram-positive bacteria (Bacillus spp., Staphylococcus aureus) and a few gram-negative bacteria (Acinetobacter baumanii, Serratia marcescens). On the other hand, it supports the growth of the chosen members of the Klebsiella pneumoniae species-complex with a characteristic green colouration. Methylene blue, tryptophan, and bile salt make up the selective components of KBA. Moreover, methylene blue, 0.6% NaCl, and glycerol render it differential. KBA was more selective than HiCrome™ Klebsiella Selective Agar Base (KSA) in replica plating experiments. KBA promoted only 157 CFUs against 209 CFUs in KSA when stamped with 253 CFUs grown on LB. The colonies so isolated were predominantly Klebsiella spp., on identification through colony polymerase chain reaction. Moreover, the differential nature of KBA distinguished Klebsiella aerogenes from other species. On the contrary, KSA lodged colonies indistinguishable from each other and Klebsiella spp. Due to its ease of formulation, high selectivity, differential nature, and cost-effective composition, KBA is a viable option for the routine culture of Klebsiella spp. in environmental and clinical settings. KEY POINTS: • Formulated a novel selective and differential media for Klebsiella spp., named Klebsiella Blue agar • Facile formulation methodology • Can be employed to isolate Klebsiella spp. from complex sources such as wastewater.

BSAC Vanguard Series: From treatment options to precision medicine: the future of 'omics-based' antibiotic resistance surveillance data

Conventional culture-based phenotypic and genomic surveillance has drawbacks and may not necessarily reflect the true burden of antibiotic resistance. The integration of metagenomic surveillance with transcriptomics and proteomics will yield a step change in the utility of surveillance data from treatment options to precision medicine.

Overcoming Data Bottlenecks in Genomic Pathogen Surveillance

Performing whole genome sequencing (WGS) for the surveillance of antimicrobial resistance offers the ability to determine not only the antimicrobials to which rates of resistance are increasing, but also the evolutionary mechanisms and transmission routes responsible for the increase at local, national, and global scales. To derive WGS-based outputs, a series of processes are required, beginning with sample and metadata collection, followed by nucleic acid extraction, library preparation, sequencing, and analysis. Throughout this pathway there are many data-related operations required (informatics) combined with more biologically focused procedures (bioinformatics). For a laboratory aiming to implement pathogen genomics, the informatics and bioinformatics activities can be a barrier to starting on the journey; for a laboratory that has already started, these activities may become overwhelming. Here we describe these data bottlenecks and how they have been addressed in laboratories in India, Colombia, Nigeria, and the Philippines, as part of the National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance. The approaches taken include the use of reproducible data parsing pipelines and genome sequence analysis workflows, using technologies such as Data-flo, the Nextflow workflow manager, and containerization of software dependencies. By overcoming barriers to WGS implementation in countries where genome sampling for some species may be underrepresented, a body of evidence can be built to determine the concordance of antimicrobial sensitivity testing and genome-derived resistance, and novel high-risk clones and unknown mechanisms of resistance can be discovered.

Integrating Scalable Genome Sequencing Into Microbiology Laboratories for Routine Antimicrobial Resistance Surveillance

Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.

Future potential of metagenomics in clinical laboratories

INTRODUCTION

Rapid and sensitive diagnostic strategies are necessary for patient care and public health. Most of the current conventional microbiological assays detect only a restricted panel of pathogens at a time or require a microbe to be successfully cultured from a sample. Clinical metagenomics next-generation sequencing (mNGS) has the potential to unbiasedly detect all pathogens in a sample, increasing the sensitivity for detection and enabling the discovery of unknown infectious agents.

AREAS COVERED

High expectations have been built around mNGS; however, this technique is far from widely available. This review highlights the advances and currently available options in terms of costs, turnaround time, sensitivity, specificity, validation, and reproducibility of mNGS as a diagnostic tool in clinical microbiology laboratories.

EXPERT OPINION

The need for a novel diagnostic tool to increase the sensitivity of microbial diagnostics is clear. mNGS has the potential to revolutionise clinical microbiology. However, its role as a diagnostic tool has yet to be widely established, which is crucial for successfully implementing the technique. A clear definition of diagnostic algorithms that include mNGS is vital to show clinical utility. Similarly to real-time PCR, mNGS will one day become a vital tool in any testing algorithm.

Bacterial genomic epidemiology with mixed samples

Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

Evaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations

Whole genome sequencing (WGS) has become the reference standard for bacterial outbreak investigation and pathogen typing, providing a resolution unattainable with conventional molecular methods. Data generated with Illumina sequencers can however only be analysed after the sequencing run has finished, thereby losing valuable time during emergency situations. We evaluated both the effect of decreasing overall run time, and also a protocol to transfer and convert intermediary files generated by Illumina sequencers enabling real-time data analysis for multiple samples part of the same ongoing sequencing run, as soon as the forward reads have been sequenced. To facilitate implementation for laboratories operating under strict quality systems, extensive validation of several bioinformatics assays (16S rRNA species confirmation, gene detection against virulence factor and antimicrobial resistance databases, SNP-based antimicrobial resistance detection, serotype determination, and core genome multilocus sequence typing) for three bacterial pathogens (Mycobacterium tuberculosis , Neisseria meningitidis , and Shiga-toxin producing Escherichia coli ) was performed by evaluating performance in function of the two most critical sequencing parameters, i.e. read length and coverage. For the majority of evaluated bioinformatics assays, actionable results could be obtained between 14 and 22 h of sequencing, decreasing the overall sequencing-to-results time by more than half. This study aids in reducing the turn-around time of WGS analysis by facilitating a faster response in time-critical scenarios and provides recommendations for time-optimized WGS with respect to required read length and coverage to achieve a minimum level of performance for the considered bioinformatics assay(s), which can also be used to maximize the cost-effectiveness of routine surveillance sequencing when response time is not essential.

Development of a database and standardized approach for rpoB sequence-based subtyping and identification of aerobic spore-forming Bacillales

Aerobic spore-forming Bacillales are a highly diverse and ubiquitous group that includes organisms that cause foodborne illnesses and food spoilage. Classical microbiological and biochemical identification of members of the order Bacillales represents a challenge due to the diversity of organisms in this group as well as the fact that the phenotypic-based taxonomic assignment of some named species in this group is not consistent with their phylogenomic characteristics. DNA-sequencing-based tools, on the other hand, can be fast and cost-effective, and can provide for a more reliable identification and characterization of Bacillales isolates. In comparison to 16S rDNA, rpoB was shown to better discriminate between Bacillales isolates and to allow for improved taxonomic assignment to the species level. However, the lack of a publicly accessible rpoB database, as well as the lack of standardized protocols for rpoB-based typing and strain identification, is a major challenge. Here, we report (i) the curation of a DNA sequence database for rpoB-based subtype classification of Bacillales isolates; (ii) the development of standardized protocols for generating rpoB sequence data, and a scheme for rpoB-based initial taxonomic identification of Bacillales isolates at the species level; and (iii) the integration of the database in a publicly accessible online platform that allows for the analysis of rpoB sequence data from uncharacterized Bacillales isolates. Specifically, we curated a database of DNA sequences for a 632-nt internal variable region within the rpoB gene from representative Bacillales reference type strains and a large number of isolates that we have previously isolated and characterized through multiple projects. As of May 21, 2021, the rpoB database contained more than 8350 rpoB sequences representing 1902 distinct rpoB allelic types that can be classified into 160 different genera. The database also includes 1129 rpoB sequences for representative Bacillales reference type strains as available on May 21, 2021 in the NCBI database. The rpoB database is integrated into the online Food Microbe Tracker platform (www.foodmicrobetracker.com) and can be queried using the integrated BLAST tool to initially subtype and taxonomically identify aerobic and facultative anaerobic spore-formers. While whole-genome sequencing is increasingly used in bacterial taxonomy, the rpoB sequence-based identification scheme described here provides a valuable tool as it allows for rapid and cost-effective initial isolate characterization, which can help to identify and characterize foodborne pathogens and food spoilage bacteria. In addition, the database and primers described here can also be adopted for metagenomics approaches that include rpoB as a target, improving discriminatory power and identification over what can be achieved using 16S rDNA as a target.

Detection of Multidrug-Resistant Enterobacterales-From ESBLs to Carbapenemases

Multidrug-resistant Enterobacterales (MDRE) are an emerging threat to global health, leading to rising health care costs, morbidity and mortality. Multidrug-resistance is commonly caused by different β-lactamases (e.g., ESBLs and carbapenemases), sometimes in combination with other resistance mechanisms (e.g., porin loss, efflux). The continuous spread of MDRE among patients in hospital settings and the healthy population require adjustments in healthcare management and routine diagnostics. Rapid and reliable detection of MDRE infections as well as gastrointestinal colonization is key to guide therapy and infection control measures. However, proper implementation of these strategies requires diagnostic methods with short time-to-result, high sensitivity and specificity. Therefore, research on new techniques and improvement of already established protocols is inevitable. In this review, current methods for detection of MDRE are summarized with focus on culture based and molecular techniques, which are useful for the clinical microbiology laboratory.

Whole-genome-based phylogenomic analysis of the Belgian 2016-2017 influenza A(H3N2) outbreak season allows improved surveillance

Seasonal influenza epidemics are associated with high mortality and morbidity in the human population. Influenza surveillance is critical for providing information to national influenza programmes and for making vaccine composition predictions. Vaccination prevents viral infections, but rapid influenza evolution results in emerging mutants that differ antigenically from vaccine strains. Current influenza surveillance relies on Sanger sequencing of the haemagglutinin (HA) gene. Its classification according to World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC) guidelines is based on combining certain genotypic amino acid mutations and phylogenetic analysis. Next-generation sequencing technologies enable a shift to whole-genome sequencing (WGS) for influenza surveillance, but this requires laboratory workflow adaptations and advanced bioinformatics workflows. In this study, 253 influenza A(H3N2) positive clinical specimens from the 2016–2017 Belgian season underwent WGS using the Illumina MiSeq system. HA-based classification according to WHO/ECDC guidelines did not allow classification of all samples. A new approach, considering the whole genome, was investigated based on using powerful phylogenomic tools including beast and Nextstrain, which substantially improved phylogenetic classification. Moreover, Bayesian inference via beast facilitated reassortment detection by both manual inspection and computational methods, detecting intra-subtype reassortants at an estimated rate of 15 %. Real-time analysis (i.e. as an outbreak is ongoing) via Nextstrain allowed positioning of the Belgian isolates into the globally circulating context. Finally, integration of patient data with phylogenetic groups and reassortment status allowed detection of several associations that would have been missed when solely considering HA, such as hospitalized patients being more likely to be infected with A(H3N2) reassortants, and the possibility to link several phylogenetic groups to disease severity indicators could be relevant for epidemiological monitoring. Our study demonstrates that WGS offers multiple advantages for influenza monitoring in (inter)national influenza surveillance, and proposes an improved methodology. This allows leveraging all information contained in influenza genomes, and allows for more accurate genetic characterization and reassortment detection.

Novel strategies to diagnose prosthetic or native bone and joint infections

INTRODUCTION

Bone and Joint Infections (BJI) are medically important, costly and occur in native and prosthetic joints. Arthroplasties will increase significantly in absolute numbers over time as well as the incidence of Prosthetic Joint Infections (PJI). Diagnosis of BJI and PJI is sub-optimal. The available diagnostic tests have variable effectiveness, are often below standard in sensitivity and/or specificity, and carry significant contamination risks during the collection of clinical samples. Improvement of diagnostics is urgently needed.

AREAS COVERED

We provide a narrative review on current and future diagnostic microbiology technologies. Pathogen identification, antibiotic resistance detection, and assessment of the epidemiology of infections via bacterial typing are considered useful for improved patient management. We confirm the continuing importance of culture methods and successful introduction of molecular, mass spectrometry-mediated and next-generation genome sequencing technologies. The diagnostic algorithms for BJI must be better defined, especially in the context of diversity of both disease phenotypes and clinical specimens rendered available.

EXPERT OPINION

Whether interventions in BJI or PJI are surgical or chemo-therapeutic (antibiotics and bacteriophages included), prior sensitive and specific pathogen detection remains a therapy-substantiating necessity. Innovative tests for earlier and more sensitive and specific detection of bacterial pathogens in BJI are urgently needed.

The global dissemination of bacterial infections necessitates the study of reverse genomic epidemiology

Whole genome sequencing (WGS) has revolutionized the genotyping of bacterial pathogens and is expected to become the new gold standard for tracing the transmissions of bacterial infectious diseases for public health purposes. Traditional genomic epidemiology often uses WGS as a verification tool, namely, when a common source or epidemiological link is suspected, the collected isolates are sequenced for the determination of clonal relationships. However, increasingly frequent international travel and food transportation, and the associated potential for the cross-border transmission of bacterial pathogens, often lead to an absence of information on bacterial transmission routes. Here we introduce the concept of 'reverse genomic epidemiology', i.e. when isolates are inspected by genome comparisons to be sufficiently similar to one another, they are assumed to be a consequence of infection from a common source. Through BacWGSTdb (http://bacdb.org/BacWGSTdb/), a database we have developed for bacterial genome typing and source tracking, we have found that almost the entire analyzed 20 bacterial species exhibit the phenomenon of cross-border clonal dissemination. Five networks were further identified in which isolates sharing nearly identical genomes were collected from at least five different countries. Three of these have been documented as real infectious disease outbreaks, therefore demonstrating the feasibility and authority of reverse genomic epidemiology. Our survey and proposed strategy would be of potential value in establishing a global surveillance system for tracing bacterial transmissions and outbreaks; the related database and techniques require urgent standardization.

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.

Applications of Raman Spectroscopy in Bacterial Infections: Principles, Advantages, and Shortcomings

Infectious diseases caused by bacterial pathogens are important public issues. In addition, due to the overuse of antibiotics, many multidrug-resistant bacterial pathogens have been widely encountered in clinical settings. Thus, the fast identification of bacteria pathogens and profiling of antibiotic resistance could greatly facilitate the precise treatment strategy of infectious diseases. So far, many conventional and molecular methods, both manual or automatized, have been developed for in vitro diagnostics, which have been proven to be accurate, reliable, and time efficient. Although Raman spectroscopy (RS) is an established technique in various fields such as geochemistry and material science, it is still considered as an emerging tool in research and diagnosis of infectious diseases. Based on current studies, it is too early to claim that RS may provide practical guidelines for microbiologists and clinicians because there is still a gap between basic research and clinical implementation. However, due to the promising prospects of label-free detection and noninvasive identification of bacterial infections and antibiotic resistance in several single steps, it is necessary to have an overview of the technique in terms of its strong points and shortcomings. Thus, in this review, we went through recent studies of RS in the field of infectious diseases, highlighting the application potentials of the technique and also current challenges that prevent its real-world applications.

Metagenomic Next-Generation Sequencing for the Diagnosis of Pneumocystis jirovecii Pneumonia in Non-HIV-Infected Patients: A Retrospective Study

Introduction

This study aimed to evaluate the utility of metagenomic next-generation sequencing (mNGS) for the diagnosis of Pneumocystis jirovecii pneumonia (PJP) in non-human immunodeficiency virus-infected patients.

Methods

We conducted a retrospective study. A total of 60 non-human immunodeficiency virus-infected PJP patients and 134 patients diagnosed with non-PJP pneumonia were included. P. jirovecii and other co-pathogens identified by mNGS in bronchoalveolar lavage fluid and/or blood samples were analyzed. Using clinical composite diagnosis as the reference standard, we compared the diagnostic performance of mNGS in PJP with conventional methods, including Gomori methenamine silver staining and serum (1,3)-β-d-glucan. Modifications of antimicrobial treatment for PJP patients after the report of mNGS results were also reviewed.

Results

mNGS reached a sensitivity of 100% in diagnosing PJP, which was remarkably higher than Gomori methenamine silver staining (25.0%) and serum (1,3)-β-d-glucan (67.4%). The specificity of mNGS (96.3%) significantly surpassed serum (1,3)-β-d-glucan (81.4%). Simultaneous mNGS of bronchoalveolar lavage fluid and blood samples was performed in 21 out of 60 PJP patients, and it showed a concordance rate of 100% in detecting P. jirovecii. Besides, mNGS showed good performance in identifying co-pathogens of PJP patients, among which cytomegalovirus and Epstein-Barr virus were most commonly seen. Initial antimicrobial treatment was modified in 71.7% of PJP patients after the report of mNGS results.

Conclusion

mNGS is a useful diagnostic tool with good performance for the diagnosis of PJP and the detection of co-pathogens. mNGS of bronchoalveolar lavage fluid and/or blood samples is suggested in patients with presumptive diagnosis of PJP. Blood samples may be a good alternative to bronchoalveolar lavage fluid for mNGS when bronchoscopic examination is not feasible.

Case Report: About a Case of Hyperammonemia Syndrome Following Lung Transplantation: Could Metagenomic Next-Generation Sequencing Improve the Clinical Management?

Background: Mycoplasma hominis and Ureaplasma spp. are responsible for opportunistic infections in transplant patients, sometimes causing a life-threatening hyperammonemia syndrome. Both pathogens are not identified with standard microbiology techniques, resulting in missed or delayed diagnosis. We present a clinical case that illustrates the added value that next-generation sequencing (NGS) may offer in the diagnosis of respiratory infections in immune-compromised patients. Results: A 55 years-old man with idiopathic pulmonary fibrosis underwent double lung transplantation. He received antibiotic prophylaxis with piperacillin-tazobactam and azythromycin. At day 4 post-transplantation (PTx), the patient presented an acute respiratory distress. A broncho-alveolar lavage (BAL) was performed. At day 5 PTx, the patient presented a status epilepticus due to diffuse cerebral oedema. Serum ammonia concentration was 661 μg/dL. BAL bacterial culture was negative. Because of the clinical presentation, special cultures were performed and identified 100.000 CFU/mL of M. hominis and Ureaplasma spp. and specific PCRs were positive for M. hominis and Ureaplasma parvum. Antibiotic therapy was shifted to therapeutic dose of azithromycin and doxycycline; within 48 h ammonia serum concentrations returned to normal but the coma persisted several weeks, followed by a persistent frontal lobe syndrome. A follow-up BAL was performed on day 11 Ptx. The Mycoplasma/Ureaplasma culture was negative, yet the specific PCRs remained positive. Bacterial culture found 100 CFU/mL of Staphylococcus aureus and viral culture was positive for Herpes Simplex Virus-1. These results were confirmed by metagenomic next-generation sequencing (mNGS). In the bacterial fraction, the majority of reads belonged to Corynebacterium propinquum (34.7%), S. aureus (24.1%) and Staphylococcus epidermidis (17.1%). Reads assigned to M. hominis, Ureaplasma urealyticum and parvum represented 0.71, 0.13, and 0.04% of the bacterial fraction and corresponded to 6.9 × 10³, 9.7 × 10², and 3.7 × 10² genome equivalents per mL of BAL fluid, respectively. These results are in favor of a cure of the atypical infection. Conclusions: mNGS offered added diagnostic and quantitative values compared to PCR tests, which can remain positive after resolved infections. The initiation of appropriate antibiotic therapy would have occurred earlier on, possibly resulting in a better clinical outcome if mNGS had been performed in a routine fashion.

ResFinder 4.0 for predictions of phenotypes from genotypes

Objectives

WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output.

Methods

The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins.

Results

Genotype–phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype–phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance.

Conclusions

WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

Recent advances in rapid antimicrobial susceptibility testing systems

INTRODUCTION

Until recently antimicrobial susceptibility testing (AST) methods based on the demonstration of phenotypic susceptibility in 16-24 h remained largely unchanged.

AREAS COVERED

Advances in rapid phenotypic and molecular-based AST systems.

EXPERT OPINION

AST has changed over the past decade, with many rapid phenotypic and molecular methods developed to demonstrate phenotypic or genotypic resistance, or biochemical markers of resistance such as β-lactamases associated with carbapenem resistance. Most methods still require isolation of bacteria from specimens before both legacy and newer methods can be used. Bacterial identification by MALDI-TOF mass spectroscopy is now widely used and is often key to the interpretation of rapid AST results. Several PCR arrays are available to detect the most frequent pathogens associated with bloodstream infections and their major antimicrobial resistance genes. Many advances in whole-genome sequencing of bacteria and fungi isolated by culture as well as directly from clinical specimens have been made but are not yet widely available. High cost and limited throughput are the major obstacles to uptake of rapid methods, but targeted use, continued development and decreasing costs are expected to result in more extensive use of these increasingly useful methods.

Driving Laboratory Standardization of Bacterial Culture and Antimicrobial Susceptibility Testing in Veterinary Clinical Microbiology in Europe and Beyond

Globally, antimicrobial resistance is one of the most important public health challenges in which the clinical microbiology laboratory plays a critical role by providing guidance for antimicrobial treatment. Despite the recognition of its importance, there is still a real need for the standardized training of clinical microbiologists and harmonization of diagnostic procedures. This is particularly true for veterinary clinical microbiology, where additional challenges exist when microbiologists are trying to fulfill a professional role very similar to that of their colleagues working in human microbiology laboratories. The specific points that need addressing to improve the outputs of veterinary microbiology laboratories discussed here include (i) harmonization of methodologies used by veterinary laboratories for antimicrobial susceptibility testing (AST); (ii) specific guidelines for interpretation and reporting of AST results for animal pathogens; (iii) guidelines for detection of antimicrobial resistance mechanisms in animal isolates; (iv) standardization of diagnostic procedures for animal clinical specimens; and (v) the need to train more veterinary clinical microbiology specialists. However, there is now a plan to address these issues, led by the European Network for Optimization of Veterinary Antimicrobial Treatment (ENOVAT), which is bringing together experts in veterinary microbiology, pharmacology, epidemiology, and antimicrobial stewardship from Europe and wider afield. ENOVAT is aiming to work with project partners toward standardization and harmonization of laboratory methodologies and optimization of veterinary antimicrobial treatment. Ultimately, the project may provide a mechanism for standardization and harmonization of veterinary clinical microbiology methodologies that could then be used as a template for implementation at a wider international level.

A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

De Novo Sequencing Provides Insights Into the Pathogenicity of Foodborne Vibrio parahaemolyticus

Vibrio parahaemolyticus is a common pathogenic marine bacterium that causes gastrointestinal infections and other health complications, which could be life-threatening to immunocompromised patients. For the past two decades, the pathogenicity of environmental V. parahaemolyticus has increased greatly, and the genomic change behind this phenomenon still needs an in-depth exploration. To investigate the difference in pathogenicity at the genomic level, three strains with different hemolysin expression and biofilm formation capacity were screened out of 69 environmental V. parahaemolyticus strains. Subsequently, 16S rDNA analysis, de novo sequencing, pathogenicity test, and antibiotic resistance assays were performed. Comparative genome-scale interpretation showed that various functional region differences in pathogenicity of the selected V. parahaemolyticus strains were due to dissimilarities in the distribution of key genetic elements and in the secretory system compositions. Furthermore, the genomic analysis-based hypothesis of distinct pathogenic effects was verified by the survival rate of mouse models infected with different V. parahaemolyticus strains. Antibiotic resistance results also presented the multi-directional evolutionary potential in environmental V. parahaemolyticus, in agreement with the phylogenetic analysis results. Our study provides a theoretical basis for better understanding of the increasing pathogenicity of environmental V. parahaemolyticus at the genome level. Further, it has a key referential value for the exploration of pathogenicity and prevention of environmental V. parahaemolyticus in the future.

Genotypic Characterization of Clinical Klebsiella spp. Isolates Collected From Patients With Suspected Community-Onset Sepsis, Sweden

Klebsiella is a genus of Gram-negative bacteria known to be opportunistic pathogens that may cause a variety of infections in humans. Highly drug-resistant Klebsiella species, especially K. pneumoniae, have emerged rapidly and are becoming a major concern in clinical management. Although K. pneumoniae is considered the most important pathogen within the genus, the true clinical significance of the other species is likely underrecognized due to the inability of conventional microbiological methods to distinguish between the species leading to high rates of misidentification. Bacterial whole-genome sequencing (WGS) enables precise species identification and characterization that other technologies do not allow. Herein, we have characterized the diversity and traits of Klebsiella spp. in community-onset infections by WGS of clinical isolates (n = 105) collected during a prospective sepsis study in Sweden. The sequencing revealed that 32 of the 82 isolates (39.0%) initially identified as K. pneumoniae with routine microbiological methods based on cultures followed by matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS) had been misidentified. Of these, 23 were identified as Klebsiella variicola and nine as other members of the K. pneumoniae complex. Comparisons of the number of resistance genes showed that significantly fewer resistance genes were detected in Klebsiella oxytoca compared to K. pneumoniae and K. variicola (both values of p < 0.001). Moreover, a high proportion of the isolates within the K. pneumoniae complex were predicted to be genotypically multidrug-resistant (MDR; 79/84, 94.0%) in contrast to K. oxytoca (3/16, 18.8%) and Klebsiella michiganensis (0/4, 0.0%). All isolates predicted as genotypically MDR were found to harbor the combination of β-lactam, fosfomycin, and quinolone resistance markers. Multi-locus sequence typing (MLST) revealed a high diversity of sequence types among the Klebsiella spp. with ST14 (10.0%) and ST5429 (10.0%) as the most prevalent ones for K. pneumoniae, ST146 for K. variicola (12.0%), and ST176 for K. oxytoca (25.0%). In conclusion, the results from this study highlight the importance of using high-resolution genotypic methods for identification and characterization of clinical Klebsiella spp. isolates. Our findings indicate that infections caused by other members of the K. pneumoniae complex than K. pneumoniae are a more common clinical problem than previously described, mainly due to high rates of misidentifications.

Trends in Molecular Diagnosis and Diversity Studies for Phytosanitary Regulated Xanthomonas

Bacteria in the genus Xanthomonas infect a wide range of crops and wild plants, with most species responsible for plant diseases that have a global economic and environmental impact on the seed, plant, and food trade. Infections by Xanthomonas spp. cause a wide variety of non-specific symptoms, making their identification difficult. The coexistence of phylogenetically close strains, but drastically different in their phenotype, poses an added challenge to diagnosis. Data on future climate change scenarios predict an increase in the severity of epidemics and a geographical expansion of pathogens, increasing pressure on plant health services. In this context, the effectiveness of integrated disease management strategies strongly depends on the availability of rapid, sensitive, and specific diagnostic methods. The accumulation of genomic information in recent years has facilitated the identification of new DNA markers, a cornerstone for the development of more sensitive and specific methods. Nevertheless, the challenges that the taxonomic complexity of this genus represents in terms of diagnosis together with the fact that within the same bacterial species, groups of strains may interact with distinct host species demonstrate that there is still a long way to go. In this review, we describe and discuss the current molecular-based methods for the diagnosis and detection of regulated Xanthomonas, taxonomic and diversity studies in Xanthomonas and genomic approaches for molecular diagnosis.

Rapid nanopore-based DNA sequencing protocol of antibiotic-resistant bacteria for use in surveillance and outbreak investigation

Outbreak investigations are essential to control and prevent the dissemination of pathogens. This study developed and validated a complete analysis protocol for faster and more accurate surveillance and outbreak investigations of antibiotic-resistant microbes based on Oxford Nanopore Technologies (ONT) DNA whole-genome sequencing. The protocol was developed using 42 methicillin-resistant Staphylococcus aureus (MRSA) isolates identified from former well-characterized outbreaks. The validation of the protocol was performed using Illumina technology (MiSeq, Illumina). Additionally, a real-time outbreak investigation of six clinical S. aureus isolates was conducted to test the ONT-based protocol. The suggested protocol includes: (1) a 20 h sequencing run; (2) identification of the sequence type (ST); (3) de novo genome assembly; (4) polishing of the draft genomes; and (5) phylogenetic analysis based on SNPs. After the sequencing run, it was possible to identify the ST in 2 h (20 min per isolate). Assemblies were achieved after 4 h (40 min per isolate) while the polishing was carried out in 7 min per isolate (42 min in total). The phylogenetic analysis took 0.6 h to confirm an outbreak. Overall, the developed protocol was able to at least discard an outbreak in 27 h (mean) after the bacterial identification and less than 33 h to confirm it. All these estimated times were calculated considering the average time for six MRSA isolates per sequencing run. During the real-time S. aureus outbreak investigation, the protocol was able to identify two outbreaks in less than 31 h. The suggested protocol enables identification of outbreaks in early stages using a portable and low-cost device along with a streamlined downstream analysis, therefore having the potential to be incorporated in routine surveillance analysis workflows. In addition, further analysis may include identification of virulence and antibiotic resistance genes for improved pathogen characterization.

Metagenomic next-generation sequencing for the diagnosis of suspected pneumonia in immunocompromised patients

OBJECTIVES

To evaluate the potential of metagenomic next-generation sequencing (mNGS), compared with that of comprehensive conventional microbiological tests (CMTs), of bronchoalveolar lavage fluid (BALF) as a front-line diagnostic for immunocompromised patients with suspected pneumonia.

METHODS

Sixty critically ill immunocompromised patients undergoing both mNGS of BALF and CMTs for suspected pneumonia were retrospectively analysed. The diagnostic performance was compared between mNGS and CMTs, using the composite diagnosis as the reference standard.

RESULTS

Forty-nine patients were diagnosed with microbiologically confirmed pneumonia, with 55% having polymicrobial infections. There was no significant difference in the overall diagnostic accuracy between mNGS and CMTs (61.7% vs 76.7%; P = 0.11). mNGS and CMTs had comparable diagnostic accuracy for bacterial and viral infections. Although mNGS identified more viral pneumonia, it had a much lower diagnostic accuracy for fungal infections (76.7% vs 99.2%; P < 0.001), mainly due to the low sensitivity for invasive pulmonary aspergillosis (45.5% vs 100%; P < 0.001).

CONCLUSION

The overall diagnostic performance of BALF mNGS as a first-line diagnostic was similar to that of comprehensive CMTs, except in the case of a lack of consideration of potential pathogens or limited CMTs. The combination of mNGS and CMTs may be the best diagnostic strategy.

Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme

Paenibacillus larvae causes the American foulbrood (AFB), a highly contagious and devastating disease of honeybees. Whole-genome sequencing (WGS) has been increasingly used in bacterial pathogen typing, but rarely applied to study the epidemiology of P. larvae. To this end, we used 125 P. larvae genomes representative of a species-wide diversity to construct a stable whole-genome multilocus sequence typing (wgMLST) scheme consisting of 5745 loci. A total of 51 P. larvae isolates originating from AFB outbreaks in Slovenia were used to assess the epidemiological applicability of the developed wgMLST scheme. In addition, wgMLST was compared with the core-genome MLST (cgMLST) and whole-genome single nucleotide polymorphism (wgSNP) analyses. All three approaches successfully identified clusters of outbreak-associated strains, which were clearly separated from the epidemiologically unlinked isolates. High levels of backward comparability of WGS-based analyses with conventional typing methods (ERIC-PCR and MLST) were revealed; however, both conventional methods lacked sufficient discriminatory power to separate the outbreak clusters. The developed wgMLST scheme provides an improved understanding of the intra- and inter-outbreak genetic diversity of P. larvae and represents an important progress in unraveling the genomic epidemiology of this important honeybee pathogen.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Whole-Genome Sequencing for Investigating a Health Care-Associated Outbreak of Carbapenem-Resistant Acinetobacter baumannii

Carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in hospital settings challenge the treatment of patients and infection control. Understanding the relatedness of clinical isolates is important in distinguishing outbreak isolates from sporadic cases. This study investigated 11 CRAB isolates from a hospital outbreak by whole-genome sequencing (WGS), utilizing various bioinformatics tools for outbreak analysis. The results of multilocus sequence typing (MLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic tree analysis by WGS through web-based tools were compared, and repetitive element polymerase chain reaction (rep-PCR) typing was performed. Through the WGS of 11 A. baumannii isolates, three clonal lineages were identified from the outbreak. The coexistence of bla_OXA-23, bla_OXA-66, bla_ADC-25, and armA with additional aminoglycoside-inactivating enzymes, predicted to confer multidrug resistance, was identified in all isolates. The MLST Oxford scheme identified three types (ST191, ST369, and ST451), and, through whole-genome MLST and whole-genome SNP analyses, different clones were found to exist within the MLST types. wgSNP showed the highest discriminatory power with the lowest similarities among the isolates. Using the various bioinformatics tools for WGS, CRAB outbreak analysis was applicable and identified three discrete clusters differentiating the separate epidemiologic relationships among the isolates.

Translatability of WGS typing results can simplify data exchange for surveillance and control of Listeria monocytogenes

Where classical epidemiology has proven to be inadequate for surveillance and control of foodborne pathogens, molecular epidemiology, using genomic typing methods, can add value. However, the analysis of whole genome sequencing (WGS) data varies widely and is not yet fully harmonised. We used genomic data on 494 Listeria monocytogenes isolates from ready-to-eat food products and food processing environments deposited in the strain collection of the German National Reference Laboratory to compare various procedures for WGS data analysis and to evaluate compatibility of results. Two different core genome multilocus sequence typing (cgMLST) schemes, different reference genomes in single nucleotide polymorphism (SNP) analysis and commercial as well as open-source software were compared. Correlation of allele distances from the different cgMLST approaches was high, ranging from 0.97 to 1, and unified thresholds yielded higher clustering concordance than scheme-specific thresholds. The number of detected SNP differences could be increased up to a factor of 3.9 using a specific reference genome compared with a general one. Additionally, specific reference genomes improved comparability of SNP analysis results obtained using different software tools. The use of a closed or a draft specific reference genome did not make a difference. The harmonisation of WGS data analysis will finally guarantee seamless data exchange, but, in the meantime, knowledge on threshold values that lead to comparable clustering of isolates by different methods may improve communication between laboratories. We therefore established a translation code between commonly applied cgMLST and SNP methods based on optimised clustering concordances. This code can work as a first filter to identify WGS-based typing matches resulting from different methods, which opens up a new perspective for data exchange and thereby accelerates time-critical analyses, such as in outbreak investigations.

National external quality assessment for next-generation sequencing-based diagnostics of primary immunodeficiencies

Dutch genome diagnostic centers (GDC) use next-generation sequencing (NGS)-based diagnostic applications for the diagnosis of primary immunodeficiencies (PIDs). The interpretation of genetic variants in many PIDs is complicated because of the phenotypic and genetic heterogeneity. To analyze uniformity of variant filtering, interpretation, and reporting in NGS-based diagnostics for PID, an external quality assessment was performed. Four main Dutch GDCs participated in the quality assessment. Unannotated variant call format (VCF) files of two PID patient analyses per laboratory were distributed among the four GDCs, analyzed, and interpreted (eight analyses in total). Variants that would be reported to the clinician and/or advised for further investigation were compared between the centers. A survey measuring the experiences of clinical laboratory geneticists was part of the study. Analysis of samples with confirmed diagnoses showed that all centers reported at least the variants classified as likely pathogenic (LP) or pathogenic (P) variants in all samples, except for variants in two genes (PSTPIP1 and BTK). The absence of clinical information complicated correct classification of variants. In this external quality assessment, the final interpretation and conclusions of the genetic analyses were uniform among the four participating genetic centers. Clinical and immunological data provided by a medical specialist are required to be able to draw proper conclusions from genetic data.

Beyond the pan-genome: current perspectives on the functional and practical outcomes of the distributed genome hypothesis

The principle of monoclonality with regard to bacterial infections was considered immutable prior to 30 years ago. This view, espoused by Koch for acute infections, has proven inadequate regarding chronic infections as persistence requires multiple forms of heterogeneity among the bacterial population. This understanding of bacterial plurality emerged from a synthesis of what-were-then novel technologies in molecular biology and imaging science. These technologies demonstrated that bacteria have complex life cycles, polymicrobial ecologies, and evolve in situ via the horizontal exchange of genic characters. Thus, there is an ongoing generation of diversity during infection that results in far more highly complex microbial communities than previously envisioned. This perspective is based on the fundamental tenet that the bacteria within an infecting population display genotypic diversity, including gene possession differences, which result from horizontal gene transfer mechanisms including transformation, conjugation, and transduction. This understanding is embodied in the concepts of the supragenome/pan-genome and the distributed genome hypothesis (DGH). These paradigms have fostered multiple researches in diverse areas of bacterial ecology including host-bacterial interactions covering the gamut of symbiotic relationships including mutualism, commensalism, and parasitism. With regard to the human host, within each of these symbiotic relationships all bacterial species possess attributes that contribute to colonization and persistence; those species/strains that are pathogenic also encode traits for invasion and metastases. Herein we provide an update on our understanding of bacterial plurality and discuss potential applications in diagnostics, therapeutics, and vaccinology based on perspectives provided by the DGH with regard to the evolution of pathogenicity.

Whole-genome sequencing as part of national and international surveillance programmes for antimicrobial resistance: a roadmap

The global spread of antimicrobial resistance (AMR) and lack of novel alternative treatments have been declared a global public health emergency by WHO. The greatest impact of AMR is experienced in resource-poor settings, because of lack of access to alternative antibiotics and because the prevalence of multidrug-resistant bacterial strains may be higher in low-income and middle-income countries (LMICs). Intelligent surveillance of AMR infections is key to informed policy decisions and public health interventions to counter AMR. Molecular surveillance using whole-genome sequencing (WGS) can be a valuable addition to phenotypic surveillance of AMR. WGS provides insights into the genetic basis of resistance mechanisms, as well as pathogen evolution and population dynamics at different spatial and temporal scales. Due to its high cost and complexity, WGS is currently mainly carried out in high-income countries. However, given its potential to inform national and international action plans against AMR, establishing WGS as a surveillance tool in LMICs will be important in order to produce a truly global picture. Here, we describe a roadmap for incorporating WGS into existing AMR surveillance frameworks, including WHO Global Antimicrobial Resistance Surveillance System, informed by our ongoing, practical experiences developing WGS surveillance systems in national reference laboratories in Colombia, India, Nigeria and the Philippines. Challenges and barriers to WGS in LMICs will be discussed together with a roadmap to possible solutions.

In silico characterisation of stand-alone response regulators of Streptococcus pyogenes

Bacterial “stand-alone” response regulators (RRs) are pivotal to the control of gene transcription in response to changing cytosolic and extracellular microenvironments during infection. The genome of group A Streptococcus (GAS) encodes more than 30 stand-alone RRs that orchestrate the expression of virulence factors involved in infecting multiple tissues, so causing an array of potentially lethal human diseases. Here, we analysed the molecular epidemiology and biological associations in the coding sequences (CDSs) and upstream intergenic regions (IGRs) of 35 stand-alone RRs from a collection of global GAS genomes. Of the 944 genomes analysed, 97% encoded 32 or more of the 35 tested RRs. The length of RR CDSs ranged from 297 to 1587 nucleotides with an average nucleotide diversity (π) of 0.012, while the IGRs ranged from 51 to 666 nucleotides with average π of 0.017. We present new evidence of recombination in multiple RRs including mga, leading to mga-2 switching, emm-switching and emm-like gene chimerization, and the first instance of an isolate that encodes both mga-1 and mga-2. Recombination was also evident in rofA/nra and msmR loci with 15 emm-types represented in multiple FCT (fibronectin-binding, collagen-binding, T-antigen)-types, including novel emm-type/FCT-type pairings. Strong associations were observed between concatenated RR allele types, and emm-type, MLST-type, core genome phylogroup, and country of sampling. No strong associations were observed between individual loci and disease outcome. We propose that 11 RRs may form part of future refinement of GAS typing systems that reflect core genome evolutionary associations. This subgenomic analysis revealed allelic traits that were informative to the biological function, GAS strain definition, and regional outbreak detection.

Molecular Epidemiology of Giardia Infections in the Genomic Era

Giardia duodenalis is a major gastrointestinal parasite of humans and animals across the globe. It is also of interest from an evolutionary perspective as it possesses many features that are unique among the eukaryotes, including its distinctive binucleate cell structure. While genomic analysis of a small number of isolates has provided valuable insights, efforts to understand the epidemiology of the disease and the population biology of the parasite have been limited by the molecular tools currently available. We review these tools and assess the impact of affordable and rapid genome sequencing systems increasingly being deployed in diagnostic settings. While these technologies have direct implications for public and veterinary health, they will also improve our understanding of the unique biology of this fascinating parasite.

Existing and emerging methods of diagnosis and monitoring of pediatric musculoskeletal infection

Methods of diagnosing and monitoring pediatric musculoskeletal infections are rapidly evolving. Key serologic tests are typically used in screening patients with suspected infections, and remain an integral part of the initial work-up. Synovial studies from arthrocentesis in possible septic arthritis, and source-specific cultures have been the foundation of our treatment algorithm. Given the prevalence of soft tissue abscesses and osteoarticular infections, advanced imaging is an advantageous tool. More affordable use and expanded access to MRI has made it a valuable adjunct to clinical picture and existing tests in order to comprehensively visualize the extent of musculoskeletal infections in children. Ongoing validation for criteria to help determine the patients that stand to benefit the most from MRI, even when surgical intervention may be delayed, remains of significant clinical interest. Given the rates of culture-negative infections, and the need for timely diagnosis, new diagnostic techniques are always being considered. The search for more accurate biomarkers, and technology such as Whole genome sequencing (WGS) and next-generation sequencing (NGS) that can rapidly identify pathogens of all types of phyla based on a small sample of DNA, has promising clinical implications. While once novel and prohibitively expensive, these tests are now being applied in university and tertiary care centers in certain scenarios. Applying these techniques to pediatric musculoskeletal will require a large change in lab workflow and training. However, the benefits of acquiring diagnostic information along with will make them a superior tool in our arsenal of diagnostic tests.

Genomic Prediction of Antimicrobial Resistance: Ready or Not, Here It Comes!

BACKGROUND

Next-generation sequencing (NGS) technologies are being used to predict antimicrobial resistance. The field is evolving rapidly and transitioning out of the research setting into clinical use. Clinical laboratories are evaluating the accuracy and utility of genomic resistance prediction, including methods for NGS, downstream bioinformatic pipeline components, and the clinical settings in which this type of testing should be offered.

CONTENT

We describe genomic sequencing as it pertains to predicting antimicrobial resistance in clinical isolates and samples. We elaborate on current methodologies and workflows to perform this testing and summarize the current state of genomic resistance prediction in clinical settings. To highlight this aspect, we include 3 medically relevant microorganism exemplars: Mycobacterium tuberculosis, Staphylococcus aureus, and Neisseria gonorrhoeae. Last, we discuss the future of genomic-based resistance detection in clinical microbiology laboratories.

SUMMARY

Antimicrobial resistance prediction by genomic approaches is in its infancy for routine patient care. Genomic approaches have already added value to the current diagnostic testing landscape in specific circumstances and will play an increasingly important role in diagnostic microbiology. Future advancements will shorten turnaround time, reduce costs, and improve our analysis and interpretation of clinically actionable results.

Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory

This review provides a state-of-the-art description of the performance of Sanger cycle sequencing of the 16S rRNA gene for routine identification of bacteria in the clinical microbiology laboratory. A detailed description of the technology and current methodology is outlined with a major focus on proper data analyses and interpretation of sequences. The remainder of the article is focused on a comprehensive evaluation of the application of this method for identification of bacterial pathogens based on analyses of 16S multialignment sequences. In particular, the existing limitations of similarity within 16S for genus- and species-level differentiation of clinically relevant pathogens and the lack of sequence data currently available in public databases is highlighted. A multiyear experience is described of a large regional clinical microbiology service with direct 16S broad-range PCR followed by cycle sequencing for direct detection of pathogens in appropriate clinical samples. The ability of proteomics (matrix-assisted desorption ionization-time of flight) versus 16S sequencing for bacterial identification and genotyping is compared. Finally, the potential for whole-genome analysis by next-generation sequencing (NGS) to replace 16S sequencing for routine diagnostic use is presented for several applications, including the barriers that must be overcome to fully implement newer genomic methods in clinical microbiology. A future challenge for large clinical, reference, and research laboratories, as well as for industry, will be the translation of vast amounts of accrued NGS microbial data into convenient algorithm testing schemes for various applications (i.e., microbial identification, genotyping, and metagenomics and microbiome analyses) so that clinically relevant information can be reported to physicians in a format that is understood and actionable. These challenges will not be faced by clinical microbiologists alone but by every scientist involved in a domain where natural diversity of genes and gene sequences plays a critical role in disease, health, pathogenicity, epidemiology, and other aspects of life-forms. Overcoming these challenges will require global multidisciplinary efforts across fields that do not normally interact with the clinical arena to make vast amounts of sequencing data clinically interpretable and actionable at the bedside.

Development and Validation of an In-House Library for Filamentous Fungi Identification by MALDI-TOF MS in a Clinical Laboratory in Medellin (Colombia)

Identification of filamentous fungi by conventional phenotypic methods are time-consuming, and a correct identification at the species level is prone to errors. Therefore, a more accurate and faster time-to-results, and cost-effective technique, is required, such as the Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS). In this study, we describe the development of an in-house spectra library for the identification of filamentous fungi frequently isolated from patients with infections. An in-house spectra library was constructed using 14 reference strains grown in solid medium. Clinical isolates were identified either by the in-house spectra library or the Biotyper commercial library from Bruker Daltonics. Fungal identification was carried following the Biotyper’s established scores: ≤1.699: not reliably identified (NRI); 1.700–1.999: genus-level; ≥2.000: species-level. Clinical isolates were identified, with the in-house library, at species- and genus-level at 88.70% (55) and 3.22% (2), respectively. While 4.80% (3) was NRI and 3.22% (2) was discrepant concerning sequencing. On the contrary, identification up to species and genus-level with the commercial library was 44.44% (16) and 22.22% (8), respectively. NRI and the discrepancy was 30.55% (11) and 2.77% (1), respectively. For the reaming 26 isolates, 16 from Neoscytalidium dimidiatum and 10 from Sporothrix spp., respectively, the absence of spectrum and the specific spectra within the Sporothrix complex in the commercial library resulted in the inability to obtain an identification. In conclusion, the current results advocate the importance that each clinical microbiological laboratory needs to develop an ad hoc library associated with the MALDI-TOF MS fungal identification to overcome the limitations of the available commercial libraries.

MDACP: A Pathogen Genome and Metagenome Analysis Cloud Platform

Pathogenic microorganism analysis based on next-generation sequencing technology is an important tool for clinical diagnosis, public health surveillance, and outbreak investigation. However, scientific researchers without the relevant background lack the time, training, or infrastructure to use large data sets or install and use command line tools. Therefore, the bioinformatic team at the Chinese Center for Disease Control and Prevention developed the Microbial Data Analysis Cloud Platform (MDACP) as a safe, professional, and efficient pathogen genetic data analysis platform for rapid microbial data mining, such as for candidate pathogen detection, genome typing, and traceability. MDACP is a web service system based on the Docker platform and can be used for data analysis on various operating systems. The platform focuses on pathogen analysis and continuously develops new analysis processes according to the analysis needs of the users. This platform has a friendly user interface and is easy to operate, allowing users to submit data through data pages or graphical clients, flexibly control parameters according to data conditions, and analyze data in parallel with multiple tasks. Researchers can quickly carry out bioinformatic analyses without coding work, promote follow-up research and information mining of projects, and improve the utilization of big data in the field of disease control. MDACP enables research personnel to conduct data analysis and management and assists clinicians and disease control personnel with mining information, such as pathogen identification, classification, and traceability.

Perceived utility and feasibility of pathogen genomics for public health practice: a survey among public health professionals working in the field of infectious diseases, Belgium, 2019

BACKGROUND

Pathogen genomics is increasingly being translated from the research setting into the activities of public health professionals operating at different levels. This survey aims to appraise the literacy level and gather the opinions of public health experts and allied professionals working in the field of infectious diseases in Belgium concerning the implementation of next-generation sequencing (NGS) in public health practice.

METHODS

In May 2019, Belgian public health and healthcare professionals were invited to complete an online survey containing eight main topics including background questions, general attitude towards pathogen genomics for public health practice and main concerns, genomic literacy, current and planned NGS activities, place of NGS in diagnostic microbiology pathways, data sharing obstacles, end-user requirements, and key drivers for the implementation of NGS. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic analysis was used to analyze free text responses. A multivariable logistic regression model was constructed to identify important predictors for a positive attitude towards the implementation of pathogen genomics in public health practice.

RESULTS

146 out of the 753 invited public health professionals completed the survey. 63% of respondents indicated that public health agencies should be using genomics to understand and control infectious diseases. Having a high level of expertise in the field of pathogen genomics was the strongest predictor of a positive attitude (OR = 4.04, 95% CI = 1.11 - 17.23). A significantly higher proportion of data providers indicated to have followed training in the field of pathogen genomics compared to data end-users (p < 0.001). Overall, 79% of participants expressed interest in receiving further training. Main concerns were related to the cost of sequencing technologies, data sharing, data integration, interdisciplinary working, and bioinformatics expertise.

CONCLUSIONS

Belgian health professionals expressed favorable views about implementation of pathogen genomics in their work activities related to infectious disease surveillance and control. They expressed the need for suitable training initiatives to strengthen their competences in the field. Their perception of the utility and feasibility of pathogen genomics for public health purposes will be a key driver for its further implementation.

Enterococcus faecium: from microbiological insights to practical recommendations for infection control and diagnostics

Early in its evolution, Enterococcus faecium acquired traits that allowed it to become a successful nosocomial pathogen. E. faecium inherent tenacity to build resistance to antibiotics and environmental stressors that allows the species to thrive in hospital environments. The continual wide use of antibiotics in medicine has been an important driver in the evolution of E. faecium becoming a highly proficient hospital pathogen.For successful prevention and reduction of nosocomial infections with vancomycin resistant E. faecium (VREfm), it is essential to focus on reducing VREfm carriage and spread. The aim of this review is to incorporate microbiological insights of E. faecium into practical infection control recommendations, to reduce the spread of hospital-acquired VREfm (carriage and infections). The spread of VREfm can be controlled by intensified cleaning procedures, antibiotic stewardship, rapid screening of VREfm carriage focused on high-risk populations, and identification of transmission routes through accurate detection and typing methods in outbreak situations. Further, for successful management of E. faecium, continual innovation in the fields of diagnostics, treatment, and eradication is necessary.

The Benefits of Whole Genome Sequencing for Foodborne Outbreak Investigation from the Perspective of a National Reference Laboratory in a Smaller Country

Gradually, conventional methods for foodborne pathogen typing are replaced by whole genome sequencing (WGS). Despite studies describing the overall benefits, National Reference Laboratories of smaller countries often show slower uptake of WGS, mainly because of significant investments required to generate and analyze data of a limited amount of samples. To facilitate this process and incite policy makers to support its implementation, a Shiga toxin-producing Escherichia coli (STEC) O157:H7 (stx1+, stx2+, eae+) outbreak (2012) and a STEC O157:H7 (stx2+, eae+) outbreak (2013) were retrospectively analyzed using WGS and compared with their conventional investigations. The corresponding results were obtained, with WGS delivering even more information, e.g., on virulence and antimicrobial resistance genotypes. Besides a universal, all-in-one workflow with less hands-on-time (five versus seven actual working days for WGS versus conventional), WGS-based cgMLST-typing demonstrated increased resolution. This enabled an accurate cluster definition, which remained unsolved for the 2013 outbreak, partly due to scarce epidemiological linking with the suspect source. Moreover, it allowed detecting two and one earlier circulating STEC O157:H7 (stx1+, stx2+, eae+) and STEC O157:H7 (stx2+, eae+) strains as closely related to the 2012 and 2013 outbreaks, respectively, which might have further directed epidemiological investigation initially. Although some bottlenecks concerning centralized data-sharing, sampling strategies, and perceived costs should be considered, we delivered a proof-of-concept that even in smaller countries, WGS offers benefits for outbreak investigation, if a sufficient budget is available to ensure its implementation in surveillance. Indeed, applying a database with background isolates is critical in interpreting isolate relationships to outbreaks, and leveraging the true benefit of WGS in outbreak investigation and/or prevention.