A pilot study of rapid benchtop sequencing of Staphylococcus aureus and Clostridium difficile for outbreak detection and surveillance

The Use of Next-Generation Sequencing in Personalized Medicine

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Evaluation of nationwide analysis surveillance for methicillin-resistant Staphylococcus aureus within Genomic Medicine Sweden

Background. National epidemiological investigations of microbial infections greatly benefit from the increased information gained by whole-genome sequencing (WGS) in combination with standardized approaches for data sharing and analysis.Aim. To evaluate the quality and accuracy of WGS data generated by different laboratories but analysed by joint pipelines to reach a national surveillance approach.Methods. A national methicillin-resistant Staphylococcus aureus (MRSA) collection of 20 strains was distributed to nine participating laboratories that performed in-house procedures for WGS. Raw data were shared and analysed by three pipelines: 1928 Diagnostics, JASEN (GMS pipeline) and CLC-Genomics Workbench. The outcomes were compared according to quality, correct strain identification and genetic distances.Results. One isolate contained intraspecies contamination and was excluded from further analysis. The mean sequencing depth varied between sites and technologies. However, all analysis methods identified 12 strains that belonged to one of five outbreak clusters. The cut-off definition was set to <10 allele differences for core genome multilocus sequence typing (cgMLST) and <20 genetic differences for SNP analysis in a pairwise comparison.Conclusions. MRSA isolates, which are whole genome sequenced by different laboratories and analysed using the same bioinformatic pipelines, yielded comparable results for outbreak clustering for both cgMLST and SNP, using the 1928 analysis pipeline. In this study, JASEN was best suited to analyse Illumina data and CLC to analyse within respective technology. In the future, real-time sharing of data and harmonized analysis within the Genomic Medicine Sweden consortium will further facilitate investigations of outbreaks and transmission routes.

Understanding the potential role of whole genome sequencing (WGS) in managing patients with gonorrhoea: A systematic review of WGS use on human pathogens in individual patient care

OBJECTIVES

The utility of whole genome sequencing (WGS) to inform sexually transmitted infection (STI) patient management is unclear. Timely WGS data might support clinical management of STIs by characterising epidemiological links and antimicrobial resistance profiles. We conducted a systematic review of clinical application of WGS to any human pathogen that may be transposable to gonorrhoea.

METHODS

We searched six databases for articles published between 01/01/2010-06/02/2023 that reported on real/near real-time human pathogen WGS to inform clinical intervention. All article types from all settings were included. Findings were analysed using narrative synthesis.

RESULTS

We identified 12,179 articles, of which eight reported applications to inform tuberculosis (n = 7) and gonorrhoea (n = 1) clinical patient management. WGS data were successfully used as an adjunct to clinical and epidemiological data to enhance contact-tracing (n = 2), inform antimicrobial therapy (n = 5) and identify cross-contamination (n = 1). WGS identified gonorrhoea transmission chains that were not established via partner notification. Future applications could include insights into pathogen exposure detected within sexual networks for targeted patient management.

CONCLUSIONS

While there was some evidence of WGS use to provide individualised tuberculosis and gonorrhoea treatment, the eight identified studies contained few participants. Future research should focus on testing WGS intervention effectiveness and examining ethical considerations of STI WGS use.

Strain Differences in Bloodstream and Skin Infection: Methicillin-Resistant Staphylococcus aureus Isolated in 2018-2021 in a Single Health System

Staphylococcus aureus is a common cause of skin and soft-tissue infections (SSTIs) and has become the most common cause of bloodstream infections (BSIs) in recent years, but whether the strains causing these two clinical syndromes overlap has not been studied adequately. USA300/500 (clonal complex [CC] 8-sequence type [ST] 8) and USA100 (CC5-ST5) have dominated among methicillin-resistant S aureus (MRSA) strains in the United States since the early 2000s. We compared the genomes of unselected MRSA isolates from 131 SSTIs with those from 145 BSIs at a single US center in overlapping periods in 2018-2021. CC8 MRSA was more common among SSTIs, and CC5 was more common among BSIs, consistent with prior literature. Based on clustering genomes with a threshold of 15 single-nucleotide polymorphisms, we identified clusters limited to patients with SSTI and separate clusters exclusively comprising patients with BSIs. However, we also identified eight clusters that included at least one SSTI and one BSI isolate. This suggests that virulent MRSA strains are transmitted from person to person locally in the healthcare setting or the community and that single lineages are often capable of causing both SSTIs and BSIs.

Uncovering the spread of drug-resistant bacteria through next-generation sequencing based surveillance: transmission of extended-spectrum β-lactamase-producing Enterobacterales by a contaminated duodenoscope

Contamination of duodenoscopes is a significant concern due to the transmission of multidrug-resistant organisms (MDROs) among patients who undergo endoscopic retrograde cholangiopancreatography (ERCP), resulting in outbreaks worldwide. In July 2020, it was determined that three different patients, all had undergone ERCP with the same duodenoscope, were infected. Two patients were infected with blaCTX-M-15 encoding Citrobacter freundii, one experiencing a bloodstream infection and the other a urinary tract infection, while another patient had a bloodstream infection caused by blaSHV-12 encoding Klebsiella pneumoniae. Molecular characterization of isolates was available as every ESBL-producing isolate undergoes Next-Generation Sequencing (NGS) for comprehensive genomic analysis in our center. After withdrawing the suspected duodenoscope, we initiated comprehensive epidemiological research, encompassing case investigations, along with a thorough duodenoscope investigation. Screening of patients who had undergone ERCP with the implicated duodenoscope, as well as a selection of hospitalized patients who had ERCP with a different duodenoscope during the outbreak period, led to the discovery of three additional cases of colonization in addition to the three infections initially detected. No microorganisms were detected in eight routine culture samples retrieved from the suspected duodenoscope. Only after destructive dismantling of the duodenoscope, the forceps elevator was found to be positive for blaSHV-12 encoding K. pneumoniae which was identical to the isolates detected in three patients. This study highlights the importance of using NGS to monitor the transmission of MDROs and demonstrates that standard cultures may fail to detect contaminated medical equipment such as duodenoscopes.

The use of next-generation sequencing in personalized medicine

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

Comparative Genomics of Clostridioides difficile

Clostridioides difficile, a Gram-positive spore-forming anaerobic bacterium, has rapidly emerged as the leading cause of nosocomial diarrhoea in hospitals. The availability of large numbers of genome sequences, mainly due to the use of next-generation sequencing methods, has undoubtedly shown their immense advantages in the determination of C. difficile population structure. The implementation of fine-scale comparative genomic approaches has paved the way for global transmission and recurrence studies, as well as more targeted studies, such as the PaLoc or CRISPR/Cas systems. In this chapter, we provide an overview of recent and significant findings on C. difficile using comparative genomic studies with implications for epidemiology, infection control and understanding of the evolution of C. difficile.

Antibiotic Susceptibility Profiling of Human Pathogenic Staphylococcus aureus Strains Using Whole Genome Sequencing and Genome-Scale Annotation Approaches

Staphylococcus species are major pathogens with increasing importance due to the rise in antibiotic resistance. Whole genome sequencing and genome-scale annotation are promising approaches to study the pathogenicity and dissemination of virulence factors in nosocomial methicillin-resistant and multidrug-resistant bacteria in intensive care units. Draft genome sequences of eight clinical S. aureus strains were assembled and annotated for the prediction of antimicrobial resistance genes, virulence factors, and phylogenetic analysis. Most of the studied S. aureus strains displayed multi-resistance toward the tested drugs, reaching more than seven drugs up to 12 in isolate S22. The mecA gene was detected in three isolates (S14, S21, and S23), mecC was identified in S8 and S9, and blaZ was commonly identified in all isolates except strain S23. Additionally, two complete mobile genomic islands coding for methicillin resistance SCCmec Iva (2B) were identified in strains S21 and S23. Numerous antimicrobial resistance genes (norA, norC, MgrA, tet(45), APH(3')-IIIa, and AAC(6')-APH(2″)) were identified in chromosomes of different strains. Plasmid analysis revealed the presence of blaZ, tetK, and ermC in different plasmid types, located in gene cassettes containing plasmid replicons (rep) and insertion sequences (IS). Additionally, the aminoglycoside-resistant determinants were identified in S1 (APH(3')-IIIa), while AAC(6)-APH(2″) was detected in strains S8 and S14. The trimethoprim (dfrC) resistance gene was detected in S. aureus S21, and the fosfomycin (fosB) resistance gene was detected only in S. aureus S14. We also noted that S. aureus S1 belongs to ST1-t127, which has been reported as one of the most frequent human pathogen types. Additionally, we noted the presence of rare plasmid-mediated mecC-MRSA in some of our isolates.

Advances in the Microbiological Diagnosis of Prosthetic Joint Infections

A significant number of prosthetic joint infections (PJI) are culture-negative and/or misinterpreted as aseptic failures in spite of the correct implementation of diagnostic culture techniques, such as tissue sample processing in a bead mill, prolonged incubation time, or sonication of removed implants. Misinterpretation may lead to unnecessary surgery and needless antimicrobial treatment. The diagnostic value of non-culture techniques has been investigated in synovial fluid, periprosthetic tissues, and sonication fluid. Different feasible improvements, such as real-time technology, automated systems and commercial kits are now available to support microbiologists. In this review, we describe non-culture techniques based on nucleic acid amplification and sequencing methods. Polymerase chain reaction (PCR) is a frequently used technique in most microbiology laboratories which allows the detection of a nucleic acid fragment by sequence amplification. Different PCR types can be used to diagnose PJI, each one requiring the selection of appropriate primers. Henceforward, thanks to the reduced cost of sequencing and the availability of next-generation sequencing (NGS), it will be possible to identify the whole pathogen genome sequence and, additionally, to detect all the pathogen sequences present in the joint. Although these new techniques have proved helpful, strict conditions need to be observed in order to detect fastidious microorganisms and rule out contaminants. Specialized microbiologists should assist clinicians in interpreting the result of the analyses at interdisciplinary meetings. New technologies will gradually be made available to improve the etiologic diagnoses of PJI, which will remain an important cornerstone of treatment. Strong collaboration among all specialists involved is essential for the correct diagnosis of PJI.

Factors affecting turnaround time of SARS-CoV-2 sequencing for inpatient infection prevention and control decision making: analysis of data from the COG-UK HOCI study

BACKGROUND

Barriers to rapid return of sequencing results can affect the utility of sequence data for infection prevention and control decisions.

AIM

To undertake a mixed-methods analysis to identify challenges that sites faced in achieving a rapid turnaround time (TAT) in the COVID-19 Genomics UK Hospital-Onset COVID-19 Infection (COG-UK HOCI) study.

METHODS

For the quantitative analysis, timepoints relating to different stages of the sequencing process were extracted from both the COG-UK HOCI study dataset and surveys of study sites. Qualitative data relating to the barriers and facilitators to achieving rapid TATs were included from thematic analysis.

FINDINGS

The overall TAT, from sample collection to receipt of sequence report by infection control teams, varied between sites (median 5.1 days, range 3.0-29.0 days). Most variation was seen between reporting of a positive COVID-19 polymerase chain reaction (PCR) result to sequence report generation (median 4.0 days, range 2.3-27.0 days). On deeper analysis, most of this variability was accounted for by differences in the delay between the COVID-19 PCR result and arrival of the sample at the sequencing laboratory (median 20.8 h, range 16.0-88.7 h). Qualitative analyses suggest that closer proximity of sequencing laboratories to diagnostic laboratories, increased staff flexibility and regular transport times facilitated a shorter TAT.

CONCLUSION

Integration of pathogen sequencing into diagnostic laboratories may help to improve sequencing TAT to allow sequence data to be of tangible value to infection control practice. Adding a quality control step upstream to increase capacity further down the workflow may also optimize TAT if lower quality samples are removed at an earlier stage.

Unsuspected Clonal Spread of Methicillin-Resistant Staphylococcus aureus Causing Bloodstream Infections in Hospitalized Adults Detected Using Whole Genome Sequencing

BACKGROUND

Though detection of transmission clusters of methicillin-resistant Staphylococcus aureus (MRSA) infections is a priority for infection control personnel in hospitals, the transmission dynamics of MRSA among hospitalized patients with bloodstream infections (BSIs) has not been thoroughly studied. Whole genome sequencing (WGS) of MRSA isolates for surveillance is valuable for detecting outbreaks in hospitals, but the bioinformatic approaches used are diverse and difficult to compare.

METHODS

We combined short-read WGS with genotypic, phenotypic, and epidemiological characteristics of 106 MRSA BSI isolates collected for routine microbiological diagnosis from inpatients in 2 hospitals over 12 months. Clinical data and hospitalization history were abstracted from electronic medical records. We compared 3 genome sequence alignment strategies to assess similarity in cluster ascertainment. We conducted logistic regression to measure the probability of predicting prior hospital overlap between clustered patient isolates by the genetic distance of their isolates.

RESULTS

While the 3 alignment approaches detected similar results, they showed some variation. A gene family-based alignment pipeline was most consistent across MRSA clonal complexes. We identified 9 unique clusters of closely related BSI isolates. Most BSIs were healthcare associated and community onset. Our logistic model showed that with 13 single-nucleotide polymorphisms, the likelihood that any 2 patients in a cluster had overlapped in a hospital was 50%.

CONCLUSIONS

Multiple clusters of closely related MRSA isolates can be identified using WGS among strains cultured from BSI in 2 hospitals. Genomic clustering of these infections suggests that transmission resulted from a mix of community spread and healthcare exposures long before BSI diagnosis.

Make It Less difficile: Understanding Genetic Evolution and Global Spread of Clostridioides difficile

Clostridioides difficile is an obligate anaerobic pathogen among the most common causes of healthcare-associated infections. It poses a global threat due to the clinical outcomes of infection and resistance to antibiotics recommended by international guidelines for its eradication. In particular, C. difficile infection can lead to fulminant colitis associated with shock, hypotension, megacolon, and, in severe cases, death. It is therefore of the utmost urgency to fully characterize this pathogen and better understand its spread, in order to reduce infection rates and improve therapy success. This review aims to provide a state-of-the-art overview of the genetic variation of C. difficile, with particular regard to pathogenic genes and the correlation with clinical issues of its infection. We also summarize the current typing techniques and, based on them, the global distribution of the most common ribotypes. Finally, we discuss genomic surveillance actions and new genetic engineering strategies as future perspectives to make it less difficile.

Whole-Genome Sequencing of Staphylococcus aureus and Staphylococcus haemolyticus Clinical Isolates from Egypt

Infections caused by antibiotic-resistant Staphylococcus are a global concern. This is true in the Middle East, where increasingly resistant Staphylococcus aureus and Staphylococcus haemolyticus strains have been detected. While extensive surveys have revealed the prevalence of infections caused by antibiotic-resistant staphylococci in Europe, Asia, and North America, the population structure of antibiotic-resistant staphylococci recovered from patients and clinical settings in Egypt remains uncharacterized. We performed whole-genome sequencing of 56 S. aureus and 10 S. haemolyticus isolates from Alexandria Main University Hospital; 46 of the S. aureus genomes and all 10 of the S. haemolyticus genomes carry mecA, which confers methicillin resistance. Supplemented with additional publicly available genomes from the other parts of the Middle East (34 S. aureus and 6 S. haemolyticus), we present the largest genomic study to date of staphylococcal isolates from the Middle East. These genomes include 20 S. aureus multilocus sequence types (MLST), including 3 new ones. They also include 9 S. haemolyticus MLSTs, including 1 new one. Phylogenomic analyses of each species' core genome largely mirrored those of the MLSTs, irrespective of geographical origin. The hospital-acquired spa t037/ST239-SCCmec III/MLST CC8 clone represented the largest clade, comprising 22% of the S. aureus isolates. Like S. aureus genome surveys of other regions, these isolates from the Middle East have an open pangenome, a strong indicator of gene exchange of virulence factors and antibiotic resistance genes with other reservoirs. Our genome analyses will inform antibiotic stewardship and infection control plans in the Middle East. IMPORTANCE Staphylococci are understudied despite their prevalence within the Middle East. Methicillin-resistant Staphylococcus aureus (MRSA) is endemic to hospitals in Egypt, as are other antibiotic-resistant strains of S. aureus and S. haemolyticus. To provide insight into the strains circulating in Egypt, we performed whole-genome sequencing of 56 S. aureus and 10 S. haemolyticus isolates from Alexandria Main University Hospital. Through analysis of these genomes, as well as all available S. aureus and S. haemolyticus genomes from the Middle East (n = 40), we were able to produce a picture of the diversity in this region more complete than those afforded by traditional molecular typing strategies. For example, we identified 4 new MLSTs. Most strains harbored genes associated with multidrug resistance, toxin production, biofilm formation, and immune evasion. These data provide invaluable insight for future antibiotic stewardship and infection control within the Middle East.

Evaluation of within-host evolution of methicillin-resistant Staphylococcus aureus (MRSA) by comparing cgMLST and SNP analysis approaches

Whole genome sequencing (WGS) of methicillin-resistant Staphylococcus aureus (MRSA) provides high-resolution typing, facilitating surveillance and outbreak investigations. The aim of this study was to evaluate the genomic variation rate in MRSA, by comparing commonly used core genome multilocus sequencing (cgMLST) against single nucleotide polymorphism (SNP) analyses. WGS was performed on 95 MRSA isolates, collected from 20 carriers during years 2003–2019. To assess variation and methodological-related differences, two different cgMLST schemes were obtained using Ridom SeqSphere+ and the cloud-based 1928 platform. In addition, two SNP methods, 1928 platform and Northern Arizona SNP Pipeline (NASP) were used. The cgMLST using Ridom SeqSphere+ and 1928 showed a median of 5.0 and 2.0 allele variants/year, respectively. In the SNP analysis, performed with two reference genomes COL and Newman, 1928 showed a median of 13 and 24 SNPs (including presumed recombination) and 3.8 respectively 4.0 SNPs (without recombination) per individual/year. Accordantly, NASP showed a median of 5.5 and 5.8 SNPs per individual/year. In conclusion, an estimated genomic variation rate of 2.0–5.8 genetic events per year (without recombination), is suggested as a general guideline to be used at clinical laboratories for surveillance and outbreak investigations independently of analysis approach used.

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.

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.

Probabilistic modelling of effects of antibiotics and calendar time on transmission of healthcare-associated infection

Healthcare-associated infection and antimicrobial resistance are major concerns. However, the extent to which antibiotic exposure affects transmission and detection of infections such as MRSA is unclear. Additionally, temporal trends are typically reported in terms of changes in incidence, rather than analysing underling transmission processes. We present a data-augmented Markov chain Monte Carlo approach for inferring changing transmission parameters over time, screening test sensitivity, and the effect of antibiotics on detection and transmission. We expand a basic model to allow use of typing information when inferring sources of infections. Using simulated data, we show that the algorithms are accurate, well-calibrated and able to identify antibiotic effects in sufficiently large datasets. We apply the models to study MRSA transmission in an intensive care unit in Oxford, UK with 7924 admissions over 10 years. We find that falls in MRSA incidence over time were associated with decreases in both the number of patients admitted to the ICU colonised with MRSA and in transmission rates. In our inference model, the data were not informative about the effect of antibiotics on risk of transmission or acquisition of MRSA, a consequence of the limited number of possible transmission events in the data. Our approach has potential to be applied to a range of healthcare-associated infections and settings and could be applied to study the impact of other potential risk factors for transmission. Evidence generated could be used to direct infection control interventions.

Assessment of Genetic Stability During Serial In Vitro Passage and In Vivo Carriage

In this study, our objective was to evaluate the genetic stability of foodborne bacterial pathogens during serial passage in vitro and persistent in vivo carriage. Six strains of Listeria, Campylobacter, Escherichia, Salmonella, and Vibrio were serially passaged 20 times. Three colonies were picked for whole-genome sequencing (WGS) from passes P0, P5, P10, P15, and P20. In addition, isolates of Salmonella and Escherichia from three patients with persistent infections were sequenced. Genetic stability was evaluated in terms of variations detected in high-quality single-nucleotide polymorphism (hqSNP), core genome multilocus sequence typing (cgMLST), seven-gene MLST, and determinants encoding serotype, antimicrobial resistance (AMR), and virulence. During serial passage, increasing diversity was observed in Listeria, Salmonella, and Vibrio as measured by hqSNPs (from median of 0 SNPs to median of 3-5 SNPs, depending on the organism) and to a lesser extent with cgMLST (from median of 0 alleles to median of 0-5 alleles), while Escherichia and Campylobacter genomes showed minimal variation. The serotype, AMR, and virulence markers remained stable in all organisms. Isolates from persistent infections lasting up to 10 weeks remained genetically stable. However, isolates from a persistent Salmonella enterica ser. Montevideo infection spanning 9 years showed early heterogeneity leading to the emergence of one predominant genotype that continued to evolve over the years, including gains and losses of AMR markers. While the hqSNP and cgMLST variation observed during the serial passage was minimal, culture passages should be limited to as few times as possible before WGS. Our WGS data show that in vivo carriage lasting for a few weeks did not appear to alter the genotype. Longer persistent infections spanning for years, particularly in the presence of selective pressure, may cause changes in the genotype making it challenging to differentiate persistent infections from reinfections.

Outbreaks in Health Care Settings

Outbreaks and pseudo-outbreaks in health care settings are complex and should be evaluated systematically using epidemiologic and molecular tools. Outbreaks result from failures of infection prevention practices, inadequate staffing, and undertrained or overcommitted health care personnel. Contaminated hands, equipment, supplies, water, ventilation systems, and environment may also contribute. Neonatal intensive care, endoscopy, oncology, and transplant units are areas at particular risk. Procedures, such as bronchoscopy and endoscopy, are sources of infection when cleaning and disinfection processes are inadequate. New types of equipment can be introduced and lead to contamination or equipment and medications can be contaminated at the manufacturing source.

Water pre-filtration methods to improve environmental DNA detection by real-time PCR and metabarcoding

Environmental DNA (eDNA) analysis is a novel approach for biomonitoring and has been mostly used in clear water. It is difficult to detect eDNA in turbid water as filter clogging occurs, and environmental samples contain various substances that inhibit the polymerase chain reaction (PCR) and affect the accuracy of eDNA analysis. Therefore, we applied a pre-filtration method to better detect the fish species (particularly pale chub, Opsariichthys platypus) present in a water body by measuring eDNA in environmental samples containing PCR inhibitors. Upon conducting 12S rRNA metabarcoding analysis (MiFish), we found that pre-filtration did not affect the number or identities of fish species detected in our samples, but pre-filtration through pore sizes resulted in significantly reduced variance among replicate samples. Additionally, PCR amplification was improved by the pre-filtration of environmental samples containing PCR inhibitors such as humic substances. Although this study may appear to be a conservative and ancillary experiment, pre-filtration is a simple technique that can not only improve the physical properties of water, such as turbidity, but also the quality of eDNA biomonitoring.

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.

Identification of Hidden Population Structure in Time-Scaled Phylogenies

Population structure influences genealogical patterns, however, data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealized genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance. [Antimicrobial resistance; coalescent; HIV; population structure.].

Whole genome sequencing of Clostridioides difficile PCR ribotype 046 suggests transmission between pigs and humans

Background

A zoonotic association has been suggested for several PCR ribotypes (RTs) of Clostridioides difficile. In central parts of Sweden, RT046 was found dominant in neonatal pigs at the same time as a RT046 hospital C. difficile infection (CDI) outbreak occurred in the southern parts of the country.

Objective

To detect possible transmission of RT046 between pig farms and human CDI cases in Sweden and investigate the diversity of RT046 in the pig population using whole genome sequencing (WGS).

Methods

WGS was performed on 47 C. difficile isolates from pigs (n = 22), the farm environment (n = 7) and human cases of CDI (n = 18). Two different core genome multilocus sequencing typing (cgMLST) schemes were used together with a single nucleotide polymorphisms (SNP) analysis and the results were related to time and location of isolation of the isolates.

Results

The pig isolates were closely related (≤6 cgMLST alleles differing in both cgMLST schemes) and conserved over time and were clearly separated from isolates from the human hospital outbreak (≥76 and ≥90 cgMLST alleles differing in the two cgMLST schemes). However, two human isolates were closely related to the pig isolates, suggesting possible transmission. The SNP analysis was not more discriminate than cgMLST.

Conclusion

No general pattern suggesting zoonotic transmission was apparent between pigs and humans, although contrasting results from two isolates still make transmission possible. Our results support the need for high resolution WGS typing when investigating hospital and environmental transmission of C. difficile.

PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks

Background

Whole-genome sequencing (WGS) is increasingly used to map the spread of bacterial and viral pathogens in nosocomial settings. A limiting factor for more widespread adoption of WGS for hospital infection prevention practices is the availability of standardized tools for genomic epidemiology.

Methods

We developed the Pathogen Sequencing Phylogenomic Outbreak Toolkit (PathoSPOT) to automate integration of genomic and medical record data for rapid detection and tracing of nosocomial outbreaks. To demonstrate its capabilities, we applied PathoSPOT to complete genome surveillance data of 197 MRSA bacteremia cases from two hospitals during a 2-year period.

Results

PathoSPOT identified 8 clonal clusters encompassing 33 patients (16.8% of cases), none of which had been recognized by standard practices. The largest cluster corresponded to a prolonged outbreak of a hospital-associated MRSA clone among 16 adults, spanning 9 wards over a period of 21 months. Analysis of precise timeline and location data with our toolkit suggested that an initial exposure event in a single ward led to infection and long-term colonization of multiple patients, followed by transmissions to other patients during recurrent hospitalizations.

Conclusions

We demonstrate that PathoSPOT genomic surveillance enables the detection of complex transmission chains that are not readily apparent from epidemiological data and that contribute significantly to morbidity and mortality, enabling more effective intervention strategies.

Efflux pump activity potentiates the evolution of antibiotic resistance across S. aureus isolates

The rise of antibiotic resistance in many bacterial pathogens has been driven by the spread of a few successful strains, suggesting that some bacteria are genetically pre-disposed to evolving resistance. Here, we test this hypothesis by challenging a diverse set of 222 isolates of Staphylococcus aureus with the antibiotic ciprofloxacin in a large-scale evolution experiment. We find that a single efflux pump, norA, causes widespread variation in evolvability across isolates. Elevated norA expression potentiates evolution by increasing the fitness benefit provided by DNA topoisomerase mutations under ciprofloxacin treatment. Amplification of norA provides a further mechanism of rapid evolution in isolates from the CC398 lineage. Crucially, chemical inhibition of NorA effectively prevents the evolution of resistance in all isolates. Our study shows that pre-existing genetic diversity plays a key role in shaping resistance evolution, and it may be possible to predict which strains are likely to evolve resistance and to optimize inhibitor use to prevent this outcome.

Detection of mixed-strain infections by FACS and ultra-low input genome sequencing

The epidemiological tracking of a bacterial outbreak may be jeopardized by the presence of multiple pathogenic strains in one patient. Nevertheless, this fact is not considered in most of the epidemiological studies and only one colony per patient is sequenced. On the other hand, the routine whole genome sequencing of many isolates from each patient would be costly and unnecessary, because the number of strains in a patient is never known a priori. In addition, the result would be biased by microbial culture conditions. Herein we propose an approach for detecting mixed-strain infection, providing C. difficile infection as an example. The cells of the target pathogenic species are collected from the bacterial suspension by the fluorescence activated cell sorting (FACS) and a shallow genome sequencing is performed. A modified sequencing library preparation protocol for low-input DNA samples can be used for low prevalence gut pathogens (< 0.1% of the total microbiome). This FACS-seq approach reduces diagnostics time (no culture is needed) and may promote discoveries of novel strains. Methodological details, possible issues and future directions for the sequencing of these natural pan-genomes are herein discussed.

Defining metrics for whole-genome sequence analysis of MRSA in clinical practice

Bacterial sequencing will become increasingly adopted in routine microbiology laboratories. Here, we report the findings of a technical evaluation of almost 800 clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates, in which we sought to define key quality metrics to support MRSA sequencing in clinical practice. We evaluated the accuracy of mapping to a generic reference versus clonal complex (CC)-specific mapping, which is more computationally challenging. Focusing on isolates that were genetically related (<50 single nucleotide polymorphisms (SNPs)) and belonged to prevalent sequence types, concordance between these methods was 99.5 %. We use MRSA MPROS0386 to control for base calling accuracy by the sequencer, and used multiple repeat sequences of the control to define a permitted range of SNPs different to the mapping reference for this control (equating to 3 standard deviations from the mean). Repeat sequences of the control were also used to demonstrate that SNP calling was most accurate across differing coverage depths (above 35×, the lowest depth in our study) when the depth required to call a SNP as present was at least 4-8×. Using 786 MRSA sequences, we defined a robust measure for mec gene detection to reduce false-positives arising from contamination, which was no greater than 2 standard deviations below the average depth of coverage across the genome. Sequencing from bacteria harvested from clinical plates runs an increased risk of contamination with the same or different species, and we defined a cut-off of 30 heterozygous sites >50 bp apart to identify same-species contamination for MRSA. These metrics were combined into a quality-control (QC) flowchart to determine whether sequence runs and individual clinical isolates passed QC, which could be adapted by future automated analysis systems to enable rapid hands-off sequence analysis by clinical laboratories.

Global and Historical Distribution of Clostridioides difficile in the Human Diet (1981-2019): Systematic Review and Meta-Analysis of 21886 Samples Reveal Sources of Heterogeneity, High-Risk Foods, and Unexpected Higher Prevalence Toward the Tropic

Clostridioides difficile (CD) is a spore-forming bacterium that causes life-threatening intestinal infections in humans. Although formerly regarded as exclusively nosocomial, there is increasing genomic evidence that person-to-person transmission accounts for only <25% of cases, supporting the culture-based hypothesis that foods may be routine sources of CD-spore ingestion in humans. To synthesize the evidence on the risk of CD exposure via foods, we conducted a systematic review and meta-analysis of studies reporting the culture prevalence of CD in foods between January 1981 and November 2019. Meta-analyses, risk-ratio estimates, and meta-regression were used to estimate weighed-prevalence across studies and food types to identify laboratory and geographical sources of heterogeneity. In total, 21886 food samples were tested for CD between 1981 and 2019 (96.4%, n = 21084, 2007–2019; 232 food-sample-sets; 79 studies; 25 countries). Culture methodology, sample size and type, region, and latitude were sources of heterogeneity (p < 0.05). Although non-strictly-anaerobic methods were reported in some studies, and we confirmed experimentally that improper anaerobiosis of media/sample-handling affects CD recovery in agar (Fisher, p < 0.01), most studies (>72%) employed the same (one-of-six) culture strategy. Because the prevalence was also meta-analytically similar across six culture strategies reported, all studies were integrated using three meta-analytical methods. At the study level (n = 79), the four-decade global cumulative-prevalence of CD in the human diet was 4.1% (95%CI = −3.71, 11.91). At the food-set level (n = 232, mean 12.9 g/sample, similar across regions p > 0.2; 95%CI = 9.7–16.2), the weighted prevalence ranged between 4.5% (95%CI = 3–6%; all studies) and 8% (95%CI = 7–8%; only CD-positive-studies). Risk-ratio ranking and meta-regression showed that milk was the least likely source of CD, while seafood, leafy green vegetables, pork, and poultry carried higher risks (p < 0.05). Across regions, the risk of CD in foods for foodborne exposure reproducibly decreased with Earth latitude (p < 0.001). In conclusion, CD in the human diet is a global non-random-source of foodborne exposure that occurs independently of laboratory culture methods, across regions, and at a variable level depending on food type and latitude. The latitudinal trend (high CD-food-prevalence toward tropic) is unexpectedly inverse to the epidemiological observations of CD-infections in humans (frequent in temperate regions). Findings suggest the plausible hypothesis that ecologically-richer microbiomes in the tropic might protect against intestinal CD colonization/infections despite CD ingestion.

Clostridium difficile: Investigating Transmission Patterns Between Infected and Colonized Patients Using Whole Genome Sequencing

Background

Whole genome sequencing (WGS) studies can enhance our understanding of the role of patients with asymptomatic Clostridium difficile colonization in transmission.

Methods

Isolates obtained from patients with Clostridium difficile infection (CDI) and colonization identified in a study conducted during 2006-2007 at 6 Canadian hospitals underwent typing by pulsed-field gel electrophoresis, multilocus sequence typing, and WGS. Isolates from incident CDI cases not in the initial study were also sequenced where possible. Ward movement and typing data were combined to identify plausible donors for each CDI case, as defined by shared time and space within predefined limits. Proportions of plausible donors for CDI cases that were colonized, infected, or both were examined.

Results

Five hundred fifty-four isolates were sequenced successfully, 353 from colonized patients and 201 from CDI cases. The NAP1/027/ST1 strain was the most common strain, found in 124 (62%) of infected and 92 (26%) of colonized patients. A donor with a plausible ward link was found for 81 CDI cases (40%) using WGS with a threshold of ≤2 single nucleotide polymorphisms to determine relatedness. Sixty-five (32%) CDI cases could be linked to both infected and colonized donors. Exclusive linkages to infected and colonized donors were found for 28 (14%) and 12 (6%) CDI cases, respectively.

Conclusions

Colonized patients contribute to transmission, but CDI cases are more likely linked to other infected patients than colonized patients in this cohort with high rates of the NAP1/027/ST1 strain, highlighting the importance of local prevalence of virulent strains in determining transmission dynamics.

A Complete Genome Screening Program of Clinical Methicillin-Resistant Staphylococcus aureus Isolates Identifies the Origin and Progression of a Neonatal Intensive Care Unit Outbreak

Whole-genome sequencing (WGS) of Staphylococcus aureus is increasingly used as part of infection prevention practices. In this study, we established a long-read technology-based WGS screening program of all first-episode methicillin-resistant Staphylococcus aureus (MRSA) blood infections at a major urban hospital.

Whole-genome sequencing (WGS) of Staphylococcus aureus is increasingly used as part of infection prevention practices. In this study, we established a long-read technology-based WGS screening program of all first-episode methicillin-resistant Staphylococcus aureus (MRSA) blood infections at a major urban hospital. A survey of 132 MRSA genomes assembled from long reads enabled detailed characterization of an outbreak lasting several months of a CC5/ST105/USA100 clone among 18 infants in a neonatal intensive care unit (NICU). Available hospital-wide genome surveillance data traced the origins of the outbreak to three patients admitted to adult wards during a 4-month period preceding the NICU outbreak. The pattern of changes among complete outbreak genomes provided full spatiotemporal resolution of its progression, which was characterized by multiple subtransmissions and likely precipitated by equipment sharing between adults and infants. Compared to other hospital strains, the outbreak strain carried distinct mutations and accessory genetic elements that impacted genes with roles in metabolism, resistance, and persistence. This included a DNA recognition domain recombination in the hsdS gene of a type I restriction modification system that altered DNA methylation. Transcriptome sequencing (RNA-Seq) profiling showed that the (epi)genetic changes in the outbreak clone attenuated agr gene expression and upregulated genes involved in stress response and biofilm formation. Overall, our findings demonstrate the utility of long-read sequencing for hospital surveillance and for characterizing accessory genomic elements that may impact MRSA virulence and persistence.

Development and Implementation of Whole Genome Sequencing-Based Typing Schemes for Clostridioides difficile

Clostridioides difficile is an important nosocomial pathogen increasingly observed in the community and in different non-human reservoirs. The epidemiology and transmissibility of C. difficile has been studied using a variety of typing methods, including more recently developed whole-genome sequence (WGS) analysis that is becoming used routinely for bacterial typing worldwide. Here we review the schemes for WGS-based typing methods available for C. difficile and their applications in the field of human C. difficile infection (CDI). The two main approaches to discover genomic variations are single nucleotide variant (SNV) analysis and methods based on gene-by-gene comparisons (frequently called core genome or whole genome MLST, cgMLST, or wgMLST). SNV analysis currently provides the ultimate resolution, however, typing nomenclature and standardized methodology are missing. On the other hand, gene-by-gene approaches allow portability and standardized nomenclature, and are therefore becoming increasingly popular in bacterial epidemiology and outbreak investigation. Two commercial software packages (BioNumerics and Ridom SeqSphere+) and an open source database (EnteroBase) for allele and sequence type determination for C. difficile are currently available. Proof-of-concept WGS studies have already enabled advances in the investigation of the population structure of C. difficile species, microevolution within the epidemic strains, intercontinental transmission over time and in tracking of transmission events. WGS of clinical C. difficile isolates demonstrated a considerable genetic diversity suggesting diverse reservoirs for CDI. WGS was also shown to aid in resolving relapses and reinfections in recurrent CDI and has potential for use as a tool for assessing hospital infection prevention and control performance.

Whole genome analysis reveals new insights into the molecular characteristics of Clostridioides difficile NAP1/BI/027/ST1 clinical isolates in the People's Republic of China

Background: The epidemic new strain NAP1/BI/027/ST-1 of Clostridioides difficile (C. difficile) causes more severe coliti and a higher mortality rate than historical strains. However, C. difficile NAP1/BI/027/ST-1 (C. difficile RT027) infections have been rarely reported in Asia, particularly in China.

Purpose: The objective of this study was to strengthen the understanding of the molecular characterizations of C. difficile RT027 in China.

Patients and methods: Two C. difficile NAP1/BI/027/ST-1 were detected from two patients, and no additional isolates were found. Whole genome sequencing (WGS) was used to characterize two C. difficile RT027 isolates and control strain CD6 (from Hong Kong), and comparative genomic analysis was performed to compare genomic differences between seven isolates from Mainland China, CD6, and 10 isolates from North America and Europe.

Results: The comparative genomic analysis revealed that isolates obtained from Mainlan China were outside of the two epidemic lineages, FQR1 and FQR2, and might have decreased virulence and transmissibility for outbreak. Furthermore, unique SNP mutations were detected in isolates obtained from Mainland China, which may affect the biological function of C. difficile.

Conclusion: We speculate that C. difficile RT027 isolates in Mainland China may have different features, compared to those in North America and Europe.

Microfluidic-Based Nucleic Acid Amplification Systems in Microbiology

Rapid, sensitive, and selective bacterial detection is a hot topic, because the progress in this research area has had a broad range of applications. Novel and innovative strategies for detection and identification of bacterial nucleic acids are important for practical applications. Microfluidics is an emerging technology that only requires small amounts of liquid samples. Microfluidic devices allow for rapid advances in microbiology, enabling access to methods of amplifying nucleic acid molecules and overcoming difficulties faced by conventional. In this review, we summarize the recent progress in microfluidics-based polymerase chain reaction devices for the detection of nucleic acid biomarkers. The paper also discusses the recent development of isothermal nucleic acid amplification and droplet-based microfluidics devices. We discuss recent microfluidic techniques for sample preparation prior to the amplification process.

Next-generation sequencing of HIV-1 single genome amplicons

The analysis of HIV-1 sequences has helped understand the viral molecular epidemiology, monitor the development of antiretroviral drug resistance, and design candidate vaccines. The introduction of single genome amplification (SGA) has been a major advancement in the field, allowing for the characterization of multiple sequences per patient while preserving linkage among polymorphisms in the same viral genome copy. Sequencing of SGA amplicons is performed by capillary Sanger sequencing, which presents low throughput, requires a high amount of template, and is highly sensitive to template/primer mismatching. In order to meet the increasing demand for HIV-1 SGA amplicon sequencing, we have developed a platform based on benchtop next-generation sequencing (NGS) (IonTorrent) accompanied by a bioinformatics pipeline capable of running on computer resources commonly available at research laboratories. During assay validation, the NGS-based sequencing of 10 HIV-1 env SGA amplicons was fully concordant with Sanger sequencing. The field test was conducted on plasma samples from 10 US Navy and Marine service members with recent HIV-1 infection (sampling interval: 2005–2010; plasma viral load: 5,884–194,984 copies/ml). The NGS analysis of 101 SGA amplicons (median: 10 amplicons/individual) showed within-individual viral sequence profiles expected in individuals at this disease stage, including individuals with highly homogeneous quasispecies, individuals with two highly homogeneous viral lineages, and individuals with heterogeneous viral populations. In a scalability assessment using the Ion Chef automated system, 41/43 tested env SGA amplicons (95%) multiplexed on a single Ion 318 chip showed consistent gene-wide coverage >50×. With lower sample requirements and higher throughput, this approach is suitable to support the increasing demand for high-quality and cost-effective HIV-1 sequences in fields such as molecular epidemiology, and development of preventive and therapeutic strategies.

Genome-Based Prediction of Bacterial Antibiotic Resistance

Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences. We examine differences between calling antibiotic resistance profiles by the simple presence or absence of previously known genes and single-nucleotide polymorphisms (SNPs) against approaches that deploy machine learning and statistical models. Often, the limitations to genome-based prediction arise from limitations of accuracy of culture-based AST in addition to an incomplete knowledge of the genetic basis of resistance. However, we need to maintain phenotypic testing even as genome-based prediction becomes more widespread to ensure that the results do not diverge over time. We argue that standardization of WGS-AST by challenge with consistently phenotyped strain sets of defined genetic diversity is necessary to compare the efficacy of methods of prediction of antibiotic resistance based on genome sequences.

From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Hospitals worldwide are facing an increasing incidence of hard-to-treat infections. Limiting infections and providing patients with optimal drug regimens require timely strain identification as well as virulence and drug-resistance profiling. Additionally, prophylactic interventions based on the identification of environmental sources of recurrent infections (e.g., contaminated sinks) and reconstruction of transmission chains (i.e., who infected whom) could help to reduce the incidence of nosocomial infections. WGS could hold the key to solving these issues. However, uptake in the clinic has been slow. Some major scientific and logistical challenges need to be solved before WGS fulfils its potential in clinical microbial diagnostics. In this review we identify major bottlenecks that need to be resolved for WGS to routinely inform clinical intervention and discuss possible solutions.

Investigation of a Carbapenemase-producing Acinetobacter baumannii outbreak using whole genome sequencing versus a standard epidemiologic investigation

Background

The standard epidemiologic investigation of outbreaks typically relies on spatiotemporal data and pulsed-field gel electrophoresis (PFGE), but whole genome sequencing (WGS) is becoming increasingly used. This investigation aimed to characterize a carbapenemase-producing Acinetobacter baumannii (CPAb) nosocomial outbreak using WGS compared to a standard outbreak investigation.

Methods

The CPAb outbreak occurred in a single center between 2012 and 2014. The standard investigation used spatiotemporal data and PFGE to generate a chain of transmission. A separate WGS investigation generated a chain of transmission based solely on WGS and date of sampling and was blinded to all other spatiotemporal data and PFGE. Core single nucleotide variant (SNV) phylogenetic analysis was performed on WGS data generated using the Illumina MiSeq platform. The chains of transmission were compared quantitatively and qualitatively to assess the concordance between both methods.

Results

28 colonized and infected cases were included. Of the 27 transmission events identified using the standard investigation, 12 (44%) were identical to the transmission events using WGS. WGS identified several transmission events that had not been detected by traditional method, and numerous transmission events that had occurred on different hospital wards than suspected by standard methods. The average number (standard deviation [SD]) of SNVs per transmission events was 1.63 (SD, 1.31) by traditional method and 0.63 (SD, 0.79) by WGS (p = 0.001) All isolates harbored the rare carbapenemase bla_OXA-237.

Conclusions

The traditional and WGS investigations had moderate concordance. When used alongside epidemiologic data and clinical information, WGS could help improve the mapping of transmission events.

Accuracy of Different Bioinformatics Methods in Detecting Antibiotic Resistance and Virulence Factors from Staphylococcus aureus Whole-Genome Sequences

In principle, whole-genome sequencing (WGS) can predict phenotypic resistance directly from a genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. We compared three WGS-based bioinformatics methods (Genefinder [read based], Mykrobe [de Bruijn graph based], and Typewriter [BLAST based]) for predicting the presence/absence of 83 different resistance determinants and virulence genes and overall antimicrobial susceptibility in 1,379 Staphylococcus aureus isolates previously characterized by standard laboratory methods (disc diffusion, broth and/or agar dilution, and PCR). In total, 99.5% (113,830/114,457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fleiss' kappa = 0.98, P < 0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b). The genotypic antimicrobial susceptibility prediction matched the laboratory phenotype in 98.3% (14,224/14,464) of cases (2,720 [18.8%] resistant, 11,504 [79.5%] susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 [0.7%] phenotypically susceptible, but all bioinformatic methods reported resistance; 89 [0.6%] phenotypically resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 [0.4%] cases, 16 phenotypically resistant, 38 phenotypically susceptible). However, in 36/54 (67%) cases, the consensus genotype matched the laboratory phenotype. In this study, the choice between these three specific bioinformatic methods to identify resistance determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations; therefore, consensus methods provide some assurance.

Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Genome-Wide Typing of Clostridium difficile

Clostridium difficile, recently renamed Clostridioides difficile, is the most common cause of antibiotic-associated nosocomial gastrointestinal infections worldwide. To differentiate endogenous infections and transmission events, highly discriminatory subtyping is necessary. Today, methods based on whole-genome sequencing data are increasingly used to subtype bacterial pathogens; however, frequently a standardized methodology and typing nomenclature are missing. Here we report a core genome multilocus sequence typing (cgMLST) approach developed for C. difficile Initially, we determined the breadth of the C. difficile population based on all available MLST sequence types with Bayesian inference (BAPS). The resulting BAPS partitions were used in combination with C. difficile clade information to select representative isolates that were subsequently used to define cgMLST target genes. Finally, we evaluated the novel cgMLST scheme with genomes from 3,025 isolates. BAPS grouping (n = 6 groups) together with the clade information led to a total of 11 representative isolates that were included for cgMLST definition and resulted in 2,270 cgMLST genes that were present in all isolates. Overall, 2,184 to 2,268 cgMLST targets were detected in the genome sequences of 70 outbreak-associated and reference strains, and on average 99.3% cgMLST targets (1,116 to 2,270 targets) were present in 2,954 genomes downloaded from the NCBI database, underlining the representativeness of the cgMLST scheme. Moreover, reanalyzing different cluster scenarios with cgMLST were concordant to published single nucleotide variant analyses. In conclusion, the novel cgMLST is representative for the whole C. difficile population, is highly discriminatory in outbreak situations, and provides a unique nomenclature facilitating interlaboratory exchange.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a “One Health” approach.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a "One Health" approach.

Genomic and phenotypic diversity of Clostridium difficile during long-term sequential recurrences of infection

Infection with the emerging pathogen Clostridioides (Clostridium) difficile might lead to colonization of the gastrointestinal tract of humans and mammals eventually resulting in antibiotic-associated diarrhea, which can be mild to possibly life-threatening. Recurrences after antibiotic treatment have been described in 15-30% of the cases and are either caused by the original (relapse) or by new strains (reinfection). In this study, we describe a patient with ongoing recurrent C. difficile infections over 13 months. During this time, ten C. difficile strains of six different ribotypes could be isolated that were further characterized by phenotypic and genomic analyses including motility and sporulation assays, growth fitness and antibiotic susceptibility as well as whole-genome sequencing. PCR ribotyping of the isolates confirmed that the recurrences were a mixture of relapses and reinfections. One recurrence was due to a mixed infection with three different strains of two different ribotypes. Furthermore, genomes were sequenced and multi-locus sequence typing (MLST) was carried out, which identified the strains as members of sequence types (STs) 10, 11, 14 and 76. Comparison of the genomes of isolates of the same ST originating from recurrent CDI (relapses) indicated little within-patient microevolution and some concurrent within-patient diversity of closely related strains. Isolates of ribotype 126 that are binary toxin positive differed from other ribotypes in various phenotypic aspects including motility, sporulation behavior and cell morphology. Ribotype 126 is genetically related to ribotype 078 that has been associated with increased virulence. Isolates of the ribotype 126 exhibited elongated cells and a chaining phenotype, which was confirmed by membrane staining and scanning electron microscopy. Furthermore, this strain exhibits a sinking behavior in liquid medium in stationary growth phase. Taken together, our observation has proven multiple CDI recurrences that were based on a mixture of relapses and reinfections.

Diagnosing tuberculosis in the 21st century - Dawn of a genomics revolution?

Tuberculosis (TB) ranks alongside HIV as the leading cause of death worldwide, killing 1.5million people in 2014. Traditional laboratory techniques do not provide sufficiently rapid results to inform clinicians on appropriate treatment, especially in the face of increasingly prevalent drug-resistant TB. Rapid molecular methods such as PCR and LAMP are vital tools in the fight against TB, however, rapid advances in next generation sequencing (NGS) technology are allowing increasingly rapid and accurate sequencing of entire bacterial genomes at ever decreasing cost, providing unprecedented depth of information. These advances mean NGS stands to revolutionise the diagnosis and epidemiological study of Mycobacterium tuberculosis infection. This review focuses on current applications of NGS for TB diagnosis including sequencing cultured isolates to predict drug resistance and, more desirably, direct diagnostic metagenomic sequencing of clinical samples. Also discussed is the potential impact of NGS on the epidemiological study of TB and some of the key challenges that need to be overcome to enable this promising technology to be translated into routine use.

Transforming bacterial disease surveillance and investigation using whole-genome sequence to probe the trace

Two decades have passed since the first bacterial whole-genome sequencing, which provides new opportunity for microbial genome. Consequently, considerable genetic diversity encoded by bacterial genomes and among the strains in the same species has been revealed. In recent years, genome sequencing techniques and bioinformatics have developed rapidly, which has resulted in transformation and expedited the application of strategy and methodology for bacterial genome comparison used in dissection of infectious disease epidemics. Bacterial whole-genome sequencing and bioinformatic computing allow genotyping to satisfy the requirements of epidemiological study in disease control. In this review, we outline the significance and summarize the roles of bacterial genome sequencing in the context of bacterial disease control and prevention.We discuss the applications of bacterial genome sequencing in outbreak detection, source tracing, transmission mode discovery, and new epidemic clone identification. Wide applications of genome sequencing and data sharing in infectious disease surveillance networks will considerably promote outbreak detection and early warning to prevent the dissemination of bacterial diseases.

Comparative Genomics of Clostridium difficile

Clostridium difficile, a gram-positive spore-forming anaerobic bacterium, has rapidly emerged as the leading cause of nosocomial diarrhoea in hospitals. The availability of genome sequences in large numbers, mainly due to the use of next-generation sequencing methods, have undoubtedly shown their immense advantages in the determination of the C. difficile population structure. The implementation of fine-scale comparative genomic approaches have paved the way to global transmission and recurrence studies, but also more targeted studies such as the PaLoc or the CRISPR/Cas systems. In this chapter, we provide an overview of the recent and significant findings on C. difficile using comparative genomics studies with implication for the epidemiology, infection control and understanding of the evolution of C. difficile.