Alignment-free design of highly discriminatory diagnostic primer sets for Escherichia coli O104:H4 outbreak strains

PUPpy: a primer design pipeline for substrain-level microbial detection and absolute quantification

Characterizing microbial communities at high resolution and with absolute quantification is crucial to unravel the complexity and diversity of microbial ecosystems. This can be achieved with PCR assays, which enable highly selective detection and absolute quantification of microbial DNA. However, a major challenge that has hindered PCR applications in microbiome research is the design of highly specific primer sets that exclusively amplify intended targets. Here, we introduce Phylogenetically Unique Primers in python (PUPpy), a fully automated pipeline to design microbe- and group-specific primers within a given microbial community. PUPpy can be executed from a user-friendly graphical user interface, or two simple terminal commands, and it only requires coding sequence files of the community members as input. PUPpy-designed primers enable the detection of individual microbes and quantification of absolute microbial abundance in defined communities below the strain level. We experimentally evaluated the performance of PUPpy-designed primers using two bacterial communities as benchmarks. Each community comprises 10 members, exhibiting a range of genetic similarities that spanned from different phyla to substrains. PUPpy-designed primers also enable the detection of groups of bacteria in an undefined community, such as the detection of a gut bacterial family in a complex stool microbiota sample. Taxon-specific primers designed with PUPpy showed 100% specificity to their intended targets, without unintended amplification, in each community tested. Lastly, we show the absolute quantification of microbial abundance using PUPpy-designed primers in droplet digital PCR, benchmarked against 16S rRNA and shotgun sequencing. Our data shows that PUPpy-designed microbe-specific primers can be used to quantify substrain-level absolute counts, providing more resolved and accurate quantification in defined communities than short-read 16S rRNA and shotgun sequencing.

IMPORTANCE

Profiling microbial communities at high resolution and with absolute quantification is essential to uncover hidden ecological interactions within microbial ecosystems. Nevertheless, achieving resolved and quantitative investigations has been elusive due to methodological limitations in distinguishing and quantifying highly related microbes. Here, we describe Phylogenetically Unique Primers in python (PUPpy), an automated computational pipeline to design taxon-specific primers within defined microbial communities. Taxon-specific primers can be used to selectively detect and quantify individual microbes and larger taxa within a microbial community. PUPpy achieves substrain-level specificity without the need for computationally intensive databases and prioritizes user-friendliness by enabling both terminal and graphical user interface applications. Altogether, PUPpy enables fast, inexpensive, and highly accurate perspectives into microbial ecosystems, supporting the characterization of bacterial communities in both in vitro and complex microbiota settings.

Multicenter Preparedness Exercise Enables Rapid Development of Cluster-Specific PCR-Based Screening Assays from Bacterial Genomic Data

PCR-based screening assays targeting strain-specific genetic markers allow the timely detection and specific differentiation of bacterial strains. Especially in situations where an infection cluster occurs, fast assay development is crucial for supporting targeted control measures. However, the turnaround times (TATs) for assay setup may be high due to insufficient knowledge about screening assay methods, workflows, and software tools. Here, two blind-coded and quality-controlled ring trials were performed in which five German laboratories established PCR-based screening assays from genomic data that specifically target selected bacterial clusters within two bacterial monospecies sample panels. While the first ring trial was conducted without a time limit to train the participants and assess assay feasibility, in the second ring trial, a challenging time limit of 2 weeks was set to force fast assay development as soon as genomic data were available. During both ring trials, we detected high interlaboratory variability regarding the screening assay methods and targets, the TATs for assay setup, and the number of screening assays. The participants designed between one and four assays per cluster that targeted cluster-specific unique genetic sequences, genes, or single nucleotide variants using conventional PCRs, high-resolution melting assays, or TaqMan PCRs. Assays were established within the 2-week time limit, with TATs ranging from 4 to 13 days. TaqMan probe delivery times strongly influenced TATs. In summary, we demonstrate that a specific exercise improved the preparedness to develop functional cluster-specific PCR-based screening assays from bacterial genomic data. Furthermore, the parallel development of several assays enhances assay availability.

Single Nucleotide Polymorphism-Based Real-Time PCR Screening Assay for Rapid Tracking of Bacterial Infection Clusters To Complement Whole-Genome Sequencing Efforts during Outbreak Investigations

Infection clusters of multidrug-resistant bacteria increase mortality and entail expensive infection control measures. Whereas whole-genome sequencing (WGS) is the current gold standard to confirm infection clusters, PCR-based assays targeting cluster-specific signatures, such as single nucleotide polymorphisms (SNPs) derived from WGS data, are more suitable to initially screen for cluster isolates within large sample sizes. Here, we evaluated four software tools (SeqSphere+, RUCS, Gegenees, and Find Differential Primers) regarding their efficiency to find SNPs within WGS data sets that were specific for two bacterial monospecies infection clusters but were absent from a WGS reference data set comprising several hundred diverse genotypes of the same bacterial species. Cluster-specific SNPs were subsequently used to establish a probe-based real-time PCR screening assay for in vitro differentiation between cluster and noncluster isolates. SeqSphere+ and RUCS found 2 and 24 SNPs for clusters 1 and 14 and 24 SNPs for cluster 2, respectively. However, some signatures detected by RUCS were not cluster specific. Interestingly, all SNPs identified by SeqSphere+ were also detected by RUCS. In contrast, analyses with the remaining tools either resulted in no SNPs (with Find Differential Primers) or failed (Gegenees). Design of six cluster-specific real-time PCR assays enabled reliable cluster screening in vitro. Our evaluation revealed that SeqSphere+ and RUCS identified cluster-specific SNPs that could be used for large-scale screening in surveillance samples via real-time PCR, thereby complementing WGS efforts. This faster and simplified approach for the surveillance of bacterial clusters will improve infection control measures and will enhance protection of patients and physicians. IMPORTANCE Infection clusters of multidrug-resistant bacteria threaten medical facilities worldwide and cause immense health care costs. In recent years, whole-genome sequencing (WGS) has been increasingly applied to detect and to further control bacterial clusters. However, as WGS is still expensive and time-consuming, its exclusive application for screening and confirmation of bacterial infection clusters contributes to high costs and enhanced turnaround times, which many hospitals cannot afford. Therefore, there is need for alternative methods that can enable further surveillance of bacterial clusters that are initially detected by WGS in a faster and more cost-efficient way. Here, we established a system based on real-time PCR that enables rapid large-scale sample screening for bacterial cluster isolates within 7 days after the initial detection of an infection cluster, thereby complementing WGS efforts. This faster and simplified surveillance of bacterial clusters will improve infection control measures and will enhance protection of patients and physicians.

Short-length Homologous Region exhaustive Search algorithm (SHRS): A primer design algorithm for differentiating bacteria at the species, subspecies, or strain level based on a whole genome sequence

In fields such as the food industry, it is very important to identify target bacteria at the species level or lower for optimal product quality control. Bacteria identification at the subspecies or lower level requires time-consuming and high-cost analyses such as multi-locus sequence typing and amplified fragment length polymorphism analyses. Herein, we developed a primer design algorithm for precisely identifying bacteria based on a whole genome DNA sequence that is easy to apply. The algorithm designs primer sets that produce fragments from all input sequences and maximizes the differences in the amplicon size or amplicon sequence among input sequences. We demonstrate that the primer sets designed by the algorithm clearly classified six subspecies of Lactobacillus delbrueckii, and we observed that the resolution of the method is equal to that of a multi-locus sequence analysis. The algorithm allows the easy but precise identification of bacteria within a short time. (SHRS is available freely from PyPI under the MIT license.).

Genome-Informed Design of a LAMP Assay for the Specific Detection of the Strain of 'Candidatus Phytoplasma asteris' Phytoplasma Occurring in Grapevines in South Africa

Grapevine yellows is one of the most damaging phytoplasma-associated diseases worldwide. It is linked to several phytoplasma species, which can vary regionally due to phytoplasma and insect-vector diversity. Specific, rapid, and reliable detection of the grapevine yellows pathogen has an important role in phytoplasma control. The purpose of this study was to develop and validate a specific loop-mediated isothermal amplification (LAMP) assay for detection of a distinct strain of grapevine 'Candidatus Phytoplasma asteris' that is present in South Africa, through implementation of a genome-informed test design approach. Several freely available, user-friendly, web-based tools were coupled to design the specific LAMP assays. The criteria for selection of the assays were set for each step of the process, which resulted in four experimentally operative LAMP assays that targeted the ftsH/hflB gene region, specific to the aster yellows phytoplasma strain from South Africa. A real-time PCR was developed, targeting the same genetic region, to provide extensive validation of the LAMP assay. The validated molecular assays are highly specific to the targeted aster yellows phytoplasma strain from South Africa, with good sensitivity and reproducibility. We show a genome-informed molecular test design and an efficient validation approach for molecular tests if reference and sample materials are sparse and hard to obtain.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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.

Development of qPCR Detection Assay for Potato Pathogen Pectobacterium atrosepticum Based on a Unique Target Sequence

The recent taxonomic diversification of bacterial genera Pectobacterium and Dickeya, which cause soft rot in plants, focuses attention on the need for improvement of existing methods for the detection and differentiation of these phytopathogens. This research presents a whole genome-based approach to the selection of marker sequences unique to particular species of Pectobacterium. The quantitative real-time PCR assay developed is selective in the context of all tested Pectobacterium atrosepticum strains and is able to detect fewer than 10² copies of target DNA per reaction. The presence of plant DNA extract did not affect the sensitivity of the assay.

SpeciesPrimer: a bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species

BACKGROUND

Quantitative real-time PCR (qPCR) is a well-established method for detecting and quantifying bacteria, and it is progressively replacing culture-based diagnostic methods in food microbiology. High-throughput qPCR using microfluidics brings further advantages by providing faster results, decreasing the costs per sample and reducing errors due to automatic distribution of samples and reagents. In order to develop a high-throughput qPCR approach for the rapid and cost-efficient quantification of microbial species in complex systems such as fermented foods (for instance, cheese), the preliminary setup of qPCR assays working efficiently under identical PCR conditions is required. Identification of target-specific nucleotide sequences and design of specific primers are the most challenging steps in this process. To date, most available tools for primer design require either laborious manual manipulation or high-performance computing systems.

RESULTS

We developed the SpeciesPrimer pipeline for automated high-throughput screening of species-specific target regions and the design of dedicated primers. Using SpeciesPrimer, specific primers were designed for four bacterial species of importance in cheese quality control, namely Enterococcus faecium, Enterococcus faecalis, Pediococcus acidilactici and Pediococcus pentosaceus. Selected primers were first evaluated in silico and subsequently in vitro using DNA from pure cultures of a variety of strains found in dairy products. Specific qPCR assays were developed and validated, satisfying the criteria of inclusivity, exclusivity and amplification efficiencies.

CONCLUSION

In this work, we present the SpeciesPrimer pipeline, a tool to design species-specific primers for the detection and quantification of bacterial species. We use SpeciesPrimer to design qPCR assays for four bacterial species and describe a workflow to evaluate the designed primers. SpeciesPrimer facilitates efficient primer design for species-specific quantification, paving the way for a fast and accurate quantitative investigation of microbial communities.

Development of the Automated Primer Design Workflow Uniqprimer and Diagnostic Primers for the Broad-Host-Range Plant Pathogen Dickeya dianthicola

Uniqprimer, a software pipeline developed in Python, was deployed as a user-friendly internet tool in Rice Galaxy for comparative genome analyses to design primer sets for PCRassays capable of detecting target bacterial taxa. The pipeline was trialed with Dickeya dianthicola, a destructive broad-host-range bacterial pathogen found in most potato-growing regions. Dickeya is a highly variable genus, and some primers available to detect this genus and species exhibit common diagnostic failures. Upon uploading a selection of target and nontarget genomes, six primer sets were rapidly identified with Uniqprimer, of which two were specific and sensitive when tested with D. dianthicola. The remaining four amplified a minority of the nontarget strains tested. The two promising candidate primer sets were trialed with DNA isolated from 116 field samples from across the United States that were previously submitted for testing. D. dianthicola was detected in 41 samples, demonstrating the applicability of our detection primers and suggesting widespread occurrence of D. dianthicola in North America.

Using a Genome-Based PCR Primer Prediction Pipeline to Develop Molecular Diagnostics for the Turfgrass Pathogen Acidovorax avenae

Acidovorax avenae is the causal agent of bacterial etiolation and decline (BED) of creeping bentgrass, a poorly understood and often misdiagnosed disease that can result in considerable aesthetic and functional damage to golf course putting greens. Current diagnostics of BED are based on laborious culture-based methods. In this work, we employed a novel alignment-free primer prediction pipeline to design diagnostic primers for turfgrass-pathogenic A. avenae using 15 draft genomes of closely related target and nontarget Acidovorax spp. as input. Twenty candidate primer sets specific to turfgrass-pathogenic A. avenae were designed. The specificity and sensitivity of these primer sets were validated via a traditional polymerase chain reaction (PCR) and a real-time PCR assay. Primer sets 0017 and 0019 coupled with an internal oligo probe showed optimal sensitivity and specificity when evaluated with the target pathogen, closely related bacterial species, and microorganisms that inhabit the same host and soil environment. Finally, the accuracy of the newly developed real-time PCR assay was evaluated to detect BED pathogens from BED-symptomatic and asymptomatic turfgrass samples. The diagnostic results produced by the real-time PCR assay were consistent with results of a cultural-based method. This assay will allow quicker and more effective detection of the BED pathogen, thus potentially reducing misdiagnoses and unnecessary usage of fungicides.

The 2011 German Enterohemorrhagic Escherichia Coli O104:H4 Outbreak-The Danger Is Still Out There

Enterohemorrhagic Escherichia coli (EHEC) are Shiga toxin (Stx) producing bacteria causing a disease characterized by bloody (or non-bloody) diarrhea, which might progress to hemolytic uremic syndrome (HUS). EHEC O104:H4 caused the largest ever recorded EHEC outbreak in Germany in 2011, which in addition showed the so far highest incidence rate of EHEC-related HUS worldwide. The aggressive outbreak strain carries an unusual combination of virulence traits characteristic to both EHEC-a chromosomally integrated Stx-encoding bacteriophage, and enteroaggregative Escherichia coli-pAA plasmid-encoded aggregative adherence fimbriae mediating its tight adhesion to epithelia cells. There are currently still open questions regarding the 2011 EHEC outbreak, e.g., with respect to the exact molecular mechanisms resulting in the hypervirulence of the strain, the natural reservoir of EHEC O104:H4, and suitable therapeutic strategies. Nevertheless, our knowledge on these issues has substantially expanded since 2011. Here, we present an overview of the epidemiological, clinical, microbiological, and molecular biological data available on the 2011 German EHEC O104:H4 outbreak.

Public Health Research Resulting from One of the World's Largest Outbreaks Caused by Entero-Hemorrhagic Escherichia coli in Germany 2011: A Review

In 2011, Germany experienced one of the largest outbreaks of entero-hemorrhagic Escherichia coli (EHEC) ever reported. Four years thereafter, we systematically searched for scientific publications in PubMed and MEDPILOT relating to this outbreak in order to assess the pattern of respective research activities and to assess the main findings and recommendations in the field of public health. Following PRISMA guidelines, we selected 133 publications, half of which were published within 17 months after outbreak onset. Clinical medicine was covered by 71, microbiology by 60, epidemiology by 46, outbreak reporting by 11, and food safety by 9 papers. Those on the last three topics drew conclusions on methods in surveillance, diagnosis, and outbreak investigation, on resources in public health, as well as on inter-agency collaboration, and public communication. Although the outbreak primarily affected Germany, most publications were conducted by multinational cooperations. Our findings document how soon and in which fields research was conducted with respect to this outbreak.

Investigation of next-generation sequencing data of Klebsiella pneumoniae using web-based tools

PURPOSE

Rapid identification and characterization of multidrug-resistant Klebsiella pneumoniae strains is necessary due to the increasing frequency of severe infections in patients. The decreasing cost of next-generation sequencing enables us to obtain a comprehensive overview of genetic information in one step. The aim of this study is to demonstrate and evaluate the utility and scope of the application of web-based databases to next-generation sequenced (NGS) data.

METHODOLOGY

The whole genomes of 11 clinical Klebsiella pneumoniae isolates were sequenced using Illumina MiSeq. Selected web-based tools were used to identify a variety of genetic characteristics, such as acquired antimicrobial resistance genes, multilocus sequence types, plasmid replicons, and identify virulence factors, such as virulence genes, cps clusters, urease-nickel clusters and efflux systems.

RESULTS

Using web-based tools hosted by the Center for Genomic Epidemiology, we detected resistance to 8 main antimicrobial groups with at least 11 acquired resistance genes. The isolates were divided into eight sequence types (ST11, 23, 37, 323, 433, 495 and 562, and a new one, ST1646). All of the isolates carried replicons of large plasmids. Capsular types, virulence factors and genes coding AcrAB and OqxAB efflux pumps were detected using BIGSdb-Kp, whereas the selected virulence genes, identified in almost all of the isolates, were detected using CLC Genomic Workbench software.

CONCLUSION

Applying appropriate web-based online tools to NGS data enables the rapid extraction of comprehensive information that can be used for more efficient diagnosis and treatment of patients, while data processing is free of charge, easy and time-efficient.

Fine-Scale Structure Analysis Shows Epidemic Patterns of Clonal Complex 95, a Cosmopolitan Escherichia coli Lineage Responsible for Extraintestinal Infection

The Escherichia coli lineage known as clonal complex 95 (CC95) is a cosmopolitan human-associated lineage responsible for a significant fraction of extraintestinal infections of humans. Whole-genome sequence data of 200 CC95 strains from various origins enabled determination of the CC95 pangenome. The pangenome analysis revealed that strains of the complex could be assigned to one of five subgroups that vary in their serotype, extraintestinal virulence, virulence gene content, and antibiotic resistance gene profile. A total of 511 CC95 strains isolated from humans living in France, Australia, and the United States were screened for their subgroup membership using a PCR-based method. The CC95 subgroups are nonrandomly distributed with respect to their geographic origin. The relative frequency of the subgroups was shown to change through time, although the nature of the changes varies with continent. Strains of the subgroups are also nonrandomly distributed with respect to source of isolation (blood, urine, or feces) and host sex. Collectively, the evidence indicates that although strains belonging to CC95 may be cosmopolitan, human movement patterns have been insufficient to homogenize the distribution of the CC95 subgroups. Rather, the manner in which CC95 strains evolve appears to vary both spatially and temporally. Although CC95 strains appeared globally as pandemic, fine-scale structure analysis shows epidemic patterns of the CC95 subgroups. Furthermore, the observation that the relative frequency of CC95 subgroups at a single locality has changed over time indicates that the relative fitness of the subgroups has changed. IMPORTANCEEscherichia coli clonal complex 95 represents a cosmopolitan, genetically diverse lineage, and the extensive substructure observed in this lineage is epidemiologically and clinically relevant. The frequency with which CC95 strains are responsible for extraintestinal infection appears to have been stable over the past 15 years. However, the different subgroups identified within this lineage have an epidemic structure depending on the host, sample, continent, and time. Thus, the evolution and spread of strains belonging to CC95 are very different from those of another cosmopolitan human-associated clonal complex, CC131, which has increased significantly in frequency as a cause of extraintestinal infection over the past 15 years due to the evolution and spread of two very closely related, nearly monomorphic lineages.

Comprehensive Characterization of Escherichia coli O104:H4 Isolated from Patients in the Netherlands

In 2011, a Shiga toxin-producing Enteroaggregative Escherichia coli (EAEC Stx2a+) O104:H4 strain caused a serious outbreak of acute gastroenteritis and hemolytic-uremic syndrome (HUS) in Germany. In 2013, E. coli O104:H4 isolates were obtained from a patient with HUS and her friend showing only gastrointestinal complaints. The antimicrobial resistance and virulence profiles of these isolates together with three EAEC Stx2a+ O104:H4 isolates from 2011 were determined and compared. Whole-genome sequencing (WGS) was performed for detailed characterization and to determine genetic relationship of the isolates. Four additional genomes of EAEC Stx2a+ O104:H4 isolates of 2009 and 2011 available on NCBI were included in the virulence and phylogenetic analysis. All E. coli O104:H4 isolates tested were positive for stx2a, aatA, and terD but were negative for escV. All, except one 2011 isolate, were positive for aggR and were therefore considered EAEC. The EAEC Stx2a+ O104:H4 isolates of 2013 belonged to sequence type (ST) ST678 as the 2011 isolates and showed slightly different resistance and virulence patterns compared to the 2011 isolates. Core-genome phylogenetic analysis showed that the isolates of 2013 formed a separate cluster from the isolates of 2011 and 2009 by 27 and 20 different alleles, respectively. In addition, only a one-allele difference was found between the isolate of the HUS-patient and that of her friend. Our study shows that EAEC Stx2a+ O104:H4 strains highly similar to the 2011 outbreak clone in their core genome are still circulating necessitating proper surveillance to prevent further outbreaks with these potentially pathogenic strains. In addition, WGS not only provided a detailed characterization of the isolates but its high discriminatory power also enabled us to discriminate the 2013 isolates from the isolates of 2009 and 2011 expediting the use of WGS in public health services to rapidly apply proper infection control strategies.

Whole-genome sequencing targets drug-resistant bacterial infections

During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today’s WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.

[High-throughput sequencing: towards a genome-based diagnosis in infectious diseases]

During a pathogen outbreak, the emergency resides in the identification and characterization of the infectious agent. In addition to the traditional phenotypic methods which are still widely used, the molecular biology is nowadays a common approach of clinical microbiology labs and the pathogen can be identified by comparing its molecular fingerprint to a data-bank. High-throughput sequencing should allow overcoming this single identification to exploit the whole information encoded in the pathogen genome. This evolution, supported by an increasing number of proof-of-concept studies, should result in moving from detection through fingerprints to the use of the pathogen whole genome; this forensic profile should allow the adaptation of the treatment to the pathogen specificities. From concept to routine use, many parameters need to be considered to promote high-throughput sequencing as a powerful tool to help physicians and clinicians in microbiological investigations.

Clinical detection and characterization of bacterial pathogens in the genomics era

The availability of genome sequences obtained using next-generation sequencing (NGS) has revolutionized the field of infectious diseases. Indeed, more than 38,000 bacterial and 5,000 viral genomes have been sequenced to date, including representatives of all significant human pathogens. These tremendous amounts of data have not only enabled advances in fundamental biology, helping to understand the pathogenesis of microorganisms and their genomic evolution, but have also had implications for clinical microbiology. Here, we first review the current achievements of genomics in the development of improved diagnostic tools, including those that are now available in the clinic, such as the design of PCR assays for the detection of microbial pathogens, virulence factors or antibiotic-resistance determinants, or the design of optimized culture media for 'unculturable' pathogens. We then review the applications of genomics to the investigation of outbreaks, either through the design of genotyping assays or the direct sequencing of the causative strains. Finally, we discuss how genomics might change clinical microbiology in the future.

Rapid MALDI-TOF mass spectrometry strain typing during a large outbreak of Shiga-Toxigenic Escherichia coli

Background

In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification.

Methods

Specific peaks in the outbreak strain’s spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak.

Results

Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates.

Conclusions

MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow.

Omics approaches in food safety: fulfilling the promise?

Genomics, transcriptomics, and proteomics are rapidly transforming our approaches to the detection, prevention, and treatment of foodborne pathogens. Microbial genome sequencing in particular has evolved from a research tool into an approach that can be used to characterize foodborne pathogen isolates as part of routine surveillance systems. Genome sequencing efforts will not only improve outbreak detection and source tracking, but will also create large amounts of foodborne pathogen genome sequence data, which will be available for data-mining efforts that could facilitate better source attribution and provide new insights into foodborne pathogen biology and transmission. Although practical uses and application of metagenomics, transcriptomics, and proteomics data and associated tools are less prominent, these tools are also starting to yield practical food safety solutions.

Repertoire of novel sequence signatures for the detection of Candidatus Liberibacter asiaticus by quantitative real-time PCR

BACKGROUND

Huanglongbing (HLB) or citrus greening is a devastating disease of citrus. The gram-negative bacterium Candidatus Liberibacter asiaticus (Las) belonging to the α-proteobacteria is responsible for HLB in North America as well as in Asia. Currently, there is no cure for this disease. Early detection and quarantine of Las-infected trees are important management strategies used to prevent HLB from invading HLB-free citrus producing regions. Quantitative real-time PCR (qRT-PCR) based molecular diagnostic assays have been routinely used in the detection and diagnosis of Las. The oligonucleotide primer pairs based on conserved genes or regions, which include 16S rDNA and the β-operon, have been widely employed in the detection of Las by qRT-PCR. The availability of whole genome sequence of Las now allows the design of primers beyond the conserved regions for the detection of Las explicitly.

RESULTS

We took a complimentary approach by systematically screening the genes in a genome-wide fashion, to identify the unique signatures that are only present in Las by an exhaustive sequence based similarity search against the nucleotide sequence database. Our search resulted in 34 probable unique signatures. Furthermore, by designing the primer pair specific to the identified signatures, we showed that most of our primer sets are able to detect Las from the infected plant and psyllid materials collected from the USA and China by qRT-PCR. Overall, 18 primer pairs of the 34 are found to be highly specific to Las with no cross reactivity to the closely related species Ca. L. americanus (Lam) and Ca. L. africanus (Laf).

CONCLUSIONS

We have designed qRT-PCR primers based on Las specific genes. Among them, 18 are suitable for the detection of Las from Las-infected plant and psyllid samples. The repertoire of primers that we have developed and characterized in this study enhanced the qRT-PCR based molecular diagnosis of HLB.

[The 2011 HUS epidemic in Germany. Challenges for disease control: what should be improved?]

From May to July 2011 [corrected] the world's largest outbreak of hemolytic uremic syndrome (HUS) occurred in northern Germany with dramatic consequences for the population, the health care system and the food industry. In the following we examine the detection of the outbreak, epidemic management and related public communication aspects based on scientific publications, media reports as well as own and new data analyses. The subsequent 17 recommendations concern issues such as participation in and implementation of existing and new surveillance systems particularly with respect to physicians, broad application of finely tuned microbiological typing, improved personnel capacity and crisis management structures within the public health service and evidence-based communication by administrations and scientific associations. Outbreaks of similar dimensions can inevitably occur again and result in costs which will far exceed investments needed for early detection and control. This societal balance should be taken into account in spite of limited resources in the public health sector.

Pattern recognition and probabilistic measures in alignment-free sequence analysis

With the massive production of genomic and proteomic data, the number of available biological sequences in databases has reached a level that is not feasible anymore for exact alignments even when just a fraction of all sequences is used. To overcome this inevitable time complexity, ultrafast alignment-free methods are studied. Within the past two decades, a broad variety of nonalignment methods have been proposed including dissimilarity measures on classical representations of sequences like k-words or Markov models. Furthermore, articles were published that describe distance measures on alternative representations such as compression complexity, spectral time series or chaos game representation. However, alignments are still the standard method for real world applications in biological sequence analysis, and the time efficient alignment-free approaches are usually applied in cases when the accustomed algorithms turn out to fail or be too inconvenient.

Lability of the pAA Virulence Plasmid in Escherichia coli O104:H4: Implications for Virulence in Humans

Background

Escherichia coli O104:H4 that caused the large German outbreak in 2011 is a highly virulent hybrid of enterohemorrhagic (EHEC) and enteroaggregative (EAEC) E. coli. The strain displays “stacked-brick” aggregative adherence to human intestinal epithelial cells mediated by aggregative adherence fimbriae I (AAF/I) encoded on the pAA plasmid. The AAF/I-mediated augmented intestinal adherence might facilitate systemic absorption of Shiga toxin, the major virulence factor of EHEC, presumably enhancing virulence of the outbreak strain. However, the stability of pAA in the outbreak strain is unknown. We therefore tested outbreak isolates for pAA, monitored pAA loss during infection, and determined the impact of pAA loss on adherence and clinical outcome of infection.

Methodology/Principal Findings

E. coli O104:H4 outbreak isolates from 170 patients (128 with hemolytic uremic syndrome [HUS] and 42 with diarrhea without HUS) were tested for pAA using polymerase chain reaction and plasmid profiling. pAA-harboring bacteria in stool samples were quantified using colony blot hybridization, and adherence to HCT-8 cells was determined. Isolates from 12 (7.1%) patients lacked pAA. Analyses of sequential stool samples demonstrated that the percentages of pAA-positive populations in the initial stools were significantly higher than those in the follow-up stools collected two to eight days later in disease (P≤0.01). This indicates a rapid loss of pAA during infections of humans. The pAA loss was associated with loss of the aggregative adherence phenotype and significantly reduced correlation with HUS (P  = 0.001).

Conclusions/Significance

The pAA plasmid can be lost by E. coli O104:H4 outbreak strain in the human gut in the course of disease. pAA loss might attenuate virulence and diminish the ability to cause HUS. The pAA instability has clinical, diagnostic, epidemiologic, and evolutionary implications.

Specific detection of enteroaggregative hemorrhagic Escherichia coli O104:H4 strains by use of the CRISPR locus as a target for a diagnostic real-time PCR

In 2011, a large outbreak of an unusual bacterial strain occurred in Europe. This strain was characterized as a hybrid of an enteroaggregative Escherichia coli (EAEC) and a Shiga toxin-producing E. coli (STEC) strain of the serotype O104:H4. Here, we present a single PCR targeting the clustered regularly interspaced short palindromic repeats locus of E. coli O104:H4 (CRISPR(O104:H4)) for specific detection of EAEC STEC O104:H4 strains from different geographical locations and time periods. The specificity of the CRISPR(O104:H4) PCR was investigated using 1,321 E. coli strains, including reference strains for E. coli O serogroups O1 to O186 and flagellar (H) types H1 to H56. The assay was compared for specificity using PCR assays targeting different O104 antigen-encoding genes (wbwC(O104), wzx(O104), and wzy(O104)). The PCR assays reacted with all types of E. coli O104 strains (O104:H2, O104:H4, O104:H7, and O104:H21) and with E. coli O8 and O9 strains carrying the K9 capsular antigen and were therefore not specific for detection of the EAEC STEC O104:H4 type. A single PCR developed for the CRISPR(O104:H4) target was sufficient for specific identification and detection of the 48 tested EAEC STEC O104:H4 strains. The 35 E. coli O104 strains expressing H types other than H4 as well as 8 E. coli strains carrying a K9 capsular antigen tested all negative for the CRISPR(O104:H4) locus. Only 12 (0.94%) of the 1,273 non-O104:H4 E. coli strains (serotypes Ont:H2, O43:H2, O141:H2, and O174:H2) reacted positive in the CRISPR(O104:H4) PCR (99.06% specificity).