Novel multiplex PCR assay for identification and subtyping of enteroinvasive Escherichia coli and differentiation from Shigella based on target genes selected by comparative genomics

Whole genome sequencing and antimicrobial resistance among clinical isolates of Shigella sonnei in Addis Ababa, Ethiopia

BACKGROUND

Shigellosis is an acute gastroenteritis infection and one of Ethiopia's most common causes of morbidity and mortality, especially in children under five. Antimicrobial resistance (AMR) has spread quickly among Shigella species due to inappropriate antibiotic use, inadequacies of diagnostic facilities, and unhygienic conditions. This study aimed to characterize Shigella sonnei (S. sonnei) using whole genome sequence (WGS) analysis in Addis Ababa, Ethiopia.

METHODS

The raw reads were quality-filtered and trimmed, and a minimum length of 50bp was retained and taxonomically classified using MiniKraken version 1. The whole genome data were aligned with Antibiotic Resistance Gene (ARG) sequences of the Comprehensive Antibiotic Resistance Database (CARD) by Resistance Gene Identifier (RGI). Plasmids were analyzed using the PlasmidFinder tool version 2.1. Additionally, AMR and virulence genes were screened at the Centre for Genomic Epidemiology (CGE) web-based server.

RESULTS

All isolates in our investigation contained genes encoding blaEC-8 and blaZEG-1. Here, 60.7% of the isolates were phenotypically sensitive to cefoxitin among the blaEC-8 genes detected in the genotyping analysis, whereas all isolates were completely resistant to amoxicillin and erythromycin phenotypically. The study also identified genes that conferred resistance to trimethoprim (dfrA). Plasmid Col156 and Col (BS512) types were found in all isolates, while IncFII and Col (MG828) plasmids were only identified in one isolate.

CONCLUSION

This study found that many resistant genes were present, confirming the high variety in S. sonnei strains and hence a divergence in phylogenetic relationships. Thus, combining WGS methods for AMR prediction and strain identification into active surveillance may be beneficial for monitoring the spread of AMR in S. sonnei and detecting the potential emergence of novel variations.

Molecular serotyping of diarrheagenic Escherichia coli with a MeltArray assay reveals distinct correlation between serotype and pathotype

Diarrheagenic Escherichia coli serotypes are associated with various clinical syndromes, yet the precise correlation between serotype and pathotype remains unclear. A major barrier to such studies is the reliance on antisera-based serotyping, which is culture-dependent, low-throughput, and cost-ineffective. We have established a highly multiplex PCR-based serotyping assay, termed the MeltArray E. coli serotyping (EST) assay, capable of identifying 163 O-antigen-encoding genes and 53 H-antigen-encoding genes of E. coli. The assay successfully identified serotypes directly from both simulated and real fecal samples, as demonstrated through spike-in validation experiments and a retrospective study. In a multi-province study involving 637 E. coli strains, it revealed that the five major diarrheagenic pathotypes have distinct serotype compositions. Notably, it differentiated 257 Shigella isolates into four major Shigella species, distinguishing them from enteroinvasive E. coli based on their distinct serotype profiles. The assay's universality was further corroborated by in silico analysis of whole-genome sequences from the EnteroBase. We conclude that the MeltArray EST assay represents a paradigm-shifting tool for molecular serotyping of E. coli, with potential routine applications for comprehensive serotype analysis, disease diagnosis, and outbreak detection.

A novel biochemistry approach combined with MALDI-TOF MS to discriminate Escherichia coli and Shigella species

Escherichia coli and Shigella spp. are closely related, making it crucial to accurately identify them for disease control and prevention. In this study, we utilized MALDI-TOF MS to identify characteristic peaks of decarboxylation products of lysine and ornithine to distinguish between E. coli and Shigella spp. Our findings indicate that the peak at m/z 103.12 ± 0.1 of the product cadaverine from lysine decarboxylase is unique to E. coli, while all Shigella species lack the m/z 103.12 ± 0.1 peak. However, S. sonnei and S. boydii serotype C13 exhibit a specific peak at m/z 89.10 ± 0.1, which is the product of putrescine from ornithine decarboxylase. We were able to correctly identify 97.06% (132 of 136) of E. coli and Shigella isolates and 100% (8 of 8) of S. sonnei isolates using this biochemical-based MALDI-TOF MS detection system. This technology is advantageous for its high-throughput, high quality, and ease of operation, and is of significant value for the diagnosis of E. coli and Shigella-related diseases.

Variable Region Sequences Influence 16S rRNA Performance

16S rRNA gene sequences are commonly analyzed for taxonomic and phylogenetic studies because they contain variable regions that can help distinguish different genera. However, intra-genus distinction using variable region homology is often impossible due to the high overall sequence identities among closely related species, even though some residues may be conserved within respective species. Using a computational method that included the allelic diversity within individual genomes, we discovered that certain Escherichia and Shigella species can be distinguished by a multi-allelic 16S rRNA variable region single nucleotide polymorphism (SNP). To evaluate the performance of 16S rRNAs with altered variable regions, we developed an in vivo system that measures the acceptance and distribution of variant 16S rRNAs into a large pool of natural versions supporting normal translation and growth. We found that 16S rRNAs containing evolutionarily disparate variable regions were underpopulated both in ribosomes and in active translation pools, even for an SNP. Overall, this study revealed that variable region sequences can substantially influence the performance of 16S rRNAs and that this biological constraint can be leveraged to justify refining taxonomic assignments of variable region sequence data. IMPORTANCE This study reevaluates the notion that 16S rRNA gene variable region sequences are uninformative for intra-genus classification and that single nucleotide variations within them have no consequence to strains that bear them. We demonstrated that the performance of 16S rRNAs in Escherichia coli can be negatively impacted by sequence changes in variable regions, even for single nucleotide changes that are native to closely related Escherichia and Shigella species; thus, biological performance is likely constraining the evolution of variable regions in bacteria. Further, the native nucleotide variations we tested occur in all strains of their respective species and across their multiple 16S rRNA gene copies, suggesting that these species evolved beyond what would be discerned from a consensus sequence comparison. Therefore, this work also reveals that the multiple 16S rRNA gene alleles found in most bacteria can provide more informative phylogenetic and taxonomic detail than a single reference allele.

Multiplex PCR: Aid to more-timely and directed therapeutic intervention for patients with infectious gastroenteritis

BACKGROUND

Multiplex PCR is a sensitive and rapid method compared with conventional methods. Therefore, we use multiplex PCR for the rapid detection of the four major intestinal pathogens causing gastroenteritis (Shigella spp., Campylobacter spp., Aeromonas spp. and Enterohemorrhagic Escherichia coli [EHEC]) in stool specimens.

MATERIALS AND METHODS

A prospective randomized study using 200 stool samples obtained from patients presented with acute gastroenteritis during the study period (between February 2019 and December 2021). Bacteria in stool samples were identified using conventional culture methods and multiplex PCR for stool samples.

RESULTS

The identified organisms using conventional cultures; were Shigella (27%), Aeromonas species (10%) and EHEC (O157) (8%). Using multiplex PCR. Shigella spp. was the most commonly identified pathogen (detected in 40.5% of positive samples), followed by Aeromonas spp. (30%), EHEC (20%) and Campylobacter species was only detected in (1%) of positive samples. The diagnostic evaluation of multiplex PCR in relation to conventional method in diagnosis of Shigella, EHEC and Aeromonas showed, sensitivity of 100% (for each), specificity of 88.5%, 92.4%, 77.8% respectively. However, the diagnostic evaluation of multiplex PCR in relation to conventional method in diagnosis of Campylobacter showed specificity of 99% and NPV of 100%.

CONCLUSIONS

Multiplex PCR is an accurate and rapid method for detection of common intestinal pathogens causing severe gastroenteritis. a rapid method that could be used in outbreaks for diagnosis of the common enteric pathogens causing fatal gastroenteritis.

MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not Differentiate Shigella spp. and Escherichia coli

Shigella spp. and E. coli are closely related and cannot be distinguished using matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) with commercially available databases. Here, three alternative approaches using MALDI-TOF MS to identify and distinguish Shigella spp., E. coli, and its pathotype EIEC were explored and evaluated using spectra of 456 Shigella spp., 42 E. coli, and 61 EIEC isolates. Identification with a custom-made database resulted in >94% Shigella identified at the genus level and >91% S. sonnei and S. flexneri at the species level, but the distinction of S. dysenteriae, S. boydii, and E. coli was poor. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although specificity was low. Discriminating markers for S. dysenteriae, S. boydii, and E. coli were not assigned at all. Classification models using machine learning correctly identified Shigella in 96% of isolates, but most E. coli isolates were also assigned to Shigella. None of the proposed alternative approaches were suitable for clinical diagnostics for identifying Shigella spp., E. coli, and EIEC, reflecting their relatedness and taxonomical classification. We suggest the use of MALDI-TOF MS for the identification of the Shigella spp./E. coli complex, but other tests should be used for distinction.

Cluster-specific gene markers enhance Shigella and enteroinvasive Escherichia coli in silico serotyping

Shigella and enteroinvasive Escherichia coli (EIEC) cause human bacillary dysentery with similar invasion mechanisms and share similar physiological, biochemical and genetic characteristics. Differentiation of Shigella from EIEC is important for clinical diagnostic and epidemiological investigations. However, phylogenetically, Shigella and EIEC strains are composed of multiple clusters and are different forms of E. coli, making it difficult to find genetic markers to discriminate between Shigella and EIEC. In this study, we identified 10 Shigella clusters, seven EIEC clusters and 53 sporadic types of EIEC by examining over 17000 publicly available Shigella and EIEC genomes. We compared Shigella and EIEC accessory genomes to identify cluster-specific gene markers for the 17 clusters and 53 sporadic types. The cluster-specific gene markers showed 99.64% accuracy and more than 97.02% specificity. In addition, we developed a freely available in silico serotyping pipeline named Shigella EIEC Cluster Enhanced Serotype Finder (ShigEiFinder) by incorporating the cluster-specific gene markers and established Shigella and EIEC serotype-specific O antigen genes and modification genes into typing. ShigEiFinder can process either paired-end Illumina sequencing reads or assembled genomes and almost perfectly differentiated Shigella from EIEC with 99.70 and 99.74% cluster assignment accuracy for the assembled genomes and read mapping respectively. ShigEiFinder was able to serotype over 59 Shigella serotypes and 22 EIEC serotypes and provided a high specificity of 99.40% for assembled genomes and 99.38% for read mapping for serotyping. The cluster-specific gene markers and our new serotyping tool, ShigEiFinder (installable package: https://github.com/LanLab/ShigEiFinder, online tool: https://mgtdb.unsw.edu.au/ShigEiFinder/), will be useful for epidemiological and diagnostic investigations.

Updates on defining and detecting diarrheagenic Escherichia coli pathotypes

PURPOSE OF REVIEW

Several types of Escherichia coli cause acute diarrhea in humans and are responsible for a large burden of disease globally. The purpose of this review is to summarize diarrheagenic Escherichia coli (DEC) pathotype definitions and discuss existing and emerging molecular, genomic, and gut microbiome methods to detect, define, and study DEC pathotypes.

RECENT FINDINGS

DEC pathotypes are currently diagnosed by molecular detection of unique virulence genes. However, some pathotypes have defied coherent molecular definitions because of imperfect gene targets, and pathotype categories are complicated by hybrid strains and isolation of pathotypes from asymptomatic individuals. Recent progress toward more efficient, sensitive, and multiplex DEC pathotype detection has been made using emerging PCR-based technologies. Genomics and gut microbiome detection methods continue to advance rapidly and are contributing to a better understanding of DEC pathotype diversity and functional potential.

SUMMARY

DEC pathotype categorizations and detection methods are useful but imperfect. The implementation of molecular and sequence-based methods and well designed epidemiological studies will continue to advance understanding of DEC pathotypes. Additional emphasis is needed on sequencing DEC genomes from regions of the world where they cause the most disease and from the pathotypes that cause the greatest burden of disease globally.

Staying out or Going in? The Interplay between Type 3 and Type 5 Secretion Systems in Adhesion and Invasion of Enterobacterial Pathogens

Enteric pathogens rely on a variety of toxins, adhesins and other virulence factors to cause infections. Some of the best studied pathogens belong to the Enterobacterales order; these include enteropathogenic and enterohemorrhagic Escherichia coli, Shigella spp., and the enteropathogenic Yersiniae. The pathogenesis of these organisms involves two different secretion systems, a type 3 secretion system (T3SS) and type 5 secretion systems (T5SSs). The T3SS forms a syringe-like structure spanning both bacterial membranes and the host cell plasma membrane that translocates toxic effector proteins into the cytoplasm of the host cell. T5SSs are also known as autotransporters, and they export part of their own polypeptide to the bacterial cell surface where it exerts its function, such as adhesion to host cell receptors. During infection with these enteropathogens, the T3SS and T5SS act in concert to bring about rearrangements of the host cell cytoskeleton, either to invade the cell, confer intracellular motility, evade phagocytosis or produce novel structures to shelter the bacteria. Thus, in these bacteria, not only the T3SS effectors but also T5SS proteins could be considered "cytoskeletoxins" that bring about profound alterations in host cell cytoskeletal dynamics and lead to pathogenic outcomes.

Incidence, clinical implications and impact on public health of infections with Shigella spp. and entero-invasive Escherichia coli (EIEC): results of a multicenter cross-sectional study in the Netherlands during 2016-2017

Background

Shigella spp. and entero-invasive E. coli (EIEC) use the same invasive mechanism to cause diarrheal diseases. Public health regulations apply only to Shigella spp. infections, but are hampered by the lack of simple methods to distinguish them from EIEC. In the last decades, molecular methods for detecting Shigella spp. and EIEC were implemented in medical microbiological laboratories (MMLs). However, shigellosis cases identified with molecular techniques alone are not notifiable in most countries. Our study investigates the impact of EIEC versus Shigella spp. infections and molecular diagnosed shigellosis versus culture confirmed shigellosis for re-examination of the rationale for the current public health regulations.

Methods

In this multicenter cross-sectional study, fecal samples of patients suspected for gastro-enteritis, referred to 15 MMLs in the Netherlands, were screened by PCR for Shigella spp. or EIEC. Samples were cultured to discriminate between the two pathogens. We compared risk factors, symptoms, severity of disease, secondary infections and socio-economic consequences for (i) culture-confirmed Shigella spp. versus culture-confirmed EIEC cases (ii) culture positive versus PCR positive only shigellosis cases.

Results

In 2016–2017, 777 PCR positive fecal samples with patient data were included, 254 of these were culture-confirmed shigellosis cases and 32 were culture-confirmed EIEC cases. EIEC cases were more likely to report ingestion of contaminated food and were less likely to be men who have sex with men (MSM). Both pathogens were shown to cause serious disease although differences in specific symptoms were observed. Culture-negative but PCR positive cases were more likely report travel or ingestion of contaminated food and were less likely to be MSM than culture-positive cases. Culture-negative cases were more likely to suffer from multiple symptoms. No differences in degree of secondary infections were observed between Shigella spp. and EIEC, and culture-negative and culture-positive cases.

Conclusions

No convincing evidence was found to support the current guidelines that employs different measures based on species or detection method. Therefore, culture and molecular detection methods for Shigella spp. and EIEC should be considered equivalent for case definition and public health regulations regarding shigellosis. Differences were found regarding risks factors, indicating that different prevention strategies may be required.

Genome Sequences of Enteroinvasive Escherichia coli Sequence Type 6, 99, and 311 Strains Acquired in Asia Pacific

Laboratory diagnosis of enteroinvasive Escherichia coli (EIEC) remains difficult and limits the availability of EIEC genomes to the research community. We report the draft genome sequences of three EIEC strains which represent three distinct sequence types and serotypes circulating in Asia Pacific and causing enterocolitis in humans.

Shifting national surveillance of Shigella infections toward geno-serotyping by the development of a tailored Luminex assay and NGS workflow

The phylogenetically closely related Shigella species and enteroinvasive Escherichia coli (EIEC) are responsible for millions of episodes of bacterial dysenteriae worldwide. Given its distinct epidemiology and public health relevance, only Shigellae are subject to mandatory reporting and follow‐up by public health authorities. However, many clinical laboratories struggle to differentiate non‐EIEC, EIEC, and Shigella in their current workflows, leading to inaccuracies in surveillance and rising numbers of misidentified E. coli samples at the National Reference Centre (NRC). In this paper, we describe two novel tools to enhance Shigella surveillance. First, we developed a low‐cost Luminex‐based multiplex assay combining five genetic markers for species identification with 11 markers for serotype prediction for S. sonnei and S. flexneri isolates. Using a test panel of 254 clinical samples, this assay has a sensitivity of 100% in differentiation of EIEC/Shigella pathotype from non‐EIEC strains, and 68.7% success rate in distinction of Shigella and EIEC. A novel, and particularly successful marker was a Shigella‐specific deletion in the spermidine acetyltransferase gene speG, reflecting its metabolic decay. For Shigella serotype prediction, the multiplex assay scored a sensitivity and specificity of 96.6% and 98.4%, respectively. All discrepancies were analyzed with whole‐genome sequencing and shown to be related to causative mutations (stop codons, indels, and promoter mutations) in glycosyltransferase genes. This observation spurred the development of an in silico workflow which extracts the Shigella serotype from Next‐Generation Sequencing (NGS) data, taking into account gene functionality. Both tools will be implemented in the workflow of the NRC, and will play a major role in the shift from phenotypic to genotyping‐based surveillance of shigellosis in Belgium.