•Next generation sequencing makes it possible to standardise methods.•Next generation sequencing has a large number of applications in clinical microbiology.•Next generation sequencing can be used to ...track outbreak-specific clones.•Next generation sequencing makes personalised microbiology possible.
Current molecular diagnostics of human pathogens provide limited information that is often not sufficient for outbreak and transmission investigation. Next generation sequencing (NGS) determines the DNA sequence of a complete bacterial genome in a single sequence run, and from these data, information on resistance and virulence, as well as information for typing is obtained, useful for outbreak investigation. The obtained genome data can be further used for the development of an outbreak-specific screening test. In this review, a general introduction to NGS is presented, including the library preparation and the major characteristics of the most common NGS platforms, such as the MiSeq (Illumina) and the Ion PGM™ (ThermoFisher). An overview of the software used for NGS data analyses used at the medical microbiology diagnostic laboratory in the University Medical Center Groningen in The Netherlands is given. Furthermore, applications of NGS in the clinical setting are described, such as outbreak management, molecular case finding, characterization and surveillance of pathogens, rapid identification of bacteria using the 16S-23S rRNA region, taxonomy, metagenomics approaches on clinical samples, and the determination of the transmission of zoonotic micro-organisms from animals to humans. Finally, we share our vision on the use of NGS in personalised microbiology in the near future, pointing out specific requirements.
Purpose
Earlier, we showed in acute myeloid leukemia (AML) patients that the microbiota changes dramatically during anticancer treatment, coinciding with gastrointestinal mucositis: The commensal ...anaerobic populations reduce in favor of potential pathogens. Therefore, interventions targeting the microbiota during mucositis might be interesting but can better be tested in animals than in vulnerable mucositis patients. Here, we aimed to study the potential microbial changes during methotrexate (MTX)-induced gastrointestinal mucositis in a well-established rat model and to study whether this model can be used for future microbial intervention studies.
Methods
After injection with MTX or saline (day 0), rats were sacrificed between days 2 and 11. Plasma citrulline level, jejunal histology, and the number and diversity of intestinal bacteria in feces (using fluorescence in situ hybridization (FISH)) were determined.
Results
Mucositis was most severe on day 4 when food intake, plasma citrulline, and villus length were the lowest, compared with controls (
P <
0.0125). At the same time, MTX-treated rats showed an overall decrease (705-fold) in most bacteria (using a universal probe), compared with controls (
P <
0.125). Reduced bacterial presence was related with the presence of diarrhea and a reduced villus length (rho = 0.38,
P <
0.05). At day 4, there was an absolute and relative decrease of anaerobes (13-fold and −58 %, respectively) and streptococci (296-fold and −1 %, respectively) but a relative increase of
Bacteroides
(+49 %), compared with controls (
P <
0.125).
Conclusions
In the mucositis rat model, we found substantial decreases in the number and diversity of microbiota, resembling earlier findings in humans. The model therefore seems well suited to study the effects of different microbial interventions on mucositis, prior to performing human studies.
The ability of Escherichia coli O157:H7 to induce cellular damage leading to disease in humans is related to numerous virulence factors, most notably the stx gene, encoding Shiga toxin (Stx) and ...carried by a bacteriophage. Loss of the Stx-encoding bacteriophage may occur during infection or culturing of the strain. Here, we collected stx-positive and stx-negative variants of E. coli O157:H7/NM (nonmotile) isolates from patients with gastrointestinal complaints. Isolates were characterized by whole-genome sequencing (WGS), and their virulence properties and phylogenetic relationship were determined. Because of the presence of the eae gene but lack of the bfpA gene, the stx-negative isolates were considered atypical enteropathogenic E. coli (aEPEC). However, they had phenotypic characteristics similar to those of the Shiga toxin-producing E. coli (STEC) isolates and belonged to the same sequence type, ST11. Furthermore, EPEC and STEC isolates shared similar virulence genes, the locus of enterocyte effacement region, and plasmids. Core genome phylogenetic analysis using a gene-by-gene typing approach showed that the sorbitol-fermenting (SF) stx-negative isolates clustered together with an SF STEC isolate and that one non-sorbitol-fermenting (NSF) stx-negative isolate clustered together with NSF STEC isolates. Therefore, these stx-negative isolates were thought either to have lost the Stx phage or to be a progenitor of STEC O157:H7/NM. As detection of STEC infections is often based solely on the identification of the presence of stx genes, these may be misdiagnosed in routine laboratories. Therefore, an improved diagnostic approach is required to manage identification, strategies for treatment, and prevention of transmission of these potentially pathogenic strains.
Urinary tract infections (UTIs) are often caused by
. Their increasing resistance to broad-spectrum antibiotics challenges the treatment of UTIs. Whereas,
ST131 is often multidrug resistant (MDR), ...ST69 remains susceptible to antibiotics such as cephalosporins. Both STs are commonly linked to community and nosocomial infections.
phylogenetic groups B2 and D are associated with virulence and resistance profiles making them more pathogenic. Little is known about the population structure of
isolates obtained from urine samples of hospitalized patients in Brazil. Therefore, we characterized
isolated from urine samples of patients hospitalized at the university and three private hospitals in Rio de Janeiro, using whole genome sequencing. A high prevalence of
ST131 and ST69 was found, but other lineages, namely ST73, ST648, ST405, and ST10 were also detected. Interestingly, isolates could be divided into two groups based on their antibiotic susceptibility. Isolates belonging to ST131, ST648, and ST405 showed a high resistance rate to all antibiotic classes tested, whereas isolates belonging to ST10, ST73, ST69 were in general susceptible to the antibiotics tested. Additionally, most ST69 isolates, normally resistant to aminoglycosides, were susceptible to this antibiotic in our population. The majority of ST131 isolates were ESBL-producing and belonged to serotype O25:H4 and the H30-R subclone. Previous studies showed that this subclone is often associated with more complicated UTIs, most likely due to their high resistance rate to different antibiotic classes. Sequenced isolates could be classified into five phylogenetic groups of which B2, D, and F showed higher resistance rates than groups A and B1. No significant difference for the predicted virulence genes scores was found for isolates belonging to ST131, ST648, ST405, and ST69. In contrast, the phylogenetic groups B2, D and F showed a higher predictive virulence score compared to phylogenetic groups A and B1. In conclusion, despite the diversity of
isolates causing UTIs, clonal groups O25:H4-B2-ST131 H30-R, O1:H6-B2-ST648, and O102:H6-D-ST405 were the most prevalent. The emergence of highly virulent and MDR
in Brazil is of high concern and requires more attention from the health authorities.
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.
(
.coli) O157 that do not produce Shiga toxin and do not possess flagellar antigen H7 are of diverse H serotypes. In this study, the antibiotic resistance properties, genotype of a set of virulence ...associated genes and the phylogenetic background of
O157:non-H7 groups were compared. Whole genome sequencing was performed on fourteen O157:non-H7 isolates collected in the STEC-ID-net study. The genomes were compared with
O157 genomes and a typical Enteropathogenic
(tEPEC) genome downloaded from NCBI. Twenty-six (86%) of the analyzed genomes had the intimin encoding gene
but of different types mostly correlating with their H types, e.g., H16, H26, H39, and H45 carried intimin type ε, β, κ, and α, respectively. They belonged to several
phylogenetic groups, i.e., to phylogenetic group A, B1, B2, and D. Seven (50%) of our collected O157:non-H7 isolates were resistant to two or more antibiotics. Several mobile genetic elements, such as plasmids, insertion elements, and pathogenicity islands, carrying a set of virulence and resistance genes were found in the
O157:non-H7 isolates. Core genome phylogenetic analysis showed that O157:non-H7 isolates probably evolved from different phylogenetic lineages and were distantly related to the
O157:H7 lineage. We hypothesize that independent acquisition of mobile genetic elements by isolates of different lineages have contributed to the different molecular features of the O157:non-H7 strains. Although distantly related to the STEC O157,
O157:non-H7 isolates from multiple genetic background could be considered as pathogen of concern for their diverse virulence and antibiotic resistance properties.
Shiga toxin-producing Escherichia coli (STEC) is an enteropathogen of public health concern because of its ability to cause serious illness and outbreaks. In this prospective study, a diagnostic ...screening algorithm to categorize STEC infections into risk groups was evaluated. The algorithm consists of prescreening stool specimens with real-time PCR (qPCR) for the presence of stx genes. The qPCR-positive stool samples were cultured in enrichment broth and again screened for stx genes and additional virulence factors (escV, aggR, aat, bfpA) and O serogroups (O26, O103, O104, O111, O121, O145, O157). Also, PCR-guided culture was performed with sorbitol MacConkey agar (SMAC) and CHROMagar STEC medium. The presence of virulence factors and O serogroups was used for presumptive pathotype (PT) categorization in four PT groups. The potential risk for severe disease was categorized from high risk for PT group I to low risk for PT group III, whereas PT group IV consists of unconfirmed stx qPCR-positive samples. In total, 5,022 stool samples of patients with gastrointestinal symptoms were included. The qPCR detected stx genes in 1.8% of samples. Extensive screening for virulence factors and O serogroups was performed on 73 samples. After enrichment, the presence of stx genes was confirmed in 65 samples (89%). By culture on selective media, STEC was isolated in 36% (26/73 samples). Threshold cycle (CT) values for stx genes were significantly lower after enrichment compared to direct qPCR (P < 0.001). In total, 11 (15%), 19 (26%), 35 (48%), and 8 (11%) samples were categorized into PT groups I, II, III, and IV, respectively. Several virulence factors (stx2, stx2a, stx2f, toxB, eae, efa1, cif, espA, tccP, espP, nleA and/or nleB, tir cluster) were associated with PT groups I and II, while others (stx1, eaaA, mch cluster, ireA) were associated with PT group III. Furthermore, the number of virulence factors differed between PT groups (analysis of variance, P < 0.0001). In conclusion, a diagnostic algorithm enables fast discrimination of STEC infections associated with a high to moderate risk for severe disease (PT groups I and II) from less-virulent STEC (PT group III).
•Next generation sequencing makes it possible to standardise methods.•Next generation sequencing has a large number of applications in clinical microbiology.•Next generation sequencing can be used to ...track outbreak-specific clones.•Next generation sequencing makes personalised microbiology possible.
Current molecular diagnostics of human pathogens provide limited information that is often not sufficient for outbreak and transmission investigation. Next generation sequencing (NGS) determines the DNA sequence of a complete bacterial genome in a single sequence run, and from these data, information on resistance and virulence, as well as information for typing is obtained, useful for outbreak investigation. The obtained genome data can be further used for the development of an outbreak-specific screening test. In this review, a general introduction to NGS is presented, including the library preparation and the major characteristics of the most common NGS platforms, such as the MiSeq (Illumina) and the Ion PGM™ (ThermoFisher). An overview of the software used for NGS data analyses used at the medical microbiology diagnostic laboratory in the University Medical Center Groningen in The Netherlands is given. Furthermore, applications of NGS in the clinical setting are described, such as outbreak management, molecular case finding, characterization and surveillance of pathogens, rapid identification of bacteria using the 16S-23S rRNA region, taxonomy, metagenomics approaches on clinical samples, and the determination of the transmission of zoonotic micro-organisms from animals to humans. Finally, we share our vision on the use of NGS in personalised microbiology in the near future, pointing out specific requirements.
In the rapidly evolving domain of e-commerce, analyzing customer feedback through reviews is crucial, particularly for understanding and enhancing consumer experience in the Bangladeshi market. Our ...comprehensive dataset, derived from two Bangladeshi e-commerce platforms, Daraz and Pickaboo, features a diverse collection of reviews in both Bengali and English, covering a broad range of products. These reviews are not only rich in linguistic variety but also encapsulate a spectrum of emotions, some even conveyed through emojis, offering a deep dive into consumer sentiment. Expert annotators have meticulously examined and categorized each review, classifying emotions into five distinct types - Happiness, Sadness, Fear, Anger, and Love - and sentiments into Positive (Happiness, Love) and Negative (Sadness, Anger, Fear) categories. This level of detailed annotation enables precise assessments of customer emotions and preferences, which are essential for evaluating and improving existing product offerings. Moreover, the insights gleaned from this dataset are invaluable for guiding future product development and uncovering new opportunities in the dynamic Bangladeshi market. Ultimately, this dataset not only serves as a significant resource for sentiment analysis using natural language processing (NLP) techniques but also contributes valuable insights into the unique consumer behavior patterns in Bangladesh, enriching the NLP community's understanding of diverse market dynamics.
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