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

Whole Genome Multi-Locus Sequence Typing and Genomic Single Nucleotide Polymorphism Analysis for Epidemiological Typing of Pseudomonas aeruginosa From Indonesian Intensive Care Units

We have previously studied carbapenem non-susceptible Pseudomonas aeruginosa (CNPA) strains from intensive care units (ICUs) in a referral hospital in Jakarta, Indonesia (Pelegrin et al., 2019). We documented that CNPA transmissions and acquisitions among patients were variable over time and that these were not significantly reduced by a set of infection control measures. Three high risk international CNPA clones (sequence type (ST)235, ST823, ST357) dominated, and carbapenem resistance was due to carbapenemase-encoding genes and mutations in the porin OprD. Pelegrin et al. (2019) reported core genome analysis of these strains. We present a more refined and detailed whole genome-based analysis of major clones represented in the same dataset. As per our knowledge, this is the first study reporting Single Nucleotide Polymorphisms (wgSNP) analysis of Pseudomonas strains. With whole genome-based Multi Locus Sequence Typing (wgMLST) of the 3 CNPA clones (ST235, ST357 and ST823), three to eleven subgroups with up to 200 allelic variants were observed for each of the CNPA clones. Furthermore, we analyzed these CNPA clone clusters for the presence of wgSNP to redefine CNPA transmission events during hospitalization. A maximum number 35350 SNPs (including non-informative wgSNPs) and 398 SNPs (ST-specific_informative-wgSNPs) were found in ST235, 34,570 SNPs (including non-informative wgSNPs) and 111 SNPs (ST-specific_informative-wgSNPs) in ST357 and 26,443 SNPs (including non-informative SNPs) and 61 SNPs (ST-specific_informative-wgSNPs) in ST823. ST-specific_Informative-wgSNPs were commonly noticed in sensor-response regulator genes. However, the majority of non-informative wgSNPs was found in conserved hypothetical proteins or in uncharacterized proteins. Of note, antibiotic resistance and virulence genes segregated according to the wgSNP analyses. A total of 8 transmission chains for ST235 strains followed by 9 and 4 possible transmission chains for ST357 and ST823 were traceable on the basis of pairwise distances of informative-wgSNPs (0 to 4 SNPs) among the strains. The present study demonstrates the value of detailed whole genome sequence analysis for highly refined epidemiological analysis of P. aeruginosa.

Severity of infection with the SARS-CoV-2 B.1.1.7 lineage among hospitalized COVID-19 patients in Belgium

Introduction

The pathogenesis of COVID-19 depends on the interplay between host characteristics, viral characteristics and contextual factors. Here, we compare COVID-19 disease severity between hospitalized patients in Belgium infected with the SARS-CoV-2 variant B.1.1.7 and those infected with previously circulating strains.

Methods

The study is conducted within a causal framework to study the severity of SARS-CoV-2 variants by merging surveillance registries in Belgium. Infection with SARS-CoV-2 B.1.1.7 (‘exposed’) was compared to infection with previously circulating strains (‘unexposed’) in terms of the manifestation of severe COVID-19, intensive care unit (ICU) admission, or in-hospital mortality. The exposed and unexposed group were matched based on the hospital and the mean ICU occupancy rate during the patient’s hospital stay. Other variables identified as confounders in a Directed Acyclic Graph (DAG) were adjusted for using regression analysis. Sensitivity analyses were performed to assess the influence of selection bias, vaccination rollout, and unmeasured confounding.

Results

We observed no difference between the exposed and unexposed group in severe COVID-19 disease or in-hospital mortality (RR = 1.15, 95% CI [0.93–1.38] and RR = 0.92, 95% CI [0.62–1.23], respectively). The estimated standardized risk to be admitted in ICU was significantly higher (RR = 1.36, 95% CI [1.03–1.68]) when infected with the B.1.1.7 variant. An age-stratified analysis showed that among the younger age group (≤65 years), the SARS-CoV-2 variant B.1.1.7 was significantly associated with both severe COVID-19 progression and ICU admission.

Conclusion

This matched observational cohort study did not find an overall increased risk of severe COVID-19 or death associated with B.1.1.7 infection among patients already hospitalized. There was a significant increased risk to be transferred to ICU when infected with the B.1.1.7 variant, especially among the younger age group. However, potential selection biases advocate for more systematic sequencing of samples from hospitalized COVID-19 patients.

Metagenomics and artificial intelligence in the context of human health

Human microbiome is ubiquitous, dynamic, and site-specific consortia of microbial communities. The pathogenic nature of microorganisms within human tissues has led to an increase in microbial studies. Characterization of genera, like Streptococcus, Cutibacterium, Staphylococcus, Bifidobacterium, Lactococcus and Lactobacillus through culture-dependent and culture-independent techniques has been reported. However, due to the unique environment within human tissues, it is difficult to culture these microorganisms making their molecular studies strenuous. MGs offer a gateway to explore and characterize hidden microbial communities through a culture-independent mode by direct DNA isolation. By function and sequence-based MGs, Scientists can explore the mechanistic details of numerous microbes and their interaction with the niche. Since the data generated from MGs studies is highly complex and multi-dimensional, it requires accurate analytical tools to evaluate and interpret the data. Artificial intelligence (AI) provides the luxury to automatically learn the data dimensionality and ease its complexity that makes the disease diagnosis and disease response easy, accurate and timely. This review provides insight into the human microbiota and its exploration and expansion through MG studies. The review elucidates the significance of MGs in studying the changing microbiota during disease conditions besides highlighting the role of AI in computational analysis of MG data.

Phylogenetic Analysis of Serogroup O5 <i>Vibrio cholerae</i> that Caused Successive Cholera Outbreaks — Guangdong Province, China, 2020–2021

Introduction

Methods

Results

Conclusions

Using MALDI-TOF spectra in epidemiological surveillance for the detection of bacterial subgroups with a possible epidemic potential

Background

For the purpose of epidemiological surveillance, the Hospital University Institute Méditerranée infection has implemented since 2013 a system named MIDaS, based on the systematic collection of routine activity materials, including MALDI-TOF spectra, and results. The objective of this paper is to present the pipeline we use for processing MALDI-TOF spectra during epidemiological surveillance in order to disclose proteinic cues that may suggest the existence of epidemic processes in complement of incidence surveillance. It is illustrated by the analysis of an alarm observed for Streptococcus pneumoniae.

Methods

The MALDI-TOF spectra analysis process looks for the existence of clusters of spectra characterized by a double time and proteinic close proximity. This process relies on several specific methods aiming at contrasting and clustering the spectra, presenting graphically the results for an easy epidemiological interpretation, and for determining the discriminating spectra peaks with their possible identification using reference databases.

Results

The use of this pipeline in the case of an alarm issued for Streptococcus pneumoniae has made it possible to reveal a cluster of spectra with close proteinic and temporal distances, characterized by the presence of three discriminant peaks (5228.8, 5917.8, and 8974.3 m/z) and the absence of peak 4996.9 m/z. A further investigation on UniProt KB showed that peak 5228.8 is possibly an OxaA protein and that the absent peak may be a transposase.

Conclusion

This example shows this pipeline may support a quasi-real time identification and characterization of clusters that provide essential information on a potentially epidemic situation. It brings valuable information for epidemiological sensemaking and for deciding on the continuation of the epidemiological investigation, in particular the involving of additional costly resources to confirm or invalidate the alarm.

Clinical trials registration

NCT03626987.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06803-3.

Analysis of the antimicrobial resistance gene frequency in whole-genome sequenced Vibrio from Latin American countries

Vibrio species are important environmental-related bacteria responsible for diverse infections in humans due to consumption of contaminated water and seafood in underdeveloped areas of the world. This study aimed to investigate the frequency of antimicrobial resistance genes in 577 sequenced Vibrio cholerae, Vibrio parahaemolyticus and Vibrio vulnificus strains isolated in Latin American countries available at the NCBI Pathogen Detection database and to determine the sequence type (ST) of the strains. Almost all strains studied (99.8%) carried at least one antimicrobial resistance gene, while 54.2 % presented a multidrug-resistance profile. The Vibrio strains exhibited genotypic resistance to 11 antimicrobial classes and almG, varG, and catB9, which confer resistance to antibiotic peptides, β-lactams and amphenicols, respectively, were the most detected genes. Vibrio parahaemolyticus and V. vulnificus showed a broad diversity of STs. Vibrio cholerae strains isolated in Haiti after 2010's earthquake presented the highest diversity and amount of resistance genes in the set of strains analysed and mostly belonged to ST69. In conclusion, the detection of resistance genes from 11 antimicrobial classes and the high number of multidrug-resistant Vibrio species strains emphasize that Latin American public health authorities should employ more efficient control measures and that special attention should be given for the rational use of antimicrobials in human therapy and aquaculture, since the consumption of contaminated water and seafood with resistant Vibrio may result in human infections difficult to be treated.

Prevention and Control of Pathogens Based on Big-Data Mining and Visualization Analysis

Morbidity and mortality caused by infectious diseases rank first among all human illnesses. Many pathogenic mechanisms remain unclear, while misuse of antibiotics has led to the emergence of drug-resistant strains. Infectious diseases spread rapidly and pathogens mutate quickly, posing new threats to human health. However, with the increasing use of high-throughput screening of pathogen genomes, research based on big data mining and visualization analysis has gradually become a hot topic for studies of infectious disease prevention and control. In this paper, the framework was performed on four infectious pathogens (Fusobacterium, Streptococcus, Neisseria, and Streptococcus salivarius) through five functions: 1) genome annotation, 2) phylogeny analysis based on core genome, 3) analysis of structure differences between genomes, 4) prediction of virulence genes/factors with their pathogenic mechanisms, and 5) prediction of resistance genes/factors with their signaling pathways. The experiments were carried out from three angles: phylogeny (macro perspective), structure differences of genomes (micro perspective), and virulence and drug-resistance characteristics (prediction perspective). Therefore, the framework can not only provide evidence to support the rapid identification of new or unknown pathogens and thus plays a role in the prevention and control of infectious diseases, but also help to recommend the most appropriate strains for clinical and scientific research. This paper presented a new genome information visualization analysis process framework based on big data mining technology with the accommodation of the depth and breadth of pathogens in molecular level research.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Analysis of Resistance Gene Prevalence in Whole-Genome Sequenced Enterobacteriales from Brazil

Enterobacteriales is an order of bacteria responsible for community and hospital-acquired infections related to high rates of antimicrobial resistance and increased treatment costs, morbidity, and mortality globally. The aims of this study were to analyze the frequency of the resistance genes detected and distribution over the years and sources of isolation in sequenced Enterobacteriales strains isolated in Brazil and available at the Pathogen Detection website. The presence of resistance genes was analyzed in 1,507 whole-genome sequenced strains of 19 Enterobacteriales species. A total of 58.0% of the strains presented resistance genes to at least one antimicrobial class and 684 strains presented a multidrug-resistant (MDR) profile. Resistance genes to 14 classes of antimicrobials were detected. Aminoglycosides presented the most prevalent and diverse resistance genes, while the sulfonamide resistance gene, sul2, was the most prevalent among the strains studied. The presence of resistance genes from 14 different antimicrobial classes, the high levels of MDR strains, and the detection of genes related to clinical and veterinary-used drugs reinforce the necessity of more efficient control measures. Moreover, it warns for the necessity of the rational use of antimicrobials in veterinary and clinical situations in Brazil, since contaminated food may act as a vehicle for human infections.

Status and potential of bacterial genomics for public health practice: a scoping review

BACKGROUND

Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist's perspective.

METHODS

In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed.

RESULTS

Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data.

CONCLUSIONS

For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist's perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance.

An Investigation of an Acute Gastroenteritis Outbreak: Cronobacter sakazakii, a Potential Cause of Food-Borne Illness

Whole genome sequencing (WGS) has been widely used in traceability of food-borne outbreaks nowadays. Here, an interesting connection between Cronobacter sakazakii and food-borne acute gastroenteritis (AGE) was noticed. In October 2016, an AGE outbreak affecting 156 cases occurred in a local senior high school. Case-control study including 70 case-patients and 295 controls indicated a strong association between eating supper at school canteen of the outbreak onset and AGE, as revealed by the Odds Ratio (OR: 95.32). Six recovered Cronobacter strains were evaluated and compared using pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST) and WGS. A phylogenetic tree of whole genomic single nucleotide polymorphisms (wgSNPs) were generated to traceback the potential contamination source in this outbreak. C. sakazakii isolates S2 from a patient's rectal swab and S4 from leftover food sample shared identical PFGE pattern and sequence type (ST73), and clustered tightly together in the SNP phylogenetic tree. C. sakazakii isolates S5 and S6 from food delivery containers were both ST4 but with different PFGE patterns. Cronobacter isolates S1 and S3 from two patients' rectal swab were sequenced to be C. malonaticus and shared another PFGE pattern (ST567). The interesting feature of this study was the implication of C. sakazakii as a causative agent in food-borne AGE occurring in healthy adults, although C. sakazakii is considered as an opportunistic pathogen and generally affects neonates, infants and immunocompromised adults.