Integrating Advanced Molecular Technologies into Public Health

Empowering public health: building advanced molecular surveillance in resource-limited settings through collaboration and capacity-building

The rapid detection and continuous surveillance of infectious diseases are important components of an effective public health response. However, establishing advanced molecular surveillance systems, crucial for monitoring and mitigating pandemics, poses significant challenges in resource-limited developing countries. In a collaborative effort, research institutions from Benin joined forces with Mali's National Institute of Public Health to implement a state-of-the-art molecular surveillance system in Mali. This approach was characterized by collaboration, multidisciplinarity, and tutoring. Key activities included a comprehensive assessment of infrastructure and human resources through document reviews, interviews, and laboratory visits; the development and validation of Standard Operating Procedures (SOPs) for advanced molecular surveillance following an inclusive approach; capacity-building initiatives for 25 biologists in Mali on sequencing techniques; and international tutoring sessions for eight Malian professionals held in Benin. These collective efforts enabled Mali to establish an advanced molecular surveillance system aligned with the WHO's global strategy for genomic surveillance. This manuscript aims to share experiences, insights, and outcomes from this initiative, with the hope of contributing to the broader discussion on strengthening global health security through collaborative approaches and capacity-building efforts, particularly in developing countries.

Optimal environmental testing frequency for outbreak surveillance

Public health surveillance for pathogens presents an optimization problem: we require enough sampling to identify intervention-triggering shifts in pathogen epidemiology, such as new introductions or sudden increases in prevalence, but not so much that costs due to surveillance itself outweigh those from pathogen-associated illness. To determine this optimal sampling frequency, we developed a general mathematical model for the introduction of a new pathogen that, once introduced, increases in prevalence exponentially. Given the relative cost of infection vs. sampling, we derived equations for the expected combined cost per unit time of disease burden and surveillance for a specified sampling frequency, and thus the sampling frequency for which the expected total cost per unit time is lowest.

Whole Genome Sequencing-Based Tracing of a 2022 Introduction and Outbreak of Xanthomonas hortorum pv. pelargonii

Globalization has made agricultural commodities more accessible, available, and affordable. However, their global movement increases the potential for invasion by pathogens and necessitates development and implementation of sensitive, rapid, and scalable surveillance methods. Here, we used 35 strains, isolated by multiple diagnostic laboratories, as a case study for using whole genome sequence data in a plant disease diagnostic setting. Twenty-seven of the strains were isolated in 2022 and identified as Xanthomonas hortorum pv. pelargonii. Eighteen of these strains originated from material sold by a plant breeding company that had notified clients following a release of infected geranium cuttings. Analyses of whole genome sequences revealed epidemiological links among the 27 strains from different growers that confirmed a common source of the outbreak and uncovered likely secondary spread events within facilities that housed plants originating from different plant breeding companies. Whole genome sequencing data were also analyzed to reveal how preparatory and analytical methods can impact conclusions on outbreaks of clonal pathogenic strains. The results demonstrate the potential power of using whole genome sequencing among a network of diagnostic labs and highlight how sharing such data can help shorten response times to mitigate outbreaks more expediently and precisely than standard methods.

Whole-Genome Sequencing of Shiga Toxin-Producing Escherichia coli for Characterization and Outbreak Investigation

Shiga toxin-producing Escherichia coli (STEC) causes high frequencies of foodborne infections worldwide and has been linked to numerous outbreaks each year. Pulsed-field gel electrophoresis (PFGE) has been the gold standard for surveillance until the recent transition to whole-genome sequencing (WGS). To further understand the genetic diversity and relatedness of outbreak isolates, a retrospective analysis of 510 clinical STEC isolates was conducted. Among the 34 STEC serogroups represented, most (59.6%) belonged to the predominant six non-O157 serogroups. Core genome single nucleotide polymorphism (SNP) analysis differentiated clusters of isolates with similar PFGE patterns and multilocus sequence types (STs). One serogroup O26 outbreak strain and another non-typeable (NT) strain, for instance, were identical by PFGE and clustered together by MLST; however, both were distantly related in the SNP analysis. In contrast, six outbreak-associated serogroup O5 strains clustered with five ST-175 serogroup O5 isolates, which were not part of the same outbreak as determined by PFGE. The use of high-quality SNP analyses enhanced the discrimination of these O5 outbreak strains into a single cluster. In all, this study demonstrates how public health laboratories can more rapidly use WGS and phylogenetics to identify related strains during outbreak investigations while simultaneously uncovering important genetic attributes that can inform treatment practices.

Preparation of polyclonal antibody against a universal bacterial antigen OmpA deduced by bioinformatic analysis and preliminary evaluation of concentration effects on foodborne pathogens

Rapid and ultrasensitive microbial detection in actual samples have challenges because of target pathogen diversity and low abundance. In this study, we attempted to capture and concentrate multiple pathogens by combining magnetic beads with polyclonal antibodies against a universal antigen of ompA, LAMOA-1, before further detection. A protein sequence consisting of 241 amino acids with spatial conformation similar to E. coli ompA was identified and expressed as a recombinant protein in prokaryotes according to the results of sequence alignment among 432 sequences of ompA belonging to intestinal bacteria from gram-negative bacteria. Purified from immunized rabbits, the anti-LAMOA-1 antibody was shown to effectively recognize 12 foodborne bacterial species. Antibody-conjugated beads were used to concentrate the bacteria when the bacterial concentration in artificially contaminated samples is between 10 and 100 CFU/mL, which shortens detection duration by 8-24 h. The enrichment strategy is potentially beneficial for detection of foodborne pathogens.

Metagenomics next-generation sequencing provides insights into the causative pathogens from critically ill patients with pneumonia and improves treatment strategies

Background

The metagenomics next-generation sequencing (mNGS) is a promising technique for pathogens diagnosis. However, whether the application of mNGS in critically ill patients with pneumonia could cause anti-infection treatment adjustment and thereby affect the prognosis of these patients has not been explored.

Methods

We retrospectively collected the clinical data of patients diagnosed with pulmonary infection in the ICU of the Affiliated Hospital of Qingdao University from January 2018 to January 2021. These patients with pneumonia were divided into mNGS group and no-mNGS group by whether being performed NGS or not. The clinical data, including demographics, illness history, APACHE II score, length of mechanical ventilation, length of stay in the hospital, length of stay in ICU and outcome, were collected. In addition, the data of pathogens and anti-infection treatment before and after NGS were also collected. Propensity score matching was performed to evaluate the mortality and deterioration rate between NGS group and non-NGS group.

Results

A total of 641 patients diagnosed with pneumonia were screened, and 94 patients were excluded based on exclusion criteria. Finally, 547 patients were enrolled, including 160 patients being performed NGS. Among these 160 patients, 142 cases had NGS-positive results. In addition, new pathogens were detected in 132 specimens by NGS, which included 82 cases with virus, 18 cases with fungus, 17 cases with bacteria, 14 cases with mycoplasma, and 1 case with mycobacterium tuberculosis. Anti-infection treatments were adjusted in some patients who performed NGS, including 48 anti-bacterial treatments, 20 antifungal treatments and 20 antiviral treatments. There were no significant differences in the mortality and deterioration rate between NGS and non-NGS group, but it exhibited a trend that the mortality and deterioration rate of NGS group was lower than non-NGS group after the propensity score matching analysis (15.8% vs 24.3%, P=0.173; 25.6% vs 37.8%, P=0.093).

Conclusion

NGS could affect the anti-infection treatments and had a trend of reducing the mortality and deterioration rate of critically ill patients with pneumonia.

Scope of coverage of medical genetics and genomics in pre-clerkship programs of Canadian faculties of medicine: A curriculum analysis

We appraised the scope of medical genetics and genomics concepts covered in the pre-clerkship programs of Canadian faculties of medicine through an analysis of course objectives. All course objectives linked to medical genetics and genomics in pre-clerkship programs of Canadian faculties of medicine were compiled. From this, the fraction of objectives dedicated to medical genetics and genomics was calculated. Course objectives were also categorized according to a curriculum and a competency classification. Of the 17 Canadian faculties of medicine, the complete set of course syllabi (5 faculties) or the listing of learning objectives (4 faculties) were obtained and reviewed. The fraction of learning objectives dedicated to medical genetics and genomics varied between 0.65% and 5.05%. From the objectives classification, "foundational knowledge" was most frequently covered (64% of the compiled objectives), while topics such as: "ethics and professionalism," "communicate genetics information," and "obtain specialist help" were covered by less than 5%. Coverage of medical genetics and genomics in pre-clerkship programs of Canadian faculties of medicine appears to be low. Genetics and genomics are playing a rapidly expanding role in healthcare and clinical practice and educational programs should consider this new reality.

Empowering quality data - the gordian knot of bringing real innovation into healthcare system

OBJECTIVES

The introduction of Personalised Medicine (PM) into healthcare systems could benefit from a clearer understanding of the distinct national and regional frameworks around the world. Recent engagement by international regulators on maximising the use of real-world evidence (RWE) has highlighted the scope for improving the exploitation of the treasure-trove of health data that is currently largely neglected in many countries. The European Alliance for Personalised Medicine (EAPM) led an international study aimed at identifying the current status of conditions.

METHODS

A literature review examined how far such frameworks exist, with a view to identifying conducive factors - and crucial gaps. This extensive review of key factors across 22 countries and 5 regions revealed a wide variety of attitudes, approaches, provisions and conditions, and permitted the construction of a comprehensive overview of the current status of PM. Based on seven key pillars identified from the literature review and expert panels, the data was quantified, and on the basis of further analysis, an index was developed to allow comparison country by country and region by region.

RESULTS

The results show that United States of America is leading according to overall outcome whereas Kenya scored the least in the overall outcome.

CONCLUSIONS

Still, common approaches exist that could help accelerate take-up of opportunities even in the less prosperous parts of the world.

A systematic analysis of and recommendations for public health events involving brucellosis from 2006 to 2019 in China

Brucellosis is a severe public health problem in China. However, analysis on related infection events is lacking. We performed a systematic analysis of brucellosis laboratory infection and vaccine infection events from 2006 to 2019 in China based on the published literatures. Our analysis showed that most laboratoryBrucellainfections in hospitals were found in Southern China. The identification and handling of suspected samples ofBrucellainfection without following the recommended biosafety protection was the main risk factor. It is important to strengthen the preventive awareness of clinical laboratory staff and physicians, while highlighting the compulsory handling and identification of suspectedBrucella-infected samples in biosafety facilities and following biosafety practices. However, a severe Brucella infection accident at the Northeast Agricultural University, with 28 positive cases, showed that strengthening the management in teaching experiments of students in the veterinary-related profession is essential. However, cluster S2 vaccine strain infection events caused by vaccination and production were mainly observed in Northern China. Strengthening vaccination skills, personal protection, and improving the biosafety management of vaccine production and implementing regular risk surveillance is mandatory. Our analysis provides helpful clues for control of public health events involving brucellosis, as well as implementing intervention strategies is urgent.

Phylogenetic analyses of Salmonella detected along the broiler production chain in Trinidad and Tobago

This study was conducted to determine the phylogenies of Salmonella strains isolated from cross-sectional studies conducted at hatcheries, broiler farms, processing plants, and retail outlets (broiler production chain) in Trinidad and Tobago over 4 yr (2016-2019). Whole-genome sequencing (WGS) was used to characterize Salmonella isolates. Core genome phylogenies of 8 serovars of public health significance were analyzed for similarities in origin and relatedness. In addition, Salmonella strains isolated from human salmonellosis cases in Trinidad were analyzed for their relatedness to the isolates detected along the broiler production chain. The common source of these isolates of diverse serovars within farms, within processing plants, between processing plants and retail outlets, and among farm-processing plant-retail outlet continuum was well-supported (bootstrap value >70%) by the core genome phylogenies for the respective serovars. Also, genome analyses revealed clustering of Salmonella serovars of regional (intra-Caribbean) and international (extra-Caribbean) origin. Similarly, strains of S. Enteritidis and S. Infantis isolated from human clinical salmonellosis in 2019 from Trinidad and Tobago clustered with our processing plant isolates recovered in 2018. This study is the first phylogenetic analysis of Salmonella isolates using WGS from the broiler industry in the Caribbean region. The use of WGS confirmed the genetic relatedness and transmission of Salmonella serovars contaminating chickens in broiler processing, and retailing in the country, with zoonotic and food safety implications for humans.

Are We Prepared for Precision Public Health? An Examination of Genomics Content in Graduate Public Health Programs

OBJECTIVE

With the completion of the Human Genome Project and swift development of genomic technologies, public health practitioners can use these advancements to more precisely target disease interventions to populations at risk. To integrate these innovations into better health outcomes, public health professionals need to have at least a basic understanding of genomics within various disciplines of public health. This descriptive study focused on the current level of genomics content in accredited master of public health (MPH) programs in the United States.

METHODS

We conducted an internet search on all 171 Council on Education for Public Health (CEPH)-accredited MPH programs in the United States for genomics content in required and elective courses using the search terms "genetics," "genomics," and "molecular."

RESULTS

Of the 171 CEPH-accredited MPH programs examined, 52 (30.4%) schools and programs in 34 states offered some type of genomics education. Thirty-five (20.5%) schools and programs had a course in genetic epidemiology, 29 (16.9%) had a course in genetic biostatistics or bioinformatics, and 17 (9.9%) had a course in general public health genomics. The remaining 119 offered no course with a focus on genetics or genomics. In addition, some electives or specifically focused courses related to genomics were offered.

CONCLUSION

We found inadequate training in public health genomics for MPH students. To realize the promise of precision public health and to increase the understanding of genomics among the public health workforce, MPH programs need to find ways to integrate genomics education into their curricula.

A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data

The introduction of genomic methods facilitated standardized molecular disease surveillance. For instance, SNP barcodes in Plasmodium vivax and Plasmodium falciparum malaria allows the characterization of haplotypes, their frequencies and prevalence to reveal temporal and spatial transmission patterns. A confounding factor is the presence of multiple genetically distinct pathogen variants within the same infection, known as multiplicity of infection (MOI). Disregarding ambiguous information, as usually done in ad-hoc approaches, leads to less confident and biased estimates. We introduce a statistical framework to obtain maximum-likelihood estimates (MLE) of haplotype frequencies and prevalence alongside MOI from malaria SNP data, i.e., multiple biallelic marker loci. The number of model parameters increases geometrically with the number of genetic markers considered and no closed-form solution exists for the MLE. Therefore, the MLE needs to be derived numerically. We use the Expectation-Maximization (EM) algorithm to derive the maximum-likelihood estimates, an efficient and easy-to-implement algorithm that yields a numerically stable solution. We also derive expressions for haplotype prevalence based on either all or just the unambiguous genetic information and compare both approaches. The latter corresponds to a biased ad-hoc estimate of prevalence. We assess the performance of our estimator by systematic numerical simulations assuming realistic sample sizes and various scenarios of transmission intensity. For reasonable sample sizes, and number of loci, the method has little bias. As an example, we apply the method to a dataset from Cameroon on sulfadoxine-pyrimethamine resistance in P. falciparum malaria. The method is not confined to malaria and can be applied to any infectious disease with similar transmission behavior. An easy-to-use implementation of the method as an R-script is provided.

PIMGAVir and Vir-MinION: Two Viral Metagenomic Pipelines for Complete Baseline Analysis of 2nd and 3rd Generation Data

The taxonomic classification of viral sequences is frequently used for the rapid identification of pathogens, which is a key point for when a viral outbreak occurs. Both Oxford Nanopore Technologies (ONT) MinION and the Illumina (NGS) technology provide efficient methods to detect viral pathogens. Despite the availability of many strategies and software, matching them can be a very tedious and time-consuming task. As a result, we developed PIMGAVir and Vir-MinION, two metagenomics pipelines that automatically provide the user with a complete baseline analysis. The PIMGAVir and Vir-MinION pipelines work on 2nd and 3rd generation data, respectively, and provide the user with a taxonomic classification of the reads through three strategies: assembly-based, read-based, and clustering-based. The pipelines supply the scientist with comprehensive results in graphical and textual format for future analyses. Finally, the pipelines equip the user with a stand-alone platform with dedicated and various viral databases, which is a requirement for working in field conditions without internet connection.

A Review of Next Generation Sequencing Methods and its Applications in Laboratory Diagnosis

Next-generation sequencing (NGS) is a new technology used to detect the sequence of DNA and RNA and to detect mutations or variations of significance. NGS generates large quantities of sequence data within a short time duration. The various types of sequencing includes Sanger Sequencing, Pyrosequencing, Sequencing by Synthesis (Illumina), Ligation (SoLID), Single molecule Fluorescent Sequencing (Helicos), Single molecule Real time Sequencing (Pacbio), Semiconductor sequencing (Ion torrent technology), Nanopore sequencing and fourth generation sequencing. These methods of sequencing have been modified and improved over the years such that it has become cost effective and accessible to diagnostic laboratories. Management of Outbreaks, rapid identification of bacteria, molecular case finding, taxonomy, detection of the zoonotic agents and guiding prevention strategies in HIV outbreaks are just a few of the many applications of Next Generation sequencing in clinical microbiology.

VPipe: an Automated Bioinformatics Platform for Assembly and Management of Viral Next-Generation Sequencing Data

Next-generation sequencing (NGS) is a powerful tool for detecting and investigating viral pathogens; however, analysis and management of the enormous amounts of data generated from these technologies remains a challenge. Here, we present VPipe (the Viral NGS Analysis Pipeline and Data Management System), an automated bioinformatics pipeline optimized for whole-genome assembly of viral sequences and identification of diverse species. VPipe automates the data quality control, assembly, and contig identification steps typically performed when analyzing NGS data. Users access the pipeline through a secure web-based portal, which provides an easy-to-use interface with advanced search capabilities for reviewing results. In addition, VPipe provides a centralized system for storing and analyzing NGS data, eliminating common bottlenecks in bioinformatics analyses for public health laboratories with limited on-site computational infrastructure. The performance of VPipe was validated through the analysis of publicly available NGS data sets for viral pathogens, generating high-quality assemblies for 12 data sets. VPipe also generated assemblies with greater contiguity than similar pipelines for 41 human respiratory syncytial virus isolates and 23 SARS-CoV-2 specimens. IMPORTANCE Computational infrastructure and bioinformatics analysis are bottlenecks in the application of NGS to viral pathogens. As of September 2021, VPipe has been used by the U.S. Centers for Disease Control and Prevention (CDC) and 12 state public health laboratories to characterize >17,500 and 1,500 clinical specimens and isolates, respectively. VPipe automates genome assembly for a wide range of viruses, including high-consequence pathogens such as SARS-CoV-2. Such automated functionality expedites public health responses to viral outbreaks and pathogen surveillance.

Applied Bioinformatics and Public Health Microbiology: challenges, discoveries and innovations during a pandemic

The eighth Applied Bioinformatics and Public Health Microbiology (ABPHM) conference showcased the recent acceleration of bioinformatic approaches used in public health settings. This included approaches for the surveillance of infectious diseases, understanding microbial evolution and diversity and pathogen interactions. Overall, the meeting highlighted the importance of data-driven approaches used by scientists during the COVID-19 pandemic.

MicrobeTrace: Retooling molecular epidemiology for rapid public health response

Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace.

Rapid advances in the fields of data science and bioinformatics have significantly improved molecular epidemiology tools used in public health and have led to major changes in the way outbreak investigation and pathogen transmission studies are conducted. However, the need for specialized computer skills often impedes the use of many of these tools in the public heath domain. We bridge this knowledge gap by development of an intuitive, standalone tool called MicrobeTrace to securely integrate, visualize and explore pathogen epidemiologic data. MicrobeTrace is an easy to use browser-based tool which can effectively merge contact tracing and/or microbial genomic data with demographic or behavioral information, resulting in elegant and informative networks as well as multiple customizable visualizations. MicrobeTrace can be used offline, with analyses being performed locally in the field, ensuring secure and confidential use of personally identifiable information (PII). We provide real world examples of how MicrobeTrace has been used in public health, including COVID outbreak investigations.

Emergency preparedness for public health threats, surveillance, modelling & forecasting

In the interconnected world, safeguarding global health security is vital for maintaining public health and economic upliftment of any nation. Emergency preparedness is considered as the key to control the emerging public health challenges at both national as well as international levels. Further, the predictive information systems based on routine surveillance, disease modelling and forecasting play a pivotal role in both policy building and community participation to detect, prevent and respond to potential health threats. Therefore, reliable and timely forecasts of these untoward events could mobilize swift and effective public health responses and mitigation efforts. The present review focuses on the various aspects of emergency preparedness with special emphasis on public health surveillance, epidemiological modelling and capacity building approaches. Global coordination and capacity building, funding and commitment at the national and international levels, under the One Health framework, are crucial in combating global public health threats in a holistic manner.

Precision Medicine and Public Health: New Challenges for Effective and Sustainable Health

The development of high-throughput omics technologies represents an unmissable opportunity for evidence-based prevention of adverse effects on human health. However, the applicability and access to multi-omics tests are limited. In Italy, this is due to the rapid increase of knowledge and the high levels of skill and economic investment initially necessary. The fields of human genetics and public health have highlighted the relevance of an implementation strategy at a national level in Italy, including integration in sanitary regulations and governance instruments. In this review, the emerging field of public health genomics is discussed, including the polygenic scores approach, epigenetic modulation, nutrigenomics, and microbiomes implications. Moreover, the Italian state of implementation is presented. The omics sciences have important implications for the prevention of both communicable and noncommunicable diseases, especially because they can be used to assess the health status during the whole course of life. An effective population health gain is possible if omics tools are implemented for each person after a preliminary assessment of effectiveness in the medium to long term.

Application of Next Generation Sequencing in Laboratory Medicine

The rapid development of next-generation sequencing (NGS) technology, including advances in sequencing chemistry, sequencing technologies, bioinformatics, and data interpretation, has facilitated its wide clinical application in precision medicine. This review describes current sequencing technologies, including short- and long-read sequencing technologies, and highlights the clinical application of NGS in inherited diseases, oncology, and infectious diseases. We review NGS approaches and clinical diagnosis for constitutional disorders; summarize the application of U.S. Food and Drug Administration-approved NGS panels, cancer biomarkers, minimal residual disease, and liquid biopsy in clinical oncology; and consider epidemiological surveillance, identification of pathogens, and the importance of host microbiome in infectious diseases. Finally, we discuss the challenges and future perspectives of clinical NGS tests.

Molecular epidemiology in the HIV and SARS-CoV-2 pandemics

PURPOSE OF REVIEW

The aim of this review was to compare and contrast the application of molecular epidemiology approaches for the improved management and understanding of the HIV versus SARS-CoV-2 epidemics.

RECENT FINDINGS

Molecular biology approaches, including PCR and whole genome sequencing (WGS), have become powerful tools for epidemiological investigation. PCR approaches form the basis for many high-sensitivity diagnostic tests and can supplement traditional contact tracing and surveillance strategies to define risk networks and transmission patterns. WGS approaches can further define the causative agents of disease, trace the origins of the pathogen, and clarify routes of transmission. When coupled with clinical datasets, such as electronic medical record data, these approaches can investigate co-correlates of disease and pathogenesis. In the ongoing HIV epidemic, these approaches have been effectively deployed to identify treatment gaps, transmission clusters and risk factors, though significant barriers to rapid or real-time implementation remain critical to overcome. Likewise, these approaches have been successful in addressing some questions of SARS-CoV-2 transmission and pathogenesis, but the nature and rapid spread of the virus have posed additional challenges.

SUMMARY

Overall, molecular epidemiology approaches offer unique advantages and challenges that complement traditional epidemiological tools for the improved understanding and management of epidemics.

The emergence of new trends in clinical laboratory diagnosis

Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical pathology, diagnosis of genetic and microbial diseases, and analysis of clinical chemistry data. These approaches are progressively used for improving the reliability of testing, resulting in reduced diagnostic errors. Artificial intelligence (AI)-based computational approaches mostly rely on training sets obtained from patient data stored in clinical databases. However, the use of AI is associated with several ethical issues, including patient privacy and data ownership. The capacity of AI-based mathematical models to interpret complex clinical data frequently leads to data bias and reporting of erroneous results based on patient data. In order to improve the reliability of computational approaches in clinical diagnostics, strategies to reduce data bias and analyzing real-life patient data need to be further refined.

Molecular and non-molecular approaches to etiologic diagnosis of gastroenteritis

Gastroenteritis is a major cause of mortality and morbidity globally and rapid identification of the causative pathogen is important for appropriate treatment and patient management, implementation of effective infection control measures, reducing hospital length of stay, and reducing overall medical costs. Although stool culture and microscopic examination of diarrheal stool has been the primary method for laboratory diagnosis, culture-independent proteomic and genomic tests are receiving increased attention. Antigen tests for stool pathogens are routinely implemented as rapid and simple analytics whereas molecular tests are now available in various formats from high complexity to waived point-of-care tests. In addition, metagenomic next-generation sequencing stands poised for use as a method for both diagnosis and routine characterization of the gut microbiome in the very near future. Analysis of host biomarkers as indicators of infection status and pathogenesis may also become important for prediction, diagnosis, and monitoring of gastrointestinal infection. Here we review current methods and emerging technologies for the etiologic diagnosis of gastroenteritis in the clinical laboratory. Benefits and limitations of these evolving methods are highlighted.

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.

Integrating whole-genome sequencing within the National Antimicrobial Resistance Surveillance Program in the Philippines

National networks of laboratory-based surveillance of antimicrobial resistance (AMR) monitor resistance trends and disseminate these data to AMR stakeholders. Whole-genome sequencing (WGS) can support surveillance by pinpointing resistance mechanisms and uncovering transmission patterns. However, genomic surveillance is rare in low- and middle-income countries. Here, we implement WGS within the established Antimicrobial Resistance Surveillance Program of the Philippines via a binational collaboration. In parallel, we characterize bacterial populations of key bug-drug combinations via a retrospective sequencing survey. By linking the resistance phenotypes to genomic data, we reveal the interplay of genetic lineages (strains), AMR mechanisms, and AMR vehicles underlying the expansion of specific resistance phenotypes that coincide with the growing carbapenem resistance rates observed since 2010. Our results enhance our understanding of the drivers of carbapenem resistance in the Philippines, while also serving as the genetic background to contextualize ongoing local prospective surveillance.

Genomics for Molecular Epidemiology and Detecting Transmission of Carbapenemase-Producing Enterobacterales in Victoria, Australia, 2012 to 2016

Carbapenemase-producing Enterobacterales (CPE) are being increasingly reported in Australia, and integrated clinical and genomic surveillance is critical to effectively manage this threat. We sought to systematically characterize CPE in Victoria, Australia, from 2012 to 2016.

Carbapenemase-producing Enterobacterales (CPE) are being increasingly reported in Australia, and integrated clinical and genomic surveillance is critical to effectively manage this threat. We sought to systematically characterize CPE in Victoria, Australia, from 2012 to 2016. Suspected CPE were referred to the state public health laboratory in Victoria, Australia, from 2012 to 2016 and examined using phenotypic, multiplex PCR and whole-genome sequencing (WGS) methods and compared with epidemiological metadata. Carbapenemase genes were detected in 361 isolates from 291 patients (30.8% of suspected CPE isolates), mostly from urine (42.1%) or screening samples (34.8%). IMP-4 (28.0% of patients), KPC-2 (25.3%), NDM (24.1%), and OXA carbapenemases (22.0%) were most common. Klebsiella pneumoniae (48.8% of patients) and Escherichia coli (26.1%) were the dominant species. Carbapenemase-inactivation method (CIM) testing reliably detected carbapenemase-positive isolates (100% sensitivity, 96.9% specificity), identifying an additional five CPE among 159 PCR-negative isolates (IMI and SME carbapenemases). When epidemiologic investigations were performed, all pairs of patients designated “highly likely” or “possible” local transmission had ≤23 pairwise single-nucleotide polymorphisms (SNPs) by genomic transmission analysis; conversely, all patient pairs designated “highly unlikely” local transmission had ≥26 pairwise SNPs. Using this proposed threshold, possible local transmission was identified involving a further 16 patients for whom epidemiologic data were unavailable. Systematic application of genomics has uncovered the emergence of polyclonal CPE as a significant threat in Australia, providing important insights to inform local public health guidelines and interventions. Using our workflow, pairwise SNP distances between CPE isolates of ≤23 SNPs suggest local transmission.

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.

The phylogenetic approach for viral infectious disease evolution and epidemiology: An updating review

In the last decade, the phylogenetic approach is recurrent in molecular evolutionary analysis. On 12 May, 2019, about 2 296 213 papers are found, but typing "phylogeny" or "epidemiology AND phylogeny" only 199 804 and 20 133 are retrieved, respectively. Molecular epidemiology in infectious diseases is widely used to define the source of infection as so as the ancestral relationships of individuals sampled from a population. Coalescent theory and phylogeographic analysis have had scientific application in several, recent pandemic events, and nosocomial outbreaks. Hepatitis viruses and immunodeficiency virus (human immunodeficiency virus) have been largely studied. Phylogenetic analysis has been recently applied on Polyomaviruses so as in the more recent outbreaks due to different arboviruses type as Zika and chikungunya viruses discovering the source of infection and the geographic spread. Data on sequences isolated by the microorganism are essential to apply the phylogenetic tools and research in the field of infectious disease phylodinamics is growing up. There is the need to apply molecular phylogenetic and evolutionary methods in areas out of infectious diseases, as translational genomics and personalized medicine. Lastly, the application of these tools in vaccine strategy so as in antibiotic and antiviral researchers are encouraged.

Whole genome sequencing uses for foodborne contamination and compliance: Discovery of an emerging contamination event in an ice cream facility using whole genome sequencing

We review how FDA surveillance identifies several ways that whole genome sequencing (WGS) improves actionable outcomes for public health and compliance in a case involving Listeria monocytogenes contamination in an ice cream facility. In late August 2017 FDA conducted environmental sampling inside an ice cream facility. These isolates were sequenced and deposited into the GenomeTrakr databases. In September 2018 the Centers for Disease Control and Prevention contacted the Florida Department of Health after finding that the pathogen analyses of three clinical cases of listeriosis (two in 2013, one in 2018) were highly related to the aforementioned L. monocytogenes isolates collected from the ice cream facility. in 2017. FDA returned to the ice cream facility in late September 2018 and conducted further environmental sampling and again recovered L. monocytogenes from environmental subsamples that were genetically related to the clinical cases. A voluntary recall was issued to include all ice cream manufactured from August 2017 to October 2018. Subsequently, FDA suspended this food facility's registration. WGS results for L. monocytogenes found in the facility and from clinical samples clustered together by 0-31 single nucleotide polymorphisms (SNPs). The FDA worked together with the Centers for Disease Control and Prevention, as well as the Florida Department of Health, and the Florida Department of Agriculture and Consumer Services to recall all ice cream products produced by this facility. Our data suggests that when available isolates from food facility inspections are subject to whole genome sequencing and the subsequent sequence data point to linkages between these strains and recent clinical isolates (i.e., <20 nucleotide differences), compliance officials should take regulatory actions early to prevent further potential illness. The utility of WGS for applications related to enforcement of FDA compliance programs in the context of foodborne pathogens is reviewed.

Platforms and Analytical Tools Used in Nucleic Acid Sequence-Based Microbial Genotyping Procedures

In the decade and a half since the introduction of next-generation sequencing (NGS), the technical feasibility, cost, and overall utility of sequencing have changed dramatically, including applications for infectious disease epidemiology. Massively parallel sequencing technologies have decreased the cost of sequencing by more than 6 orders or magnitude over this time, with a corresponding increase in data generation and complexity. This review provides an overview of the basic principles, chemistry, and operational mechanics of current sequencing technologies, including both conventional Sanger and NGS approaches. As the generation of large amounts of sequence data becomes increasingly routine, the role of bioinformatics in data analysis and reporting becomes all the more critical, and the successful deployment of NGS in public health settings requires careful consideration of changing information technology, bioinformatics, workforce, and regulatory requirements. While there remain important challenges to the sustainable implementation of NGS in public health, in terms of both laboratory and bioinformatics capacity, the impact of these technologies on infectious disease surveillance and outbreak investigations has been nothing short of revolutionary. Understanding the important role that NGS plays in modern public health laboratory practice is critical, as is the need to ensure appropriate workforce, infrastructure, facilities, and funding consideration for routine NGS applications, future innovation, and rapidly scaling NGS-based infectious disease surveillance and outbreak response activities. *This article is part of a curated collection.

MYCOBACTERIUM CHIMAERA INFECTIONS AFTER CARDIOVASCULAR SURGERY: LESSONS FROM A GLOBAL OUTBREAK

A global outbreak of invasive Mycobacterium chimaera infections has been associated with exposure to certain heater-cooler devices (HCDs) used during cardiopulmonary bypass. Outbreak investigations have shown that these HCDs harbor M. chimaera in water circuits and generate bio-aerosols in the operating room, leading to airborne transmission to patients during surgery. Whole genome sequencing data support a common-source outbreak originating at an HCD manufacturing facility. Most clinical infections are associated with implanted devices, diagnosis is often delayed, and treatment requires device removal and prolonged antibiotic therapy. Because it is nearly impossible to eradicate M. chimaera from HCDs using existing disinfection approaches, strict separation of HCD exhaust from operating room air is necessary to prevent patient exposure. Lessons learned from this outbreak include: 1) medical device risks are difficult to predict, requiring improved expert review before approval, and 2) advances in genomics provide powerful tools for outbreak investigation and public health surveillance.

HCV adaptation to HIV coinfection

Human immunodeficiency virus (HIV) infection is rising as a leading cause of morbidity and mortality among hepatitis C virus (HCV)-infected patients. Both viruses interact in co-infected hosts, which may affect their intra-host evolution, potentially leading to differing genetic composition of viral populations in co-infected (CIP) and mono-infected (MIP) patients. Here, we investigate genetic differences between intra-host variants of the HCV hypervariable region 1 (HVR1) sampled from CIP and MIP. Nucleotide (nt) sequences of intra-host HCV HVR1 variants (N = 28,622) obtained from CIP (N = 112) and MIP (n = 176) were represented using 148 physical-chemical (PhyChem) indexes of DNA nt dimers. Significant (p < .0001) differences in the means and frequency distributions of 7 PhyChem properties were found between HVR1 variants from both groups. Linear projection analysis of 29 PhyChem features extracted from such PhyChem properties showed that the CIP and MIP HVR1 variants have a distinct distribution in the modeled 2D-space, with only ~1.3% of PhyChem profiles (N = 6782), shared by all HVR1 variants, being found in both groups. Probabilistic neural network (PNN) and naïve Bayesian (NB) classifiers trained on the PhyChem features accurately classified HVR1 variants by the group in cross-validation experiments (AUROC ≥ 0.96). Similarly, both models showed a high accuracy (AUROC ≥ 0.95) when evaluated on a test dataset of HVR1 sequences obtained from 10 patients, data from whom were not used for model building. Both models performed at the expected lower accuracy on randomly labeled datasets in cross-validation experiments (AUROC = 0.50). The random-label trained PNN showed a similar drop in accuracy on the test dataset (AUROC = 0.48), indicating that the detected associations were unlikely due to random correlations. Marked differences in genetic composition of HCV HVR1 variants sampled from CIP and MIP suggest differing intra-host HCV evolution in the presence of HIV infection. PhyChem features identified here may be used for detection of HIV infection from intra-host HCV variants alone in co-infected patients, thus facilitating monitoring for HIV introduction to high-risk populations with high HCV prevalence.

Molecular versus culture-based testing for gastrointestinal infection

PURPOSE OF REVIEW

Molecular-based diagnostic methods for the detection of gastrointestinal pathogens are becoming increasingly commonplace in microbiology laboratories. This review aims to summarize recent developments in this field and discuss the clinical application and limitations of implementing these techniques.

RECENT FINDINGS

Recent evaluations of multiplex PCR assays show increased sensitivity whenever compared with standard microbiological culture-based methods. In addition to shorter turnaround times, assays can detect an increased repertoire of pathogens from a single specimen and provide useful information for infection prevention and control practices. There are many limitations, however, associated with their use, including clinical interpretation of results and lack of concordance between different test panels. Newer technologies, such as metagenomic analysis, can provide comprehensive information useful to both patient management and public health surveillance.

SUMMARY

Molecular techniques are capable of replacing culture in the diagnosis of gastrointestinal infections. Whether all positive results, however, represent true infection is still debateable, as is the clinical significance of identifying more than one pathogen. As it currently stands, microbiological culture remains vital for public health surveillance, monitoring antibiotic resistance and managing outbreaks.

From public health genomics to precision public health: a 20-year journey

In this paper, we review the evolution of the field of public health genomics in the United States in the past two decades. Public health genomics focuses on effective and responsible translation of genomic science into population health benefits. We discuss the relationship of the field to the core public health functions and essential services, review its evidentiary foundation, and provide examples of current US public health priorities and applications. We cite examples of publications to illustrate how Genetics in Medicine reflected the evolution of the field. We also reflect on how public-health genomics is contributing to the emergence of "precision public health" with near-term opportunities offered by the US Precision Medicine (AllofUs) Initiative.

Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology

BACKGROUND

Next generation sequencing (NGS) is increasingly being used in clinical microbiology. Like every new technology adopted in microbiology, the integration of NGS into clinical and routine workflows must be carefully managed.

AIM

To review the practical aspects of implementing bacterial whole genome sequencing (WGS) in routine diagnostic laboratories.

SOURCES

Review of the literature and expert opinion.

CONTENT

In this review, we discuss when and how to integrate whole genome sequencing (WGS) in the routine workflow of the clinical laboratory. In addition, as the microbiology laboratories have to adhere to various national and international regulations and criteria for their accreditation, we deliberate on quality control issues for using WGS in microbiology, including the importance of proficiency testing. Furthermore, the current and future place of this technology in the diagnostic hierarchy of microbiology is described as well as the necessity of maintaining backwards compatibility with already established methods. Finally, we speculate on the question of whether WGS can entirely replace routine microbiology in the future and the tension between the fact that most sequencers are designed to process multiple samples in parallel whereas for optimal diagnosis a one-by-one processing of the samples is preferred. Special reference is made to the cost and turnaround time of WGS in diagnostic laboratories.

IMPLICATIONS

Further development is required to improve the workflow for WGS, in particular to shorten the turnaround time, reduce costs, and streamline downstream data analyses. Only when these processes reach maturity will reliance on WGS for routine patient management and infection control management become feasible, enabling the transformation of clinical microbiology into a genome-based and personalized diagnostic field.