Discovering disease-causing pathogens in resource-scarce Southeast Asia using a global metagenomic pathogen monitoring system

First parechovirus reported case in Saudi Arabia in hospitalized immunocompromised adult patient

Human parechovirus, a member of the Picornaviridae family (PeVs), can lead to severe infections, including severe meningitis, meningoencephalitis, and sepsis-like syndrome. We report a case of human parechovirus-related encephalitis in a 52-year-old woman diagnosed with glioblastoma multiforme. She underwent surgical resection in June 2022. Unfortunately, her disease recurred, and she underwent a second resection in August 2022, followed by radiation therapy and Temozolomide therapy. She presented to the hospital with acute confusion followed by seizures, necessitating intubation for airway support. A cerebrospinal fluid (CSF) sample was obtained and processed using the Biofire FilmArray, which reported the detection of HSV-1. Despite being on Acyclovir, the patient did not show signs of improvement. Consequently, a second CSF sample was obtained and sent for next-generation sequencing (NGS), which returned a positive result for Parechovirus. In this presented case, the patient exhibited symptoms of an unknown infectious cause. The utilization of NGS and metagenomic analysis helped identify Parechovirus as the primary pathogen present, in addition to previously identified HSV. This comprehensive approach facilitated a thorough assessment of the underlying infection and guided targeted treatment. In conclusion, the application of NGS techniques and metagenomic analysis proved instrumental in identifying the root cause of the infection.

Metagenomics for Pathogen Detection During a Mass Mortality Event in Songbirds

Mass mortality events in wildlife can be indications of an emerging infectious disease. During the spring and summer of 2021, hundreds of dead passerines were reported across the eastern US. Birds exhibited a range of clinical signs including swollen conjunctiva, ocular discharge, ataxia, and nystagmus. As part of the diagnostic investigation, high-throughput metagenomic next-generation sequencing was performed across three molecular laboratories on samples from affected birds. Many potentially pathogenic microbes were detected, with bacteria forming the largest proportion; however, no singular agent was consistently identified, with many of the detected microbes also found in unaffected (control) birds and thus considered to be subclinical infections. Congruent results across laboratories have helped drive further investigation into alternative causes, including environmental contaminants and nutritional deficiencies. This work highlights the utility of metagenomic approaches in investigations of emerging diseases and provides a framework for future wildlife mortality events.

Determining Potential Link between Environmental and Clinical Isolates of Cryptococcus neoformans/Cryptococcus gattii Species Complexes Using Phenotypic and Genotypic Characterisation

Opportunistic infections due to Cryptococcus neoformans and C. gattii species complexes continue to rise unabated among HIV/AIDS patients, despite improved antifungal therapies. Here, we collected a total of 20 environmental and 25 presumptive clinical cryptococcal isolates from cerebrospinal fluid (CSF) samples of 175 patients enrolled in an ongoing clinical trial Ambition 1 Project (Botswana-Harvard Partnership). Identity confirmation of the isolates was done using MALDI-TOF MS and PCR. We describe the diversity of the isolates by PCR fingerprinting and sequencing (Oxford Nanopore Technology) of the intergenic spacer region. Mating types of the isolates were determined by amplification of the MAT locus. We report an unusual prevalence of 42.1% of C. neoformans x C. deneoformans hybrids Serotype AD (n = 16), followed by 39.5% of C. neoformans Serotype A (n = 15), 5.3% of C. deneoformans, Serotype D (n = 2), 7.9% of C. gattii (n = 3), and 5.3% of C. tetragattii (n = 2) in 38 representative isolates that have been characterized. Mating type-specific PCR performed on 38 representative environmental and clinical isolates revealed that 16 (42.1%) were MATa/MATα hybrids, 17 (44.7%) were MATα, and five (13.2%) possessed MATa mating type. We used conventional and NGS platforms to demonstrate a potential link between environmental and clinical isolates and lay a foundation to further describe mating patterns/history in Botswana.

Exploring clonality and virulence gene associations in bloodstream infections using whole-genome sequencing and clinical data

Background

Bloodstream infections (BSIs) remain a significant cause of mortality worldwide. Causative pathogens are routinely identified and susceptibility tested but only very rarely investigated for their resistance genes, virulence factors, and clonality. Our aim was to gain insight into the clonality patterns of different species causing BSI and the clinical relevance of distinct virulence genes.

Methods

For this study, we whole-genome-sequenced over 400 randomly selected important pathogens isolated from blood cultures in our diagnostic department between 2016 and 2021. Genomic data on virulence factors, resistance genes, and clonality were cross-linked with in-vitro data and demographic and clinical information.

Results

The investigation yielded extensive and informative data on the distribution of genes implicated in BSI as well as on the clonality of isolates across various species.

Conclusion

Associations between survival outcomes and the presence of specific genes must be interpreted with caution, and conducting replication studies with larger sample sizes for each species appears mandatory. Likewise, a deeper knowledge of virulence and host factors will aid in the interpretation of results and might lead to more targeted therapeutic and preventive measures. Monitoring transmission dynamics more efficiently holds promise to serve as a valuable tool in preventing in particular BSI caused by nosocomial pathogens.

Untangling an insect's virome from its endogenous viral elements

BACKGROUND

Insects are an important reservoir of viral biodiversity, but the vast majority of viruses associated with insects have not been discovered. Recent studies have employed high-throughput RNA sequencing, which has led to rapid advances in our understanding of insect viral diversity. However, insect genomes frequently contain transcribed endogenous viral elements (EVEs) with significant homology to exogenous viruses, complicating the use of RNAseq for viral discovery.

METHODS

In this study, we used a multi-pronged sequencing approach to study the virome of an important agricultural pest and prolific vector of plant pathogens, the potato aphid Macrosiphum euphorbiae. We first used rRNA-depleted RNAseq to characterize the microbes found in individual insects. We then used PCR screening to measure the frequency of two heritable viruses in a local aphid population. Lastly, we generated a quality draft genome assembly for M. euphorbiae using Illumina-corrected Nanopore sequencing to identify transcriptionally active EVEs in the host genome.

RESULTS

We found reads from two insect-specific viruses (a Flavivirus and an Ambidensovirus) in our RNAseq data, as well as a parasitoid virus (Bracovirus), a plant pathogenic virus (Tombusvirus), and two phages (Acinetobacter and APSE). However, our genome assembly showed that part of the 'virome' of this insect can be attributed to EVEs in the host genome.

CONCLUSION

Our work shows that EVEs have led to the misidentification of aphid viruses from RNAseq data, and we argue that this is a widespread challenge for the study of viral diversity in insects.

Threat Net: A Metagenomic Surveillance Network for Biothreat Detection and Early Warning

Early detection of novel pathogens can prevent or substantially mitigate biological incidents, including pandemics. Metagenomic next-generation sequencing (mNGS) of symptomatic clinical samples may enable detection early enough to contain outbreaks, limit international spread, and expedite countermeasure development. In this article, we propose a clinical mNGS architecture we call "Threat Net," which focuses on the hospital emergency department as a high-yield surveillance location. We develop a susceptible-exposed-infected-removed (SEIR) simulation model to estimate the effectiveness of Threat Net in detecting novel respiratory pathogen outbreaks. Our analysis serves to quantify the value of routine clinical mNGS for respiratory pandemic detection by estimating the cost and epidemiological effectiveness at differing degrees of hospital coverage across the United States. We estimate that a biological threat detection network such as Threat Net could be deployed across hospitals covering 30% of the population in the United States. Threat Net would cost between $400 million and $800 million annually and have a 95% chance of detecting a novel respiratory pathogen with traits of SARS-CoV-2 after 10 emergency department presentations and 79 infections across the United States. Our analyses suggest that implementing Threat Net could help prevent or substantially mitigate the spread of a respiratory pandemic pathogen in the United States.

National dengue surveillance, Cambodia 2002-2020

Global dengue incidence has increased dramatically over the past few decades from approximately 500 000 reported cases in 2000 to over 5 million in 2019. This trend has been attributed to population growth in endemic areas, rapid unplanned urbanization, increasing global connectivity, and climate change expanding the geographic range of the Aedes spp. mosquito, among other factors. Reporting dengue surveillance data is key to understanding the scale of the problem, identifying important changes in the landscape of disease, and developing policies for clinical management, vector control and vaccine rollout. However, surveillance practices are not standardized, and data may be difficult to interpret particularly in low- and middle-income countries with fragmented health-care systems. The latest national dengue surveillance data for Cambodia was published in 2010. Since its publication, the country experienced marked changes in health policies, population demographics, climate and urbanization. How these changes affected dengue control remains unknown. In this article, we summarize two decades of policy changes, published literature, country statistics, and dengue case data collected by the Cambodia National Dengue Control Programme to: (i) identify important changes in the disease landscape; and (ii) derive lessons to inform future surveillance and disease control strategies. We report that while dengue case morbidity and mortality rates in Cambodia fell between 2002 and 2020, dengue incidence doubled and age at infection increased. Future national surveillance, disease prevention and treatment, and vector control policies will have to account for these changes to optimize disease control.

Clinical metagenomics-challenges and future prospects

Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.

Metagenomic Sequencing of Positive Blood Culture Fluid for Accurate Bacterial and Fungal Species Identification: A Pilot Study

With blood stream infections (BSIs) representing a major cause of mortality and morbidity worldwide, blood cultures play a crucial role in diagnosis, but their clinical application is dampened by the long turn-around time and the detection of only culturable pathogens. In this study, we developed and validated a shotgun metagenomics next-generation sequencing (mNGS) test directly from positive blood culture fluid, allowing for the identification of fastidious or slow growing microorganisms more rapidly. The test was built based on previously validated next-generation sequencing tests, which rely on several key marker genes for bacterial and fungal identification. The new test utilizes an open-source metagenomics CZ-ID platform for the initial analysis to generate the most likely candidate species, which is then used as a reference genome for downstream, confirmatory analysis. This approach is innovative because it takes advantage of an open-source software's agnostic taxonomic calling capability while still relying on the more established and previously validated marker gene-based identification scheme, increasing the confidence in the final results. The test showed high accuracy (100%, 30/30) for both bacterial and fungal microorganisms. We further demonstrated its clinical utility especially for anaerobes and mycobacteria that are either fastidious, slow growing, or unusual. Although applicable in only limited settings, the Positive Blood Culture mNGS test provides an incremental improvement in solving the unmet clinical needs for the diagnosis of challenging BSIs.

Metagenomic next-generation sequencing to characterize potential etiologies of non-malarial fever in a cohort living in a high malaria burden area of Uganda

Causes of non-malarial fevers in sub-Saharan Africa remain understudied. We hypothesized that metagenomic next-generation sequencing (mNGS), which allows for broad genomic-level detection of infectious agents in a biological sample, can systematically identify potential causes of non-malarial fevers. The 212 participants in this study were of all ages and were enrolled in a longitudinal malaria cohort in eastern Uganda. Between December 2020 and August 2021, respiratory swabs and plasma samples were collected at 313 study visits where participants presented with fever and were negative for malaria by microscopy. Samples were analyzed using CZ ID, a web-based platform for microbial detection in mNGS data. Overall, viral pathogens were detected at 123 of 313 visits (39%). SARS-CoV-2 was detected at 11 visits, from which full viral genomes were recovered from nine. Other prevalent viruses included Influenza A (14 visits), RSV (12 visits), and three of the four strains of seasonal coronaviruses (6 visits). Notably, 11 influenza cases occurred between May and July 2021, coinciding with when the Delta variant of SARS-CoV-2 was circulating in this population. The primary limitation of this study is that we were unable to estimate the contribution of bacterial microbes to non-malarial fevers, due to the difficulty of distinguishing bacterial microbes that were pathogenic from those that were commensal or contaminants. These results revealed the co-circulation of multiple viral pathogens likely associated with fever in the cohort during this time period. This study illustrates the utility of mNGS in elucidating the multiple potential causes of non-malarial febrile illness. A better understanding of the pathogen landscape in different settings and age groups could aid in informing diagnostics, case management, and public health surveillance systems.

Dengue in Cambodia 2002-2020: Cases, Characteristics and Capture by National Surveillance

Objective

Data from 19 years of national dengue surveillance in Cambodia (2002-2020) were analyzed to describe trends in dengue case characteristics and incidence.

Methods

Generalized additive models were fitted to dengue case incidence and characteristics (mean age, case phenotype, fatality) over time. Dengue incidence in a pediatric cohort study (2018-2020) was compared to national data during the same period to evaluate disease under-estimation by national surveillance.

Findings

During 2002-2020, there were 353,270 cases of dengue (average age-adjusted incidence 1.75 cases/1,000 persons/year) recorded in Cambodia, with an estimated 2.1-fold increase in case incidence between 2002 and 2020 (slope = 0.0058, SE = 0.0021, p = 0.006). Mean age of infected individuals increased from 5.8 years in 2002 to 9.1 years in 2020 (slope = 0.18, SE = 0.088, p <0.001); case fatality rates decreased from 1.77% in 2002 to 0.10% in 2020 (slope = -0.16, SE = 0.0050, p <0.001). When compared to cohort data, national data under-estimated clinically apparent dengue case incidence by 5.0-fold (95% CI 0.2 - 26.5), and overall dengue case incidence (both apparent and inapparent cases) by 33.6-fold (range: 18.7- 53.6).

Conclusion

Dengue incidence in Cambodia is increasing and disease is shifting to older pediatric populations. National surveillance continues to under-estimate case numbers. Future interventions should account for disease under-estimation and shifting demographics for scaling and to target appropriate age groups.

Pathogen and Antibody Identification in Children with Encephalitis in Myanmar

OBJECTIVE

Prospective studies of encephalitis are rare in regions where encephalitis is prevalent, such as low middle-income Southeast Asian countries. We compared the diagnostic yield of local and advanced tests in cases of pediatric encephalitis in Myanmar.

METHODS

Children with suspected subacute or acute encephalitis at Yangon Children's Hospital, Yangon, Myanmar, were prospectively recruited from 2016-2018. Cohort 1 (n = 65) had locally available diagnostic testing, whereas cohort 2 (n = 38) had advanced tests for autoantibodies (ie, cell-based assays, tissue immunostaining, studies with cultured neurons) and infections (ie, BioFire FilmArray multiplex Meningitis/Encephalitis multiplex PCR panel, metagenomic sequencing, and pan-viral serologic testing [VirScan] of cerebrospinal fluid).

RESULTS

A total of 20 cases (13 in cohort 1 and 7 in cohort 2) were found to have illnesses other than encephalitis. Of the 52 remaining cases in cohort 1, 43 (83%) had presumed infectious encephalitis, of which 2 cases (4%) had a confirmed infectious etiology. Nine cases (17%) had presumed autoimmune encephalitis. Of the 31 cases in cohort 2, 23 (74%) had presumed infectious encephalitis, of which one (3%) had confirmed infectious etiology using local tests only, whereas 8 (26%) had presumed autoimmune encephalitis. Advanced tests confirmed an additional 10 (32%) infections, 4 (13%) possible infections, and 5 (16%) cases of N-methyl-D-aspartate receptor antibody encephalitis.

INTERPRETATION

Pediatric encephalitis is prevalent in Myanmar, and advanced technologies increase identification of treatable infectious and autoimmune causes. Developing affordable advanced tests to use globally represents a high clinical and research priority to improve the diagnosis and prognosis of encephalitis. ANN NEUROL 2023;93:615-628.

Determinants of exposure to Aedes mosquitoes: A comprehensive geospatial analysis in peri-urban Cambodia

Aedes mosquitoes are some of the most important and globally expansive vectors of disease. Public health efforts are largely focused on prevention of human-vector contact. A range of entomological indices are used to measure risk of disease, though with conflicting results (i.e. larval or adult abundance does not always predict risk of disease). There is a growing interest in the development and use of biomarkers for exposure to mosquito saliva, including for Aedes spp, as a proxy for disease risk. In this study, we conduct a comprehensive geostatistical analysis of exposure to Aedes mosquito bites among a pediatric cohort in a peri‑urban setting endemic to dengue, Zika, and chikungunya viruses. We use demographic, household, and environmental variables (the flooding index (NFI), land type, and proximity to a river) in a Bayesian geostatistical model to predict areas of exposure to Aedes aegypti bites. We found that hotspots of exposure to Ae. aegypti salivary gland extract (SGE) were relatively small (< 500 m and sometimes < 250 m) and stable across the two-year study period. Age was negatively associated with antibody responses to Ae. aegypti SGE. Those living in agricultural settings had lower antibody responses than those living in urban settings, whereas those living near recent surface water accumulation were more likely to have higher antibody responses. Finally, we incorporated measures of larval and adult density in our geostatistical models and found that they did not show associations with antibody responses to Ae. aegypti SGE after controlling for other covariates in the model. Our results indicate that targeted house- or neighborhood-focused interventions may be appropriate for vector control in this setting. Further, demographic and environmental factors more capably predicted exposure to Ae. aegypti mosquitoes than commonly used entomological indices.

Evolution and emergence of mosquito-borne viruses of medical importance: towards a routine metagenomic surveillance approach

During the last two decades, the world has witnessed the emergence and re-emergence of arthropod-borne viruses, better known as arboviruses. The close contact between sylvatic, rural and peri-urban vector species and humans has been mainly determined by the environment-modifying human activity. The resulting interactions have led to multiple dead-end host infections and have allowed sylvatic arboviruses to eventually adapt to new vectors and hosts, contributing to the establishment of urban transmission cycles of some viruses with enormous epidemiologic impact. The metagenomic next-generation sequencing (NGS) approach has allowed obtaining unbiased sequence information of millions of DNA and RNA molecules from clinical and environmental samples. Robust bioinformatics tools have enabled the assembly of individual sequence reads into contigs and scaffolds partially or completely representing the genomes of the microorganisms and viruses being present in biological samples of clinical relevance. In this review, we describe the different ecological scenarios for the emergence of viral diseases, the virus adaptation process required for the establishment of a new transmission cycle and the usefulness of NGS and computational methods for the discovery and routine genomic surveillance of mosquito-borne viruses in their ecosystems.

Application of metagenomic next-generation sequencing in cutaneous tuberculosis

Tuberculous infection in a skin wound is a rare but well-known condition. This study describes a child infected with tuberculosis after being wounded. Because of swelling and pain in his wrist tissue, he was admitted to the Affiliated Hospital of Jining Medical University of Shandong Province on 16 October 2021. His medical history only included a wound. He was discharged after debridement. The laboratory data were normal. Two months after surgery, his wound was still swollen and painful. Secretions from the wound were sent for metagenomic next-generation sequencing (mNGS), which revealed three reads related to the Mycobacterium tuberculosis complex group (MTBC). A diagnosis of cutaneous tuberculosis (TB) was made. The wound disappeared after anti-TB drugs were administered. This case demonstrates that, while TB presenting as a severe cutaneous wound is rare, it should be considered in the clinical diagnosis. Clinicians should also pay attention to extrapulmonary infection with MTBC in patients, particularly in some long-suffering patients, and identify the specific pathogen as soon as possible. mNGS could help to identify pathogens and facilitate early treatment, thereby improving the prognosis.

Metagenomic Pathogen Sequencing in Resource-Scarce Settings: Lessons Learned and the Road Ahead

Metagenomic next-generation sequencing (mNGS) is the process of sequencing all genetic material in a biological sample. The technique is growing in popularity with myriad applications including outbreak investigation, biosurveillance, and pathogen detection in clinical samples. However, mNGS programs are costly to build and maintain, and additional obstacles faced by low- and middle-income countries (LMICs) may further widen global inequities in mNGS capacity. Over the past two decades, several important infectious disease outbreaks have highlighted the importance of establishing widespread sequencing capacity to support rapid disease detection and containment at the source. Using lessons learned from the COVID-19 pandemic, LMICs can leverage current momentum to design and build sustainable mNGS programs, which would form part of a global surveillance network crucial to the elimination of infectious diseases.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Case Report: Cambodian National Malaria Surveillance Program Detection of Plasmodium knowlesi

Despite recent success in reducing the regional incidence of Plasmodium falciparum malaria, cases of zoonotic malaria are on the rise in Southeast Asia. The Cambodian National Malaria Surveillance Program has previously relied on rapid diagnostic tests and blood smear microscopy with confirmatory polymerase chain reaction (PCR) testing in a subset of cases to further distinguish P. falciparum, P. malariae, P. ovale, and P. vivax species. Here, metagenomic next-generation sequencing identified P. knowlesi mono-infection in six Cambodian patients initially diagnosed with P. malariae by blood smear microscopy in February–May 2020. These findings of recent human infections with P. knowlesi in Cambodia led to the incorporation of P. knowlesi–specific PCR diagnostics to national malaria surveillance efforts.