Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens

Investigation of acute encephalitis syndrome with implementation of metagenomic next generation sequencing in Nepal

BACKGROUND

The causative agents of Acute Encephalitis Syndrome remain unknown in 68-75% of the cases. In Nepal, the cases are tested only for Japanese encephalitis, which constitutes only about 15% of the cases. However, there could be several organisms, including vaccine-preventable etiologies that cause acute encephalitis, when identified could direct public health efforts for prevention, including addressing gaps in vaccine coverage.

OBJECTIVES

This study employs metagenomic next-generation-sequencing in the investigation of underlying causative etiologies contributing to acute encephalitis syndrome in Nepal.

METHODS

In this study, we investigated 90, Japanese-encephalitis-negative, banked cerebrospinal fluid samples that were collected as part of a national surveillance network in 2016 and 2017. Randomization was done to include three age groups (< 5-years; 5-14-years; >15-years). Only some metadata (age and gender) were available. The investigation was performed in two batches which included total nucleic-acid extraction, followed by individual library preparation (DNA and RNA) and sequencing on Illumina iSeq100. The genomic data were interpreted using Chan Zuckerberg-ID and confirmed with polymerase-chain-reaction.

RESULTS

Human-alphaherpes-virus 2 and Enterovirus-B were seen in two samples. These hits were confirmed by qPCR and semi-nested PCR respectively. Most of the other samples were marred by low abundance of pathogen, possible freeze-thaw cycles, lack of process controls and associated clinical metadata.

CONCLUSION

From this study, two documented causative agents were revealed through metagenomic next-generation-sequencing. Insufficiency of clinical metadata, process controls, low pathogen abundance and absence of standard procedures to collect and store samples in nucleic-acid protectants could have impeded the study and incorporated ambiguity while correlating the identified hits to infection. Therefore, there is need of standardized procedures for sample collection, inclusion of process controls and clinical metadata. Despite challenging conditions, this study highlights the usefulness of mNGS to investigate diseases with unknown etiologies and guide development of adequate clinical-management-algorithms and outbreak investigations in Nepal.

Considerations for applying emerging technologies in paediatric laboratory medicine

Emerging technology in laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Paediatric laboratory medicine itself may be considered an emerging area of specialisation that is established relatively recently following increased appreciation and understanding of the unique physiology and healthcare needs of the children. Through four clinical (neonatal hypoglycaemia, neonatal hyperbilirubinaemia, sickle cell disorder, congenital adrenal hyperplasia) and six technological (microassays, noninvasive testing, alternative matrices, next generation sequencing, exosome analysis, machine learning) illustrations, key takeaways of application of emerging technology for each area are summarised. Additionally, nine key considerations when applying emerging technology in paediatric laboratory medicine setting are discussed.

The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples

Objectives

Metagenomic next-generation sequencing (mNGS) is a powerful tool for pathogen detection. The accuracy depends on both wet lab and dry lab procedures. The objective of our study was to assess the influence of read length and dataset size on pathogen detection.

Methods

In this study, 43 clinical BALF samples, which tested positive via clinical mNGS and were consistent with the diagnosis, were subjected to re-sequencing on the Illumina NovaSeq 6000 platform. The raw re-sequencing data, consisting of 100 million (M) paired-end 150 bp (PE150) reads, were divided into simulated datasets with eight different data sizes (5 M, 10 M, 15 M, 20 M, 30 M, 50 M, 75 M, 100 M) and five different read lengths (single-end 50 bp (SE50), SE75, SE100, PE100, and PE150). Both Kraken2 and IDseq bioinformatics pipelines were employed to analyze the previously diagnosed pathogens in the simulated data. Detection of pathogens was based on read counts ranging from 1 to 10 and RPM values ranging from 0.2 to 2.

Results

Our results revealed that increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection. However, a larger data sizes for mNGS require higher economic costs and longer turnaround time for data analysis. Our findings indicate 20 M reads being sufficient for SE75 mode to achieve high recall rates. Additionally, high nucleic acid loads in samples can lead to increased stability in pathogen detection efficiency, reducing the impact of sequencing strategies. The choice of bioinformatics pipelines had a significant impact on recall rates achieved in pathogen detection.

Conclusions

Increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection but increase the economic and time costs of sequencing and data analysis. Currently, the 20 M reads in SE75 mode may be the best sequencing option.

Clinical Metagenomic Next-Generation Sequencing for Diagnosis of Central Nervous System Infections: Advances and Challenges

Central nervous system (CNS) infections carry a substantial burden of morbidity and mortality worldwide, and accurate and timely diagnosis is required to optimize management. Metagenomic next-generation sequencing (mNGS) has proven to be a valuable tool in detecting pathogens in patients with suspected CNS infection. By sequencing microbial nucleic acids present in a patient's cerebrospinal fluid, brain tissue, or samples collected outside of the CNS, such as plasma, mNGS can detect a wide range of pathogens, including rare, unexpected, and/or fastidious organisms. Furthermore, its target-agnostic approach allows for the identification of both known and novel pathogens. This is particularly useful in cases where conventional diagnostic methods fail to provide an answer. In addition, mNGS can detect multiple microorganisms simultaneously, which is crucial in cases of mixed infections without a clear predominant pathogen. Overall, clinical mNGS testing can help expedite the diagnostic process for CNS infections, guide appropriate management decisions, and ultimately improve clinical outcomes. However, there are key challenges surrounding its use that need to be considered to fully leverage its clinical impact. For example, only a few specialized laboratories offer clinical mNGS due to the complexity of both the laboratory methods and analysis pipelines. Clinicians interpreting mNGS results must be aware of both false negatives-as mNGS is a direct detection modality and requires a sufficient amount of microbial nucleic acid to be present in the sample tested-and false positives-as mNGS detects environmental microbes and their nucleic acids, despite best practices to minimize contamination. Additionally, current costs and turnaround times limit broader implementation of clinical mNGS. Finally, there is uncertainty regarding the best practices for clinical utilization of mNGS, and further work is needed to define the optimal patient population(s), syndrome(s), and time of testing to implement clinical mNGS.

Overcoming colonialism in pathogen genomics

Historical legacies of colonialism affect the distribution and control of scientific knowledge today, including within the pathogen genomics field, which remains dominated by high-income countries (HICs). We discuss the imperatives for decolonising pathogen genomics, including the need for more equitable representation, collaboration, and capacity-strengthening, and the shared responsibilities that both low-income and middle-income countries (LMICs) and HICs have in this endeavour. By highlighting examples from LMICs, we illuminate the pathways and challenges that researchers in LMICs face in the bid to gain autonomy in this crucial domain. Recognising the inherent value of local expertise and resources, we argue for a more inclusive, globally collaborative approach to pathogen genomics. Such an approach not only fosters scientific growth and innovation, but also strengthens global health security by equipping all nations with the tools needed to respond to health crises.

Advances in Host Depletion and Pathogen Enrichment Methods for Rapid Sequencing-Based Diagnosis of Bloodstream Infection

Bloodstream infection remains a major cause of morbidity and death worldwide. Timely and appropriate treatment can reduce mortality among critically ill patients. Current diagnostic methods are too slow to inform precise antibiotic choice, leading to the prescription of empirical antibiotics, which may fail to cover the resistance profile of the pathogen, risking poor patient outcomes. Additionally, overuse of broad-spectrum antibiotics may lead to more resistant organisms, putting further pressure on the dwindling pipeline of antibiotics, and risk transmission of these resistant organisms in the health care environment. Therefore, rapid diagnostics are urgently required to better inform antibiotic choice early in the course of treatment. Sequencing offers great promise in reducing time to microbiological diagnosis; however, the amount of host DNA compared with the pathogen in patient samples presents a significant obstacle. To address this, various host-depletion and bacterial-enrichment strategies have been used in samples, such as saliva, urine, or tissue. However, these methods have yet to be collectively integrated and/or extensively explored for rapid bloodstream infection diagnosis. Although most of these workflows possess individual strengths, their lack of analytical/clinical sensitivity and/or comprehensiveness demands additional improvements or synergistic application. Therefore, this review provides a distinctive classification system for these methods based on their working principles to guide future research, discusses their strengths and limitations, and explores potential avenues for improvement.

Central nervous system infections in the tropics

PURPOSE OF REVIEW

Emerging and re-emerging central nervous system (CNS) infections are a major public health concern in the tropics. The reasons for this are myriad; climate change, rainfall, deforestation, increased vector density combined with poverty, poor sanitation and hygiene. This review focuses on pathogens, which have emerged and re-emerged, with the potential for significant morbidity and mortality.

RECENT FINDINGS

In recent years, multiple acute encephalitis outbreaks have been caused by Nipah virus, which carries a high case fatality. Arboviral infections, predominantly dengue, chikungunya and Zika are re-emerging increasingly especially in urban areas due to changing human habitats, vector behaviour and viral evolution. Scrub typhus, another vector borne disease caused by the bacterium Orientia tsutsugamushi , is being established as a leading cause of CNS infections in the tropics.

SUMMARY

A syndromic and epidemiological approach to CNS infections in the tropics is essential to plan appropriate diagnostic tests and management. Rapid diagnostic tests facilitate early diagnosis and thus help prompt initiation and focusing of therapy to prevent adverse outcomes. Vector control, cautious urbanization and deforestation, and reducing disturbance of ecosystems can help prevent spread of vector-borne diseases. Regional diagnostic and treatment approaches and specific vaccines are required to avert morbidity and mortality.

Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious Diseases

Metagenomics offers the potential to replace and simplify classical methods used in the clinical diagnosis of human and veterinary infectious diseases. Metagenomics boasts a high pathogen discovery rate and high specificity, advantages absent in most classical approaches. However, its widespread adoption in clinical settings is still pending, with a slow transition from research to routine use. While longer turnaround times and higher costs were once concerns, these issues are currently being addressed by automation, better chemistries, improved sequencing platforms, better databases, and automated bioinformatics analysis. However, many technical options and steps, each producing highly variable outcomes, have reduced the technology's operational value, discouraging its implementation in diagnostic labs. We present a case for utilizing non-targeted RNA sequencing (NT-RNA-seq) as an ideal metagenomics method for the detection of infectious disease-causing agents in humans and animals. Additionally, to create operational value, we propose to identify best practices for the "core" of steps that are invariably shared among many human and veterinary protocols. Reference materials, sequencing procedures, and bioinformatics standards should accelerate the validation processes necessary for the widespread adoption of this technology. Best practices could be determined through "implementation research" by a consortium of interested institutions working on common samples.

Literature Review of Pathogen Agnostic Molecular Testing of Clinical Specimens From Difficult-to-Diagnose Patients: Implications for Public Health

To better identify emerging or reemerging pathogens in patients with difficult-to-diagnose infections, it is important to improve access to advanced molecular testing methods. This is particularly relevant for cases where conventional microbiologic testing has been unable to detect the pathogen and the patient's specimens test negative. To assess the availability and utility of such testing for human clinical specimens, a literature review of published biomedical literature was conducted. From a corpus of more than 4,000 articles, a set of 34 reports was reviewed in detail for data on where the testing was being performed, types of clinical specimens tested, pathogen agnostic techniques and methods used, and results in terms of potential pathogens identified. This review assessed the frequency of advanced molecular testing, such as metagenomic next generation sequencing that has been applied to clinical specimens for supporting clinicians in caring for difficult-to-diagnose patients. Specimen types tested were from cerebrospinal fluid, respiratory secretions, and other body tissues and fluids. Publications included case reports and series, and there were several that involved clinical trials, surveillance studies, research programs, or outbreak situations. Testing identified both known human pathogens (sometimes in new sites) and previously unknown human pathogens. During this review, there were no apparent coordinated efforts identified to develop regional or national reports on emerging or reemerging pathogens. Therefore, development of a coordinated sentinel surveillance system that applies advanced molecular methods to clinical specimens which are negative by conventional microbiological diagnostic testing would provide a foundation for systematic characterization of emerging and underdiagnosed pathogens and contribute to national biodefense strategy goals.

Therapeutic mitigation of measles-like immune amnesia and exacerbated disease after prior respiratory virus infections in ferrets

Measles cases have surged pre-COVID-19 and the pandemic has aggravated the problem. Most measles-associated morbidity and mortality arises from destruction of pre-existing immune memory by measles virus (MeV), a paramyxovirus of the morbillivirus genus. Therapeutic measles vaccination lacks efficacy, but little is known about preserving immune memory through antivirals and the effect of respiratory disease history on measles severity. We use a canine distemper virus (CDV)-ferret model as surrogate for measles and employ an orally efficacious paramyxovirus polymerase inhibitor to address these questions. A receptor tropism-intact recombinant CDV with low lethality reveals an 8-day advantage of antiviral treatment versus therapeutic vaccination in maintaining immune memory. Infection of female ferrets with influenza A virus (IAV) A/CA/07/2009 (H1N1) or respiratory syncytial virus (RSV) four weeks pre-CDV causes fatal hemorrhagic pneumonia with lung onslaught by commensal bacteria. RNAseq identifies CDV-induced overexpression of trefoil factor (TFF) peptides in the respiratory tract, which is absent in animals pre-infected with IAV. Severe outcomes of consecutive IAV/CDV infections are mitigated by oral antivirals even when initiated late. These findings validate the morbillivirus immune amnesia hypothesis, define measles treatment paradigms, and identify priming of the TFF axis through prior respiratory infections as risk factor for exacerbated morbillivirus disease.

Diagnostic performance of metagenomic next-generation sequencing for the detection of pathogens in cerebrospinal fluid in pediatric patients with central nervous system infection: a systematic review and meta-analysis

BACKGROUND

Detecting pathogens in pediatric central nervous system infection (CNSI) is still a major challenge in medicine. In addition to conventional diagnostic patterns, metagenomic next-generation sequencing (mNGS) shows great potential in pathogen detection. Therefore, we systematically evaluated the diagnostic performance of mNGS in cerebrospinal fluid (CSF) in pediatric patients with CNSI.

METHODS

Related literature was searched in the Web of Science, PubMed, Embase, and Cochrane Library. We screened the literature and extracted the data according to the selection criteria. The quality of included studies was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and the certainty of the evidence was measured by the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) score system. Then, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odd's ratio (DOR), and area under the curve (AUC) of the summary receiver operating characteristic curve (sROC) were estimated in Stata Software and MetaDisc. Subgroup analyses were performed to investigate the potential factors that influence the diagnostic performance.

RESULTS

A total of 10 studies were included in the meta-analysis. The combined sensitivity was 0.68 (95% confidence interval [CI]: 0.59 to 0.76, I2 = 66.77%, p < 0.001), and the combined specificity was 0.89 (95% CI: 0.80 to 0.95, I2 = 83.37%, p < 0.001). The AUC of sROC was 0.85 (95% CI, 0.81 to 0.87). The quality level of evidence elevated by the GRADE score system was low.

CONCLUSIONS

Current evidence shows that mNGS presents a good diagnostic performance in pediatric CNSI. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.

Review of dengue, zika and chikungunya infections in nervous system in endemic areas

Dengue, zika, and chikungunya are arboviruses of great epidemiological relevance worldwide. The emergence and re-emergence of viral infections transmitted by mosquitoes constitute a serious human public health problem. The neurological manifestations caused by these viruses have a high potential for death or sequelae. The complications that occur in the nervous system associated with arboviruses can be a challenge for diagnosis and treatment. In endemic areas, suspected cases should include acute encephalitis, myelitis, encephalomyelitis, polyradiculoneuritis, and/or other syndromes of the central or peripheral nervous system, in the absence of a known explanation. The confirmation diagnosis is based on viral (isolation or RT-PCR) or antigens detection in tissues, blood, cerebrospinal fluid, or other body fluids, increase in IgG antibody titers between paired serum samples, specific IgM antibody in cerebrospinal fluid and serological conversion to IgM between paired serum samples (non-reactive in the acute phase and reactive in the convalescent). The cerebrospinal fluid examination can demonstrate: 1. etiological agent; 2. inflammatory reaction or protein-cytological dissociation depending on the neurological condition; 3. specific IgM, 4. intrathecal synthesis of specific IgG (dengue and chikungunya); 5. exclusion of other infectious agents. The treatment of neurological complications aims to improve the symptoms, while the vaccine represents the great hope for the control and prevention of neuroinvasive arboviruses. This narrative review summarizes the updated epidemiology, general features, neuropathogenesis, and neurological manifestations associated with dengue, zika, and chikungunya infection.

Identification and characterization of porcine Rotavirus A in Chilean swine population

Rotavirus A (RVA) is a common cause of diarrhea in newborn pigs, leading to significant economic losses. RVA is considered a major public health concern due to genetic evolution, high prevalence, and pathogenicity in humans and animals. The objective of this study was to identify and characterize RVA in swine farms in Chile. A total of 154 samples (86 oral fluids and 68 fecal samples) were collected, from 22 swine farms. 58 (38%) samples belonging to 14 farms were found positive for RVA by real-time RT-PCR. The samples with low Ct values (21) and the two isolates were selected for whole genome sequencing. Nearly complete genomes were assembled from both isolates and partial genomes were assembled from five clinical samples. BLAST analysis confirmed that these sequences are related to human and swine-origin RVA. The genomic constellation was G5/G3-P[7]-I5-R1-C1-M1-A8-N1-T1-E1-H1. Phylogenetic analysis showed that VP4, VP1, VP2, NSP2, NSP3, NSP4, and NSP5 sequences were grouped in monophyletic clusters, suggesting a single introduction. The phylogenies for VP7, VP6, VP3, and NSP1 indicated two different origins of the Chilean sequences. The phylogenetic trees showed that most of the Chilean RVA sequences are closely related to human and swine-origin RVA detected across the world. The results highlight the potential zoonotic nature of RVA circulating in Chilean swine farms. Therefore, it is important to continue RVA whole genome sequencing globally to fully understand its complex epidemiology and early detection and characterization of zoonotic strains.

Untargeted metagenomic sequencing identifies Toscana virus in patients with idiopathic meningitis, southern Spain, 2015 to 2019

BackgroundVarious pathogens, including bacteria, fungi, parasites, and viruses can lead to meningitis. Among viruses causing meningitis, Toscana virus (TOSV), a phlebovirus, is transmitted through sandfly bites. TOSV infection may be suspected if patients with enterovirus- and herpesvirus-negative aseptic (non-bacterial) meningitis recall recent insect bites. Other epidemiological factors (season, rural area) may be considered. The broad range of possible meningitis aetiologies poses considerable diagnosis challenges. Untargeted metagenomic next-generation sequencing (mNGS) can potentially identify pathogens, which are not considered or detected in routine diagnostic panels.AimIn this retrospective, single-centre observational study, we investigated mNGS usefulness to understand the cause of meningitis when conventional approaches fail.MethodsCerebrospinal fluid (CSF) samples from patients hospitalised in southern Spain in 2015-2019 with aseptic meningitis and no aetiology found by conventional testing, were subjected to mNGS. Patients' demographic characteristics had been recorded and physicians had asked them about recent insect bites. Obtained viral genome sequences were phylogenetically analysed.ResultsAmong 23 idiopathic cases, TOSV was identified in eight (all male; median age:  39 years, range: 15-78 years). Five cases lived in an urban setting, three occurred in autumn and only one recalled insect bites. Phylogenetic analysis of TOSV segment sequences supported one intra-genotype reassortment event.ConclusionsOur study highlights the usefulness of mNGS for identifying viral pathogens directly in CSF. In southern Spain, TOSV should be considered regardless of recalling of insect bites or other epidemiological criteria. Detection of a disease-associated reassortant TOSV emphasises the importance of monitoring the spread and evolution of phleboviruses in Mediterranean countries.

Clinical and Metagenomic Characterization of Neurological Infections of People With Human Immunodeficiency Virus in the Peruvian Amazon

Background

Neurological opportunistic infections cause significant morbidity and mortality in people with human immunodeficiency virus (HIV) but are difficult to diagnose.

Methods

One hundred forty people with HIV with acute neurological symptoms from Iquitos, Peru, were evaluated for cerebral toxoplasmosis with quantitative polymerase chain reaction (qPCR) of cerebrospinal fluid (CSF) and for cryptococcal meningitis with cryptococcal antigen test (CrAg) in serum or CSF. Differences between groups were assessed with standard statistical methods. A subset of samples was evaluated by metagenomic next-generation sequencing (mNGS) of CSF to compare standard diagnostics and identify additional diagnoses.

Results

Twenty-seven participants were diagnosed with cerebral toxoplasmosis by qPCR and 13 with cryptococcal meningitis by CrAg. Compared to participants without cerebral toxoplasmosis, abnormal Glasgow Coma Scale score (P = .05), unilateral focal motor signs (P = .01), positive Babinski reflex (P = .01), and multiple lesions on head computed tomography (CT) (P = .002) were associated with cerebral toxoplasmosis. Photophobia (P = .03) and absence of lesions on head CT (P = .02) were associated with cryptococcal meningitis. mNGS of 42 samples identified 8 cases of cerebral toxoplasmosis, 7 cases of cryptococcal meningitis, 5 possible cases of tuberculous meningitis, and incidental detections of hepatitis B virus (n = 1) and pegivirus (n = 1). mNGS had a positive percentage agreement of 71% and a negative percentage agreement of 91% with qPCR for T gondii. mNGS had a sensitivity of 78% and specificity of 100% for Cryptococcus diagnosis.

Conclusions

An infection was diagnosed by any method in only 34% of participants, demonstrating the challenges of diagnosing neurological opportunistic infections in this population and highlighting the need for broader, more sensitive diagnostic tests for central nervous system infections.

Metagenomics analysis reveals presence of the Merida-like virus in Georgia

Arbovirus surveillance is fundamental for the discovery of novel viruses and prevention of febrile vector-borne illnesses. Vector-borne pathogens can rapidly expand and adapt in new geographic and environmental conditions. In this study, metagenomic surveillance was conducted to identify novel viruses in the Country of Georgia. A total of 521 mosquitoes were captured near a military training facility and pooled from species Culex pipiens (Linnaeus) (87%) and Aedes albopictus (Skuse) (13%). We decided to further analyze the Culex pipiens mosquitoes, due to the more extensive number of samples collected. Our approach was to utilize an unbiased total RNA-seq for pathogen discovery in order to explore the mosquito virome. The viral reads from this analysis were mostly aligned to Insect-specific viruses from two main families, the Iflaviridae; a positive-stranded RNA virus and the Rhabdoviridae; a negative- and single-stranded RNA virus. Our pathogen discovery analysis revealed viral reads aligning to the Merida-like virus Turkey (MERDLVT) strain among the Rhabdoviridae. To further validate this result, we conducted a BLAST sequence comparison analysis of our samples with the MERDLVT strain. Our positive samples aligned to the MERDLVT strain with 96-100% sequence identity and 99.7-100% sequence coverage. A bootstrapped maximum-likelihood phylogenetic tree was used to evaluate the evolutionary relationships among these positive pooled specimens with the (MERDLVT) strain. The Georgia samples clustered most closely with two strains from Turkey, the Merida-like virus KE-2017a isolate 139-1-21 and the Merida-like virus Turkey isolate P431. Collectively, these results show the presence of the MERDLVT strain in Georgia.

Survey of white-footed mice in Connecticut, USA reveals low SARS-CoV-2 seroprevalence and infection with divergent betacoronaviruses

Diverse mammalian species display susceptibility to and infection with SARS-CoV-2. Potential SARS-CoV-2 spillback into rodents is understudied despite their host role for numerous zoonoses and human proximity. We assessed exposure and infection among white-footed mice (Peromyscus leucopus) in Connecticut, USA. We observed 1% (6/540) wild-type neutralizing antibody seroprevalence among 2020-2022 residential mice with no cross-neutralization of variants. We detected no SARS-CoV-2 infections via RT-qPCR, but identified non-SARS-CoV-2 betacoronavirus infections via pan-coronavirus PCR among 1% (5/468) of residential mice. Sequencing revealed two divergent betacoronaviruses, preliminarily named Peromyscus coronavirus-1 and -2. Both belong to the Betacoronavirus 1 species and are ~90% identical to the closest known relative, Porcine hemagglutinating encephalomyelitis virus. Low SARS-CoV-2 seroprevalence suggests white-footed mice may not be sufficiently susceptible or exposed to SARS-CoV-2 to present a long-term human health risk. However, the discovery of divergent, non-SARS-CoV-2 betacoronaviruses expands the diversity of known rodent coronaviruses and further investigation is required to understand their transmission extent.

UltraSEQ, a Universal Bioinformatic Platform for Information-Based Clinical Metagenomics and Beyond

Applied metagenomics is a powerful emerging capability enabling the untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of-its-kind accurate and scalable metagenomic bioinformatic tool for potential clinical diagnostics and biosurveillance utility. Here, we present the results of the evaluation of our novel UltraSEQ pipeline using an in silico-synthesized metagenome, mock microbial community data sets, and publicly available clinical data sets from samples of different infection types, including both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community data set. For clinical data sets, even without requiring data set-specific configuration setting changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Furthermore, as an initial demonstration with a limited patient sample set, we show UltraSEQ's ability to provide antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above-described results demonstrate that the UltraSEQ platform offers a transformative approach for microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for the classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infections. IMPORTANCE Traditional clinical microbiology-based diagnostic tests rely on targeted methods that can detect only one to a few preselected organisms or slow, culture-based methods. Although widely used today, these methods have several limitations, resulting in rates of cases of an unknown etiology of infection of >50% for several disease types. Massive developments in sequencing technologies have made it possible to apply metagenomic methods to clinical diagnostics, but current offerings are limited to a specific disease type or sequencer workflow and/or require laboratory-specific controls. The limitations associated with current clinical metagenomic offerings result from the fact that the backend bioinformatic pipelines are optimized for the specific parameters described above, resulting in an excess of unmaintained, redundant, and niche tools that lack standardization and explainable outputs. In this paper, we demonstrate that UltraSEQ uses a novel, information-based approach that enables accurate, evidence-based predictions for diagnosis as well as the functional characterization of a sample.

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.

A multicentre study reveals dysbiosis in the microbial co-infection and antimicrobial resistance gene profile in the nasopharynx of COVID-19 patients

The impact of SARS-CoV-2 infection on the nasopharyngeal microbiome has not been well characterised. We sequenced genetic material extracted from nasopharyngeal swabs of SARS-CoV-2-positive individuals who were asymptomatic (n = 14), had mild (n = 64) or severe symptoms (n = 11), as well as from SARS-CoV-2-negative individuals who had never-been infected (n = 5) or had recovered from infection (n = 7). Using robust filters, we identified 1345 taxa with approximately 0.1% or greater read abundance. Overall, the severe cohort microbiome was least diverse. Bacterial pathogens were found in all cohorts, but fungal species identifications were rare. Few taxa were common between cohorts suggesting a limited human nasopharynx core microbiome. Genes encoding resistance mechanisms to 10 antimicrobial classes (> 25% sequence coverages, 315 genes, 63 non-redundant) were identified, with β-lactam resistance genes near ubiquitous. Patients infected with SARS-CoV-2 (asymptomatic and mild) had a greater incidence of antibiotic resistance genes and a greater microbial burden than the SARS-CoV-2-negative individuals. This should be considered when deciding how to treat COVID-19 related bacterial infections.

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.

A case for investment in clinical metagenomics in low-income and middle-income countries

Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.

Progress and Challenges in Bacterial Meningitis: A Review

IMPORTANCE

Bacterial meningitis is a worldwide health problem, with incidence rates ranging from approximately 0.9 per 100 000 individuals per year in high-income countries to 80 per 100 000 individuals per year in low-income countries. In low-income countries, bacterial meningitis has a mortality rate of up to 54%. Up to 24% of those who survive develop chronic neurological sequelae, such as hearing loss or focal neurological deficits.

OBSERVATIONS

Streptococcus pneumoniae causes about 72% and Neisseria meningitidis causes about 11% of cases of bacterial meningitis in people older than 16 years. Escherichia coli and Streptococcus agalactiae cause about 35% of cases of early-onset neonatal meningitis. In adults, risk factors for bacterial meningitis include older age and immunosuppressive conditions. The most common symptoms are headache (84%), fever (74%), stiff neck (74%), altered mental status (median [IQR] Glasgow Coma Scale score of 11 [9-14] on a scale ranging from 3-15), and nausea (62%). Brain imaging should be performed before lumbar puncture if patients present with altered mental status, focal neurological deficits, papilledema, or history of immunocompromising conditions or central nervous system disease. Bacterial meningitis should be suspected if any of the following are present on admission: serum leukocytes greater than 10.0 ×109/L, cerebrospinal fluid (CSF) leukocytes greater than 2000/μL, CSF granulocytes greater than 1180/μL, CSF protein greater than 2.2 g/L, CSF glucose less than 34.23 mg/dL, or fever. A positive Gram stain result for bacteria is diagnostic, but the sensitivity of a positive Gram stain result for bacterial meningitis ranges from 50% to 90%. In countries in which the prevalence of ceftriaxone-resistant Streptococcus pneumoniae exceeds 1%, vancomycin and ceftriaxone are the empirical antibiotics of choice, with the addition of ampicillin in neonates, older patients, and immunocompromised patients. Adjunctive dexamethasone should be used in patients with bacterial meningitis but stopped if Listeria monocytogenes is confirmed.

CONCLUSIONS AND RELEVANCE

Bacterial meningitis affects approximately 0.9 per 100 000 individuals to 80 per 100 000 individuals per year and has a mortality rate as high as 54%. First-line therapy is prompt empirical intravenous antibiotic therapy and adjunctive dexamethasone.

Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis

Objective

It is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generation sequencing (mNGS) has been increasingly adopted to improve the diagnostic yield. The present study sought to evaluate the value of mNGS in CNS infection diagnosis.

Methods

Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2022 guidelines, we searched relevant articles published in seven databases, including PubMed, Web of Science, and Cochrane Library, published from January 2014 to January 2022. High-quality articles related to mNGS applications in the CNS infection diagnosis were included. The comparison between mNGS and the gold standard of CNS infection, such as culture, PCR or serology, and microscopy, was conducted to obtain true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values, which were extracted for sensitivity and specificity calculation.

Results

A total of 272 related studies were retrieved and strictly selected according to the inclusion and exclusion criteria. Finally, 12 studies were included for meta-analysis and the pooled sensitivity was 77% (95% CI: 70–82%, I² = 39.69%) and specificity was 96% (95% CI: 93–98%, I² = 72.07%). Although no significant heterogeneity in sensitivity was observed, a sub-group analysis was conducted based on the pathogen, region, age, and sample pretreatment method to ascertain potential confounders. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for CNS infection was 0.91 (95% CI: 0.88–0.93). Besides, Deek's Funnel Plot Asymmetry Test indicated no publication bias in the included studies (Figure 3, p > 0.05).

Conclusion

Overall, mNGS exhibits good sensitivity and specificity for diagnosing CNS infection and diagnostic performance during clinical application by assisting in identifying the pathogen. However, the efficacy remains inconsistent, warranting subsequent studies for further performance improvement during its clinical application.

Study registration number

INPLASY202120002

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.

Direct Metagenomic Diagnosis of Community-Acquired Meningitis: State of the Art

Current routine diagnosis of community-acquired meningitis (CAM) by multiplex real-time polymerase chain reaction (RT-PCR) is limited in the number of tested pathogens and their full characterisation, requiring additional in vitro investigations to disclose genotype and antimicrobial susceptibility. We reviewed 51 studies published through December 2021 reporting metagenomic next generation sequencing (mNGS) directly applied to the cerebrospinal fluid (CSF). This approach, potentially circumventing the above-mentioned limitations, indicated 1,248 investigated patients, and 617 patients dually investigated by routine diagnosis and mNGS, in whom 116 microbes were detected, including 50 by mNGS only, nine by routine methods only, and 57 by both routine methods and mNGS. Of 217 discordant CSF findings, 103 CSF samples were documented by mNGS only, 87 CSF samples by routine methods only, and 27 CSF samples in which the pathogen identified by mNGS was different than that found using routine methods. Overall, mNGS allowed for diagnosis and genomic surveillance of CAM causative pathogens in real-time, with a cost which is competitive with current routine multiplex RT-PCR. mNGS could be implemented at point-of-care (POC) laboratories as a part of routine investigations to improve the diagnosis and molecular epidemiology of CAM, particularly in the event of failure of routine assays.

Pneumonia surveillance with culture-independent metatranscriptomics in HIV-positive adults in Uganda: a cross-sectional study

BACKGROUND

Pneumonia is a leading cause of death worldwide and is a major health-care challenge in people living with HIV. Despite this, the causes of pneumonia in this population remain poorly understood. We aimed to assess the feasibility of metatranscriptomics for epidemiological surveillance of pneumonia in patients with HIV in Uganda.

METHODS

We performed a retrospective observational study in patients with HIV who were admitted to Mulago Hospital, Kampala, Uganda between Oct 1, 2009, and Dec 31, 2011. Inclusion criteria were age 18 years or older, HIV-positivity, and clinically diagnosed pneumonia. Exclusion criteria were contraindication to bronchoscopy or an existing diagnosis of tuberculosis. Bronchoalveolar lavage fluid was collected within 72 h of admission and a combination of RNA sequencing and Mycobacterium tuberculosis culture plus PCR were performed. The primary outcome was detection of an established or possible respiratory pathogen in the total study population.

FINDINGS

We consecutively enrolled 217 patients during the study period. A potential microbial cause for pneumonia was identified in 211 (97%) patients. At least one microorganism of established respiratory pathogenicity was identified in 113 (52%) patients, and a microbe of possible pathogenicity was identified in an additional 98 (45%). M tuberculosis was the most commonly identified established pathogen (35 [16%] patients; in whom bacterial or viral co-infections were identified in 13 [37%]). Streptococcus mitis, although not previously reported as a cause of pneumonia in patients with HIV, was the most commonly identified bacterial organism (37 [17%] patients). Haemophilus influenzae was the most commonly identified established bacterial pathogen (20 [9%] patients). Pneumocystis jirovecii was only identified in patients with a CD4 count of less than 200 cells per mL.

INTERPRETATION

We show the feasibility of using metatranscriptomics for epidemiologic surveillance of pneumonia by describing the spectrum of respiratory pathogens in adults with HIV in Uganda. Applying these methods to a contemporary cohort could enable broad assessment of changes in pneumonia aetiology following the emergence of SARS-CoV-2.

FUNDING

US National Institutes of Health, Chan Zuckerberg Biohub.

Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics

The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

Tuberculous meningitis is difficult to differentiate from meningitis caused by other pathogens. Here, the authors combine metagenomics-based pathogen detection in cerebrospinal fluid with a host gene expression-based machine learning classifier for diagnosis.

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

SignificanceMetagenomic pathogen sequencing offers an unbiased approach to characterizing febrile illness. In resource-scarce settings with high biodiversity, it is critical to identify disease-causing pathogens in order to understand burden and to prioritize efforts for control. Here, metagenomic next-generation sequencing (mNGS) characterization of the pathogen landscape in Cambodia revealed diverse vector-borne and zoonotic pathogens irrespective of age and gender as risk factors. Identification of key pathogens led to changes in national program surveillance. This study is a "real world" example of the use of mNGS surveillance of febrile individuals, executed in-country, to identify outbreaks of vector-borne, zoonotic, and other emerging pathogens in a resource-scarce setting.

Optimization of cerebrospinal fluid microbial DNA metagenomic sequencing diagnostics

Infection in the central nervous system is a severe condition associated with high morbidity and mortality. Despite ample testing, the majority of encephalitis and meningitis cases remain undiagnosed. Metagenomic sequencing of cerebrospinal fluid has emerged as an unbiased approach to identify rare microbes and novel pathogens. However, several major hurdles remain, including establishment of individual limits of detection, removal of false positives and implementation of universal controls. Twenty-one cerebrospinal fluid samples, in which a known pathogen had been positively identified by available clinical techniques, were subjected to metagenomic DNA sequencing. Fourteen samples contained minute levels of Epstein-Barr virus. The detection threshold for each sample was calculated by using the total leukocyte content in the sample and environmental contaminants found in the bioinformatic classifiers. Virus sequences were detected in all ten samples, in which more than one read was expected according to the calculations. Conversely, no viral reads were detected in seven out of eight samples, in which less than one read was expected according to the calculations. False positive pathogens of computational or environmental origin were readily identified, by using a commonly available cell control. For bacteria, additional filters including a comparison between classifiers removed the remaining false positives and alleviated pathogen identification. Here we show a generalizable method for identification of pathogen species using DNA metagenomic sequencing. The choice of bioinformatic method mainly affected the efficiency of pathogen identification, but not the sensitivity of detection. Identification of pathogens requires multiple filtering steps including read distribution, sequence diversity and complementary verification of pathogen reads.

Metronidazole treatment rapidly reduces genital inflammation through effects on bacterial vaginosis-associated bacteria rather than lactobacilli

BACKGROUND

Bacterial vaginosis (BV) causes genital inflammation and increases HIV risk, while a vaginal microbiota dominated by Lactobacillus species is associated with immune quiescence and relative HIV protection. BV treatment reduces genital inflammation, but it is unclear whether this is driven by a decrease in BV-associated bacteria or an increase in Lactobacillus.

METHODS

To evaluate the short-term impact of standard BV treatment on genital immunology and the vaginal microbiota, vaginal swabs were collected immediately before and after metronidazole treatment for BV and analyzed with multiplex ELISA, metagenomic sequencing, and quantitative polymerase chain reaction.

RESULTS

Topical metronidazole treatment rapidly reduced vaginal levels of proinflammatory cytokines, chemokines, and soluble immune markers of epithelial barrier disruption. Although the vaginal microbiota shifted to dominance by L. iners or L. jensenii, this proportional shift was primarily driven by a 2-4 log10 fold reduction in BV-associated bacteria absolute abundance; BV treatment induced no change in the absolute abundance of L. crispatus or L. iners, and only minor (<1 log10 fold) increases in L. gasseri and L. jensenii that were not independently associated with reduced inflammation in multivariable models.

CONCLUSION

The genital immune benefits that are associated with Lactobacillus dominance following BV treatment were not directly attributable to an absolute increase in lactobacilli, but rather to the loss of BV-associated bacteria.TRAIL REGISTRATION. Participants were recruited as part of a randomized controlled trial (NCT02766023) from 2016 to 2020.

FUNDING

Canadian Institutes of Health Research (PJT-156123) and the National Institute of Allergy and Infectious Diseases (HHSN2722013000141 and HHSN27200007).

Canine Meningoencephalitis of Unknown Origin-The Search for Infectious Agents in the Cerebrospinal Fluid via Deep Sequencing

Meningoencephalitis of unknown origin (MUO) describes a group of meningoencephalitides in dogs with a hitherto unknown trigger. An infectious agent has been suggested as one possible trigger of MUO but has not been proven so far. A relatively new method to screen for viral RNA or DNA is next-generation sequencing (NGS) or deep sequencing. In this study, a metagenomics analysis of the virome in a sample is analyzed and scanned for known or unknown viruses. We examined fresh-frozen CSF of 6 dogs with MUO via NGS using a modified sequence-independent, single-primer amplification protocol to detect a possible infectious trigger. Analysis of sequencing reads obtained from the six CSF samples showed no evidence of a virus infection. The inability to detect a viral trigger which could be implicated in the development of MUO in the examined population of European dogs, suggests that the current techniques are not sufficiently sensitive to identify a possible virus infection, that the virus is already eliminated at the time-point of disease outbreak, the trigger might be non-infectious or that there is no external trigger responsible for initiating MUO in dogs.

Metagenomic Next-Generation Sequencing for Diagnosis of Pediatric Meningitis and Encephalitis: A Review

Metagenomic next-generation sequencing is a novel diagnostic test with the potential to revolutionize the diagnosis of pediatric meningitis and encephalitis through unbiased detection of bacteria, viruses, parasites, and fungi in cerebrospinal fluid. Current literature is mostly observational with variable indications, populations, and timing of testing with resulting variability in diagnostic yield and clinical impact. Diagnostic stewardship strategies are needed to direct testing toward high-impact pediatric populations, to optimize timing of testing, to ensure appropriate interpretation of results, and to guide prompt optimization of antimicrobials. This review highlights the high clinical potential of this test, though future studies are needed to gather clinical impact and cost-effectiveness data for specific indications in pediatric populations.

Viral metagenomic sequencing in the diagnosis of meningoencephalitis: a review of technical advances and diagnostic yield

INTRODUCTION

Meningoencephalitis patients are often severely impaired and benefit from early etiological diagnosis, though many cases remain without identified cause. Metagenomics as pathogen agnostic approach can result in additional etiological findings; however, the exact diagnostic yield when used as a secondary test remains unknown.

AREAS COVERED

This review aims to highlight recent advances with regard to wet and dry lab methodologies of metagenomic testing and technical milestones that have been achieved. A selection of procedures currently applied in accredited diagnostic laboratories is described in more detail to illustrate best practices. Furthermore, a meta-analysis was performed to assess the additional diagnostic yield utilizing metagenomic sequencing in meningoencephalitis patients. Finally, the remaining challenges for successful widespread implementation of metagenomic sequencing for the diagnosis of meningoencephalitis are addressed in a future perspective.

EXPERT OPINION

The last decade has shown major advances in technical possibilities for using mNGS in diagnostic settings including cloud-based analysis. An additional advance may be the current established infrastructure of platforms for bioinformatic analysis of SARS-CoV-2, which may assist to pave the way for global use of clinical metagenomics.

Toward Establishing Integrated, Comprehensive, and Sustainable Meningitis Surveillance in Africa to Better Inform Vaccination Strategies

Large populations across sub-Saharan Africa remain at risk of devastating acute bacterial meningitis epidemics and endemic disease. Meningitis surveillance is a cornerstone of disease control, essential for describing temporal changes in disease epidemiology, the rapid detection of outbreaks, guiding vaccine introduction and monitoring vaccine impact. However, meningitis surveillance in most African countries is weak, undermined by parallel surveillance systems with little to no synergy and limited laboratory capacity. African countries need to implement comprehensive meningitis surveillance systems to adapt to the rapidly changing disease trends and vaccine landscapes. The World Health Organization and partners have developed a new investment case to restructure vaccine-preventable disease surveillance. With this new structure, countries will establish comprehensive and sustainable meningitis surveillance systems integrated with greater harmonization between population-based and sentinel surveillance systems. There will also be stronger linkage with existing surveillance systems for vaccine-preventable diseases, such as polio, measles, yellow fever, and rotavirus, as well as with other epidemic-prone diseases to leverage their infrastructure, transport systems, equipment, human resources and funding. The implementation of these concepts is currently being piloted in a few countries in sub-Saharan Africa with support from the World Health Organization and other partners. African countries need to take urgent action to improve synergies and coordination between different surveillance systems to set joint priorities that will inform action to control devastating acute bacterial meningitis effectively.

Invasive Bacterial Vaccine-Preventable Disease Surveillance: Successes and Lessons Learned in Bangladesh for a Sustainable Path Forward

We have made considerable progress in setting and scaling up surveillance systems to drive evidence-based policy decisions, but the recent epidemics highlight that current systems are not optimally designed. Good surveillance systems should be coordinated, comprehensive, and adaptive. They should generate data in real time for immediate analysis and intervention, whether for endemic diseases or potential epidemics. Such systems are especially needed in low-resource settings where disease burden is the highest, but tracking systems are the weakest here due to competing priorities and constraints on available resources. In this article, using the examples of 3 large, and mostly successful, infectious disease surveillance studies in Bangladesh, we identify 2 core limitations—the pathogen bias and the vaccine bias—in the way current surveillance programs are designed for low-resource settings. We highlight the strengths of the current Global Invasive Bacterial Vaccine Preventable Disease Surveillance Network of the World Health Organization and present case studies from Bangladesh to illustrate how this surveillance platform can be leveraged to overcome its limitations. Finally, we propose a set of criteria for building a comprehensive infectious disease surveillance system with the hope of encouraging current systems to use the limited resources as optimally as possible to generate the maximum amount of knowledge.

The importance of molecular diagnostics for infectious diseases in low-resource settings

In settings with limited resources and a wide range of possible etiologies, molecular technologies offer an effective solution for infectious disease diagnostics, because they are agile, fast and flexible. Health systems that routinely use molecular diagnostics will achieve economies of scale, maximize limited expertize and rapidly respond to new threats.

Metagenomic characterization of swine slurry in a North American swine farm operation

Modern day large-scale, high-density farming environments are inherently susceptible to viral outbreaks, inadvertently creating conditions that favor increased pathogen transmission and potential zoonotic spread. Metagenomic sequencing has proven to be a useful tool for characterizing the microbial burden in both people, livestock, and environmental samples. International efforts have been successful at characterizing pathogens in commercial farming environments, especially swine farms, however it is unclear whether the full extent of microbial agents have been adequately captured or is representative of farms elsewhere. To augment international efforts we performed metagenomic next-generation sequencing on nine swine slurry and three environmental samples from a United States of America (U.S.A.) farm operation, characterized the microbial composition of slurry, and identified novel viruses. We assembled a remarkable total of 1792 viral genomes, of which 554 were novel/divergent. We assembled 1637 Picobirnavirus genome segments, of which 538 are novel. In addition, we discovered 10 new viruses belonging to a novel taxon: porcine Statoviruses; which have only been previously reported in human, macaques, mouse, and cows. We assembled 3 divergent Posaviruses and 3 swine Picornaviruses. In addition to viruses described, we found other eukaryotic genera such as Entamoeba and Blastocystis, and bacterial genera such as Listeria, Treponema, Peptoclostridium and Bordetella in the slurry. Of these, two species Entamoeba histolytica and Listeria monocytogenes known to cause human disease were detected. Further, antimicrobial resistance genes such as tetracycline and MLS (macrolide, lincosamide, streptogramin) were also identified. Metagenomic surveillance in swine fecal slurry has great potential for novel and antimicrobial resistant pathogen detection.

Clinical Features of Acute Chikungunya Virus Infection in Children and Adults during an Outbreak in the Maldives

The chikungunya virus is an arthritogenic arbovirus that has re-emerged in many tropical and subtropical regions, causing explosive outbreaks. This re-emergence is due to a genomic polymorphism that has increased the vector susceptibility of the virus. The majority of those infected with chikungunya virus exhibit symptoms of fever, rash, and debilitating polyarthralgia or arthritis. Symptoms can persist for weeks, and patients can relapse months later. Fatalities are rare, but individuals of extreme age can develop severe infection. Here, we describe the 2019 outbreak, the second-largest since the virus re-emerged in the Maldives after the 2004 Indian Ocean epidemic, in which a total of 1,470 cases were reported to the Health Ministry. Sixty-seven patients presenting at the main referral tertiary care hospital in the Maldives capital with acute undifferentiated illness were recruited following a negative dengue serology. A novel point-of-care antigen kit was used to screen suspected cases, 50 of which were subsequently confirmed using real-time reverse transcription-polymerase chain reaction. We describe the genotype and polymorphism of Maldives chikungunya virus using phylogenetic analysis. All isolates were consistent with the East Central South African genotype of the Indian Ocean lineage, with a specific E1-K211E mutation. In addition, we explored the clinical and laboratory manifestations of acute chikungunya in children and adults, of which severe infection was found in some children, whereas arthritis primarily occurred in adults. Arthritides in adults occurred irrespective of underlying comorbidities and were associated with the degree of viremia.

Current Status of Chikungunya in India

Chikungunya fever (CHIKF) is an arbovirus disease caused by chikungunya virus (CHIKV), an alphavirus of Togaviridae family. Transmission follows a human-mosquito-human cycle starting with a mosquito bite. Subsequently, symptoms develop after 2-6 days of incubation, including high fever and severe arthralgia. The disease is self-limiting and usually resolve within 2 weeks. However, chronic disease can last up to several years with persistent polyarthralgia. Overlapping symptoms and common vector with dengue and malaria present many challenges for diagnosis and treatment of this disease. CHIKF was reported in India in 1963 for the first time. After a period of quiescence lasting up to 32 years, CHIKV re-emerged in India in 2005. Currently, every part of the country has become endemic for the disease with outbreaks resulting in huge economic and productivity losses. Several mutations have been identified in circulating strains of the virus resulting in better adaptations or increased fitness in the vector(s), effective transmission, and disease severity. CHIKV evolution has been a significant driver of epidemics in India, hence, the need to focus on proper surveillance, and implementation of prevention and control measure in the country. Presently, there are no licensed vaccines or antivirals available; however, India has initiated several efforts in this direction including traditional medicines. In this review, we present the current status of CHIKF in India.

Leapfrogging laboratories: the promise and pitfalls of high-tech solutions for antimicrobial resistance surveillance in low-income settings

The scope and trajectory of today’s escalating antimicrobial resistance (AMR) crisis is inadequately captured by existing surveillance systems, particularly those of lower income settings. AMR surveillance systems typically collate data from routine culture and susceptibility testing performed in diagnostic bacteriology laboratories to support healthcare. Limited access to high quality culture and susceptibility testing results in the dearth of AMR surveillance data, typical of many parts of the world where the infectious disease burden and antimicrobial need are high. Culture and susceptibility testing by traditional techniques is also slow, which limits its value in infection management. Here, we outline hurdles to effective resistance surveillance in many low-income settings and encourage an open attitude towards new and evolving technologies that, if adopted, could close resistance surveillance gaps. Emerging advancements in point-of-care testing, laboratory detection of resistance through or without culture, and in data handling, have the potential to generate resistance data from previously unrepresented locales while simultaneously supporting healthcare. Among them are microfluidic, nucleic acid amplification technology and next-generation sequencing approaches. Other low tech or as yet unidentified innovations could also rapidly accelerate AMR surveillance. Parallel advances in data handling further promise to significantly improve AMR surveillance, and new frameworks that can capture, collate and use alternate data formats may need to be developed. We outline the promise and limitations of such technologies, their potential to leapfrog surveillance over currently available, conventional technologies in use today and early steps that health systems could take towards preparing to adopt them.

Characterization of the Blood and Cerebrospinal Fluid Microbiome in Children with Bacterial Meningitis and Its Potential Correlation with Inflammation

Bacterial meningitis shows a higher incidence in children than adults, but signs may be scarce. Although some pathogenic microorganisms of meningitis from cerebrospinal fluid (CSF) have been reported, the signature of the representative microbiota in CSF and blood samples from patients remains incompletely revealed. To extend the understanding of the microbiome in patients, we recruited 32 children with bacterial meningitis, 30 undiagnosed infectious children, and 10 matched healthy individuals, which was followed by untargeted metagenomic next-generation sequencing (mNGS) and bioinformatic analysis. Our results showed that children with bacterial meningitis exhibited different microbiome signatures in their CSF and blood compared with undiagnosed and healthy children, and patients could be divided into varied subsets according to these signatures, including Escherichia coli, Klebsiella pneumoniae, Thermothelomyces thermophila, Lactobacillus acidophilus, and Staphylococcus haemolyticus. To further explore their potential role in patients’ conditions, we examined their correlation with clinical parameters. Importantly, microbiome signatures with compositional changes were correlated with the C-reactive protein (CRP) level in blood and granulocyte percentage in CSF. Moreover, the blood in subsets of patients with a predominance of Klebsiella pneumoniae could replace CSF as the main specimen for clinical monitoring.

IMPORTANCE This study revealed the microbial compositions in children with bacterial meningitis who were treated with antibiotics and made a comprehensive comparison between blood and CSF specimens for the risk and prognosis assessment. We found that microbiome signatures could distinguish patient subsets in the children and were correlated with the CRP level in blood and granulocyte percentage in CSF. The compositional changes in representative microbiota constituents could provide guidance for clinical monitoring and antibiotic intervention.

Use of unbiased metagenomic and transcriptomic analyses to investigate the association between feline calicivirus and feline chronic gingivostomatitis in domestic cats

OBJECTIVE

To identify associations between microbes and host genes in cats with feline chronic gingivostomatitis (FCGS), a debilitating inflammatory oral mucosal disease with no known cause, compared with healthy cats and cats with periodontitis (control cats).

ANIMALS

19 control cats and 23 cats with FCGS.

PROCEDURES

At least 1 caudal oral mucosal swab specimen was obtained from each cat. Each specimen underwent unbiased metatranscriptomic next-generation RNA sequencing (mNGS). Filtered mNGS reads were aligned to all known genetic sequences from all organisms and to the cat transcriptome. The relative abundances of microbial and host gene read alignments were compared between FCGS-affected cats and control cats and between FCGS-affected cats that did and did not clinically respond to primary treatment. Assembled feline calicivirus (FCV) genomes were compared with reverse transcription PCR (RT-PCR) primers commonly used to identify FCV.

RESULTS

The only microbe strongly associated with FCGS was FCV, which was detected in 21 of 23 FCGS-affected cats but no control cats. Problematic base pair mismatches were identified between the assembled FCV genomes and RT-PCR primers. Puma feline foamy virus was detected in 9 of 13 FCGS-affected cats that were refractory to treatment and 5 healthy cats but was not detected in FCGS-affected cats that responded to tooth extractions. The most differentially expressed genes in FCGS-affected cats were those associated with antiviral activity.

CONCLUSIONS AND CLINICAL RELEVANCE

Results suggested that FCGS pathogenesis has a viral component. Many FCV strains may yield false-negative results on RT-PCR-based assays. Coinfection of FCGS-affected cats with FCV and puma feline foamy virus may adversely affect response to treatment.

Evaluating Infectious, Neoplastic, Immunological, and Degenerative Diseases of the Central Nervous System with Cerebrospinal Fluid-Based Next-Generation Sequencing

Cerebrospinal fluid (CSF) is a clear and paucicellular fluid that circulates within the ventricular system and the subarachnoid space of the central nervous system (CNS), and diverse CNS disorders can impact its composition, volume, and flow. As conventional CSF testing suffers from suboptimal sensitivity, this review aimed to evaluate the role of next-generation sequencing (NGS) in the work-up of infectious, neoplastic, neuroimmunological, and neurodegenerative CNS diseases. Metagenomic NGS showed improved sensitivity—compared to traditional methods—to detect bacterial, viral, parasitic, and fungal infections, while the overall performance was maximized in some studies when all diagnostic modalities were used. In patients with primary CNS cancer, NGS findings in the CSF were largely concordant with the molecular signatures derived from tissue-based molecular analysis; of interest, additional mutations were identified in the CSF in some glioma studies, reflecting intratumoral heterogeneity. In patients with metastasis to the CNS, NGS facilitated diagnosis, prognosis, therapeutic management, and monitoring, exhibiting higher sensitivity than neuroimaging, cytology, and plasma-based molecular analysis. Although evidence is still rudimentary, NGS could enhance the diagnosis and pathogenetic understanding of multiple sclerosis in addition to Alzheimer and Parkinson disease. To conclude, NGS has shown potential to aid the research, facilitate the diagnostic approach, and improve the management outcomes of all the aforementioned CNS diseases. However, to establish its role in clinical practice, the clinical validity and utility of each NGS protocol should be determined. Lastly, as most evidence has been derived from small and retrospective studies, results from randomized control trials could be of significant value.

Next-generation Sequencing of Cerebrospinal Fluid for the Diagnosis of Unexplained Central Nervous System Infections

BACKGROUND

Central nervous system infections cause substantial morbidity and mortality in pediatric patients. However, in approximately half of the clinical cases, the etiology is unidentified. As an unbiased molecular diagnostic technology, next-generation sequencing is gradually being applied to investigate central nervous system infections. This review summarizes and critiques the literature on this new technology for etiologic identification of unexplained central nervous system infections in pediatric patients and discusses the future prospects for development of this technology in pediatrics.

METHODS

A comprehensive PubMed search was conducted of articles published from January 1, 2008, to June 26, 2020 in order to retrieve all available studies on this topic. Other relevant articles were identified from recent reviews and the bibliographies of the retrieved full-text articles.

RESULTS

Among the 441 studies retrieved, 26 pediatric studies, comprising 15 case reports and 11 case series, used next-generation sequencing as a diagnostic tool. In these 26 studies, next-generation sequencing was performed on cerebrospinal fluid samples from 529 pediatric patients, and potential causal pathogens were identified in 22.1% of the cases.

CONCLUSION

There is increasing evidence that next-generation sequencing can play a role in identifying the causes of unexplained encephalitis, meningoencephalitis, and meningitis in pediatric patients, although the diagnostic value of next-generation sequencing is difficult to quantify. There is an increasing need for close collaboration between laboratory scientists and clinicians. We believe that further clinical studies should be performed to evaluate the performance of next-generation sequencing for individual targets and in high-risk populations.

Genome Sequence of a Dengue Virus Serotype 2 Strain Identified during the 2019 Outbreak in Bangladesh

A nearly complete genome sequence of a dengue virus serotype 2 strain detected in the serum of a patient in 2019 during the largest outbreak of dengue fever in Bangladesh is reported.

A nearly complete genome sequence of a dengue virus serotype 2 strain detected in the serum of a patient in 2019 during the largest outbreak of dengue fever in Bangladesh is reported.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Sensitive universal detection of blood parasites by selective pathogen-DNA enrichment and deep amplicon sequencing

BACKGROUND

Targeted amplicon deep sequencing (TADS) has enabled characterization of diverse bacterial communities, yet the application of TADS to communities of parasites has been relatively slow to advance. The greatest obstacle to this has been the genetic diversity of parasitic agents, which include helminths, protozoa, arthropods, and some acanthocephalans. Meanwhile, universal amplification of conserved loci from all parasites without amplifying host DNA has proven challenging. Pan-eukaryotic PCRs preferentially amplify the more abundant host DNA, obscuring parasite-derived reads following TADS. Flaherty et al. (2018) described a pan-parasitic TADS method involving amplification of eukaryotic 18S rDNA regions possessing restriction sites only in vertebrates. Using this method, host DNA in total DNA extracts could be selectively digested prior to PCR using restriction enzymes, thereby increasing the number of parasite-derived reads obtained following NGS. This approach showed promise though was only as sensitive as conventional PCR.

RESULTS

Here, we expand on this work by designing a second set of pan-eukaryotic primers flanking the priming sites already described, enabling nested PCR amplification of the established 18S rDNA target. This nested approach facilitated introduction of a second restriction digestion between the first and second PCR, reducing the proportional mass of amplifiable host-derived DNA while increasing the number of PCR amplification cycles. We applied this method to blood specimens containing Babesia, Plasmodium, various kinetoplastids, and filarial nematodes and confirmed its limit of detection (LOD) to be approximately 10-fold lower than previously described, falling within the range of most qPCR methods.

CONCLUSIONS

The assay detects and differentiates the major malaria parasites of humans, along with several other clinically important blood parasites. This represents an important step towards a TADS-based universal parasite diagnostic (UPDx) test with a sufficient LOD for routine applications. Video Abstract.

A Novel Sub-Lineage of Chikungunya Virus East/Central/South African Genotype Indian Ocean Lineage Caused Sequential Outbreaks in Bangladesh and Thailand

In recent decades, chikungunya virus (CHIKV) has become geographically widespread. In 2004, the CHIKV East/Central/South African (ECSA) genotype moved from Africa to Indian ocean islands and India followed by a large epidemic in Southeast Asia. In 2013, the CHIKV Asian genotype drove an outbreak in the Americas. Since 2016, CHIKV has re-emerged in the Indian subcontinent and Southeast Asia. In the present study, CHIKVs were obtained from Bangladesh in 2017 and Thailand in 2019, and their nearly full genomes were sequenced. Phylogenetic analysis revealed that the recent CHIKVs were of Indian Ocean Lineage (IOL) of genotype ECSA, similar to the previous outbreak. However, these CHIKVs were all clustered into a new distinct sub-lineage apart from the past IOL CHIKVs, and they lacked an alanine-to-valine substitution at position 226 of the E1 envelope glycoprotein, which enhances CHIKV replication in Aedes albopictus. Instead, all the re-emerged CHIKVs possessed mutations of lysine-to-glutamic acid at position 211 of E1 and valine-to-alanine at position 264 of E2. Molecular clock analysis suggested that the new sub-lineage CHIKV was introduced to Bangladesh around late 2015 and Thailand in early 2017. These results suggest that re-emerged CHIKVs have acquired different adaptations than the previous CHIKVs.