How next-generation sequencing and multiscale data analysis will transform infectious disease management

Case report: A toxoplasmic encephalitis in an immunocompromised child detected through metagenomic next-generation sequencing

There exist numerous pathogens that are capable of causing infections within the central nervous system (CNS); however, conventional detection and analysis methods prove to be challenging. Clinical diagnosis of CNS infections often depends on clinical characteristics, cerebrospinal fluid (CSF) analysis, imaging, and molecular detection assays. Unfortunately, these methods can be both insensitive and time consuming, which can lead to missed diagnoses and catastrophic outcomes, especially in the case of infrequent diseases. Despite the application of appropriate prophylactic regimens and evidence-based antimicrobial agents, CNS infections continue to result in significant morbidity and mortality in hospital settings. Metagenomic next-generation sequencing (mNGS) is a novel tool that enables the identification of thousands of pathogens in a target-independent manner in a single run. The role of this innovative detection method in clinical pathogen diagnostics has matured over time. In this particular research, clinicians employed mNGS to investigate a suspected CNS infection in a child with leukemia, and unexpectedly detected Toxoplasma gondii.

Case

A 3-year-old child diagnosed with T-cell lymphoblastic lymphoma was admitted to our hospital due to a 2-day history of fever and headache, along with 1 day of altered consciousness. Upon admission, the patient's Glasgow Coma Scale score was 14. Brain magnetic resonance imaging revealed multiple abnormal signals. Due to the patient's atypical clinical symptoms and laboratory test results, determining the etiology and treatment plan was difficulty.Subsequently, the patient underwent next-generation sequencing examination of cerebrospinal fluid. The following day, the results indicated the presence of Toxoplasma gondii. The patient received treatment with a combination of sulfamethoxazole (SMZ) and azithromycin. After approximately 7 days, the patient's symptoms significantly improved, and they were discharged from the hospital with oral medication to continue at home. A follow-up polymerase chain reaction (PCR) testing after about 6 weeks revealed the absence of Toxoplasma.

Conclusion

This case highlights the potential of mNGS as an effective method for detecting toxoplasmic encephalitis (TE). Since mNGS can identify thousands of pathogens in a single run, it may be a promising detection method for investigating the causative pathogens of central nervous system infections with atypical features.

Multi-site implementation of whole genome sequencing for hospital infection control: A prospective genomic epidemiological analysis

BACKGROUND

Current microbiological methods lack the resolution to accurately identify multidrug-resistant organism (MDRO) transmission, however, whole genome sequencing can identify highly-related patient isolates providing opportunities for precision infection control interventions. We investigated the feasibility and potential impact of a prospective multi-centre genomics workflow for hospital infection control.

METHODS

We conducted a prospective genomics implementation study across eight Australian hospitals over 15 months (2017,2018), collecting all clinical and screening isolates from inpatients with vanA VRE, MRSA, ESBL Escherichia coli (ESBL-Ec), or ESBL Klebsiella pneumoniae (ESBL-Kp). Genomic and epidemiologic data were integrated to assess MDRO transmission.

FINDINGS

In total, 2275 isolates were included from 1970 patients, predominantly ESBL-Ec (40·8%) followed by MRSA (35·6%), vanA VRE (15·2%), and ESBL-Kp (8·3%).Overall, hospital and genomic epidemiology showed 607 patients (30·8%) acquired their MDRO in hospital, including the majority of vanA VRE (266 patients, 86·4%), with lower proportions of ESBL-Ec (186 patients, 23·0%), ESBL-Kp (42 patients, 26·3%), and MRSA (113 patients, 16·3%). Complex patient movements meant the majority of MDRO transmissions would remain undetected without genomic data.The genomics implementation had major impacts, identifying unexpected MDRO transmissions prompting new infection control interventions, and contributing to vanA VRE becoming a notifiable condition. We identified barriers to implementation and recommend strategies for mitigation.

INTERPRETATION

Implementation of a multi-centre genomics-informed infection control workflow is feasible and identifies many unrecognised MDRO transmissions. This provides critical opportunities for interventions to improve patient safety in hospitals.

FUNDING

Melbourne Genomics Health Alliance (supported by State Government of Victoria, Australia), and National Health and Medical Research Council (Australia).

Unlocking Access to Broad Molecular Profiling: Benefits, Barriers, and Policy Solutions

OBJECTIVES

"Personalized healthcare" is generating new approaches to disease management by considering inter-individual variability in genes, environment, and lifestyle. Technologies such as comprehensive genomic profiling (CGP) are drivers of this shift. Here, we address the significant hurdles to the equitable implementation of CGP into routine clinical practice.

METHODS

This article draws on published evidence on the value of genomic profiling, as well as interviews with nine academic and clinical experts from six different countries to validate findings and test policy proposals for reforms.

RESULTS

The potential benefits of CGP extend beyond direct patient outcomes, to healthcare systems with societal and economic impacts. Among key barriers impeding integration into routine clinical practice are the lack of infrastructure to ensure reliable clinical testing and the limited understanding of genomics among healthcare personnel. In addition, the absence of health economic evidence supporting broader use of CGP is creating concerns for payers regarding the systemic benefits and affordability of this technology.

CONCLUSION

Policy proposals that aim to improve equitable patient access to CGP will need to consider new funding models, health technology assessment processes that capture both patient and systemic benefits, and appropriate regulatory standards to determine the quality of genomic profiling tests.

Application of Metagenomic Sequencing in the Diagnosis of Infectious Uveitis

Purpose: to summarize the origin and very recent history of the use of metagenomic sequencing for the diagnosis of infectious uveitis, convey the technique as described by one of the primary institutions experimenting with the technology, and present recent successful applications of the technology as well as potential advantages and pitfalls compared to other current diagnostic tools.Methods: review of peer-reviewed literature concerning metagenomic sequencing for the diagnosis of infectious uveitis.Conclusion: compared to existing diagnostic methods, metagenomic deep sequencing is a sensitive, unbiased, and comprehensive technique with great potential for diagnosing the causative pathogens of cases of infectious uveitis. However, many issues remain to be addressed in the process of developing this technology, including but not limited to the potentially overwhelming amount of information generated, definition of diagnostic thresholds, demonstration of validity, contamination, and cost.

Healthcare Associated Infections: An Interoperable Infrastructure for Multidrug Resistant Organism Surveillance

Prevention and surveillance of healthcare associated infections caused by multidrug resistant organisms (MDROs) has been given increasing attention in recent years and is nowadays a major priority for health care systems. The creation of automated regional, national and international surveillance networks plays a key role in this respect. A surveillance system has been designed for the Abruzzo region in Italy, focusing on the monitoring of the MDROs prevalence in patients, on the appropriateness of antibiotic prescription in hospitalized patients and on foreseeable interactions with other networks at national and international level. The system has been designed according to the Service Oriented Architecture (SOA) principles, and Healthcare Service Specification (HSSP) standards and Clinical Document Architecture Release 2 (CDAR2) have been adopted. A description is given with special reference to implementation state, specific design and implementation choices and next foreseeable steps. The first release will be delivered at the Complex Operating Unit of Infectious Diseases of the Local Health Authority of Pescara (Italy).

Next-Generation Sequencing Coupled With in situ Hybridization: A Novel Diagnostic Platform to Investigate Swine Emerging Pathogens and New Variants of Endemic Viruses

Next generation sequencing (NGS) can be applied to identify and characterize the entire set of microbes within a sample. However, this platform does not provide a morphological context or specific association between the viral or bacterial sequences detected and the histological lesions. This limitation has generated uncertainty whether the sequences identified by NGS are actually contributing or not for the clinical outcome. Although in situ hybridization (ISH) and immunohistochemistry (IHC) can be used to detect pathogens in tissue samples, only ISH has the advantage of being rapidly developed in a context of an emerging disease, especially because it does not require development of specific primary antibodies against the target pathogen. Based on the sequence information provided by NGS, ISH is able to check the presence of a certain pathogen within histological lesions, by targeting its specific messenger RNA, helping to build the relationship between the pathogen and the clinical outcome. In this mini review we have compiled results of the application of NGS-ISH to the investigation of challenging diagnostic cases or emerging pathogens in pigs, that resulted in the detection of porcine circovirus type 3, porcine parvovirus type 2, Senecavirus A, and Mycoplasma hyorhinis.

Genomic Surveillance Reveals Diversity of Multidrug-Resistant Organism Colonization and Infection: A Prospective Cohort Study in Liver Transplant Recipients

Background

Multidrug-resistant organisms (MDROs) are an important cause of morbidity and mortality after solid organ transplantation. We aimed to characterize MDRO colonization dynamics and infection in liver transplant (LT) recipients through innovative use of active surveillance and whole-genome sequencing (WGS).

Methods

We prospectively enrolled consecutive adult patients undergoing LT from March 2014 to March 2016. Fecal samples were collected at multiple timepoints from time of enrollment to 12 months posttransplant. Samples were screened for carbapenem-resistant Enterobacteriaceae (CRE), Enterobacteriaceae resistant to third-generation cephalosporins (Ceph-RE), and vancomycin-resistant enterococci. We performed WGS of CRE and selected Ceph-RE isolates. We also collected clinical data including demographics, transplant characteristics, and infection data.

Results

We collected 998 stool samples and 119 rectal swabs from 128 patients. MDRO colonization was detected in 86 (67%) patients at least once and was significantly associated with subsequent MDRO infection (0 vs 19.8%, P = .002). Child-Turcotte-Pugh score at LT and duration of post-LT hospitalization were independent predictors of both MDRO colonization and infection. Temporal dynamics differed between MDROs with respect to onset of colonization, clearance, and infections. We detected an unexpected diversity of CRE colonizing isolates and previously unrecognized transmission that spanned Ceph-RE and CRE phenotypes, as well as a cluster of mcr-1-producing isolates.

Conclusions

Active surveillance and WGS showed that MDRO colonization is a highly dynamic and complex process after LT. Understanding that complexity is crucial for informing decisions regarding MDRO infection control, use of therapeutic decolonization, and empiric treatment regimens.

Metagenomics in diagnosis and improved targeted treatment of UTI

INTRODUCTION

The genomic revolution has transformed our understanding of urinary tract infection. There has been a paradigm shift from the dogmatic statement that urine is sterile in healthy people, as we are becoming forever more familiar with the knowledge that bacterial communities exist within the urinary tracts of healthy people. Metagenomics can investigate the broad populations of microbial communities, analysing all the DNA present within a sample, providing comprehensive data regarding the state of the microenvironment of a patient's urinary tract. This permits medical practitioners to more accurately target organisms that may be responsible for disease-a form of 'precision medicine'.

METHODS AND RESULTS

This paper is derived from an extensive review and analysis of the available literature on the topic of metagenomic sequencing in urological science, using the PubMed search engine. The search yielded a total of 406 results, and manual selection of appropriate papers was subsequently performed. Only one randomised clinical trial comparing metagenomic sequencing to standard culture and sensitivity in the arena of urinary tract infection was found.

CONCLUSION

Out of this process, this paper explores the limitations of traditional methods of culture and sensitivity and delves into the recent studies involving new high-throughput genomic technologies in urological basic and clinical research, demonstrating the advances made in the urinary microbiome in its entire spectrum of pathogens and the first attempts of clinical implementation in several areas of urology. Finally, this paper discusses the challenges that must be overcome for such technology to become widely used in clinical practice.

Automated data mining of the electronic health record for investigation of healthcare-associated outbreaks

BACKGROUND

Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.

METHODS

We retrospectively analyzed 9 hospital outbreaks that occurred during 2011-2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.

RESULTS

Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.

CONCLUSIONS

Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.

Mapping the Evolutionary Potential of RNA Viruses

The deterministic force of natural selection and stochastic influence of drift shape RNA virus evolution. New deep-sequencing and microfluidics technologies allow us to quantify the effect of mutations and trace the evolution of viral populations with single-genome and single-nucleotide resolution. Such experiments can reveal the topography of the genotype-fitness landscapes that shape the path of viral evolution. By combining historical analyses, like phylogenetic approaches, with high-throughput and high-resolution evolutionary experiments, we can observe parallel patterns of evolution that drive important phenotypic transitions. These developments provide a framework for quantifying and anticipating potential evolutionary events. Here, we examine emerging technologies that can map the selective landscapes of viruses, focusing on their application to pathogenic viruses. We identify areas where these technologies can bolster our ability to study the evolution of viruses and to anticipate and possibly intervene in evolutionary events and prevent viral disease.

Dynamics of monocytic HLA-DR expression differs between bacterial etiologies during the course of bloodstream infection

Objective

In the pathogenesis of sepsis, activation of both pro- and anti-inflammatory responses are key components, but knowledge is lacking on the association between bacterial etiology and development of dysregulated responses with sustained immunosuppression. The aim of this study was to evaluate how the immunosupression marker HLA-DR on monocytes (mHLA-DR) is associated with bacterial etiology and markers of inflammation during the clinical trajectory of bloodstream infection (BSI).

Methods

Ninety-one adults, predominantly non-ICU patients, with BSI caused by Streptococcus pneumoniae (n = 27), Staphylococcus aureus (n = 22), Escherichia coli/Klebsiella pneumoniae (n = 23), and other species (n = 19) were prospectively included, and sampled on admission (day 0) and on days 1–2, 3, 7±1, 14±2, and 28±4.

Results

The dynamics of mHLA-DR, measured by flow cytometry, differed significantly between etiology groups (p<0.001). Patients with S. pneumoniae and S. aureus BSI demonstrated low initial mHLA-DR, with the S. aureus group showing delayed recovery over time. Eleven patients (55% S. aureus) had negative outcome (secondary bacteremia or death) and they demonstrated sustained C-reactive protein elevation, neutrophilia, lymphocytopenia, and loss of mHLA-DR.

Conclusions

Dynamics of mHLA-DR varied according to the bacterial etiology of infection, with delayed recovery in patients with S. aureus BSI. Patients with negative outcome showed sustained CRP elevation, neutrophilia, lymphocytopenia, and low levels of mHLA-DR, supporting the theory of a dysregulated host response with persistent inflammation and immunosuppression in late stages of deleterious sepsis.

Community-Acquired Cavitary Pseudomonas Pneumonia Linked to Use of a Home Humidifier

Pseudomonas aeruginosa is an opportunistic pathogen that rarely causes pneumonia in otherwise healthy patients. We describe a case of community-acquired P. aeruginosa pneumonia in a previously healthy individual who likely acquired the infection from a home humidifier.

Estimating Local Costs Associated With Clostridium difficile Infection Using Machine Learning and Electronic Medical Records

BACKGROUND Reported per-patient costs of Clostridium difficile infection (CDI) vary by 2 orders of magnitude among different hospitals, implying that infection control officers need precise, local analyses to guide rational decision making between interventions. OBJECTIVE We sought to comprehensively estimate changes in length of stay (LOS) attributable to CDI at a single urban tertiary-care facility using only data automatically extractable from the electronic medical record (EMR). METHODS We performed a retrospective cohort study of 171,938 visits spanning a 7-year period. In total, 23,968 variables were extracted from EMR data recorded within 24 hours of admission to train elastic-net regularized logistic regression models for propensity score matching. To address time-dependent bias (reverse causation), we separately stratified comparisons by time of infection, and we fit multistate models. RESULTS The estimated difference in median LOS for propensity-matched cohorts varied from 3.1 days (95% CI, 2.2-3.9) to 10.1 days (95% CI, 7.3-12.2) depending on the case definition; however, dependency of the estimate on time to infection was observed. Stratification by time to first positive toxin assay, excluding probable community-acquired infections, showed a minimum excess LOS of 3.1 days (95% CI, 1.7-4.4). Under the same case definition, the multistate model averaged an excess LOS of 3.3 days (95% CI, 2.6-4.0). CONCLUSIONS In this study, 2 independent time-to-infection adjusted methods converged on similar excess LOS estimates. Changes in LOS can be extrapolated to marginal dollar costs by multiplying by average costs of an inpatient day. Infection control officers can leverage automatically extractable EMR data to estimate costs of CDI at their own institutions. Infect Control Hosp Epidemiol. 2017;38:1478-1486.

Pseudomonas Endocarditis with an unstable phenotype: the challenges of isolate characterization and Carbapenem stewardship with a partial review of the literature

Background

Pseudomonas endocarditis is exceedingly rare, especially in patients without predisposing risks. We present such a case that included unexpected switches in antibacterial resistance profiles in two Pseudomonas aeruginosa (PA) strains with the same whole-genome sequence. The case also involved diagnostic and treatment challenges, such as issues with automated testing platforms, choosing the optimal aminoglycoside, minimizing unnecessary carbapenem exposure, and the need for faster, more informative laboratory tests.

Case presentation

On hospital day one (HD-1) a cefepime and piperacillin-tazobactam (FEP-TZP)-susceptible P. aeruginosa was isolated from the bloodstream of a 62-year-old man admitted for evaluation of possible endocarditis and treated with gentamicin and cefepime. On HD-2, his antibiotic regimen was changed to tobramycin and cefepime. On HD-11, he underwent aortic valve replacement, and P. aeruginosa was isolated from the explanted valve. Unexpectedly, it was FEP-TZP-resistant, so cefepime was switched to meropenem. On HD-14, in preparation for whole-genome sequencing (WGS), valve and blood isolates were removed from cryo-storage, re-cultured, and simultaneously tested with the same platforms, reagents, and inoculations previously used. Curiously, the valve isolate was now FEP-TZP-susceptible. WGS revealed that both isolates were phylogenetically identical, differing by a single nucleotide in a chemotaxis-encoding gene. They also contained the same resistance genes (bla_ADC35, aph(3′)-II, bla_OXA-50, catB7, fosA).

Conclusion

Repeated testing on alternate platforms and WGS did not definitively determine the resistance mechanism(s), which in this case, is most likely unstable de-repression of a chromosomal AmpC β-lactamase, porin alterations, or efflux upregulation, with reversion to baseline (non-efflux) transcription. Although sub-culture on specialized media to select for less fit (more resistant) colonies, followed by transcriptome analysis, and multiple sequence alignment, might have revealed the mechanism and better informed the optimal choice of β-lactam, such approaches are neither rapid, nor feasible for hospital laboratories. In this era of escalating drug resistance and dwindling antibiotics, use of the most potent anti-pseudomonals must be balanced with stewardship. Clinicians need access to validated genomic correlates of resistance, and faster, more informative diagnostics. Therefore, we placed these isolates and their sequences in the public domain for inclusion in the Pseudomonas pan-genome and database projects for further countermeasure development.

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission-aiding infection control measures and policies-emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: (i) automation and algorithmic reliance impacting freedom of choice, (ii) big data analytics complexity impacting informed consent, (iii) reliance on profiling impacting individual and group identities and justice/fair access and (iv) increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement.

Pathology of infectious diseases: what does the future hold?

The demand for expertise in pathology for the diagnosis of infectious diseases (ID) is continually growing, due to an increase in ID in immunocompromised patients and in the (re)-emergence of common and uncommon diseases, including tropical infections and infections with newly identified microbes. The microbiology laboratory plays a crucial role in diagnosing infections, identifying the responsible infectious agents and establishing sensitivity of pathogens to drug therapy. Pathology, however, is the only way to correlate the presence of an infectious agent with the reaction it evokes at cell and tissue level. For pathologists working in the field of ID pathology, it is essential to dispose of competence in cell and tissue pathology as well as in microbiology. Expertise in ID includes understanding of taxonomy and classification of pathogens as well as morphological criteria supporting their identification. Moreover, ID pathologists must master the methods used to detect pathogens in fixed cell and tissue samples, notably immunohistochemistry, in situ hybridization and the polymerase chain reaction. Paradoxically, the increasing frequency of lesions caused by pathogens and diagnosed in a pathology laboratory appears to be paralleled by a gradual loss of expertise of pathologists in the field of infectious and tropical diseases. We contend that this may be due at least in part to the continuously increasing number of samples of tumor tissue pathologists deal with and the rapidly expanding number of tissue based biomarkers with predictive value for new anti-cancer therapies. In this review, we highlight current and future issues pertaining to ID pathology, in order to increase awareness of its importance for surgical and molecular pathology. The intention is to contribute to the development of best practice in ID pathology.

Challenges in fecal donor selection and screening for fecal microbiota transplantation: A review

Fecal microbiota transplantation is best understood as an effective and inexpensive therapy for recurrent Clostridium difficile infection but fecal donor selection and screening should be periodically revised. Here, we review current recommendations for selection and screening of fecal donors for fecal microbiota transplantation. We recommend considering diabetes mellitus, prior cardiovascular events, and clinical healthcare exposure as fecal donor exclusion criteria until more is known about the association of these conditions with the human gut microbiome. We review the non-bacterial members of the human gut microbiome, associations of the gut microbiome with colorectal malignancies, the human gut resistome and how these may impact future donor screening recommendations. Collaboration between clinicians, clinical laboratory scientists, industry and regulatory agencies will be critically important for continued improvement in donor selection and screening.

Antimicrobial Stewardship: How the Microbiology Laboratory Can Right the Ship

Antimicrobial stewardship is a bundle of integrated interventions employed to optimize the use of antimicrobials in health care settings. While infectious-disease-trained physicians, with clinical pharmacists, are considered the main leaders of antimicrobial stewardship programs, clinical microbiologists can play a key role in these programs. This review is intended to provide a comprehensive discussion of the different components of antimicrobial stewardship in which microbiology laboratories and clinical microbiologists can make significant contributions, including cumulative antimicrobial susceptibility reports, enhanced culture and susceptibility reports, guidance in the preanalytic phase, rapid diagnostic test availability, provider education, and alert and surveillance systems. In reviewing this material, we emphasize how the rapid, and especially the recent, evolution of clinical microbiology has reinforced the importance of clinical microbiologists' collaboration with antimicrobial stewardship programs.

Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens

BACKGROUND

Ocular infections remain a major cause of blindness and morbidity worldwide. While prognosis is dependent on the timing and accuracy of diagnosis, the etiology remains elusive in ~50 % of presumed infectious uveitis cases. The objective of this study is to determine if unbiased metagenomic deep sequencing (MDS) can accurately detect pathogens in intraocular fluid samples of patients with uveitis.

METHODS

This is a proof-of-concept study, in which intraocular fluid samples were obtained from five subjects with known diagnoses, and one subject with bilateral chronic uveitis without a known etiology. Samples were subjected to MDS, and results were compared with those from conventional diagnostic tests. Pathogens were identified using a rapid computational pipeline to analyze the non-host sequences obtained from MDS.

RESULTS

Unbiased MDS of intraocular fluid produced results concordant with known diagnoses in subjects with (n = 4) and without (n = 1) uveitis. Samples positive for Cryptococcus neoformans, Toxoplasma gondii, and herpes simplex virus 1 as tested by a Clinical Laboratory Improvement Amendments-certified laboratory were correctly identified with MDS. Rubella virus was identified in one case of chronic bilateral idiopathic uveitis. The subject's strain was most closely related to a German rubella virus strain isolated in 1992, one year before he developed a fever and rash while living in Germany. The pattern and the number of viral identified mutations present in the patient's strain were consistent with long-term viral replication in the eye.

CONCLUSIONS

MDS can identify fungi, parasites, and DNA and RNA viruses in minute volumes of intraocular fluid samples. The identification of chronic intraocular rubella virus infection highlights the eye's role as a long-term pathogen reservoir, which has implications for virus eradication and emerging global epidemics.

Advanced Molecular Detection of Malarone Resistance

The rapid emergence of drug-resistant malaria parasites during the course of an infection remains a major challenge for providing accurate treatment guidelines. This is particularly important in cases of malaria treatment failure. Using a previously well-characterized case of malaria treatment failure, we show the utility of using next-generation sequencing for early detection of the rise and selection of a previously reported atovaquone-proguanil (malarone) drug resistance-associated mutation.