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Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. The group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

ABSTRACT Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific tests, sometimes over days to weeks, whereas metagenomic next-generation sequencing (mNGS) profiles all nucleic acid in a sample. In this single-center, prospective study, 68 hospitalized patients with known (n = 44) or suspected (n = 24) CNS infections underwent mNGS from RNA and DNA to identify potential pathogens and also targeted sequencing of viruses using hybrid capture. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects, 3 of whom had no clinical diagnosis by routine workup. Among subjects diagnosed with infection by serology and/or peripheral samples, we demonstrated the utility of mNGS to detect pathogen nucleic acid in CSF, importantly for the Ixodes scapularis tick-borne pathogens Powassan virus, Borrelia burgdorferi, and Anaplasma phagocytophilum. We also evaluated two methods to enhance the detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed the detection of varicella-zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with efficacy similar to that of pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. IMPORTANCE Meningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40 to 60% of people with meningitis or encephalitis have no clear cause of CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 prospectively enrolled patients with known (n = 44) or suspected (n = 24) CNS viral infection from a single center in New England and evaluated enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become integrated into the diagnostic toolkit for CNS infections.

The combination therapy of the Artemisinin-derivative Artemether (ART) with Lumefantrine (LM) (Coartem®) is an important malaria treatment regimen in many endemic countries. Resistance to Artemisinin has already been reported, and it is feared that LM resistance (LMR) could also evolve quickly. Therefore molecular markers which can be used to track Coartem® efficacy are urgently needed. Often, stable resistance arises from initial, unstable phenotypes that can be identified in vitro. Here we have used the Plasmodium falciparum multidrug resistant reference strain V1S to induce LMR in vitro by culturing the parasite under continuous drug pressure for 16 months. The initial IC(50) (inhibitory concentration that kills 50% of the parasite population) was 24 nM. The resulting resistant strain V1S(LM), obtained after culture for an estimated 166 cycles under LM pressure, grew steadily in 378 nM of LM, corresponding to 15 times the IC(50) of the parental strain. However, after two weeks of culturing V1S(LM) in drug-free medium, the IC(50) returned to that of the initial, parental strain V1S. This transient drug tolerance was associated with major changes in gene expression profiles: using the PFSANGER Affymetrix custom array, we identified 184 differentially expressed genes in V1S(LM). Among those are 18 known and putative transporters including the multidrug resistance gene 1 (pfmdr1), the multidrug resistance associated protein and the V-type H+ pumping pyrophosphatase 2 (pfvp2) as well as genes associated with fatty acid metabolism. In addition we detected a clear selective advantage provided by two genomic loci in parasites grown under LM drug pressure, suggesting that all, or some of those genes contribute to development of LM tolerance--they may prove useful as molecular markers to monitor P. falciparum LM susceptibility.