MIDAS2: Metagenomic Intra-species Diversity Analysis System.

SUMMARY: The Metagenomic Intra-Species Diversity Analysis System (MIDAS) is a scalable metagenomic pipeline that identifies single nucleotide variants (SNVs) and gene copy number variants in microbial populations. Here, we present MIDAS2, which addresses the computational challenges presented by increasingly large reference genome databases, while adding functionality for building custom databases and leveraging paired-end reads to improve SNV accuracy. This fast and scalable reengineering of the MIDAS pipeline enables thousands of metagenomic samples to be efficiently genotyped. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/czbiohub/MIDAS2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

FLASH: a next-generation CRISPR diagnostic for multiplexed detection of antimicrobial resistance sequences.

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

Integration of Genomic Sequencing Drives Therapeutic Targeting of PDGFRA in T-Cell Acute Lymphoblastic Leukemia/Lymphoblastic Lymphoma.

PURPOSE: Patients with relapsed or refractory T-cell acute lymphoblastic leukemia (T-ALL) or lymphoblastic lymphoma (T-LBL) have limited therapeutic options. Clinical use of genomic profiling provides an opportunity to identify targetable alterations to inform therapy. EXPERIMENTAL DESIGN: We describe a cohort of 14 pediatric patients with relapsed or refractory T-ALL enrolled on the Leukemia Precision-based Therapy (LEAP) Consortium trial (NCT02670525) and a patient with T-LBL, discovering alterations in platelet-derived growth factor receptor-α (PDGFRA) in 3 of these patients. We identified a novel mutation in PDGFRA, p.D842N, and used an integrated structural modeling and molecular biology approach to characterize mutations at D842 to guide therapeutic targeting. We conducted a preclinical study of avapritinib in a mouse patient-derived xenograft (PDX) model of FIP1L1-PDGFRA and PDGFRA p.D842N leukemia. RESULTS: Two patients with T-ALL in the LEAP cohort (14%) had targetable genomic alterations affecting PDGFRA, a FIP1-like 1 protein/PDGFRA (FIP1L1-PDGFRA) fusion and a novel mutation in PDGFRA, p.D842N. The D842N mutation resulted in PDGFRA activation and sensitivity to tested PDGFRA inhibitors. In a T-ALL PDX model, avapritinib treatment led to decreased leukemia burden, significantly prolonged survival, and even cured a subset of mice. Avapritinib treatment was well tolerated and yielded clinical benefit in a patient with refractory T-ALL. CONCLUSIONS: Refractory T-ALL has not been fully characterized. Alterations in PDGFRA or other targetable kinases may inform therapy for patients with refractory T-ALL who otherwise have limited treatment options. Clinical genomic profiling, in real time, is needed for fully informed therapeutic decision making.

Fast and accurate metagenotyping of the human gut microbiome with GT-Pro.

Single nucleotide polymorphisms (SNPs) in metagenomics are used to quantify population structure, track strains and identify genetic determinants of microbial phenotypes. However, existing alignment-based approaches for metagenomic SNP detection require high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. To address these issues, we developed the GenoTyper for Prokaryotes (GT-Pro), a suite of methods to catalog SNPs from genomes and use unique k-mers to rapidly genotype these SNPs from metagenomes. Compared to methods that use read alignment, GT-Pro is more accurate and two orders of magnitude faster. Using high-quality genomes, we constructed a catalog of 104 million SNPs in 909 human gut species and used unique k-mers targeting this catalog to characterize the global population structure of gut microbes from 7,459 samples. GT-Pro enables fast and memory-efficient metagenotyping of millions of SNPs on a personal computer.

Targeting serine hydroxymethyltransferases 1 and 2 for T-cell acute lymphoblastic leukemia therapy.

Despite progress in the treatment of acute lymphoblastic leukemia (ALL), T-cell ALL (T-ALL) has limited treatment options, particularly in the setting of relapsed/refractory disease. Using an unbiased genome-scale CRISPR-Cas9 screen we sought to identify pathway dependencies for T-ALL which could be harnessed for therapy development. Disruption of the one-carbon folate, purine and pyrimidine pathways scored as the top metabolic pathways required for T-ALL proliferation. We used a recently developed inhibitor of SHMT1 and SHMT2, RZ-2994, to characterize the effect of inhibiting these enzymes of the one-carbon folate pathway in T-ALL and found that T-ALL cell lines were differentially sensitive to RZ-2994, with the drug inducing a S/G2 cell cycle arrest. The effects of SHMT1/2 inhibition were rescued by formate supplementation. Loss of both SHMT1 and SHMT2 was necessary for impaired growth and cell cycle arrest, with suppression of both SHMT1 and SHMT2 inhibiting leukemia progression in vivo. RZ-2994 also decreased leukemia burden in vivo and remained effective in the setting of methotrexate resistance in vitro. This study highlights the significance of the one-carbon folate pathway in T-ALL and supports further development of SHMT inhibitors for treatment of T-ALL and other cancers.

Percutaneous Closure of Ventricular Septal Defects in 116 Patients: Experience with different devices.

OBJECTIVES: This study aimed to review the experience with percutaneous closure of ventricular septal defects (VSDs) at the National Heart Center (NHC) in Muscat, Oman. METHODS: This retrospective study was conducted from November 2008 to December 2017. Patients' electronic medical records were reviewed to identify their clinical, imaging and interventional data before and after the procedure and on the last follow-up. RESULTS: A total of 116 patients, the majority of which were female (58%), underwent 118 percutaneous procedures for VSD closure at a median age of 3.54 years (range: 0.25-33 years) and a median weight of 12 kg (range: 3.5-78 kg). The mean diameter of the VSDs as determined by transoesophageal echocardiogram was 5.6 ± 1.9 mm (n = 105). The commonest type of VSD was perimembranous (n = 75, 63.5%). Devices were successfully placed during 111 (94.1%) procedures in 109 (94.0%) patients, with the commonest device being a Amplatzer™ duct occluder I (St. Jude Medical, Little Canada, Minnesota, USA; n = 39, 35.1%). There was no mortality. Early major cardiac complications occurred in six patients (5.5%) with device embolisation being the commonest (n = 4, 3.7%). The median follow-up period was 19 months (range: 1-84 months) in 89 (81.7%) of the patients. One patient (0.9%) required a permanent pacemaker for a complete heart block. CONCLUSION: This study has demonstrated a good rate of VSD closure with low morbidity and no mortality using the percutaneous approach with different devices. Long-term follow-up is needed to specifically evaluate the function of adjacent structures and the long-term effects on conduction systems.

IDseq-An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource-limited environments. FINDINGS: We present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline, which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics that are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2. CONCLUSION: The IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.

Metagenomic next-generation sequencing of samples from pediatric febrile illness in Tororo, Uganda.

Febrile illness is a major burden in African children, and non-malarial causes of fever are uncertain. In this retrospective exploratory study, we used metagenomic next-generation sequencing (mNGS) to evaluate serum, nasopharyngeal, and stool specimens from 94 children (aged 2-54 months) with febrile illness admitted to Tororo District Hospital, Uganda. The most common microbes identified were Plasmodium falciparum (51.1% of samples) and parvovirus B19 (4.4%) from serum; human rhinoviruses A and C (40%), respiratory syncytial virus (10%), and human herpesvirus 5 (10%) from nasopharyngeal swabs; and rotavirus A (50% of those with diarrhea) from stool. We also report the near complete genome of a highly divergent orthobunyavirus, tentatively named Nyangole virus, identified from the serum of a child diagnosed with malaria and pneumonia, a Bwamba orthobunyavirus in the nasopharynx of a child with rash and sepsis, and the genomes of two novel human rhinovirus C species. In this retrospective exploratory study, mNGS identified multiple potential pathogens, including 3 new viral species, associated with fever in Ugandan children.

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

The burden of meningitis in low-and-middle-income countries remains significant, but the infectious causes remain largely unknown, impeding institution of evidence-based treatment and prevention decisions. We conducted a validation and application study of unbiased metagenomic next-generation sequencing (mNGS) to elucidate etiologies of meningitis in Bangladesh. This RNA mNGS study was performed on cerebrospinal fluid (CSF) specimens from patients admitted in the largest pediatric hospital, a World Health Organization sentinel site, with known neurologic infections (n = 36), with idiopathic meningitis (n = 25), and with no infection (n = 30), and six environmental samples, collected between 2012 and 2018. We used the IDseq bioinformatics pipeline and machine learning to identify potentially pathogenic microbes, which we then confirmed orthogonally and followed up through phone/home visits. In samples with known etiology and without infections, there was 83% concordance between mNGS and conventional testing. In idiopathic cases, mNGS identified a potential bacterial or viral etiology in 40%. There were three instances of neuroinvasive Chikungunya virus (CHIKV), whose genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause febrile illness in 2017. CHIKV-specific qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 (n = 472) revealed 17 additional CHIKV meningitis cases, exposing an unrecognized meningitis outbreak. Orthogonal molecular confirmation, case-based clinical data, and patient follow-up substantiated the findings. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis, conduct surveillance, and predict outbreaks. The improved patient- and population-level data can inform evidence-based policy decisions.IMPORTANCE Globally, there are an estimated 10.6 million cases of meningitis and 288,000 deaths every year, with the vast majority occurring in low- and middle-income countries. In addition, many survivors suffer from long-term neurological sequelae. Most laboratories assay only for common bacterial etiologies using culture and directed PCR, and the majority of meningitis cases lack microbiological diagnoses, impeding institution of evidence-based treatment and prevention strategies. We report here the results of a validation and application study of using unbiased metagenomic sequencing to determine etiologies of idiopathic (of unknown cause) cases. This included CSF from patients with known neurologic infections, with idiopathic meningitis, and without infection admitted in the largest children's hospital of Bangladesh and environmental samples. Using mNGS and machine learning, we identified and confirmed an etiology (viral or bacterial) in 40% of idiopathic cases. We detected three instances of Chikungunya virus (CHIKV) that were >99% identical to each other and to a strain previously recognized to cause systemic illness only in 2017. CHIKV qPCR of all remaining stored 472 CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital uncovered an unrecognized CHIKV meningitis outbreak. CSF mNGS can complement conventional diagnostic methods to identify etiologies of meningitis, and the improved patient- and population-level data can inform better policy decisions.