Ryan J. King

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.

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.

Abstract Pancreatic adenocarcinoma is moderately responsive to gemcitabine-based chemotherapy, the most widely used single-agent therapy for pancreatic cancer. Although the prognosis in pancreatic cancer remains grim in part due to poor response to therapy, previous attempts at identifying and targeting the resistance mechanisms have not been very successful. By leveraging The Cancer Genome Atlas dataset, we identified lipid metabolism as the metabolic pathway that most significantly correlated with poor gemcitabine response in pancreatic cancer patients. Furthermore, we investigated the relationship between alterations in lipogenesis pathway and gemcitabine resistance by utilizing tissues from the genetically engineered mouse model and human pancreatic cancer patients. We observed a significant increase in fatty acid synthase (FASN) expression with increasing disease progression in spontaneous pancreatic cancer mouse model, and a correlation of high FASN expression with poor survival in patients and poor gemcitabine responsiveness in cell lines. We observed a synergistic effect of FASN inhibitors with gemcitabine in pancreatic cancer cells in culture and orthotopic implantation models. Combination of gemcitabine and the FASN inhibitor orlistat significantly diminished stemness, in part due to induction of endoplasmic reticulum (ER) stress that resulted in apoptosis. Moreover, direct induction of ER stress with thapsigargin caused a similar decrease in stemness and showed synergistic activity with gemcitabine. Our in vivo studies with orthotopic implantation models demonstrated a robust increase in gemcitabine responsiveness upon inhibition of fatty acid biosynthesis with orlistat. Altogether, we demonstrate that fatty acid biosynthesis pathway manipulation can help overcome the gemcitabine resistance in pancreatic cancer by regulating ER stress and stemness. Cancer Res; 77(20); 5503–17. ©2017 AACR.