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Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity, and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments, and proficiency testing on standardized cell line–derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas below this limit detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false-negatives) were more common than erroneous candidates (false-positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best-practice guidelines and provides a resource for precision oncology., Editorial summary: Reliable detection of mutations below 0.5% variant allele frequency remains a key challenge for circulating tumor DNA sequencing assays.

Background Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. Results In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5–100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. Conclusion These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.

SUMMARYThe primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next generation sequencing (NGS) method that enables more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. This advancement was enabled by designing a synthetic internal standard spike-in for each actionable mutation target, suitable for use in NGS following hybrid-capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position, in each sample. True positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Summary The primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next-generation sequencing (NGS) method that will enable more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. To accomplish this, a synthetic internal standard spike-in was designed for each actionable mutation target, suitable for use in NGS following hybrid capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position in each sample. True-positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.

Fluoroquinolones (FQs) are effective second-line drugs for treating antibiotic-resistant tuberculosis (TB) and are being considered for use as first-line agents. Because FQs are used to treat a range of infections, in a setting of undiagnosed TB, there is potential to select for drug-resistant Mycobacterium tuberculosis mutants during FQ-based treatment of other infections, including pneumonia. Here we present a detailed characterization of ofloxacin-resistant M. tuberculosis samples isolated directly from patients in Taiwan, which demonstrates that selection for FQ resistance can occur within patients who have not received FQs for the treatment of TB. Several of these samples showed no mutations in gyrA or gyrB based on PCR-based molecular assays, but genome-wide next-generation sequencing (NGS) revealed minority populations of gyrA and/or gyrB mutants. In other samples with PCR-detectable gyrA mutations, NGS revealed subpopulations containing alternative resistance-associated genotypes. Isolation of individual clones from these apparently heterogeneous samples confirmed the presence of the minority drug-resistant variants suggested by the NGS data. Further NGS of these purified clones established evolutionary links between FQ-sensitive and -resistant clones derived from the same patient, suggesting de novo emergence of FQ-resistant TB. Importantly, most of these samples were isolated from patients without a history of FQ treatment for TB. Thus, selective pressure applied by FQ monotherapy in the setting of undiagnosed TB infection appears to be able to drive the full or partial emergence of FQ-resistant M. tuberculosis , which has the potential to confound diagnostic tests for antibiotic susceptibility and limit the effectiveness of FQs in TB treatment.

The ability to simultaneously characterize the bacterial and host expression programs during infection would facilitate a comprehensive understanding of pathogen-host interactions. Although RNA sequencing (RNA-seq) has greatly advanced our ability to study the transcriptomes of prokaryotes and eukaryotes separately, limitations in existing protocols for the generation and analysis of RNA-seq data have hindered simultaneous profiling of host and bacterial pathogen transcripts from the same sample. Here we provide a detailed protocol for simultaneous analysis of host and bacterial transcripts by RNA-seq. Importantly, this protocol details the steps required for efficient host and bacteria lysis, barcoding of samples, technical advances in sample preparation for low-yield sample inputs and a computational pipeline for analysis of both mammalian and microbial reads from mixed host-pathogen RNA-seq data. Sample preparation takes 3 d from cultured cells to pooled libraries. Data analysis takes an additional day. Compared with previous methods, the protocol detailed here provides a sensitive, facile and generalizable approach that is suitable for large-scale studies and will enable the field to obtain in-depth analysis of host-pathogen interactions in infection models.

Summary Successful treatment of Mycobacterium tuberculosis infection typically requires a complex regimen administered over at least 6 months. Interestingly, many of the antibiotics used to treat M. tuberculosis are prodrugs that require intracellular activation. Here, we describe three small molecules, active against both replicating and non-replicating M. tuberculosis , that require activation by Baeyer-Villiger monooxygenases (BVMOs). Two molecules require BVMO EthA (Rv3854c) for activation and the third molecule requires the BVMO MymA (Rv3083). While EthA is known to activate the antitubercular drug ethionamide, this is the first description of MymA as an activating enzyme of a prodrug. Furthermore, we found that MymA also plays a role in activating ethionamide, with loss of MymA function resulting in ethionamide-resistant M. tuberculosis . These findings suggest overlap in function and specificity of the BVMOs in M. tuberculosis .

During Mycobacterium tuberculosis infection, a population of bacteria likely becomes refractory to antibiotic killing in the absence of genotypic resistance, making treatment challenging. We describe an in vitro model capable of yielding a phenotypically antibiotic-tolerant subpopulation of cells, often called persisters, within populations of Mycobacterium smegmatis and M. tuberculosis . We find that persisters are distinct from the larger antibiotic-susceptible population, as a small drop in dissolved oxygen (DO) saturation (20%) allows for their survival in the face of bactericidal antibiotics. In contrast, if high levels of DO are maintained, all cells succumb, sterilizing the culture. With increasing evidence that bactericidal antibiotics induce cell death through the production of reactive oxygen species (ROS), we hypothesized that the drop in DO decreases the concentration of ROS, thereby facilitating persister survival, and maintenance of high DO yields sufficient ROS to kill persisters. Consistent with this hypothesis, the hydroxyl-radical scavenger thiourea, when added to M. smegmatis cultures maintained at high DO levels, rescues the persister population. Conversely, the antibiotic clofazimine, which increases ROS via an NADH-dependent redox cycling pathway, successfully eradicates the persister population. Recent work suggests that environmentally induced antibiotic tolerance of bulk populations may result from enhanced antioxidant capabilities. We now show that the small persister subpopulation within a larger antibiotic-susceptible population also shows differential susceptibility to antibiotic-induced hydroxyl radicals. Furthermore, we show that stimulating ROS production can eradicate persisters, thus providing a potential strategy to managing persistent infections.

Encounters between immune cells and invading bacteria ultimately determine the course of infection. These interactions are usually measured in populations of cells, masking cell-to-cell variation that may be important for infection outcome. To characterize the gene expression variation that underlies distinct infection outcomes and monitor infection phenotypes, we developed an experimental system that combines single-cell RNA-seq with fluorescent markers. Probing the responses of individual macrophages to invading Salmonella, we find that variation between individual infected host cells is determined by the heterogeneous activity of bacterial factors in individual infecting bacteria. We illustrate how variable PhoPQ activity in the population of invading bacteria drives variable host type I IFN responses by modifying LPS in a subset of bacteria. This work demonstrates a causative link between host and bacterial variability, with cell-to-cell variation between different bacteria being sufficient to drive radically different host immune responses. This co-variation has implications for host-pathogen dynamics in vivo., National Institutes of Health (U.S.) (grant HG002295), National Institutes of Health (U.S.) (grant DK043351), National Institutes of Health (U.S.) (grant NIH U19AI109725), National Institutes of Health (U.S.) (grant NIH F32 HD075541-02), National Human Genome Research Institute (U.S.) ((CEGS) Center of Cell Circuits (P50 HG006193)), Klarman Cell Observatory

Current analytical protein methods show phosphorylation to be the most ubiquitous, evolutionary conserved post-translational modification Post-Translational Modification (PTM). The reversible and transient nature of protein phosphorylation allows signal transduction pathways to carry out diverse cellular functions. From bacteria to humans, phosphorylation serves to modify protein function by altering protein stability, cellular location, substrate affinity, complex formation, and activity; thus allowing essential events such as cell cycle and growth to occur at precise times and locations. Phosphorylation controls a variety of events at many biological levels including: housekeeping activities controlled by single cells such as DNA transcription, cell-cycle regulation, and energy metabolism; and cellular processes that involve signaling between cells or the environment including such as neuronal migration and immune system recognition. This review summarizes state-of-the-art proteomics technologies available to study phosphorylation in biological systems. We highlight the tremendous steps the field has made in the last 5 years which allow quantitative global analyses while pointing out caveats in experimentation.