Dorsal root ganglion toxicity after AAV intra-CSF delivery of a RNAi expression construct into non-human primates and mice.

Dorsal root ganglion (DRG) toxicity has been consistently reported as a potential safety concern after delivery of adeno-associated viruses (AAVs) containing gene-replacement vectors but has yet to be reported for RNAi-based vectors. Here, we report DRG toxicity after AAV intra-CSF delivery of an RNAi expression construct-artificial microRNA targeting superoxide dismutase 1 (SOD1)-in non-human primates (NHPs) and provide evidence that this can be recapitulated within mice. Histopathology evaluation showed that NHPs and mice develop DRG toxicity after AAV delivery, including DRG neuron degeneration and necrosis and nerve-fiber degeneration that were associated with increases in cerebrospinal fluid (CSF) and serum phosphorylated neurofilament heavy chain (pNF-H).

scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing.

Background: Single-cell RNA sequencing is a state-of-the-art technology to understand gene expression in complex tissues. With the growing amount of data being generated, the standardization and automation of data analysis are critical to generating hypotheses and discovering biological insights.

Results: Here, we present scRNASequest, a semi-automated single-cell RNA-seq (scRNA-seq) data analysis workflow which allows (1) preprocessing from raw UMI count data, (2) harmonization by one or multiple methods, (3) reference-dataset-based cell type label transfer and embedding projection, (4) multi-sample, multi-condition single-cell level differential gene expression analysis, and (5) seamless integration with cellxgene VIP for visualization and with CellDepot for data hosting and sharing by generating compatible h5ad files.

RNASequest: An End-to-End Reproducible RNAseq Data Analysis and Publishing Framework.

We present RNASequest, a customizable RNA sequencing (RNAseq) analysis, app management, and result publishing framework. Its three-in-one RNAseq data analysis ecosystem consists of (1) a reproducible, configurable expression analysis (EA) module, (2) multi-faceted result presentation in R Shiny, a Bookdown document and an online slide deck, and (3) a centralized data management system. In principle, following up our well-received omics data visualization tool Quickomics, RNASequest automates the differential gene expression analysis step, eases statistical model design by built-in covariates testing module, and further provides a web-based tool, ShinyOne, to manage apps powered by Quickomics and reports generated by running the pipeline on multiple projects in one place.

Characterizing the composition of iPSC derived cells from bulk transcriptomics data with CellMap.

Induced pluripotent stem cell (iPSC) derived cell types are increasingly employed as in vitro model systems for drug discovery. For these studies to be meaningful, it is important to understand the reproducibility of the iPSC-derived cultures and their similarity to equivalent endogenous cell types. Single-cell and single-nucleus RNA sequencing (RNA-seq) are useful to gain such understanding, but they are expensive and time consuming, while bulk RNA-seq data can be generated quicker and at lower cost.

Plasma-Based Measurements of Tumor Heterogeneity Correlate with Clinical Outcomes in Metastatic Colorectal Cancer.

Sequencing circulating tumor DNA (ctDNA) from liquid biopsies may better assess tumor heterogeneity than limited sampling of tumor tissue. Here, we explore ctDNA-based heterogeneity and its correlation with treatment outcome in STEAM, which assessed efficacy and safety of concurrent and sequential FOLFOXIRI-bevacizumab (BEV) vs. FOLFOX-BEV for first-line treatment of metastatic colorectal cancer.

OmicsView: Omics data analysis through interactive visual analytics.

With advances in NGS technologies, transcriptional profiling of human tissue across many diseases is becoming more routine, leading to the generation of petabytes of data deposited in public repositories. There is a need for bench scientists with little computational expertise to be able to access and mine this data to understand disease pathology, identify robust biomarkers of disease and the effect of interventions ( or ). To this end we release an open source analytics and visualization platform for expression data called OmicsView, http://omicsview.

Next-generation Bruton's tyrosine kinase inhibitor BIIB091 selectively and potently inhibits B cell and Fc receptor signaling and downstream functions in B cells and myeloid cells.

Objectives: Bruton's tyrosine kinase (BTK) plays a non-redundant signaling role downstream of the B-cell receptor (BCR) in B cells and the receptors for the Fc region of immunoglobulins (FcR) in myeloid cells. Here, we characterise BIIB091, a novel, potent, selective and reversible small-molecule inhibitor of BTK.

Methods: BIIB091 was evaluated and in preclinical models and in phase 1 clinical trial.

Benchmarking and optimization of a high-throughput sequencing based method for transgene sequence variant analysis in biotherapeutic cell line development.

In recent years, High-Throughput Sequencing (HTS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols.

Quickomics: exploring omics data in an intuitive, interactive and informative manner.

Summary: We developed Quickomics, a feature-rich R Shiny-powered tool to enable biologists to fully explore complex omics statistical analysis results and perform advanced analysis in an easy-to-use interactive interface. It covers a broad range of secondary and tertiary analytical tasks after primary analysis of omics data is completed. Each functional module is equipped with customizable options and generates both interactive and publication-ready plots to uncover biological insights from data.

Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology.

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.

Two Distinct Mechanisms of Inhibition of LpxA Acyltransferase Essential for Lipopolysaccharide Biosynthesis.

The lipopolysaccharide biosynthesis pathway is considered an attractive drug target against the rising threat of multi-drug-resistant Gram-negative bacteria. Here, we report two novel small-molecule inhibitors (compounds and ) of the acyltransferase LpxA, the first enzyme in the lipopolysaccharide biosynthesis pathway. We show genetically that the antibacterial activities of the compounds against efflux-deficient are mediated by LpxA inhibition.

Interplay of Klebsiella pneumoniae and Mutations Leads to LpxC Inhibitor-Dependent Growth Resulting from Loss of Membrane Homeostasis.

Tight coordination of inner and outer membrane biosynthesis is very important in Gram-negative bacteria. Biosynthesis of the lipid A moiety of lipopolysaccharide, which comprises the outer leaflet of the outer membrane has garnered interest for Gram-negative antibacterial discovery. In particular, several potent inhibitors of LpxC (the first committed step of the lipid A pathway) are described.

Simultaneous Viral Exposure and Protection from Neanderthal Introgression.

In this issue, Enard and Petrov present intriguing results on the possibility of genetic traces left behind in our genomes from adaptation to past viral epidemics that may have been initiated by interaction with Neanderthal archaic hominins. The work highlights how powerful infectious agents can act as a selective force to shape our genetic makeup.

Mode of Action of the Monobactam LYS228 and Mechanisms Decreasing Susceptibility in Escherichia coli and Klebsiella pneumoniae.

The monobactam scaffold is attractive for the development of new agents to treat infections caused by drug-resistant Gram-negative bacteria because it is stable to metallo-β-lactamases (MBLs). However, the clinically used monobactam aztreonam lacks stability to serine β-lactamases (SBLs) that are often coexpressed with MBLs. LYS228 is stable to MBLs and most SBLs.

Leveraging Multiple Populations across Time Helps Define Accurate Models of Human Evolution: A Reanalysis of the Lactase Persistence Adaptation.

Access to a geographically diverse set of modern human samples from the present time and from ancient remains, combined with archaic hominin samples, provides an unprecedented level of resolution to study both human history and adaptation. The amount and quality of ancient human data continue to improve and enable tracking the trajectory of genetic variation over time. These data have the potential to help us redefine or generate new hypotheses of how human evolution occurred and to revise previous conjectures.

Correlation of BK Virus Neutralizing Serostatus With the Incidence of BK Viremia in Kidney Transplant Recipients.

Background: BK virus (BKV)-associated nephropathy is the second leading cause of graft loss in kidney transplant recipients. Due to the high prevalence of persistent infection with BKV in the general population, it is possible that either the transplant recipient or donor may act as the source of virus resulting in viruria and viremia. Although several studies suggest a correlation between donor-recipient serostatus and the development of BK viremia, specific risk factors for BKV-related complications in the transplant setting remain to be established.

High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications.

Archaic inheritance: supporting high-altitude life in Tibet.

The Tibetan Plateau, often called the roof of the world, sits at an average altitude exceeding 4,500 m. Because of its extreme altitude, the Plateau is one of the harshest human-inhabited environments in the world. This, however, did not impede human colonization, and the Tibetan people have made the Tibetan Plateau their home for many generations.

Discovering anti-platelet drug combinations with an integrated model of activator-inhibitor relationships, activator-activator synergies and inhibitor-inhibitor synergies.

Identifying effective therapeutic drug combinations that modulate complex signaling pathways in platelets is central to the advancement of effective anti-thrombotic therapies. However, there is no systems model of the platelet that predicts responses to different inhibitor combinations. We developed an approach which goes beyond current inhibitor-inhibitor combination screening to efficiently consider other signaling aspects that may give insights into the behaviour of the platelet as a system.

Alternate virtual populations elucidate the type I interferon signature predictive of the response to rituximab in rheumatoid arthritis.

Background: Mechanistic biosimulation can be used in drug development to form testable hypotheses, develop predictions of efficacy before clinical trial results are available, and elucidate clinical response to therapy. However, there is a lack of tools to simultaneously (1) calibrate the prevalence of mechanistically distinct, large sets of virtual patients so their simulated responses statistically match phenotypic variability reported in published clinical trial outcomes, and (2) explore alternate hypotheses of those prevalence weightings to reflect underlying uncertainty in population biology. Here, we report the development of an algorithm, MAPEL (Mechanistic Axes Population Ensemble Linkage), which utilizes a mechanistically-based weighting method to match clinical trial statistics.

Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs.

Background: Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks.

Results: We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes.

Cattle demographic history modelled from autosomal sequence variation.

The phylogeography of cattle genetic variants has been extensively described and has informed the history of domestication. However, there remains a dearth of demographic models inferred from such data. Here, we describe sequence diversity at 37 000 bp sampled from 17 genes in cattle from Africa, Europe and India.

Discovery of small molecule inhibitors of protein-protein interactions using combined ligand and target score normalization.

Docking experiments of multiple compounds typically focus on a single protein. However, other targets provide information about relative binding efficiencies that is otherwise lacking. We developed a docking strategy that normalized results in both the ligand and target dimensions.

Variational method for estimating the rate of convergence of Markov-chain Monte Carlo algorithms.

We demonstrate the use of a variational method to determine a quantitative lower bound on the rate of convergence of Markov chain Monte Carlo (MCMC) algorithms as a function of the target density and proposal density. The bound relies on approximating the second largest eigenvalue in the spectrum of the MCMC operator using a variational principle and the approach is applicable to problems with continuous state spaces. We apply the method to one dimensional examples with Gaussian and quartic target densities, and we contrast the performance of the random walk Metropolis-Hastings algorithm with a "smart" variant that incorporates gradient information into the trial moves, a generalization of the Metropolis adjusted Langevin algorithm.