Enforced Bcl-2 Expression Inhibits Antigen-mediated Clonal Elimination of Peripheral B Cells in an Antigen Dose–dependent Manner and Promotes Receptor Editing in Autoreactive, Immature B Cells

The mechanisms that establish immune tolerance in immature and mature B cells appear to be distinct. Membrane-bound autoantigen is thought to induce developmental arrest and receptor editing in immature B cells, whereas mature B cells have shortened lifespans when exposed to the same stimulus. In this study, we used Eμ–bcl-2-22 transgenic (Tg) mice to test the prediction that enforced expression of the Bcl-2 apoptotic inhibitor in B cells would rescue mature, but not immature, B cells from tolerance induction. To monitor tolerance to the natural membrane autoantigen H-2Kb, we bred 3–83μδ (anti-Kk,b) Ig Tg mice to H-2b mice or to mice expressing transgene-driven Kb in the periphery. In 3–83μδ/bcl-2 Tg mice, deletion of autoreactive B cells induced by peripheral Kb antigen expression in the liver (MT-Kb Tg) or epithelia (KerIV-Kb Tg), was partly or completely inhibited, respectively. Furthermore, Bcl-2 protected peritoneal B-2 B cells from deletion mediated by acute antigen exposure, but this protection could be overcome by higher antigen dose. In contrast to its ability to block peripheral self-tolerance, Bcl-2 overexpression failed to inhibit central tolerance induced by bone marrow antigen expression, but instead, enhanced the receptor editing process. These studies indicate that apoptosis plays distinct roles in central and peripheral B cell tolerance

A Case Study Competition among Methods for Analyzing Large Spatial Data

The Gaussian process is an indispensable tool for spatial data analysts. The onset of the "big data" era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alternatives to the full Gaussian process that are more amenable to handling big spatial data have been proposed. These modern methods often exploit low rank structures and/or multi-core and multi-threaded computing environments to facilitate computation. This study provides, first, an introductory overview of several methods for analyzing large spatial data. Second, this study describes the results of a predictive competition among the described methods as implemented by different groups with strong expertise in the methodology. Specifically, each research group was provided with two training datasets (one simulated and one observed) along with a set of prediction locations. Each group then wrote their own implementation of their method to produce predictions at the given location and each which was subsequently run on a common computing environment. The methods were then compared in terms of various predictive diagnostics. Supplementary materials regarding implementation details of the methods and code are available for this article online

Selection platforms for directed evolution in synthetic biology

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules – gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function – be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code