Immunization with a heat-killed preparation of the environmental bacterium Mycobacterium vaccae promotes stress resilience in mice.

The prevalence of inflammatory diseases is increasing in modern urban societies. Inflammation increases risk of stress-related pathology; consequently, immunoregulatory or antiinflammatory approaches may protect against negative stress-related outcomes. We show that stress disrupts the homeostatic relationship between the microbiota and the host, resulting in exaggerated inflammation. Repeated immunization with a heat-killed preparation of Mycobacterium vaccae, an immunoregulatory environmental microorganism, reduced subordinate, flight, and avoiding behavioral responses to a dominant aggressor in a murine model of chronic psychosocial stress when tested 1-2 wk following the final immunization. Furthermore, immunization with M. vaccae prevented stress-induced spontaneous colitis and, in stressed mice, induced anxiolytic or fear-reducing effects as measured on the elevated plus-maze, despite stress-induced gut microbiota changes characteristic of gut infection and colitis. Immunization with M. vaccae also prevented stress-induced aggravation of colitis in a model of inflammatory bowel disease. Depletion of regulatory T cells negated protective effects of immunization with M. vaccae on stress-induced colitis and anxiety-like or fear behaviors. These data provide a framework for developing microbiome- and immunoregulation-based strategies for prevention of stress-related pathologies.

Genome-wide mapping of mutations at single-nucleotide resolution for protein, metabolic and genome engineering.

Improvements in DNA synthesis and sequencing have underpinned comprehensive assessment of gene function in bacteria and eukaryotes. Genome-wide analyses require high-throughput methods to generate mutations and analyze their phenotypes, but approaches to date have been unable to efficiently link the effects of mutations in coding regions or promoter elements in a highly parallel fashion. We report that CRISPR-Cas9 gene editing in combination with massively parallel oligomer synthesis can enable trackable editing on a genome-wide scale. Our method, CRISPR-enabled trackable genome engineering (CREATE), links each guide RNA to homologous repair cassettes that both edit loci and function as barcodes to track genotype-phenotype relationships. We apply CREATE to site saturation mutagenesis for protein engineering, reconstruction of adaptive laboratory evolution experiments, and identification of stress tolerance and antibiotic resistance genes in bacteria. We provide preliminary evidence that CREATE will work in yeast. We also provide a webtool to design multiplex CREATE libraries.

Quantifying complexity in metabolic engineering using the LASER database.

We previously introduced the LASER database (Learning Assisted Strain EngineeRing, https://bitbucket.org/jdwinkler/laser_release) (Winkler et al. 2015) to serve as a platform for understanding past and present metabolic engineering practices. Over the past year, LASER has been expanded by 50% to include over 600 engineered strains from 450 papers, including their growth conditions, genetic modifications, and other information in an easily searchable format. Here, we present the results of our efforts to use LASER as a means for defining the complexity of a metabolic engineering "design". We evaluate two complexity metrics based on the concepts of construction difficulty and novelty. No correlation is observed between expected product yield and complexity, allowing minimization of complexity without a performance trade-off. We envision the use of such complexity metrics to filter and prioritize designs prior to implementation of metabolic engineering efforts, thereby potentially reducing the time, labor, and expenses of large-scale projects. Possible future developments based on an expanding LASER database are then discussed.

The Resistome: A Comprehensive Database of Escherichia coli Resistance Phenotypes.

The microbial ability to resist stressful environmental conditions and chemical inhibitors is of great industrial and medical interest. Much of the data related to mutation-based stress resistance, however, is scattered through the academic literature, making it difficult to apply systematic analyses to this wealth of information. To address this issue, we introduce the Resistome database: a literature-curated collection of Escherichia coli genotypes-phenotypes containing over 5,000 mutants that resist hundreds of compounds and environmental conditions. We use the Resistome to understand our current state of knowledge regarding resistance and to detect potential synergy or antagonism between resistance phenotypes. Our data set represents one of the most comprehensive collections of genomic data related to resistance currently available. Future development will focus on the construction of a combined genomic-transcriptomic-proteomic framework for understanding E. coli's resistance biology. The Resistome can be downloaded at https://bitbucket.org/jdwinkler/resistome_release/overview .

A Web Interface for Codon Compression.

Saturation mutagenesis is widely used in protein engineering and other experiments. A common practice is to utilize the single degenerate codon NNK. However, this approach suffers from amino acid bias and the presence of a stop codon and of the wild type amino acid. These extra features needlessly increase library size and consequently downstream screening load. Recently, we developed the DYNAMCC algorithms for codon compression that find the minimal set of degenerate codons, covering any defined set of amino acids, with no off-target codons and with redundancy control. Additionally, we experimentally demonstrated the advantages of this approach over the standard NNK method. While the code is freely available from our Web site, we have now made this method more accessible to a broader audience without any computational background by building a user-friendly web-based interface for those algorithms. The Web site can be accessed through: www.dynamcc.com .

Rapid and Efficient One-Step Metabolic Pathway Integration in E. coli.

Methods for importing heterologous genes into genetically tractable hosts are among the most desired tools of synthetic biology. Easy plug-and-play construction methods to rapidly test genes and pathways stably in the host genome would expedite synthetic biology and metabolic engineering applications. Here, we describe a CRISPR-based strategy that allows highly efficient, single step integration of large pathways in Escherichia coli. This strategy allows high efficiency integration in a broad range of homology arm sizes and genomic positions, with efficiencies ranging from 70 to 100% in 7 distinct loci. To demonstrate the large size capability, we integrated a 10 kb construct to implement isobutanol production in a single day. The ability to efficiently integrate entire metabolic pathways in a rapid and markerless manner will facilitate testing and engineering of novel pathways using the E. coli genome as a stable testing platform.

The LASER database: Formalizing design rules for metabolic engineering.

The ability of metabolic engineers to conceptualize, implement, and evaluate strain designs has dramatically increased in the last decade. Unlike other engineering fields, no centralized, open-access, and easily searched repository exists for cataloging these designs and the lessons learned from their construction and evaluation. To address this issue, we have developed a repository for metabolic engineering strain designs, known as LASER (Learning Assisted Strain EngineeRing, laser.colorado.edu) and a formal standard for disseminating designs to metabolic engineers. Curation of every available genetically-defined E. coli and S. cerevisiae strain from 310 metabolic engineering papers published over the last 21 years yields a total of 417 designs containing a total of 2661 genetic modifications. This collection has been deposited in LASER and represents the known bibliome of genetically defined and tested metabolic engineering designs in the academic literature. Properties of LASER designs and the analysis pipeline are examined to provide insight into LASER capabilities. Several future research directions utilizing LASER capabilities are discussed to highlight the potential of the LASER database for metabolic engineering.

The emergence of commodity-scale genetic manipulation.

Since the 1970s technological advancements in the fields of synthetic biology and metabolic engineering have led to a dramatic reduction in both time and cost required for generating genomic mutations in a variety of organisms. The union of genomic editing machinery, DNA inkjet printers, and bioinformatics algorithms allows engineers to design a library of thousands of unique oligos as well as build and test these designs on a ∼2 months time-scale and at a cost of roughly ∼0.3 cents per base pair. The implications of these capabilities for a variety of fields are far-reaching, with potential impacts in defense, agricultural, human health, and environmental research. The explosion of synthetic biology applications over the past two decades have led many to draw parallels between biological engineering and the computer sciences. In this review, we highlight some important parallels between these fields and emphasize the importance of engineering design strategies.

Complex systems in metabolic engineering.

Metabolic engineers manipulate intricate biological networks to build efficient biological machines. The inherent complexity of this task, derived from the extensive and often unknown interconnectivity between and within these networks, often prevents researchers from achieving desired performance. Other fields have developed methods to tackle the issue of complexity for their unique subset of engineering problems, but to date, there has not been extensive and comprehensive examination of how metabolic engineers use existing tools to ameliorate this effect on their own research projects. In this review, we examine how complexity affects engineering at the protein, pathway, and genome levels within an organism, and the tools for handling these issues to achieve high-performing strain designs. Quantitative complexity metrics and their applications to metabolic engineering versus traditional engineering fields are also discussed. We conclude by predicting how metabolic engineering practices may advance in light of an explicit consideration of design complexity.