Thomas J. Mansell

Ligand binding and allostery can emerge simultaneously.

A heterotropic allosteric effect involves an effector molecule that is distinct from the substrate or ligand of the protein. How heterotropic allostery originates is an unanswered question. We have previously created several heterotropic allosteric enzymes by recombining the genes for TEM1 β‐lactamase (BLA) and maltose binding protein (MBP) to create BLAs that are positively or negatively regulated by maltose. We show here that one of these engineered enzymes has ∼106 M−1 affinity for Zn2+, a property that neither of the parental proteins possesses. Furthermore, Zn2+ is a negative effector that noncompetitively switches off β‐lactam hydrolysis activity. Mutagenesis experiments indicate that the Zn2+‐binding site does not involve a histidine or a cysteine, which is atypical of natural Zn2+‐binding sites. These studies also implicate helices 1 and 12 of the BLA domain in allosteric signal propagation. These results support a model for the evolution of heterotropic allostery in which effector affinity and allosteric signaling emerge simultaneously.

Multiplexed tracking of combinatorial genomic mutations in engineered cell populations.

Multiplexed genome engineering approaches can be used to generate targeted genetic diversity in cell populations on laboratory timescales, but methods to track mutations and link them to phenotypes have been lacking. We present an approach for tracking combinatorial engineered libraries (TRACE) through the simultaneous mapping of millions of combinatorially engineered genomes at single-cell resolution. Distal genomic sites are assembled into individual DNA constructs that are compatible with next-generation sequencing strategies. We used TRACE to map growth selection dynamics for Escherichia coli combinatorial libraries created by recursive multiplex recombineering at a depth 104-fold greater than before. TRACE was used to identify genotype-to-phenotype correlations and to map the evolutionary trajectory of two individual combinatorial mutants in E. coli. Combinatorial mutations in the human ES2 ovarian carcinoma cell line were also assessed with TRACE. TRACE completes the combinatorial engineering cycle and enables more sophisticated approaches to genome engineering in both bacteria and eukaryotic cells than are currently possible.

A rapid protein folding assay for the bacterial periplasm

An array of genetic screens and selections has been developed for reporting protein folding and solubility in the cytoplasm of living cells. However, there are currently no analogous folding assays for the bacterial periplasm, despite the significance of this compartment for the expression of recombinant proteins, especially those requiring important posttranslational modifications (e.g., disulfide bond formation). Here, we describe an engineered genetic selection for monitoring protein folding in the periplasmic compartment of Escherichia coli cells. In this approach, target proteins are sandwiched between an N‐terminal signal recognition particle (SRP)‐dependent signal peptide and a C‐terminal selectable marker, TEM‐1 β‐lactamase. The resulting chimeras are localized to the periplasmic space via the cotranslational SRP pathway. Using a panel of native and heterologous proteins, we demonstrate that the folding efficiency of various target proteins correlates directly with in vivo β‐lactamase activity and thus resistance to ampicillin. We also show that this reporter is useful for the discovery of extrinsic periplasmic factors (e.g., chaperones) that affect protein folding and for obtaining folding‐enhanced proteins via directed evolution. Collectively, these data demonstrate that our periplasmic folding reporter is a powerful tool for screening and engineering protein folding in a manner that does not require any structural or functional information about the target protein.

A filamentous phage display system for N-linked glycoproteins

We have developed a filamentous phage display system for the detection of asparagine‐linked glycoproteins in Escherichia coli that carry a plasmid encoding the protein glycosylation locus (pgl) from Campylobacter jejuni. In our assay, fusion of target glycoproteins to the minor phage coat protein g3p results in the display of glycans on phage. The glyco‐epitope displayed on phage is the product of biosynthetic enzymes encoded by the C. jejuni pgl pathway and minimally requires three essential factors: a pathway for oligosaccharide biosynthesis, a functional oligosaccharyltransferase, and an acceptor protein with a D/E‐X1‐N‐X2‐S/T motif. Glycosylated phages could be recovered by lectin chromatography with enrichment factors as high as 2 × 105 per round of panning and these enriched phages retained their infectivity after panning. Using this assay, we show that desired glyco‐phenotypes can be reliably selected by panning phage‐displayed glycoprotein libraries on lectins that are specific for the glycan. For instance, we used our phage selection to identify permissible residues in the −2 position of the bacterial consensus acceptor site sequence. Taken together, our results demonstrate that a genotype–phenotype link can be established between the phage‐associated glyco‐epitope and the phagemid‐encoded genes for any of the three essential components of the glycosylation process. Thus, we anticipate that our phage display system can be used to isolate interesting variants in any step of the glycosylation process, thereby making it an invaluable tool for genetic analysis of protein glycosylation and for glycoengineering in E. coli cells.

Engineering the Protein Folding Landscape in Gram-Negative Bacteria

Gram-negative bacteria, especially Escherichia coli, are often the preferred hosts for recombinant protein production because of their fast doubling times, ability to grow to high cell density, propensity for high recombinant protein titers and straightforward protein purification techniques. The utility of simple bacteria in such studies continues to improve as a result of an ever-increasing body of knowledge regarding their native protein biogenesis machinery. From translation on the ribosome to interaction with cytosolic accessory factors to transport across the inner membrane into the periplasmic space, cellular proteins interact with many different types of cellular machinery and each interaction can have a profound effect on the protein folding process. This review addresses key aspects of cellular protein folding, solubility and expression in E. coli with particular focus on the elegant biological machinery that orchestrates the transition from nascent polypeptide to folded, functional protein. Specifically highlighted are a variety of different techniques to intentionally alter the folding environment of the cell as a means to understand and engineer intracellular protein folding and stability.

Mining mammalian genomes for folding competent proteins using Tat‐dependent genetic selection in Escherichia coli

Recombinant expression of eukaryotic proteins in Escherichia coli is often limited by poor folding and solubility. To address this problem, we employed a recently developed genetic selection for protein folding and solubility based on the bacterial twin‐arginine translocation (Tat) pathway to rapidly identify properly folded recombinant proteins or soluble protein domains of mammalian origin. The coding sequences for 29 different mammalian polypeptides were cloned as sandwich fusions between an N‐terminal Tat export signal and a C‐terminal selectable marker, namely β‐lactamase. Hence, expression of the selectable marker and survival on selective media was linked to Tat export of the target mammalian protein. Since the folding quality control feature of the Tat pathway prevents export of misfolded proteins, only correctly folded fusion proteins reached the periplasm and conferred cell survival. In general, the ability to confer growth was found to relate closely to the solubility profile and molecular weight of the protein, although other features such as number of contiguous hydrophobic amino acids and cysteine content may also be important. These results highlight the capacity of Tat selection to reveal the folding potential of mammalian proteins and protein domains without the need for structural or functional information about the target protein.

Parallel Mapping of Antibiotic Resistance Alleles in Escherichia coli

Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, but its scope is often limited by the throughput of genome-scale library construction and genotype-phenotype mapping. Here we report a method for rapid, parallel, and deep characterization of the response to antibiotics in Escherichia coli using a barcoded genome-scale library, next-generation sequencing, and streamlined bioinformatics software. The method provides quantitative growth data (over 200,000 measurements) and identifies contributing antimicrobial resistance and susceptibility alleles. Using multivariate analysis, we also find that subtle differences in the population responses resonate across multiple levels of functional hierarchy. Finally, we use machine learning to identify a unique allelic and proteomic fingerprint for each antibiotic. The method can be broadly applied to tolerance for any chemical from toxic metabolites to next-generation biofuels and antibiotics.

Trackable Multiplex Recombineering for Gene-Trait Mapping in E. coli

Recent advances in homologous recombination in Escherichia coli have enabled improved genome engineering by multiplex recombineering. In this chapter, we present trackable multiplex recombineering (TRMR), a method for gene-trait mapping which creates simulated knockdown and overexpression mutants for virtually all genes in the E. coli genome. The method combines oligonucleotide synthesis with multiplex recombineering to create two libraries comprising of over 8,000 E. coli strains in total that can be selected for traits of interest via high-throughput screening or selection. DNA barcodes included in the recombineering cassette allow for rapid characterization of a naïve or selected population via DNA microarray analysis. Important considerations for oligonucleotide design, DNA library construction, recombineering, strain characterization, and selection are discussed.

Engineered genetic selection links in vivo protein folding and stability with asparagine-linked glycosylation

Predicting the structural consequences of site-specific glycosylation remains a major challenge due in part to the lack of convenient experimental tools for rapidly determining how glycosylation influences protein folding. To address this shortcoming, we developed a genetic selection that directly links the in vivo folding of asparagine-linked (N-linked) glycoproteins with antibiotic resistance. Using this assay, we identified three known or putative glycoproteins from Campylobacter jejuni (Peb3, CjaA, and Cj0610c) whose folding was significantly affected by N-glycosylation. We also used the genetic selection to isolate a glycoengineered variant of the Escherichia coli colicin E7 immunity protein (Im7) whose intracellular folding and stability were enhanced as a result of N-glycosylation. In addition to monitoring the effect of glycan attachment on protein folding in living cells, this strategy could easily be extended for optimizing protein folding in vivo and engineering glycosylation enzymes, pathways, and hosts for optimal performance.

Improving Designer Glycan Production in Escherichia coli through Model-Guided Metabolic Engineering

Asparagine-linked (N-linked) glycosylation is the most common protein modification in eukaryotes, affecting over two-thirds of the proteome. Glycosylation is also critical to the pharmacokinetic activity and immunogenicity of many therapeutic proteins currently produced in complex eukaryotic hosts. The discovery of a protein glycosylation pathway in the pathogen Campylobacter jejuni and its subsequent transfer into laboratory strains of Escherichia coli has spurred great interest in glycoprotein production in prokaryotes. However, prokaryotic glycoprotein production has several drawbacks, including insufficient availability of non-native glycan precursors. To address this limitation, we used a constraint-based model of E. coli metabolism in combination with heuristic optimization to design gene knockout strains that overproduced glycan precursors. First, we incorporated reactions associated with C. jejuni glycan assembly into a genome-scale model of E. coli metabolism. We then identified gene knockout strains that coupled optimal growth to glycan synthesis. Simulations suggested that these growth-coupled glycan overproducing strains had metabolic imbalances that rerouted flux toward glycan precursor synthesis. We then validated the model-identified knockout strains experimentally by measuring glycan expression using a flow cytometric-based assay involving fluorescent labeling of cell surface-displayed glycans. Overall, this study demonstrates the promising role that metabolic modeling can play in optimizing the performance of a next-generation microbial glycosylation platform.