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1.  Biogenesis of Influenza A Virus Hemagglutinin Cross-Protective Stem Epitopes 
PLoS Pathogens  2014;10(6):e1004204.
Antigenic variation in the globular domain of influenza A virus (IAV) hemagglutinin (HA) precludes effective immunity to this major human pathogen. Although the HA stem is highly conserved between influenza virus strains, HA stem-reactive antibodies (StRAbs) were long considered biologically inert. It is now clear, however, that StRAbs reduce viral replication in animal models and protect against pathogenicity and death, supporting the potential of HA stem-based immunogens as drift-resistant vaccines. Optimally designing StRAb-inducing immunogens and understanding StRAb effector functions require thorough comprehension of HA stem structure and antigenicity. Here, we study the biogenesis of HA stem epitopes recognized in cells infected with various drifted IAV H1N1 strains using mouse and human StRAbs. Using a novel immunofluorescence (IF)-based assay, we find that human StRAbs bind monomeric HA in the endoplasmic reticulum (ER) and trimerized HA in the Golgi complex (GC) with similar high avidity, potentially good news for producing effective monomeric HA stem immunogens. Though HA stem epitopes are nestled among several N-linked oligosaccharides, glycosylation is not required for full antigenicity. Rather, as N-linked glycans increase in size during intracellular transport of HA through the GC, StRAb binding becomes temperature-sensitive, binding poorly to HA at 4°C and well at 37°C. A de novo designed, 65-residue protein binds the mature HA stem independently of temperature, consistent with a lack of N-linked oligosaccharide steric hindrance due to its small size. Likewise, StRAbs bind recombinant HA carrying simple N-linked glycans in a temperature-independent manner. Chemical cross-linking experiments show that N-linked oligosaccharides likely influence StRAb binding by direct local effects rather than by globally modifying the conformational flexibility of HA. Our findings indicate that StRAb binding to HA is precarious, raising the possibility that sufficient immune pressure on the HA stem region could select for viral escape mutants with increased steric hindrance from N-linked glycans.
Author Summary
Extensive variation in the IAV HA globular domain severely impedes influenza vaccination. Recent findings demonstrate that StRAbs, specific Abs to the highly conserved stem region of HA, can protect hosts against a broad variety of influenza virus strains. In investigating the binding of StRAbs to HA during its biogenesis in IAV-infected cells, we find that these Abs can bind HA monomers prior to their trimerization in the GC. Binding to HA becomes temperature-dependent, however, as N-linked oligosaccharides mature during transport of trimerized HA through the GC to the cell surface. Our findings support the potential use of monomeric HA stem immunogens to induce broadly neutralizing Abs, but raise the possibility of eventual viral escape from StRAbs, based on structural alterations in the HA that increase steric hindrance of HA stem N-linked glycans on StRAb binding.
doi:10.1371/journal.ppat.1004204
PMCID: PMC4055778  PMID: 24945804
2.  A Synthetic Genetic Edge Detection Program 
Cell  2009;137(7):1272-1281.
Summary
Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.
doi:10.1016/j.cell.2009.04.048
PMCID: PMC2775486  PMID: 19563759

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