10 research outputs found
The Genesis Solar Wind Concentrator
The primary goal of the Genesis Mission is to collect solar wind ions and, from their analysis, establish key isotopic ratios that will help constrain models of solar nebula formation and evolution. The ratios of primary interest include ^(17)O/^(16)O and ^(18)O/^(16)O to ±0.1%, ^(15)N/^(14)N to ±1%, and the Li, Be, and B elemental and isotopic abundances. The required accuracies in N and O ratios cannot be achieved without concentrating the solar wind and implanting it into low-background target materials that are returned to Earth for analysis. The Genesis Concentrator is designed to concentrate the heavy ion flux from the solar wind by an average factor of at least 20 and implant it into a target of ultra-pure, well-characterized materials. High-transparency grids held at high voltages are used near the aperture to reject >90% of the protons, avoiding damage to the target. Another set of grids and applied voltages are used to accelerate and focus the remaining ions to implant into the target. The design uses an energy-independent parabolic ion mirror to focus ions onto a 6.2 cm diameter target of materials selected to contain levels of O and other elements of interest established and documented to be below 10% of the levels expected from the concentrated solar wind. To optimize the concentration of the ions, voltages are constantly adjusted based on real-time solar wind speed and temperature measurements from the Genesis ion monitor. Construction of the Concentrator required new developments in ion optics; materials; and instrument testing and handling
Deciphering eukaryotic gene-regulatory logic with 100 million random promoters
How transcription factors (TFs) interpret cis-regulatory DNA sequence to control gene expression remains unclear, largely because past studies using native and engineered sequences had insufficient scale. Here, we measure the expression output of >100 million synthetic yeast promoter sequences that are fully random. These sequences yield diverse, reproducible expression levels that can be explained by their chance inclusion of functional TF binding sites. We use machine learning to build interpretable models of transcriptional regulation that predict ~94% of the expression driven from independent test promoters and ~89% of the expression driven from native yeast promoter fragments. These models allow us to characterize each TF’s specificity, activity and interactions with chromatin. TF activity depends on binding-site strand, position, DNA helical face and chromatin context. Notably, expression level is influenced by weak regulatory interactions, which confound designed-sequence studies. Our analyses show that massive-throughput assays of fully random DNA can provide the big data necessary to develop complex, predictive models of gene regulation. ©2019, The Author(s), under exclusive licence to Springer Nature America, Inc.NIH (grant no. K99-HG009920-01)Fellowship from the Canadian Institutes for Health ResearchMIT Presidential Fellowshi
The role of Streptococcus pneumoniae virulence factors in host respiratory colonization and disease
Streptococcus pneumoniae is a Gram-positive bacterial pathogen that colonizes the mucosal surfaces of the host nasopharynx and upper airway. Through a combination of virulence-factor activity and an ability to evade the early components of the host immune response, this organism can spread from the upper respiratory tract to the sterile regions of the lower respiratory tract, which leads to pneumonia. In this Review, we describe how S. pneumoniae uses its armamentarium of virulence factors to colonize the upper and lower respiratory tracts of the host and cause disease.Aras Kadioglu, Jeffrey N. Weiser, James C. Paton and Peter W. Andre