Histoplasma capsulatum proteome response to decreased iron availability

<p>Abstract</p> <p>Background</p> <p>A fundamental pathogenic feature of the fungus <it>Histoplasma capsulatum </it>is its ability to evade innate and adaptive immune defenses. Once ingested by macrophages the organism is faced with several hostile environmental conditions including iron limitation. <it>H. capsulatum </it>can establish a persistent state within the macrophage. A gap in knowledge exists because the identities and number of proteins regulated by the organism under host conditions has yet to be defined. Lack of such knowledge is an important problem because until these proteins are identified it is unlikely that they can be targeted as new and innovative treatment for histoplasmosis.</p> <p>Results</p> <p>To investigate the proteomic response by <it>H. capsulatum </it>to decreasing iron availability we have created <it>H. capsulatum </it>protein/genomic databases compatible with current mass spectrometric (MS) search engines. Databases were assembled from the <it>H. capsulatum </it>G217B strain genome using gene prediction programs and expressed sequence tag (EST) libraries. Searching these databases with MS data generated from two dimensional (2D) in-gel digestions of proteins resulted in over 50% more proteins identified compared to searching the publicly available fungal databases alone. Using 2D gel electrophoresis combined with statistical analysis we discovered 42 <it>H. capsulatum </it>proteins whose abundance was significantly modulated when iron concentrations were lowered. Altered proteins were identified by mass spectrometry and database searching to be involved in glycolysis, the tricarboxylic acid cycle, lysine metabolism, protein synthesis, and one protein sequence whose function was unknown.</p> <p>Conclusion</p> <p>We have created a bioinformatics platform for <it>H. capsulatum </it>and demonstrated the utility of a proteomic approach by identifying a shift in metabolism the organism utilizes to cope with the hostile conditions provided by the host. We have shown that enzyme transcripts regulated by other fungal pathogens in response to lowering iron availability are also regulated in <it>H. capsulatum </it>at the protein level. We also identified <it>H. capsulatum </it>proteins sensitive to iron level reductions which have yet to be connected to iron availability in other pathogens. These data also indicate the complexity of the response by <it>H. capsulatum </it>to nutritional deprivation. Finally, we demonstrate the importance of a strain specific gene/protein database for <it>H. capsulatum </it>proteomic analysis.</p

Developing Innovative Metallomics Approaches to Characterize Trace Biometals

Many elements have been claimed as essential for health but their precise roles in life are largely uncharacterized. The increasing interests in the metals/metalloids within biological systems have been driving the fast growth of metallomics, a subject originated to establish the links between metals/metalloids and life. The foundation of metallomics relies on precise determination of biological metal(loid) species. The aim of this dissertation is characterization of such species, primarily metalloproteins, in various biological systems using innovative metallomics approaches. These include several multi-technique methods in which the traditional elemental speciation with HPLC-ICPMS (inductively coupled plasma mass spectrometry) and LC-MS/MS based proteomics were combined to meet the challenges of metalloprotein characterization in animals and plants. Two biologically important elements were intensively studied, zinc (Zn) in murine macrophages and selenium (Se) in plants. The metallomics study in macrophages revealed that Zn played a fundamental role in host defense against Histoplasma capsulatum infection, and a few Zn-binding proteins selectively responded to macrophage activation or the pathogen infection. The Se study elucidated the complete profiles of Se metabolites in kale ( Brassica oleracea) and soybean (Glycine max) and more importantly, it discovered the first Se-containing protein in plants, the Se-containing Bowman-Birk proteinase isoinhibitor D-II [Glycine max] derived from the Se-enriched soybean. These findings not only opened new avenues to study Zn’s precise roles in immunity and Se-containing proteins in plants, but also lead the interactions between metallomics and other research areas, such as immunology and proteomics

Observations of boundary layer wind and turbulence of a landfalling tropical cyclone

This study investigates the atmospheric boundary layer structure based on multiple-level tower observations with a height of 350 m during the landfall of Super Typhoon Mangkhut (2018). Results show a layer of log wind profile outside of the radius of maximum wind speed with a height of 100 m or larger. The log layer height increases with the wind speed. The height of the constant flux layer reaches ~ 300 m for 10-m wind speeds less than 13 m s−1while this height decreases with the wind speed. Momentum fluxes and turbulent kinetic energy increase with the wind speed at all vertical levels. The drag coefficient and surface roughness length estimated at the tower location have values of 7.3 × 10–3and 0.09 m, respectively, which are independent of wind speed. The estimated vertical eddy diffusivity and mixing length increase with height up to ~ 160 m and then slowly decrease with height. The vertical eddy diffusivity increases with the wind speed while the vertical mixing length has no dependence on the wind speed. Comparing our results with previous work indicates that the vertical eddy diffusivity is larger over land than over ocean at a given wind speed range

sj-docx-1-dhj-10.1177_20552076221149528 - Supplemental material for A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study

Supplemental material, sj-docx-1-dhj-10.1177_20552076221149528 for A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study by Huiling Shao, Wing Chi Lawrence Chan, Heng Du and Xiangyan Fiona Chen, Qilin Ma, Zhiyu Shao in Digital Health</p

sj-pptx-2-dhj-10.1177_20552076221149528 - Supplemental material for A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study

Supplemental material, sj-pptx-2-dhj-10.1177_20552076221149528 for A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study by Huiling Shao, Wing Chi Lawrence Chan, Heng Du and Xiangyan Fiona Chen, Qilin Ma, Zhiyu Shao in Digital Health</p