Engineering the Maize Root Microbiome: A Rapid MoClo Toolkit and Identification of Potential Bacterial Chassis for Studying Plant-Microbe Interactions.

Sustainably enhancing crop production is a global necessity to meet the escalating demand for staple crops while sustainably managing their associated carbon/nitrogen inputs. Leveraging plant-associated microbiomes is a promising avenue for addressing this demand. However, studying these communities and engineering them for sustainable enhancement of crop production have remained a challenge due to limited genetic tools and methods. In this work, we detail the development of the Maize Root Microbiome ToolKit (MRMTK), a rapid Modular Cloning (MoClo) toolkit that only takes 2.5 h to generate desired constructs (5400 potential plasmids) that replicate and express heterologous genes in Enterobacter ludwigii strain AA4 (Elu), Pseudomonas putida strain AA7 (Ppu), Herbaspirillum robiniae strain AA6 (Hro), Stenotrophomonas maltophilia strain AA1 (Sma), and Brucella pituitosa strain AA2 (Bpi), which comprise a model maize root synthetic community (SynCom). In addition to these genetic tools, we describe a highly efficient transformation protocol (107-109 transformants/µg of DNA) 1 for each of these strains. Utilizing this highly efficient transformation protocol, we identified endogenous Expression Sequences (ES; promoter and ribosomal binding sites) for each strain via genomic promoter trapping. Overall, MRMTK is a scalable and adaptable platform that expands the genetic engineering toolbox while providing a standardized, high-efficiency transformation method across a diverse group of root commensals. These results unlock the ability to elucidate and engineer plant-microbe interactions promoting plant growth for each of the 5 bacterial strains in this study.

Building a collaborative cloud platform to accelerate heart, lung, blood, and sleep research.

Research increasingly relies on interrogating large-scale data resources. The NIH National Heart, Lung, and Blood Institute developed the NHLBI BioData CatalystⓇ (BDC), a community-driven ecosystem where researchers, including bench and clinical scientists, statisticians, and algorithm developers, find, access, share, store, and compute on large-scale datasets. This ecosystem provides secure, cloud-based workspaces, user authentication and authorization, search, tools and workflows, applications, and new innovative features to address community needs, including exploratory data analysis, genomic and imaging tools, tools for reproducibility, and improved interoperability with other NIH data science platforms. BDC offers straightforward access to large-scale datasets and computational resources that support precision medicine for heart, lung, blood, and sleep conditions, leveraging separately developed and managed platforms to maximize flexibility based on researcher needs, expertise, and backgrounds. Through the NHLBI BioData Catalyst Fellows Program, BDC facilitates scientific discoveries and technological advances. BDC also facilitated accelerated research on the coronavirus disease-2019 (COVID-19) pandemic.

Dug: a semantic search engine leveraging peer-reviewed knowledge to query biomedical data repositories.

MOTIVATION: As the number of public data resources continues to proliferate, identifying relevant datasets across heterogenous repositories is becoming critical to answering scientific questions. To help researchers navigate this data landscape, we developed Dug: a semantic search tool for biomedical datasets utilizing evidence-based relationships from curated knowledge graphs to find relevant datasets and explain why those results are returned. RESULTS: Developed through the National Heart, Lung and Blood Institute's (NHLBI) BioData Catalyst ecosystem, Dug has indexed more than 15 911 study variables from public datasets. On a manually curated search dataset, Dug's total recall (total relevant results/total results) of 0.79 outperformed default Elasticsearch's total recall of 0.76. When using synonyms or related concepts as search queries, Dug (0.36) far outperformed Elasticsearch (0.14) in terms of total recall with no significant loss in the precision of its top results. AVAILABILITY AND IMPLEMENTATION: Dug is freely available at https://github.com/helxplatform/dug. An example Dug deployment is also available for use at https://search.biodatacatalyst.renci.org/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mesenchymal stromal cell-derived exosomes improve mitochondrial health in pulmonary arterial hypertension.

Secreted exosomes are bioactive particles that elicit profound responses in target cells. Using targeted metabolomics and global microarray analysis, we identified a role of exosomes in promoting mitochondrial function in the context of pulmonary arterial hypertension (PAH). Whereas chronic hypoxia results in a glycolytic shift in pulmonary artery smooth muscle cells (PASMCs), exosomes restore energy balance and improve O2 consumption. These results were confirmed in a hypoxia-induced mouse model and a semaxanib/hypoxia rat model of PAH wherein exosomes improved the mitochondrial dysfunction associated with disease. Importantly, exosome exposure increased PASMC expression of pyruvate dehydrogenase (PDH) and glutamate dehydrogenase 1 (GLUD1), linking exosome treatment to the TCA cycle. Furthermore, we show that although prolonged hypoxia induced sirtuin 4 expression, an upstream inhibitor of both GLUD1 and PDH, exosomes reduced its expression. These data provide direct evidence of an exosome-mediated improvement in mitochondrial function and contribute new insights into the therapeutic potential of exosomes in PAH.