bioRxiv ScienceSearch

Biology subjects

Ji, M.

Publications and source records attributed to Ji, M..

2 recordsLinked to original sources

Effective soil extraction method for cultivating previously uncultured soil bacteria

Here, a new medium named as intensive soil extract medium (ISEM) based on new soil extract (NSE) using 80% ethanol was used to efficiently isolate previously uncultured bacteria and new taxonomic candidates, which accounted for 49% and 55% of the total isolates examined (n=258), respectively. The new isolates were affiliating with seven phyla such as Proteobacteria, Acidobacteria, Firmicutes, Actinobacteria, Verrucomicrobia, Planctomycetes, and Bacteroidetes. The result of chemical analysis showed that NSE included more diverse components of low-molecular-weight organic substances than two conventional soil extracts using distilled water. Cultivation of previously uncultured bacteria is expected to extend knowledge through the discovery of new phenotypic, physiological and functional properties, and even roles of unknown genes.\n\nIMPORTANCEEither metagenomics or single-cell sequencing can detect unknown genes from uncultured microbial strains in environments and may find their significant potential metabolites and roles. However, such gene/genome-based techniques still have a critical problem making impossible for further applications through cultivation. To solve this problem, various approaches for cultivation of uncultured bacteria have been developed, but they still have lack of skill to grow them on solid media for isolation and subculture.

microbiology

Standardized Informatics Computing Platform for Advancing Biomedical Discovery Through Data Sharing

ObjectiveThe goal is to develop a standardized informatics computing system that can support end-to-end research data lifecycle management for biomedical research applications.\n\nMaterials and MethodsDesign and implementation of biomedical research informatics computing system (BRICS) is demonstrated. The system architecture is modular in design with several integrated tools: global unique identifier, validation, upload, download and query tools that support user friendly informatics system capability.\n\nResultsBRICS instances were deployed to support research for improvements in diagnosis of traumatic brain injury, biomarker discovery for Parkinsons Disease, the National Ophthalmic Disease Genotyping and Phenotyping network, the informatics core for the Center for Neuroscience and Regenerative Medicine, the Common Data Repository for Nursing Science, Global Rare Diseases Patient Registry, and National Institute of Neurological Disorders and Stroke Clinical Informatics system for trials and research.\n\nDiscussionData deidentification is conducted by using global unique identifier methodology. No personally identifiable information exists on the BRICS supported repositories. The Data Dictionary provides defined Common Data Elements and Unique Data Elements, specific to each of the BRICS instance that enables Query Tool to search through research data. All instances are supported by the Medical Imaging Processing, statistical analysis R, and Visualization software program.\n\nConclusionThe BRICS core modules can be easily adapted for various biomedical research needs thereby reducing cost in developing new instances for additional biomedical research needs. It provides user friendly tools for researchers to query and aggregate genetic, phenotypic, clinical and medical imaging data. Data sets are findable, accessible and reusable for researchers to foster new research on various diseases.

bioinformatics