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Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
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In most mammalian species, females have two X sex chromosomes and males have an X and Y. As a result, mutations on the X chromosome in females may be masked by the presence of a normal allele on the second X. In contrast, a mutation on the X chromosome in males more often causes observable biological defects, as there is no normal X to compensate. Trait variations arising from mutations on the X chromosome are called “X-linked”.
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In 1971, Peter Perlman and Eva Engvall developed an Enzyme-linked immunosorbent assay (ELISA or EIA). ELISA differs from western blot in that the assays are conducted in microtiter plates or in vivo rather than on an absorbent membrane.
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Disbiome database: linking the microbiome to disease.

Yorick Janssens1, Joachim Nielandt2, Antoon Bronselaer2

  • 1Drug Quality and Registration (DruQuaR) Group, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000, Ghent, Belgium.

BMC Microbiology
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The Disbiome database centralizes research on the human microbiome and its connection to diseases. It standardizes and presents data on microbial composition changes across various medical conditions for easier access.

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DatabaseDysbiosisHealth statusMedDRA

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Area of Science:

  • Microbiology
  • Medical Informatics
  • Genomics

Background:

  • Emerging evidence links host health to microbial inhabitants.
  • High-throughput sequencing reveals microbial composition changes in diseases.
  • This critical data is currently fragmented across multiple disciplines.

Purpose of the Study:

  • To create a centralized database for microbiota-disease information.
  • To standardize and present published data on microbial composition in diseases.
  • To facilitate research by consolidating dispersed information.

Main Methods:

  • Collected and curated published microbiota-disease data.
  • Classified diseases using the Medical Dictionary for Regulatory Activities (MedDRA) system.
  • Linked microorganisms to NCBI and SILVA taxonomy.
  • Assessed study reporting quality using a standardized questionnaire.

Main Results:

  • Developed Disbiome, a comprehensive database of microbiota-disease associations.
  • Standardized disease classification and microbial taxonomy.
  • Included quality assessment for all studies.

Conclusions:

  • Disbiome offers a clear, concise, and up-to-date overview of disease-associated microbial differences.
  • The database integrates references for diverse search strategies.
  • Human annotation ensures a structured and user-friendly presentation of data.