Multi-platform Approach for Microbial Biomarker Identification Using Borrelia burgdorferi as a Model
Autor: | Kathryn J. Pflughoeft, Michael Mash, Nicole R. Hasenkampf, Mary B. Jacobs, Amanda C. Tardo, D. Mitchell Magee, Lusheng Song, Joshua LaBaer, Mario T. Philipp, Monica E. Embers, David P. AuCoin |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
0301 basic medicine
Microbiology (medical) Biomarker identification Proteomics Serum 030106 microbiology Immunology lcsh:QR1-502 Computational biology microbial biomarker discovery Urine Microbiology lcsh:Microbiology 03 medical and health sciences Lyme disease Cellular and Infection Microbiology In vivo medicine early diagnostic Animals Humans Borrelia burgdorferi Original Research Antigens Bacterial Bacteriological Techniques Lyme Disease biology antibody response biology.organism_classification medicine.disease Antibodies Bacterial Macaca mulatta 3. Good health 030104 developmental biology Infectious Diseases Antibody response Early Diagnosis Biomarker (medicine) Identification (biology) Bacterial antigen Biomarkers |
Zdroj: | Frontiers in Cellular and Infection Microbiology Frontiers in Cellular and Infection Microbiology, Vol 9 (2019) |
ISSN: | 2235-2988 |
Popis: | The identification of microbial biomarkers is critical for the diagnosis of a disease early during infection. However, the identification of reliable biomarkers is often hampered by a low concentration of microbes or biomarkers within host fluids or tissues. We have outlined a multi-platform strategy to assess microbial biomarkers that can be consistently detected in host samples, using Borrelia burgdorferi, the causative agent of Lyme disease, as an example. Key aspects of the strategy include the selection of a macaque model of human disease, in vivo Microbial Antigen Discovery (InMAD), and proteomic methods that include microbial biomarker enrichment within samples to identify secreted proteins circulating during infection. Using the described strategy, we have identified 6 biomarkers from multiple samples. In addition, the temporal antibody response to select bacterial antigens was mapped. By integrating biomarkers identified from early infection with temporal patterns of expression, the described platform allows for the data driven selection of diagnostic targets. |
Databáze: | OpenAIRE |
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