https://www.frontiersin.org/articles/10.3389/fcimb.2019.00179/full

Front. Cell. Infect. Microbiol., 11 June 2019 | https://doi.org/10.3389/fcimb.2019.00179

Multi-platform Approach for Microbial Biomarker Identification Using Borrelia burgdorferi as a Model

Kathryn J. Pflughoeft1,2, Michael Mash1,2, Nicole R. Hasenkampf3, Mary B. Jacobs3, Amanda C. Tardo3, D. Mitchell Magee4, Lusheng Song4, Joshua LaBaer4, Mario T. Philipp3, Monica E. Embers3 and David P. AuCoin1,2*

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.

Please see initial link for entire study but I summarize some highlights below:
  • The authors state that testing delays can take days to weeks for diagnosis
  • Samples with a low bioburden may drive false-negative results, but amplification steps require even more time
  • In the case of Lyme disease, current CDC testing requires an immune response which is problematic as it delays treatment by several weeks, as well as the fact many patients remain seronegative, requiring additional testing, and doesn’t distinguish between new and previously treated infections.
  • The authors utilized multiple platforms to unmask B.b biomarkers and they mentioned the study by Turko group which focused on identifying biomarkers found abundant in B. burgdorferi B31 cultured in vitro, in patient samples using MS and that they found peptides from the OspA could be detected in early patient serum samples but not in those samples collected later (Cheung et al., 2015).
  • A conservative approach to biomarker identification was taken and proteins that were identified more than once were classified as potential biomarkers, and those identified three or more times were classified as high-potential biomarkers. The resulting data identified six proteins that were detected as early microbial indicators of infection.
  • Please be aware that this test can only identify Lyme disease – not other pathogens often involved with tick borne illness such as Babesia, Bartonella, Mycoplasma, tick-borne viruses, RMSF, etc.
  • In the discussion section that authors state they are also working on another multi-platform approach to define antigenic biomarkers for Tularemia (can be spread by ticks & deer flies) and Melioidois (also called Whitmore’s disease).