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Host-associated microbe PCR (hamPCR): accessing new biology through convenient measurement of both microbial load and community composition

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Lundberg,  DS       
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Ayutthaya,  PPN       
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Shirsekar,  G       
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Lo,  W-S       
Department Integrative Evolutionary Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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Weigel,  D       
Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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引用

Lundberg, D., Ayutthaya, P., Strauß, A., Shirsekar, G., Lo, W.-S., Lahaye, T., & Weigel, D. (2021). Host-associated microbe PCR (hamPCR): accessing new biology through convenient measurement of both microbial load and community composition. In 1st International Student Conference on Biotechnology and Life Science (INSCOBIOL) (pp. 9).


引用: https://hdl.handle.net/21.11116/0000-000E-5244-9
要旨
The ratio of microbial population size relative to the amount of host tissue, or "microbial load", is a fundamental metric of colonization and infection, but it cannot be directly deduced from microbial amplicon data such as 16S rRNA gene counts. Because conventional methods to determine load, such as serial dilution plating or quantitative PCR, add substantial experimental burden, they are only rarely paired with amplicon sequencing. Alternatively, whole metagenome sequencing of DNA contributed by host and microbes both reveals microbial community composition and enables determination of microbial load, but host DNA typically greatly outweighs microbial DNA, severely limiting the cost-effectiveness and scalability of this approach. We introduce host-associated microbe PCR (hamPCR), a robust amplicon sequencing strategy to quantify microbial load and describe interkingdom microbial community composition in a single, cost-effective library. We demonstrate its accuracy and flexibility across multiple host and microbe systems, including nematodes and major crops. We further present a technique that can be used, prior to sequencing, to optimize the host representation in a batch of libraries without loss of information. Because of its simplicity, and the fact that it provides an experimental solution to the well-known statistical challenges provided by compositional data, hamPCR will become a transformative approach throughout culture-independent microbiology.