QMEC: a tool for high-throughput quantitative assessment of microbial functional potential in C, N, P, and S biogeochemical cycling

Bangxiao Zheng, Yongguan Zhu, Jordi Sardans, Josep Peñuelas, Jianqiang Su

    Research output: Contribution to journalArticleResearch

    17 Citations (Scopus)

    Abstract

    © 2018, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature. Microorganisms are major drivers of elemental cycling in the biosphere. Determining the abundance of microbial functional traits involved in the transformation of nutrients, including carbon (C), nitrogen (N), phosphorus (P) and sulfur (S), is critical for assessing microbial functionality in elemental cycling. We developed a high-throughput quantitative-PCR-based chip, Quantitative microbial element cycling (QMEC), for assessing and quantifying the genetic potential of microbiota to mineralize soil organic matter and to release C, N, P and S. QMEC contains 72 primer pairs targeting 64 microbial functional genes for C, N, P, S and methane metabolism. These primer pairs were characterized by high coverage (average of 18–20 phyla covered per gene) and sufficient specificity (>70% match rate) with a relatively low detection limit (7–102 copies per run). QMEC was successfully applied to soil and sediment samples, identifying significantly different structures, abundances and diversities of the functional genes (P<0.05). QMEC was also able to determine absolute gene abundance. QMEC enabled the simultaneous qualitative and quantitative determination of 72 genes from 72 samples in one run, which is promising for comprehensively investigating microbially mediated ecological processes and biogeochemical cycles in various environmental contexts including those of the current global change.
    Original languageEnglish
    Pages (from-to)1451-1462
    JournalScience China Life Sciences
    Volume61
    DOIs
    Publication statusPublished - 1 Dec 2018

    Keywords

    • biogeochemical cycle
    • ecological process
    • elemental cycling
    • functional potential
    • high-throughput qPCR
    • microbial genes

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