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Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition.

ABSTRACT: 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 existing methods to determine load, such as serial dilution plating, quantitative PCR, and whole metagenome sequencing add substantial cost and/or experimental burden, they are only rarely paired with amplicon sequencing. We introduce host-associated microbe PCR (hamPCR), a robust strategy to both quantify microbial load and describe interkingdom microbial community composition in a single amplicon library. We demonstrate its accuracy across multiple study systems, including nematodes and major crops, and further present a cost-saving technique to reduce host overrepresentation in the library prior to sequencing. Because hamPCR provides an accessible experimental solution to the well-known limitations and statistical challenges of compositional data, it has far-reaching potential in culture-independent microbiology.

SUBMITTER: Lundberg DS

PROVIDER: S-EPMC8387020 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition.

Lundberg Derek S DS Pramoj Na Ayutthaya Pratchaya P Strauß Annett A Shirsekar Gautam G Lo Wen-Sui WS Lahaye Thomas T Weigel Detlef D

eLife 20210722

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 existing methods to determine load, such as serial dilution plating, quantitative PCR, and whole metagenome sequencing add substantial cost and/or experimental burden, they are only rarely paired with amplicon sequencing. We introduce host-assoc ...[more]

PMID: 34292157

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Project description:BackgroundFerromanganese nodule-bearing deep-sea sediments cover vast areas of the ocean floor, representing a distinctive habitat in the abyss. These sediments harbor unique conditions characterized by high iron concentration and low degradable nutrient levels, which pose challenges to the survival and growth of most microorganisms. While the microbial diversity in ferromanganese nodule-associated sediments has been surveyed several times, little is known about the functional capacities of the communities adapted to these unique habitats.ResultsSeven sediment samples collected adjacent to ferromanganese nodules from the Clarion-Clipperton Fracture Zone (CCFZ) in the eastern Pacific Ocean were subjected to metagenomic analysis. As a result, 179 high-quality metagenome-assembled genomes (MAGs) were reconstructed and assigned to 21 bacterial phyla and 1 archaeal phylum, with 88.8% of the MAGs remaining unclassified at the species level. The main mechanisms of resistance to heavy metals for microorganisms in sediments included oxidation (Mn), reduction (Cr and Hg), efflux (Pb), synergy of reduction and efflux (As), and synergy of oxidation and efflux (Cu). Iron, which had the highest content among all metallic elements, may occur mainly as Fe(III) that potentially functioned as an electron acceptor. We found that microorganisms with a diverse array of CAZymes did not exhibit higher community abundance. Instead, microorganisms mainly obtained energy from oxidation of metal (e.g., Mn(II)) and sulfur compounds using oxygen or nitrate as an electron acceptor. Chemolithoautotrophic organisms (Thaumarchaeota and Nitrospirota phyla) were found to be potential manganese oxidizers. The functional profile analysis of the dominant microorganisms further indicated that utilization of inorganic nutrients by redox reactions (rather than organic nutrient metabolism) is a major adaptive strategy used by microorganisms to support their survival in the ferromanganese nodule sediments.ConclusionsThis study provides a comprehensive metagenomic analysis of microbes inhabiting metal-rich ferromanganese nodule sediments. Our results reveal extensive redundancy across taxa for pathways of metal resistance and transformation, the highly diverse mechanisms used by microbes to obtain nutrition, and their participation in various element cycles in these unique environments. Video Abstract.

Project description:BACKGROUNDLower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging because noninfectious respiratory illnesses appear clinically similar and because existing microbiologic tests are often falsely negative or detect incidentally carried microbes, resulting in antimicrobial overuse and adverse outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and treatment remains unclear.METHODSWe used tracheal aspirate RNA-Seq to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n = 117) or of noninfectious respiratory failure (n = 50). We then developed a classifier that integrates the host LRTI probability, abundance of respiratory viruses, and dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm.RESULTSThe host classifier achieved a median AUC of 0.967 by cross-validation, driven by activation markers of T cells, alveolar macrophages, and the interferon response. The integrated classifier achieved a median AUC of 0.986 and increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n = 94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those.CONCLUSIONLower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.FUNDINGSupport for this study was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Heart, Lung, and Blood Institute (UG1HD083171, 1R01HL124103, UG1HD049983, UG01HD049934, UG1HD083170, UG1HD050096, UG1HD63108, UG1HD083116, UG1HD083166, UG1HD049981, K23HL138461, and 5R01HL155418) as well as by the Chan Zuckerberg Biohub.

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Dataset Information

Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition.

Publications

Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition.

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