Dataset Information

Towards Quantitative Microbiome Community Profiling Using Internal Standards.

ABSTRACT: An inherent issue in high-throughput rRNA gene tag sequencing microbiome surveys is that they provide compositional data in relative abundances. This often leads to spurious correlations, making the interpretation of relationships to biogeochemical rates challenging. To overcome this issue, we quantitatively estimated the abundance of microorganisms by spiking in known amounts of internal DNA standards. Using a 3-year sample set of diverse microbial communities from the Western Antarctica Peninsula, we demonstrated that the internal standard method yielded community profiles and taxon cooccurrence patterns substantially different from those derived using relative abundances. We found that the method provided results consistent with the traditional CHEMTAX analysis of pigments and total bacterial counts by flow cytometry. Using the internal standard method, we also showed that chloroplast 16S rRNA gene data in microbial surveys can be used to estimate abundances of certain eukaryotic phototrophs such as cryptophytes and diatoms. In Phaeocystis, scatter in the 16S/18S rRNA gene ratio may be explained by physiological adaptation to environmental conditions. We conclude that the internal standard method, when applied to rRNA gene microbial community profiling, is quantitative and that its application will substantially improve our understanding of microbial ecosystems.IMPORTANCE High-throughput-sequencing-based marine microbiome profiling is rapidly expanding and changing how we study the oceans. Although powerful, the technique is not fully quantitative; it provides taxon counts only in relative abundances. In order to address this issue, we present a method to quantitatively estimate microbial abundances per unit volume of seawater filtered by spiking known amounts of internal DNA standards into each sample. We validated this method by comparing the calculated abundances to other independent estimates, including chemical markers (pigments) and total bacterial cell counts by flow cytometry. The internal standard approach allows us to quantitatively estimate and compare marine microbial community profiles, with important implications for linking environmental microbiomes to quantitative processes such as metabolic and biogeochemical rates.

SUBMITTER: Lin Y

PROVIDER: S-EPMC6384117 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Towards Quantitative Microbiome Community Profiling Using Internal Standards.

Lin Yajuan Y Gifford Scott S Ducklow Hugh H Schofield Oscar O Cassar Nicolas N

Applied and environmental microbiology 20190220 5

An inherent issue in high-throughput rRNA gene tag sequencing microbiome surveys is that they provide compositional data in relative abundances. This often leads to spurious correlations, making the interpretation of relationships to biogeochemical rates challenging. To overcome this issue, we quantitatively estimated the abundance of microorganisms by spiking in known amounts of internal DNA standards. Using a 3-year sample set of diverse microbial communities from the Western Antarctica Penins ...[more]

PMID: 30552195

Similar Datasets

Project description:Identifying the functional microbes in spontaneous food fermentation is important for improving food quality. To identify the key flavor producers in Chinese liquor fermentation, we propose a novel quantitative microbiome profiling method that uses indigenous internal standards to normalize high-throughput amplicon sequencing results. We screened Lactobacillus acetotolerans and Lactobacillus jinshani as indigenous internal standards based on their high distribution frequencies and relative abundances. After determining the absolute abundance of indigenous internal standards using quantitative PCR with species-specific primers, the liquor-fermented bacterial community and its dynamics were better characterized by internal standards normalization. Based on quantitative microbiome profiling, we identified that Lactobacillus was a key flavor producer correlated with eight flavor compounds. Metatranscriptomic analysis indicated that Lactobacillus was active in transcribing genes involving the biosynthesis of flavor compounds and their precursors. This work has developed a novel and extensible absolute quantification method for microbiota that will alleviate concerns in the statistical analyses based on relative microbiome profiling, and shed insights into the function of Lactobacillus in food fermentation. It can potentially be applied to other microbial ecology studies.IMPORTANCE In this study, we developed a novel strategy using indigenous internal standards to normalize the high-throughput amplicon sequencing results. We chose two Lactobacillus species as indigenous internal standards and characterized the absolute abundance of the bacterial community. Further, we identified Lactobacillus as the key flavor producer using quantitative microbiome profiling combined with multivariate statistics and metatranscriptomic analysis. This work developed a novel strategy for absolute quantitative abundance analysis of microbiota and expanded our understanding of the role of Lactobacillus in food fermentation.

Project description:A hallmark of neurodegeneration is the aggregation of disease related proteins that are resistant to detergent extraction. In the major pathological subtype of frontotemporal lobar degeneration (FTLD), modified TAR-DNA binding protein 43 (TDP-43), including phosphorylated, ubiquitinated, and proteolytically cleaved forms, is enriched in detergent-insoluble fractions from post-mortem brain tissue. Additional proteins that accumulate in the detergent-insoluble FTLD brain proteome remain largely unknown. In this study, we used proteins from stable isotope-labeled (SILAC) human embryonic kidney 293 cells (HEK293) as internal standards for peptide quantitation across control and FTLD insoluble brain proteomes. Proteins were identified and quantified by liquid-chromatography coupled with tandem mass spectrometry (LC-MS/MS) and 21 proteins were determined to be enriched in FTLD using SILAC internal standards. In parallel, label-free quantification of only the unlabeled brain derived peptides by spectral counts (SC) and G-test analysis identified additional brain-specific proteins significantly enriched in disease. Several proteins determined to be enriched in FTLD using SILAC internal standards were not considered significant by G-test due to their low total number of SC. However, immunoblotting of FTLD and control samples confirmed enrichment of these proteins, highlighting the utility of SILAC internal standard to quantify low-abundance proteins in brain. Of these, the RNA binding protein PTB-associated splicing factor (PSF) was further characterized because of structural and functional similarities to TDP-43. Full-length PSF and shorter molecular weight fragments, likely resulting from proteolytic cleavage, were enriched in FTLD cases. Immunohistochemical analysis of PSF revealed predominately nuclear localization in control and FTLD brain tissue and was not associated with phosphorylated pathologic TDP-43 neuronal inclusions. However, in a subset of FTLD cases, PSF was aberrantly localized to the cytoplasm of oligodendrocytes. These data raise the possibility that PSF directed RNA processes in oligodendrocytes are altered in neurodegenerative disease.

Dataset Information

Towards Quantitative Microbiome Community Profiling Using Internal Standards.

Publications

Towards Quantitative Microbiome Community Profiling Using Internal Standards.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets