Dataset Information

Gene-targeted microfluidic cultivation validated by isolation of a gut bacterium listed in Human Microbiome Project's Most Wanted taxa.

ABSTRACT: This paper describes a microfluidics-based workflow for genetically targeted isolation and cultivation of microorganisms from complex clinical samples. Data sets from high-throughput sequencing suggest the existence of previously unidentified bacterial taxa and functional genes with high biomedical importance. Obtaining isolates of these targets, preferably in pure cultures, is crucial for advancing understanding of microbial genetics and physiology and enabling physical access to microbes for further applications. However, the majority of microbes have not been cultured, due in part to the difficulties of both identifying proper growth conditions and characterizing and isolating each species. We describe a method that enables genetically targeted cultivation of microorganisms through a combination of microfluidics and on- and off-chip assays. This method involves (i) identification of cultivation conditions for microbes using growth substrates available only in small quantities as well as the correction of sampling bias using a "chip wash" technique; and (ii) performing on-chip genetic assays while also preserving live bacterial cells for subsequent scale-up cultivation of desired microbes, by applying recently developed technology to create arrays of individually addressable replica microbial cultures. We validated this targeted approach by cultivating a bacterium, here referred to as isolate microfluidicus 1, from a human cecal biopsy. Isolate microfluidicus 1 is, to our knowledge, the first successful example of targeted cultivation of a microorganism from the high-priority group of the Human Microbiome Project's "Most Wanted" list, and, to our knowledge, the first cultured representative of a previously unidentified genus of the Ruminococcaceae family.

SUBMITTER: Ma L

PROVIDER: S-EPMC4103313 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Gene-targeted microfluidic cultivation validated by isolation of a gut bacterium listed in Human Microbiome Project's Most Wanted taxa.

Ma Liang L Kim Jungwoo J Hatzenpichler Roland R Karymov Mikhail A MA Hubert Nathaniel N Hanan Ira M IM Chang Eugene B EB Ismagilov Rustem F RF

Proceedings of the National Academy of Sciences of the United States of America 20140625 27

This paper describes a microfluidics-based workflow for genetically targeted isolation and cultivation of microorganisms from complex clinical samples. Data sets from high-throughput sequencing suggest the existence of previously unidentified bacterial taxa and functional genes with high biomedical importance. Obtaining isolates of these targets, preferably in pure cultures, is crucial for advancing understanding of microbial genetics and physiology and enabling physical access to microbes for f ...[more]

PMID: 24965364

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Project description:Despite the substantial progress made in human gut culturomics, little is known about the culturability of the swine gut microbiota. In this study, we cultured swine gut microbiota using 53 bacterial cultivation methods with different medium and gas combinations from three pigs at four different growth stages. Both culture-dependent (CD; colony mixtures from each method) and culture-independent (CI; original fecal suspensions) samples were subjected to 16S rRNA gene amplicon sequencing. Increasing microbial diversities were observed in both CI and CD samples from successive growth stages. While a total of 378, 482, 565, and 555 bacterial amplicon sequence variants (ASVs) were observed in the CI samples, higher microbial diversities (415, 675, 808, and 823 observed ASVs) were detected using the CD methods at the lactation, nursery, growing, and finishing stages, respectively. We constructed reference culture maps showing the preferred cultivation conditions for specific bacterial taxa and examined the effects of culturing factors such as oxygen, medium, donor pig age, antibiotics, and blood culture preincubation on swine gut microbiota cultivation. We focused on a wide range of beneficial bacteria, chose 1,299 colonies based on the reference map, and Sanger sequenced their 16S rRNA genes. These isolates clustered into 148 different bacterial taxa covering 28 genera. We observed 11, 19, 33, and 25 pairs of cooccurring ASVs in both CD and CI samples at four successive growth stages. This study provides guidance in culturing the swine gut microbiota of interest, which is critical when characterizing their functions in this important animal species. IMPORTANCE The swine gut microbiome has been the focus of many investigations due to the fact that pigs serve as both an excellent biomedical model for human diseases and an important protein source. Substantial progress has been made in swine gut microbiome studies using next-generation sequencing-based culture-independent approaches, but little is known about the culturability of the swine gut microbiota. To understand their roles in swine production, it is critical to culture bacterial strains of interest. In this study, we cultured the gut microbiota from pigs at different growth stages using 53 bacterial cultivation methods with different medium and gas combinations. This study provides evidence that the swine gut microbiota is much more diverse based on a culture-dependent approach than previously known. It provides preliminary guidance for isolating certain bacteria of interest from pigs, which is critical in establishing causal relationships between the gut microbiota and the health status of pigs.

Project description:Background: The accuracy of microbial community detection in 16S rRNA marker-gene and metagenomic studies suffers from contamination and sequencing errors that lead to either falsely identifying microbial taxa that were not in the sample or misclassifying the taxa of DNA fragment reads. Removing contaminants and filtering rare features are two common approaches to deal with this problem. While contaminant detection methods use auxiliary sequencing process information to identify known contaminants, filtering methods remove taxa that are present in a small number of samples and have small counts in the samples where they are observed. The latter approach reduces the extreme sparsity of microbiome data and has been shown to correctly remove contaminant taxa in cultured "mock" datasets, where the true taxa compositions are known. Although filtering is frequently used, careful evaluation of its effect on the data analysis and scientific conclusions remains unreported. Here, we assess the effect of filtering on the alpha and beta diversity estimation as well as its impact on identifying taxa that discriminate between disease states. Results: The effect of filtering on microbiome data analysis is illustrated on four datasets: two mock quality control datasets where the same cultured samples with known microbial composition are processed at different labs and two disease study datasets. Results show that in microbiome quality control datasets, filtering reduces the magnitude of differences in alpha diversity and alleviates technical variability between labs while preserving the between samples similarity (beta diversity). In the disease study datasets, DESeq2 and linear discriminant analysis Effect Size (LEfSe) methods were used to identify taxa that are differentially abundant across groups of samples, and random forest models were used to rank features with the largest contribution toward disease classification. Results reveal that filtering retains significant taxa and preserves the model classification ability measured by the area under the receiver operating characteristic curve (AUC). The comparison between the filtering and the contaminant removal method shows that they have complementary effects and are advised to be used in conjunction. Conclusions: Filtering reduces the complexity of microbiome data while preserving their integrity in downstream analysis. This leads to mitigation of the classification methods' sensitivity and reduction of technical variability, allowing researchers to generate more reproducible and comparable results in microbiome data analysis.

Dataset Information

Gene-targeted microfluidic cultivation validated by isolation of a gut bacterium listed in Human Microbiome Project's Most Wanted taxa.

Publications

Gene-targeted microfluidic cultivation validated by isolation of a gut bacterium listed in Human Microbiome Project's Most Wanted taxa.

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