Dataset Information

Automated purification and suspension array detection of 16S rRNA from soil and sediment extracts by using tunable surface microparticles.

ABSTRACT: Autonomous, field-deployable molecular detection systems require seamless integration of complex biochemical solutions and physical or mechanical processing steps. In an attempt to simplify the fluidic requirements for integrated biodetection systems, we used tunable surface microparticles both as an rRNA affinity purification resin in a renewable microcolumn sample preparation system and as the sensor surface in a flow cytometer detector. The tunable surface detection limits in both low- and high-salt buffers were 1 ng of total RNA ( approximately 10(4) cell equivalents) in 15-min test tube hybridizations and 10 ng of total RNA ( approximately 10(5) cell equivalents) in hybridizations with the automated system (30-s contact time). RNA fragmentation was essential for achieving tunable surface suspension array specificity. Chaperone probes reduced but did not completely eliminate cross-hybridization, even with probes sharing <50% identity to target sequences. Nonpurified environmental extracts did not irreparably affect our ability to classify color-coded microparticles, but residual environmental constituents significantly quenched the Alexa-532 reporter fluor. Modulating surface charge did not influence the interaction of soluble environmental contaminants with conjugated beads. The automated system greatly reduced the effects of fluorescence quenching, especially in the soil background. The automated system was as efficacious as manual methods for simultaneous sample purification, hybridization, and washing prior to flow cytometry detection. The implications of unexpected target cross-hybridization and fluorescence quenching are discussed relative to the design and implementation of an integrated microbial monitoring system.

SUBMITTER: Chandler DP

PROVIDER: S-EPMC404419 | biostudies-literature | 2004 May

REPOSITORIES: biostudies-literature

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Automated purification and suspension array detection of 16S rRNA from soil and sediment extracts by using tunable surface microparticles.

Chandler Darrell P DP Jarrell Ann E AE

Applied and environmental microbiology 20040501 5

Autonomous, field-deployable molecular detection systems require seamless integration of complex biochemical solutions and physical or mechanical processing steps. In an attempt to simplify the fluidic requirements for integrated biodetection systems, we used tunable surface microparticles both as an rRNA affinity purification resin in a renewable microcolumn sample preparation system and as the sensor surface in a flow cytometer detector. The tunable surface detection limits in both low- and hi ...[more]

PMID: 15128511

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Project description:BackgroundSequential membrane filtration as a pre-processing step for capturing sediment-associated microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques. However, the effects of sample pre-processing via filtration on DNA-based profiling of sediment-associated microbial community diversity and composition are poorly understood. Specifically, the influences of pre-processing on the quality and quantity of extracted DNA, high-throughput DNA sequencing reads, and detected microbial taxa need further evaluation.ResultsWe assessed the impact of pre-processing freshwater sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size) for 16S rRNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the qualities and quantities of extracted DNA and PCR amplicons, and the read abundance after bioinformatics processing (i.e., denoising and chimeric-read filtering steps) between the two methods. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods' absolute read abundance. More so, at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition.ConclusionsOur observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

Dataset Information

Automated purification and suspension array detection of 16S rRNA from soil and sediment extracts by using tunable surface microparticles.

Publications

Automated purification and suspension array detection of 16S rRNA from soil and sediment extracts by using tunable surface microparticles.

Similar Datasets

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