PhenoSelection Manuscript 16S amplicons

Reichart, Nicholas; Steiger, Andrea; Van Fossen, Elise; McClure, Ryan; Overkleeftf, Herman S; Wright, Aaron

doi:10.25584/1959236

Title: PhenoSelection Manuscript 16S amplicons

Dataset
Other Related Research

Abstract

Multi-omic analyses can provide a great deal of information on the potential for activity within a microbial community but often lack specificity to link functions to cell and primarily offer potential for function, not true expression of function. Functional assays are necessary for understanding in situ microbial activity to better describe and improve microbiome biology. Targeting enzyme activity through activity-based protein profiling enhances the accuracy of functional studies. Here, we introduce PhenoSelection, a pipeline of coupling activity-based probing with fluorescence-activated cell sorting and downstream activity assays to isolate and examine viable populations of cells expressing a function of interest. We applied PhenoSelection to a soil microbiome to enrich for communities with elevated activity for lignocellulose-degradation phenotypes. PhenoSelection was able to separate and identify taxonomic members with activity for glycosyl hydrolases, and expanding to various probes for other function, this process can be applied to unique phenotypes of interest.

Authors:

; Steiger, Andrea;

;

; Overkleeftf, Herman S;

Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pacific Northwest National Laboratory
Absci
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Universiteit Leiden

Publication Date:: Fri Feb 10 04:00:00 UTC 2023

DOE Contract Number:: AC05-76RL01830

Research Org.:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Org.:: USDOE Laboratory Directed Research and Development (LDRD) Program

Subject:: 59 BASIC BIOLOGICAL SCIENCES

OSTI Identifier:: 1959236

DOI:: https://doi.org/10.25584/1959236

Citation Formats


                    Reichart, Nicholas, Steiger, Andrea, Van Fossen, Elise, McClure, Ryan, Overkleeftf, Herman S, and Wright, Aaron. PhenoSelection Manuscript 16S amplicons.  United States: N. p., 2023. 
        Web.  doi:10.25584/1959236.

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                    Reichart, Nicholas, Steiger, Andrea, Van Fossen, Elise, McClure, Ryan, Overkleeftf, Herman S, & Wright, Aaron. PhenoSelection Manuscript 16S amplicons.  United States.  doi:https://doi.org/10.25584/1959236

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                    Reichart, Nicholas, Steiger, Andrea, Van Fossen, Elise, McClure, Ryan, Overkleeftf, Herman S, and Wright, Aaron. 2023.  
"PhenoSelection Manuscript 16S amplicons".  United States.  doi:https://doi.org/10.25584/1959236.  https://www.osti.gov/servlets/purl/1959236. Pub date:Fri Feb 10 04:00:00 UTC 2023

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@article{osti_1959236,

  title        = {PhenoSelection Manuscript 16S amplicons},

  author       = {Reichart, Nicholas and Steiger, Andrea and Van Fossen, Elise and McClure, Ryan and Overkleeftf, Herman S and Wright, Aaron},

  abstractNote = {Multi-omic analyses can provide a great deal of information on the potential for activity within a microbial community but often lack specificity to link functions to cell and primarily offer potential for function, not true expression of function. Functional assays are necessary for understanding in situ microbial activity to better describe and improve microbiome biology. Targeting enzyme activity through activity-based protein profiling enhances the accuracy of functional studies. Here, we introduce PhenoSelection, a pipeline of coupling activity-based probing with fluorescence-activated cell sorting and downstream activity assays to isolate and examine viable populations of cells expressing a function of interest. We applied PhenoSelection to a soil microbiome to enrich for communities with elevated activity for lignocellulose-degradation phenotypes. PhenoSelection was able to separate and identify taxonomic members with activity for glycosyl hydrolases, and expanding to various probes for other function, this process can be applied to unique phenotypes of interest.},

  doi          = {10.25584/1959236},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Feb 10 04:00:00 UTC 2023},

  month        = {Fri Feb 10 04:00:00 UTC 2023}

}

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DOI: https://doi.org/10.25584/1959236

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