ArticlePloS one2011
Screening of peptide libraries against protective antigen of Bacillus anthracis in a disposable microfluidic cartridge.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 26 citations in OpenAlex.
- Identification of Microorganisms that Bind Specifically to Target Materials of Interest Using a Magnetophoretic Microfluidic Platform.ACS applied materials & interfaces · 2023Article
- The next generation of biopanning: next gen sequencing improves analysis of bacterial display libraries.BMC biotechnology · 2019Article
- Protein-Catalyzed Capture Agents.Chemical reviews · 2019Review
- Semi-automated Biopanning of Bacterial Display Libraries for Peptide Affinity Reagent Discovery and Analysis of Resulting Isolates.Journal of visualized experiments : JoVE · 2017Article
- A magneto-fluidic nanoparticle trapping platform for surface-enhanced Raman spectroscopy.Biomicrofluidics · 2017Article
- Translating microfluidics: Cell separation technologies and their barriers to commercialization.Cytometry. Part B, Clinical cytometry · 2017Review
- Unraveling the Roots of Selectivity of Peptide Affinity Reagents for Structurally Similar Ribosomal Inactivating Protein Derivatives.Molecules (Basel, Switzerland) · 2016Article
- Screening and characterization of anti-SEB peptides using a bacterial display library and microfluidic magnetic sorting.Journal of molecular recognition : JMR · 2014Article
- Genetically engineered peptides for inorganics: study of an unconstrained bacterial display technology and bulk aluminum alloy.Advanced materials (Deerfield Beach, Fla.) · 2013Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacterial surface peptide display has gained popularity as a method of affinity reagent generation for a wide variety of applications ranging from drug discovery to pathogen detection. In order to isolate the bacterial clones that express peptides with high affinities to the target molecule, multiple rounds of manual magnetic activated cell sorting (MACS) followed by multiple rounds of fluorescence activated cell sorting (FACS) are conventionally used. Although such manual methods are effective, alternative means of library screening which improve the reproducibility, reduce the cost, reduce cross contamination, and minimize exposure to hazardous target materials are highly desired for practical application. Toward this end, we report the first semi-automated system demonstrating the potential for screening bacterially displayed peptides using disposable microfluidic cartridges. The Micro-Magnetic Separation platform (MMS) is capable of screening a bacterial library containing 3 × 10¹⁰ members in 15 minutes and requires minimal operator training. Using this system, we report the isolation of twenty-four distinct peptide ligands that bind to the protective antigen (PA) of Bacilus anthracis in three rounds of selection. A consensus motif WXCFTC was found using the MMS and was also found in one of the PA binders isolated by the conventional MACS/FACS approach. We compared MMS and MACS rare cell recovery over cell populations ranging from 0.1% to 0.0000001% and found that both magnetic sorting methods could recover cells down to 0.0000001% initial cell population, with the MMS having overall lower standard deviation of cell recovery. We believe the MMS system offers a compelling approach towards highly efficient, semi-automated screening of molecular libraries that is at least equal to manual magnetic sorting methods and produced, for the first time, 15-mer peptide binders to PA protein that exhibit better affinity and specificity than peptides isolated using conventional MACS/FACS.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.