Evidence map›Paper›PMID 28414024›Full record

ArticleJournal of immunological methods2017

Novel high-throughput cell-based hybridoma screening methodology using the Celigo Image Cytometer.

Haohai Zhang, Leo Li-Ying Chan, William Rice, Nasim Kassam, Maria Serena Longhi, Haitao Zhao, Simon C Robson, Wenda Gao, Yan Wu

Open access · greenAbstract read
In one paragraph

Article in Journal of immunological methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 20 citations in OpenAlex.

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  8. A high-throughput chemotaxis detection method for CCR4Journal of immunological methods · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Haohai ZhangDepartment of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100730, China; Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States.
Leo Li-Ying ChanDepartment of Technology R&D, Nexcelom Bioscience LLC, Lawrence, MA 01843, United States.
William RiceDepartment of Technology R&D, Nexcelom Bioscience LLC, Lawrence, MA 01843, United States.
Nasim KassamBrigham Woman's Hospital, Harvard Medical School, Boston, MA 02215, United States.
Maria Serena LonghiBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States.
Haitao ZhaoDepartment of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100730, China.
Simon C RobsonBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States.
Wenda GaoAntagen Pharmaceuticals, Inc., Boston, MA 02118, United States.
Yan WuBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States. Electronic address: ywu@bidmc.harvard.edu.
Beth Israel Deaconess Medical Center · USAntagen Pharmaceuticals (United States) · USChinese Academy of Medical Sciences & Peking Union Medical College · CNHarvard University · USPeking Union Medical College Hospital · CN

Funding

Therapeutic assessment of synthetic heparin sulfates in transplantation modelsP01HL107152 · NHLBI · VIRGINIA COMMONWEALTH UNIVERSITY · PI DESAI, UMESH RAMANLAL · 2011 to 2017
$15.8M
Engineering Inhibitory Antibodies to Ectoenzymes for Cancer TreatmentR21CA164970 · NCI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI ROBSON, SIMON C. · 2012 to 2013
$405k
NCI NIH HHS R21 CA164970NHLBI NIH HHS P01 HL107152
6 · The paper itself

Abstract

Hybridoma screening is a critical step for antibody discovery, which necessitates prompt identification of potential clones from hundreds to thousands of hybridoma cultures against the desired immunogen. Technical issues associated with ELISA- and flow cytometry-based screening limit accuracy and diminish high-throughput capability, increasing time and cost. Conventional ELISA screening with coated antigen is also impractical for difficult-to-express hydrophobic membrane antigens or multi-chain protein complexes. Here, we demonstrate novel high-throughput screening methodology employing the Celigo Image Cytometer, which avoids nonspecific signals by contrasting antibody binding signals directly on living cells, with and without recombinant antigen expression. The image cytometry-based high-throughput screening method was optimized by detecting the binding of hybridoma supernatants to the recombinant antigen CD39 expressed on Chinese hamster ovary (CHO) cells. Next, the sensitivity of the image cytometer was demonstrated by serial dilution of purified CD39 antibody. Celigo was used to measure antibody affinities of commercial and in-house antibodies to membrane-bound CD39. This cell-based screening procedure can be completely accomplished within one day, significantly improving throughput and efficiency of hybridoma screening. Furthermore, measuring direct antibody binding to living cells eliminated both false positive and false negative hits. The image cytometry method was highly sensitive and versatile, and could detect positive antibody in supernatants at concentrations as low as ~5ng/mL, with concurrent K

Indexed as

AnimalsAntibodies, MonoclonalAntibody AffinityAntigens, CDApyraseCHO CellsCricetulusEnzyme-Linked Immunosorbent AssayHigh-Throughput Screening AssaysHybridomasImage CytometrySensitivity and SpecificityAntibodies, MonoclonalAntigens, CDApyraseCD39 antigenAntibody discoveryCeligoHigh-throughputHybridoma screeningImage cytometry

Identifiers

PMID28414024
PMCPMC5538021
OpenAlexW2606318636

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.