Evidence map›Paper›PMID 35333580›Full record

ArticleScience advances2022

Multivariate mining of an alpaca immune repertoire identifies potent cross-neutralizing SARS-CoV-2 nanobodies.

Leo Hanke, Daniel J Sheward, Alec Pankow, Laura Perez Vidakovics, Vivien Karl, Changil Kim, Egon Urgard, Natalie L Smith, Juan Astorga-Wells, Simon Ekström and 3 more

Open access · goldAbstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.6field-weighted citation impact, top 5% 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

20 citing papers in PubMed, 40 citations in OpenAlex.

  1. mAbs · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Application of nanobody‑based CAR‑T in tumor immunotherapy (Review).International journal of molecular medicine · 2025
    Review
  6. Article
  7. Improving the production and stability of nanobodies.Protein engineering, design & selection : PEDS · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Nanobodies: Robust miniprotein binders in biomedicine.Advanced drug delivery reviews · 2023
    Review
  17. Article
  18. Article
  19. Review
  20. Article
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

13 authors at 3 institutions in 2 countries.

Leo HankeDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-5514-2418
Daniel J ShewardDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-0227-5636
Alec PankowDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-9108-1683
Laura Perez VidakovicsDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-4283-812X
Vivien KarlDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-7026-7622
Changil KimDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-4977-4384
Egon UrgardDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.
Natalie L SmithDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.
Juan Astorga-WellsDepartment of Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden.ORCID 0000-0003-1017-8841
Simon EkströmSwedish National Infrastructure for Biological Mass Spectrometry (BioMS), Lund University, Lund, Sweden.
Jonathan M CoquetDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-5967-4857
Gerald M McInerneyDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-2257-7241
Ben MurrellDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-0393-4445
Karolinska Institutet · SELund University · SEUniversity of Cape Town · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional approaches to isolate and characterize nanobodies are laborious. We combine phage display, multivariate enrichment, next-generation sequencing, and a streamlined screening strategy to identify numerous anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nanobodies. We characterize their potency and specificity using neutralization assays and hydrogen/deuterium exchange mass spectrometry (HDX-MS). The most potent nanobodies bind to the receptor binding motif of the receptor binding domain (RBD), and we identify two exceptionally potent members of this category (with monomeric half-maximal inhibitory concentrations around 13 and 16 ng/ml). Other nanobodies bind to a more conserved epitope on the side of the RBD and are able to potently neutralize the SARS-CoV-2 founder virus (42 ng/ml), the Beta variant (B.1.351/501Y.V2) (35 ng/ml), and also cross-neutralize the more distantly related SARS-CoV-1 (0.46 μg/ml). The approach presented here is well suited for the screening of phage libraries to identify functional nanobodies for various biomedical and biochemical applications.

Indexed as

Camelids, New WorldCOVID-19Single-Domain AntibodiesAnimalsAntibodies, MonoclonalAntibodies, ViralHumansMembrane GlycoproteinsNeutralization TestsSARS-CoV-2Spike Glycoprotein, CoronavirusViral Envelope ProteinsAntibodies, MonoclonalAntibodies, ViralMembrane GlycoproteinsSingle-Domain AntibodiesSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Viral Envelope Proteins

Identifiers

PMID35333580
PMCPMC8956255
OpenAlexW4220841727

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.