Evidence map›Paper›PMID 34508004›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Sequential in vivo labeling of insulin secretory granule pools in

Elisabeth Kemter, Andreas Müller, Martin Neukam, Anna Ivanova, Nikolai Klymiuk, Simone Renner, Kaiyuan Yang, Johannes Broichhagen, Mayuko Kurome, Valeri Zakhartchenko and 9 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

19 authors.

Elisabeth KemterChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany.ORCID 0000-0001-7785-7502
Andreas MüllerGerman Center for Diabetes Research, 85764 Neuherberg, Germany.ORCID 0000-0002-3560-5769
Martin NeukamGerman Center for Diabetes Research, 85764 Neuherberg, Germany.ORCID 0000-0002-5743-9204
Anna IvanovaGerman Center for Diabetes Research, 85764 Neuherberg, Germany.
Nikolai KlymiukChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany.
Simone RennerChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany.
Kaiyuan YangGerman Center for Diabetes Research, 85764 Neuherberg, Germany.
Johannes BroichhagenDepartment of Chemical Biology, Max Planck Institute for Medical Research, 69120 Heidelberg, Germany.ORCID 0000-0003-3084-6595
Mayuko KuromeChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany.
Valeri ZakhartchenkoChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany.ORCID 0000-0002-5974-9759
Barbara KesslerChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany.ORCID 0000-0001-7036-238X
Klaus-Peter KnochGerman Center for Diabetes Research, 85764 Neuherberg, Germany.
Marc BickleTechnology Development Studio (TDS), Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
Barbara LudwigGerman Center for Diabetes Research, 85764 Neuherberg, Germany.ORCID 0000-0003-0771-5247
Kai JohnssonDepartment of Chemical Biology, Max Planck Institute for Medical Research, 69120 Heidelberg, Germany.
Heiko LickertGerman Center for Diabetes Research, 85764 Neuherberg, Germany.
Thomas KurthCenter for Molecular and Cellular Bioengineering Technology Platform, Technische Universität Dresden, 01307 Dresden, Germany.ORCID 0000-0001-5624-1717
Eckhard WolfChair for Molecular Animal Breeding and Biotechnology Gene Center, Ludwig Maximilian University of Munich, 81377 Munich, Germany; ewolf@genzentrum.lmu.de Michele.Solimena@uniklinikum-dresden.de.ORCID 0000-0002-0430-9510
Michele SolimenaGerman Center for Diabetes Research, 85764 Neuherberg, Germany; ewolf@genzentrum.lmu.de Michele.Solimena@uniklinikum-dresden.de.ORCID 0000-0002-3653-8107

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

β cells produce, store, and secrete insulin upon elevated blood glucose levels. Insulin secretion is a highly regulated process. The probability for insulin secretory granules to undergo fusion with the plasma membrane or being degraded is correlated with their age. However, the molecular features and stimuli connected to this behavior have not yet been fully understood. Furthermore, our understanding of β cell function is mostly derived from studies of ex vivo isolated islets in rodent models. To overcome this translational gap and study insulin secretory granule turnover in vivo, we have generated a transgenic pig model with the SNAP-tag fused to insulin. We demonstrate the correct targeting and processing of the tagged insulin and normal glycemic control of the pig model. Furthermore, we show specific single- and dual-color granular labeling of in vivo-labeled pig pancreas. This model may provide unprecedented insights into the in vivo insulin secretory granule behavior in an animal close to humans.

Indexed as

AnimalsAnimals, Genetically ModifiedCell MembraneExocytosisFluorescent DyesGlucoseInsulinInsulin-Secreting CellsInsulin SecretionMaleSecretory VesiclesSNARE ProteinsSwineFluorescent DyesGlucoseInsulinSNARE Proteinsdiabetes mellitusinsulin turnoverpig modelβ cell

Identifiers

PMID34508004
PMCPMC8449372

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.