Evidence map›Paper›PMID 39728915›Full record

ArticleProteomes2024

Peptidomic Analysis Reveals Temperature-Dependent Proteolysis in Rainbow Trout (

Miyu Sakuyama, Yuri Kominami, Hideki Ushio

Abstract read
In one paragraph

Article in Proteomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Miyu SakuyamaDepartment of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-865, Japan.
Yuri KominamiDepartment of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-865, Japan.ORCID 0000-0002-4239-8542
Hideki UshioDepartment of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo 113-865, Japan.

Funding

Japan Society for the Promotion of Science 22H0507the TOBE MAKI Foundation 22-JA-501
6 · The paper itself

Abstract

Sous vide, a cooking method that involves vacuum-sealed fish at low temperatures, yields a uniquely tender, easily flaked texture. Previous research on sous-vide tenderization has focused on thermal protein denaturation. On the other hand, the contribution of proteases, activated at low temperatures in fish meat, has been suggested. However, the details of protein degradation remain unclear. This study employed SDS-PAGE/immunoblot and peptidomic analysis of rainbow trout to assess proteolysis during sous-vide cooking. The results from SDS-PAGE and immunoblot analysis indicated reduced thermal aggregation of sarcoplasmic proteins and increased depolymerization of actin under low-temperature cooking conditions. A comparison of the peptidome showed that the proteolysis of myofibrillar proteins was accelerated during sous-vide cooking, with distinct proteases potentially activated at different cooking temperatures. Terminome analysis revealed the contribution of specific proteases at higher temperatures in rainbow trout. The results of this study demonstrate the thermal denaturation of sarcoplasmic proteins and proteolysis of myofibrillar proteins in rainbow trout meat during sous-vide cooking and its temperature dependence. The methodology in the present study could provide insights into the optimization of cooking conditions for different fish species, potentially leading to improved texture and quality of sous-vide products.

Indexed as

peptidomeproteolysissous-vide cookingterminome

Identifiers

PMID39728915
PMCPMC11679362

What OpenQuestion holds

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Registered trials

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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.