Skip to content
#protein folding Open access

Profile of the digestive and absorptive functions in the intestine of fish with different dietary habits and in response to increased dietary carbohydrate or protein

Sep 2026 · bioRxiv · 0 citations · 34 references
Biology

Abstract

Global aquaculture has grown significantly, but to maintain current consumption, supply must double over the next 20 years. Here, we characterised the digestive and absorptive capacities in the intestines of three commercially important, farmed fish species with varying natural diets: Nile tilapia (Oreochromis niloticus), common carp (Cyprinus carpio), and rainbow trout (Oncorhynchus mykiss). Disaccharidase activity (maltase, sucrase) and sodium-dependent D-glucose absorption were highest in Nile tilapia, followed by common carp, and lowest in rainbow trout. We found regional intestinal differences in disaccharidase activity and SGLT1 expression in the three species. Aminopeptidase A (APA) and aminopeptidase N (APN) activities were typically highest in Nile tilapia. Intestinal expression of the neutral amino acid transporter B0AT1 was approx. double in tilapia and carp compared to trout. We also assessed common carp, zebrafish and Rainbow trout’s digestion profile when fed low-carbohydrate/high protein and high-carbohydrate/low-protein diets. Common carp and zebrafish adapted to high-carbohydrate diets by up-regulating both digestive enzymes and SGLT1. Common carp increased SGLT1 protein abundance 2.7-fold in the foregut and 4.6-fold in the hindgut. Rainbow trout increased disaccharidase activity but not SGLT1 expression in response to a high-carbohydrate diet. Both Rainbow trout and common carp down-regulated their APN activity but upregulated their B0AT1 expression 2-fold in response to increased dietary protein. These physiological limitations are critical considerations for formulating sustainable plant-based aquafeeds.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.