1
|
Breves JP, Shaughnessy CA. Endocrine control of gill ionocyte function in euryhaline fishes. J Comp Physiol B 2024:10.1007/s00360-024-01555-3. [PMID: 38739280 DOI: 10.1007/s00360-024-01555-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 02/16/2024] [Accepted: 04/11/2024] [Indexed: 05/14/2024]
Abstract
The endocrine system is an essential regulator of the osmoregulatory organs that enable euryhaline fishes to maintain hydromineral balance in a broad range of environmental salinities. Because branchial ionocytes are the primary site for the active exchange of Na+, Cl-, and Ca2+ with the external environment, their functional regulation is inextricably linked with adaptive responses to changes in salinity. Here, we review the molecular-level processes that connect osmoregulatory hormones with branchial ion transport. We focus on how factors such as prolactin, growth hormone, cortisol, and insulin-like growth-factors operate through their cognate receptors to direct the expression of specific ion transporters/channels, Na+/K+-ATPases, tight-junction proteins, and aquaporins in ion-absorptive (freshwater-type) and ion-secretory (seawater-type) ionocytes. While these connections have historically been deduced in teleost models, more recently, increased attention has been given to understanding the nature of these connections in basal lineages. We conclude our review by proposing areas for future investigation that aim to fill gaps in the collective understanding of how hormonal signaling underlies ionocyte-based processes.
Collapse
Affiliation(s)
- Jason P Breves
- Department of Biology, Skidmore College, 815 N. Broadway, Saratoga Springs, NY, 12866, USA.
| | - Ciaran A Shaughnessy
- Department of Integrative Biology, Oklahoma State University, 501 Life Sciences West, Stillwater, OK, 74078, USA
| |
Collapse
|
2
|
Zou H. iHBPs-VWDC: variable-length window-based dynamic connectivity approach for identifying hormone-binding proteins. J Biomol Struct Dyn 2023:1-10. [PMID: 37978902 DOI: 10.1080/07391102.2023.2283150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/08/2023] [Indexed: 11/19/2023]
Abstract
Hormone-binding proteins (HBPs) are soluble carrier proteins that play a vital role in the growth and development of living organisms. Identifying HBPs accurately is crucial for understanding their functions. However, traditional wet lab experimental methods are labor intensive and cost ineffective. Therefore, there is a need for computational methods to efficiently identify HBPs. In this study, a machine learning method based on support vector machine (SVM) was proposed for the accurate and efficient identification of HBPs. The encoding of protein sequences involved using fifty different physicochemical (PC) properties. A variable-length window-based dynamic connectivity method was applied to capture the connection information between two different PC properties through two distinct strategies. The canonical correlation analysis algorithm was then used to fuse features obtained from these approaches. Feature selection was performed using the F-score approach to choose the most discriminative features. Finally, these selected features were fed into the SVM to discriminate between HBPs and non-HBPs. The proposed method achieved high classification accuracies of 99.19%, 96.77%, and 94.57% on the main dataset and two independent datasets, respectively, as demonstrated in the jackknife test. Comparative results showed that our proposed method outperforms existing approaches on the same datasets, indicating its potential as a useful tool for identifying HBPs. The Matlab codes and datasets used in the current study are freely available at https://figshare.com/articles/online_resource/iHBPs-VWDC/23559834.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Hongliang Zou
- School of Communications and Electronics, Jiangxi Science and Technology Normal University, Nanchang, China
- Jiangxi Engineering Research Center of Unattended Perception System and Artificial Intelligence Technology, Jiangxi Science and Technology Normal University, Nanchang, China
| |
Collapse
|
3
|
Guo Y, Hou L, Zhu W, Wang P. Prediction of Hormone-Binding Proteins Based on K-mer Feature Representation and Naive Bayes. Front Genet 2021; 12:797641. [PMID: 34887905 PMCID: PMC8650314 DOI: 10.3389/fgene.2021.797641] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 11/05/2021] [Indexed: 11/29/2022] Open
Abstract
Hormone binding protein (HBP) is a soluble carrier protein that interacts selectively with different types of hormones and has various effects on the body's life activities. HBPs play an important role in the growth process of organisms, but their specific role is still unclear. Therefore, correctly identifying HBPs is the first step towards understanding and studying their biological function. However, due to their high cost and long experimental period, it is difficult for traditional biochemical experiments to correctly identify HBPs from an increasing number of proteins, so the real characterization of HBPs has become a challenging task for researchers. To measure the effectiveness of HBPs, an accurate and reliable prediction model for their identification is desirable. In this paper, we construct the prediction model HBP_NB. First, HBPs data were collected from the UniProt database, and a dataset was established. Then, based on the established high-quality dataset, the k-mer (K = 3) feature representation method was used to extract features. Second, the feature selection algorithm was used to reduce the dimensionality of the extracted features and select the appropriate optimal feature set. Finally, the selected features are input into Naive Bayes to construct the prediction model, and the model is evaluated by using 10-fold cross-validation. The final results were 95.45% accuracy, 94.17% sensitivity and 96.73% specificity. These results indicate that our model is feasible and effective.
Collapse
Affiliation(s)
- Yuxin Guo
- Key Laboratory of Computational Science and Application of Hainan Province, Haikou, China
- Yangtze Delta Region Institute, University of Electronic Science and Technology of China, Quzhou, China
- Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education, Haikou, China
- School of Mathematics and Statistics, Hainan Normal University, Haikou, China
| | - Liping Hou
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Wen Zhu
- Key Laboratory of Computational Science and Application of Hainan Province, Haikou, China
- Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education, Haikou, China
- School of Mathematics and Statistics, Hainan Normal University, Haikou, China
| | - Peng Wang
- Key Laboratory of Computational Science and Application of Hainan Province, Haikou, China
- Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education, Haikou, China
- School of Mathematics and Statistics, Hainan Normal University, Haikou, China
| |
Collapse
|
4
|
Nisembaum LG, Martin P, Lecomte F, Falcón J. Melatonin and osmoregulation in fish: A focus on Atlantic salmon Salmo salar smoltification. J Neuroendocrinol 2021; 33:e12955. [PMID: 33769643 DOI: 10.1111/jne.12955] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 02/07/2021] [Accepted: 02/09/2021] [Indexed: 10/21/2022]
Abstract
Part of the life cycle of several fish species includes important salinity changes, as is the case for the sea bass (Dicentrarchus labrax) or the Atlantic salmon (Salmo salar). Salmo salar juveniles migrate downstream from their spawning sites to reach seawater, where they grow and become sexually mature. The process of preparation enabling juveniles to migrate downstream and physiologically adapt to seawater is called smoltification. Daily and seasonal variations of photoperiod and temperature play a role in defining the timing of smoltification, which may take weeks to months, depending on the river length and latitude. Smoltification is characterised by a series of biochemical, physiological and behavioural changes within the neuroendocrine axis. This review discusses the current knowledge and gaps related to the neuroendocrine mechanisms that mediate the effects of light and temperature on smoltification. Studies performed in S. salar and other salmonids, as well as in other species undergoing important salinity changes, are reviewed, and a particular emphasis is given to the pineal hormone melatonin and its possible role in osmoregulation. The daily and annual variations of plasma melatonin levels reflect corresponding changes in external photoperiod and temperature, which suggests that the hormonal time-keeper melatonin might contribute to controlling smoltification. Here, we review studies on (i) the impact of pinealectomy and/or melatonin administration on smoltification; (ii) melatonin interactions with hormones involved in osmoregulation (e.g., prolactin, growth hormone and cortisol); (iii) the presence of melatonin receptors in tissues involved in osmoregulation; and (iv) the impacts of salinity changes on melatonin receptors and circulating melatonin levels. Altogether, these studies show evidence indicating that melatonin interacts with the neuroendocrine pathways controlling smoltification, although more information is needed to clearly decipher its mechanisms of action.
Collapse
Affiliation(s)
- Laura Gabriela Nisembaum
- Sorbonne Université, CNRS, Biologie Intégrative des Organismes Marins, (BIOM), Banyuls-sur-Mer, France
| | - Patrick Martin
- Conservatoire National du Saumon Sauvage, Chanteuges, France
| | - Frédéric Lecomte
- Ministère des Forêts, de la Faune et des Parcs, Direction de l'expertise sur la faune aquatique, Québec, Canada
| | - Jack Falcón
- Biologie des Organismes et Ecosystèmes Aquatiques (BOREA), MNHN, CNRS 7208, SU, IRD 207, UCN, UA, Muséum National d'Histoire Naturelle, Paris, France
| |
Collapse
|
5
|
Basith S, Manavalan B, Shin TH, Lee G. iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree. Comput Struct Biotechnol J 2018; 16:412-420. [PMID: 30425802 PMCID: PMC6222285 DOI: 10.1016/j.csbj.2018.10.007] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 10/04/2018] [Accepted: 10/12/2018] [Indexed: 11/27/2022] Open
Abstract
A soluble carrier growth hormone binding protein (GHBP) that can selectively and non-covalently interact with growth hormone, thereby acting as a modulator or inhibitor of growth hormone signalling. Accurate identification of the GHBP from a given protein sequence also provides important clues for understanding cell growth and cellular mechanisms. In the postgenomic era, there has been an abundance of protein sequence data garnered, hence it is crucial to develop an automated computational method which enables fast and accurate identification of putative GHBPs within a vast number of candidate proteins. In this study, we describe a novel machine-learning-based predictor called iGHBP for the identification of GHBP. In order to predict GHBP from a given protein sequence, we trained an extremely randomised tree with an optimal feature set that was obtained from a combination of dipeptide composition and amino acid index values by applying a two-step feature selection protocol. During cross-validation analysis, iGHBP achieved an accuracy of 84.9%, which was ~7% higher than the control extremely randomised tree predictor trained with all features, thus demonstrating the effectiveness of our feature selection protocol. Furthermore, when objectively evaluated on an independent data set, our proposed iGHBP method displayed superior performance compared to the existing method. Additionally, a user-friendly web server that implements the proposed iGHBP has been established and is available at http://thegleelab.org/iGHBP.
Collapse
Affiliation(s)
- Shaherin Basith
- Department of Physiology, Ajou University School of Medicine, Suwon, Republic of Korea
| | | | - Tae Hwan Shin
- Department of Physiology, Ajou University School of Medicine, Suwon, Republic of Korea
- Institute of Molecular Science and Technology, Ajou University, Suwon, Republic of Korea
| | - Gwang Lee
- Department of Physiology, Ajou University School of Medicine, Suwon, Republic of Korea
- Institute of Molecular Science and Technology, Ajou University, Suwon, Republic of Korea
| |
Collapse
|
6
|
Björnsson BT, Einarsdóttir IE, Johansson M, Gong N. The Impact of Initial Energy Reserves on Growth Hormone Resistance and Plasma Growth Hormone-Binding Protein Levels in Rainbow Trout Under Feeding and Fasting Conditions. Front Endocrinol (Lausanne) 2018; 9:231. [PMID: 29867764 PMCID: PMC5968089 DOI: 10.3389/fendo.2018.00231] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 04/23/2018] [Indexed: 11/13/2022] Open
Abstract
The growth hormone (GH)-insulin-like growth factor I (IGF-I) system regulates important physiological functions in salmonid fish, including hydromineral balance, growth, and metabolism. While major research efforts have been directed toward this complex endocrine system, understanding of some key aspects is lacking. The aim was to provide new insights into GH resistance and growth hormone-binding proteins (GHBPs). Fish frequently respond to catabolic conditions with elevated GH and depressed IGF-I plasma levels, a condition of acquired GH resistance. The underlying mechanisms or the functional significance of GH resistance are, however, not well understood. Although data suggest that a significant proportion of plasma GH is bound to specific GHBPs, the regulation of plasma GHBP levels as well as their role in modulating the GH-IGF-I system in fish is virtually unknown. Two in vivo studies were conducted on rainbow trout. In experiment I, fish were fasted for 4 weeks and then refed and sampled over 72 h. In experiment II, two lines of fish with different muscle adiposity were sampled after 1, 2, and 4 weeks of fasting. In both studies, plasma GH, IGF-I, and GHBP levels were assessed as well as the hepatic gene expression of the growth hormone receptor 2a (ghr2a) isoform. While most rainbow trout acquired GH resistance within 4 weeks of fasting, fish selected for high muscle adiposity did not. This suggests that GH resistance does not set in while fat reserves as still available for energy metabolism, and that GH resistance is permissive for protein catabolism. Plasma GHBP levels varied between 5 and 25 ng ml-1, with large fluctuations during both long-term (4 weeks) fasting and short-term (72 h) refeeding, indicating differentiated responses depending on prior energy status of the fish. The two opposing functions of GHBPs of prolonging the biological half-life of GH while decreasing GH availability to target tissues makes the data interpretation difficult, but nutritional regulatory mechanisms are suggested. The lack of correlation between hepatic ghr2a expression and plasma GHBP levels indicate that ghr2a assessment cannot be used as a proxy measure for GHBP levels, even if circulating GHBPs are derived from the GH receptor molecule.
Collapse
Affiliation(s)
- Björn Thrandur Björnsson
- Fish Endocrinology Laboratory, Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | | | | | | |
Collapse
|
7
|
Bergan-Roller HE, Sheridan MA. The growth hormone signaling system: Insights into coordinating the anabolic and catabolic actions of growth hormone. Gen Comp Endocrinol 2018; 258:119-133. [PMID: 28760716 DOI: 10.1016/j.ygcen.2017.07.028] [Citation(s) in RCA: 90] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Revised: 07/19/2017] [Accepted: 07/27/2017] [Indexed: 12/16/2022]
Abstract
Although growth hormone (GH) is a multifunctional factor that coordinates various aspects of feeding, reproduction, osmoregulation, and immune system function, perhaps two of its most studied actions are the regulation of growth and metabolism, particularly lipid metabolism. In this review, we describe the major growth-promoting and lipid metabolic actions of GH and then discuss how the GH system regulates these actions. Numerous intrinsic and extrinsic factors provide information about the metabolic status of the organism and influence the production of release of GH. The actions of GH are mediated by GH receptors (GHR), which are widely distributed among tissues. Teleosts possess multiple forms of GHRs that arose through the evolution of this group. Modulation of tissue responsiveness to GH is regulated by molecular and functional expression of GHRs, and in teleosts GHR subtypes, by various factors that reflect the metabolic and growth status of the organism, including nutritional state. The action of GH is propagated by the linkage of GHRs to several cellular effector systems, including JAK-STAT, ERK, PI3K-Akt, and PKC. The differential activation of these pathways, which is governed by nutrient status, underlies GH stimulation of growth or GH stimulation of lipolysis. Taken together, the multi-functional actions of GH are determined by the distribution and abundance of GHRs (and GHR subtypes in teleosts) as well as by the GHR-effector system linkages.
Collapse
Affiliation(s)
| | - Mark A Sheridan
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409 USA.
| |
Collapse
|
8
|
Li M, Jiang C, Zhang Y, Zhang S. Activities of Amphioxus GH-Like Protein in Osmoregulation: Insight into Origin of Vertebrate GH Family. Int J Endocrinol 2017; 2017:9538685. [PMID: 28408927 PMCID: PMC5376476 DOI: 10.1155/2017/9538685] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 11/14/2016] [Indexed: 01/21/2023] Open
Abstract
GH is known to play an important role in both growth promotion and osmoregulation in vertebrates. We have shown that amphioxus possesses a single GH-like hormone (GHl) gene encoding a functional protein capable of promoting growth. However, if GHl can mediate osmoregulation remains open. Here, we demonstrated clearly that GHl increased not only the survival rate of amphioxus but also the muscle moisture under high salinity. Moreover, GHl induced the expression of both the ion transporter Na+-K+-ATPase (NKA) and Na+-K+-2Cl- cotransporter (NKCC) in the gill as well as the mediator of GH action IGFl in the hepatic caecum, indicating that GHl fulfills this osmoregulatory activity through the same mechanisms of vertebrate GH. These results together suggest that the osmoregulatory activities of GH had emerged in the basal chordate amphioxus. We also proposed a new model depicting the origin of pituitary hormone family in vertebrates.
Collapse
Affiliation(s)
- Mengyang Li
- Laboratory for Evolution & Development, Institute of Evolution & Marine Biodiversity and Department of Marine Biology, Ocean University of China, Qingdao 266003, China
- Institute for Translational Medicine, Qingdao University, Qingdao 266021, China
| | - Chengyan Jiang
- Laboratory for Evolution & Development, Institute of Evolution & Marine Biodiversity and Department of Marine Biology, Ocean University of China, Qingdao 266003, China
- College of Life Science and Technology, Hong He University, Mengzi, Yunnan 661100, China
| | - Yu Zhang
- Laboratory for Evolution & Development, Institute of Evolution & Marine Biodiversity and Department of Marine Biology, Ocean University of China, Qingdao 266003, China
- *Yu Zhang: and
| | - Shicui Zhang
- Laboratory for Evolution & Development, Institute of Evolution & Marine Biodiversity and Department of Marine Biology, Ocean University of China, Qingdao 266003, China
- *Shicui Zhang:
| |
Collapse
|
9
|
Botta PE, Simó I, Sciara AA, Arranz SE. Growth hormone receptors in the atherinid Odontesthes bonariensis: characterization and expression profile after fasting-refeeding and growth hormone administration. JOURNAL OF FISH BIOLOGY 2016; 88:1870-1885. [PMID: 27097742 DOI: 10.1111/jfb.12954] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Accepted: 02/16/2016] [Indexed: 06/05/2023]
Abstract
In order to improve the understanding of pejerrey Odontesthes bonariensis, growth hormone (Gh)-insulin-like growth factor-1(Igf1) axis, O. bonariensis growth hormone receptor type 1 (ghr1) and type 2 (ghr2) mRNA sequences were obtained. Both transcripts were ubiquitously expressed except in kidney, encephalon and anterior intestine. Alternative transcripts of both receptors were found in muscle. Interestingly, two different ghr2 transcripts with alternative polyadenylation (APA) sites located in the long 3' untranslated region (UTR-APA) were also found in liver. Hepatic ghr1, ghr2 and insulin-like growth factor type 1 (igf1) transcript levels were examined under two different metabolic conditions. In the first experimental condition, fish were fasted for 2 weeks and then re-fed for another 2 weeks. Despite igf1 mRNA relative expression did not show significant differences under the experimental period of time examined, both ghr transcripts decreased their expression levels after the fasting period and returned to their control levels after re-feeding. In the second treatment, recombinant O. bonariensis growth hormone (r-pjGh) was orally administered once a week. After 4 weeks of treatment, liver igf1, ghr1 and ghr2 mRNA relative expression increased (13, 4·5 and 2·1 fold, P < 0·05) compared to control values. These results add novel information to the growth hormone-insulin-like growth factor system in teleosts.
Collapse
Affiliation(s)
- P E Botta
- Instituto de Biología Molecular y Celular de Rosario, CONICET - Área Biología, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, 2000 Rosario, Argentina
| | - I Simó
- Instituto de Biología Molecular y Celular de Rosario, CONICET - Área Biología, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, 2000 Rosario, Argentina
| | - A A Sciara
- Instituto de Biología Molecular y Celular de Rosario, CONICET - Área Biología, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, 2000 Rosario, Argentina
| | - S E Arranz
- Instituto de Biología Molecular y Celular de Rosario, CONICET - Área Biología, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, 2000 Rosario, Argentina
| |
Collapse
|