Insulin signaling and pharmacology in humans and in corals

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Biochemistry, Biophysics and Molecular Biology


The proposed review aims to conduct an in-depth exploration and comparison of INS signaling pathways in humans and corals, two organisms that exhibit significant evolutionary distance. The necessity of such an investigation arises from the pivotal role INS plays in maintaining glucose homeostasis in mammalian systems, and the potential existence of analogous systems in non-mammalian organisms such as corals. In humans, alterations to INS signaling pathways often result in debilitating metabolic diseases, including diabetes. Conversely, in corals, which are foundational organisms within marine ecosystems, a thorough understanding of potential INS signaling pathways is notably absent. This omission is significant, as corals are currently under considerable threat due to anthropogenic activities and climate change, making insights into their resilience mechanisms vitally important. Bridging knowledge gaps between mammalian and non-mammalian INS signaling has the potential to expand our comprehension of evolutionary biology, provide novel insights into metabolic disease pathophysiology, and afford valuable knowledge for the conservation of coral species.

Intended audience

This review aims to provide valuable knowledge to a diverse scientific audience, encompassing researchers and academics engaged in disciplines such as biochemistry, cellular biology, endocrinology, and marine biology. It seeks to furnish scientists specializing in human metabolism and endocrine disorders with novel insights gleaned from non-mammalian systems. Concurrently, it aspires to equip marine biologists and coral ecologists with a deeper understanding of potential INS signaling within coral biology. Moreover, this review will be beneficial for pharmacologists, particularly those seeking to apply their understanding of human INS signaling to burgeoning fields such as “coral pharmacology.” Educators may find this comparative study valuable as a teaching resource, and students will gain exposure to the application of established biological concepts to innovative contexts. Ultimately, by delineating connections between humans and corals, the review aims to foster interdisciplinary dialogues, encourage collaborative research initiatives, and contribute to both human and coral health.

Evolutionary conservation of INS

INS signaling is an evolutionarily ancient function, as evidenced by the fact that INS-like molecules have been identified in prokaryotes, microbial eukaryotes, insects, invertebrates (including Hydrozoa), and plants (Le Roith et al., 1980; LeRoith et al., 1981; Baig & Khaleeq, 2020). Antibodies raised against human INS recognize INS-like material from unicellular eukaryotes such as Tetrahymena pyriformis, a ciliated protozoan, and Neurospora crassa (Muthukumar & Lenard, 1991; Kole, Muthukumar & Lenard, 1991) and Aspergillus fumigatus, both fungi, and even prokaryotes (LeRoith et al., 1981). The fact that both prokaryotes and eukaryotes synthesize INS suggests that it may play a role in co-evolution.

Conservation at the sequence level is mirrored by conservation at the functional level (Abou-Sabe’ & Reilly, 1978; Le Roith et al., 1980). For example, effects of mammalian INS on E. coli have been described (Abou-Sabe’ & Reilly, 1978; LeRoith et al., 1981); similarly, INS shows metabolic effects on N. crassa cells such as enhanced glucose metabolism, enhanced growth, improved viability, and accumulation of intracellular sodium (Muthukumar & Lenard, 1991; Kole, Muthukumar & Lenard, 1991). INS-like preparations from more primitive organisms have effects on rat cells (Schmidt, Siegel & Creutzfeldt, 1985; Aguan et al., 1994; Cheng et al., 2007). These functional effects are likely achieved through a phosphorylation cascade as shown by the enhanced phosphorylation of specific proteins on serine/threonine and tyrosine residues (Kole, Muthukumar & Lenard, 1991).

Recently, an INS-INSR pair has been described in detail for Acanthamoeba castellanii, an early mitochondrial unicellular eukaryotic organism (Baig & Khaleeq, 2020). Not only did they show typical mammalian INS-induced effects on Acanthamoeba cells, but they also investigated the anti-diabetic drug metformin, and conducted homology modeling of the putative Acanthamoeba INS-INSR pair. This study strongly supports the notion of a high degree of conservation of the INS-INSR pair across billions of years of evolution and pioneers the use of a human antidiabetic drug (metformin) in the context of a primitive organism.

Most recently, remote homologues of INS and INSR have been identified in the stony coral, Pocillopora damicornis (Roger et al., 2022), using a new bioinformatics pipeline for identifying functions in non-model organisms (Kumar et al., 2023) based on remote homology detection suitable for comparison of sequences that show large divergence due to evolutionary separation called HHblits (Remmert et al., 2011). The conservation of INS signaling in corals is also seen in another cnidarian, Hydra, which belong to another phylum of cnidarian. Corals have evolved before the split into Deuterostomia such as humans and Protostomia like the model organisms C. elegans and Drosophila melanogaster 700 million years ago (mya). The Anthozoa-Hydrozoa separation, i.e., the coral-Hydra separation, occurred >500 mya (Khalturin et al., 2019). In Hydra, a receptor protein-tyrosine kinase responding to an INS-like molecule was found to be involved in regulating cell division and differentiation (Steele et al., 1996).

These evidences for evolutionary conservation of INS and its function open the door to comparison of model and non-model organisms. Most of our understanding of the function of INS comes from studies in human as a model organism. We will therefore first review what is known about INS in humans and then compare the findings in detail to one non-model organism, Pocillopora damicornis. Because corals are threatened by extinction, we hope that the extension of our understand from the well-studied human INS pharmacology may provide clues to how we could treat the growing problem of coral bleaching and stimulate a new era of “coral pharmacology”.

Introduction to glucose homeostasis and insulin function in humans

The primary source of energy for most cells in the body is glucose and it is also a substrate for many biochemical reactions (Nakrani, Wineland & Anjum, 2023). Blood glucose levels in the body are maintained and balanced by glucose homeostasis (Da Silva Xavier, 2018), as outlined in Fig. 1. Glucose, as a highly polar molecule, cannot diffuse into the lipid membranes of cells and its transport is therefore facilitated by glucose transporters (GLUTs), a family of 12 members (Navale & Paranjape, 2016). Glucose is phosphorylated upon entering the cell and is broken down through glycolysis, followed by oxidative phosphorylation of pyruvate in the TCA cycle, generating ATP (Fukunaga & Hunter, 1997; Watowich et al., 1999). Alternatively, it is polymerized to glycogen for storage of excess glucose (Nakrani, Wineland & Anjum, 2023). To maintain the balance between these opposing processes resulting in regulated blood glucose levels hormones are produced from a group of multicellular endocrine cells called Islets of Langerhans (Da Silva Xavier, 2018). On average, the human pancreas contains 3.2 million islets. Islets consist of four major types of cells: α-cells, β-cells, δ-cells, and pancreatic polypeptide (PP)-cells (Erlandsen et al., 1976; Da Silva Xavier, 2018). β-cells produce and store insulin (INS) which lowers blood glucose levels, while α-cells produce glucagon (GCG) raising blood glucose concentrations, and δ-cells produce somatostatin (SST) which inhibits the secretion of growth hormones and GCG, while PP cells secrete gastrointestinal and intestinal enzymes (Erlandsen et al., 1976), shown in Fig. 1.

The role of insulin signaling in glucose regulation.

Figure 1: The role of insulin signaling in glucose regulation.

(Left) Regulation of blood glucose in humans. The rise in the blood glucose level releases INS from the pancreas into the bloodstream. This INS stimulates the liver to convert blood glucose into glycogen for storage and SST secreted inhibits GCG secretion. When blood glucose level is low, pancreas release GCG, which causes the liver to turn stored glycogen back into glucose and release it into the bloodstream. SST in this case inhibits INS secretion. (Right) Schematic of Islet of Langerhans architecture. Created with

INS release is triggered when the glucose concentration in blood rises above 90 mg/dL (5 mM) (Steiner et al., 1967; Fu, Gilbert & Liu, 2013). GLUT1 mediates intracellular glucose transport in the β-cells and triggers the immediate release of INS into the blood from β-cells. INS then binds to insulin receptors (INSRs) on target tissues (Steiner et al., 1967; Xu, Paxton & Fujita-Yamaguchi, 1990; Bremser et al., 1999). This is followed by a cascade of phosphorylation reactions initiated by INSR resulting in mitogenic and widespread metabolic effects of INS such as activation of the phosphatidylinositol-3-kinase (P13K) signaling pathway as described in detail below and references (Xu, Paxton & Fujita-Yamaguchi, 1990; Jones et al., 1991; Vainikka et al., 1994; Fukunaga & Hunter, 1997; Watowich et al., 1999; Hennige et al., 2000; Zhang et al., 2006; Kuo et al., 2007). INS signaling stimulates glucose translocation by INS-responsive GLUT4 and uptake of glucose by target tissues (Steiner et al., 1967; Kawanishi et al., 2000). GLUT4 is found in skeletal muscle, heart, brain and adipose tissues (Navale & Paranjape, 2016). Many putative intra-islet messengers have been implicated in regulating INS secretion, including ATP, Zn2+, γ-aminobutyric acid (GABA), and glucagon-like peptide-1 (GLP-1) (Reetz et al., 1991; Franklin & Wollheim, 2004; El et al., 2021). GABA released from β-cells binds and activates GABAA receptors on α- and δ-cells, which in turn mediates glucose-dependent GCG release and increases SST secretion via activation of INSR on α- and δ-cells, respectively (Xu et al., 2006; Braun et al., 2009). Glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 are secreted in response to ingestion of glucose and amino acids in the gut (El et al., 2021). In the pancreas, binding of GIP and GLP-1 to G protein coupled receptors (GPCRs) such as GLP-1R and glucagon receptor (GCGR) activates adenylyl cyclase/adenylate cyclase 8 (ADCY8) increasing intracellular cAMP signals and stimulates release of INS, GCG and SST (Moreau et al., 2006; Cheng et al., 2007; Fridlyand & Philipson, 2016). GCG from the pancreatic α-cells is the primary proglucagon derived peptide (PGDP) and GLP-1 and GLP-2 are related to GCG as they are co-encoded within the same proglucagon gene (Drucker, 2005). GLP-1 has been reported to improve insulin resistance and increase insulin sensitivity in obese and diabetic humans by modulating endoplasmic reticulum stress response via mTOR signaling pathway inhibition and activation of central GLP-1R (Sinclair & Drucker, 2005; Parlevliet et al., 2010; Jiang et al., 2018). GLP-2 is co-secreted with GLP-1 in the gut but very little is known about its action on glucose regulation in humans. So far, it is clear that GLP-2 is not involved in INS release (Schmidt, Siegel & Creutzfeldt, 1985; Sinclair & Drucker, 2005; Amato, Baldassano & Mulè, 2016). However, when GLP-2 is injected into healthy non-obese humans and diabetic patients, it increases glucagon secretion in plasma (Meier et al., 2006; Amato, Baldassano & Mulè, 2016). In humans afflicted by obesity and type 2 diabetes there is an association between GLP-2 and INS resistance with beneficial effects on glucose metabolism (Amato, Baldassano & Mulè, 2016). The main function of GLP-2 are energy uptake regulation and maintenance of intestinal mucosal integrity, function, and morphology (Amato, Baldassano & Mulè, 2016).

In summary, INS controls the glucose levels in the body and stimulates update of glucose which accumulates and is converted to glycogen and fat within muscles, liver, and adipose tissues (Quesada et al., 2008). GCG counterbalances INS action by activating glycogenolysis and gluconeogenesis in the liver. SST inhibits endocrine hormone secretions. The evidence so far further suggests that GLP-1 is involved in INS release, and less in INS signaling, while the role of GLP-2 in INS signaling has not yet been widely investigated.

Understanding these hormone actions and their downstream signaling pathways is crucial because of the clinical relevance for diabetes. Diabetes is a metabolic disorder in which the body produces less INS or has reduced sensitivity to INS. GLP-1R agonists are well-studied for the treatment of diabetes as they regulate blood glucose by increasing INS secretion and inhibit GCG secretion and appetite (Drucker, 2005). In the standard treatment for advanced diabetes, INS is supplied to compensate (Drucker, 2005). However, the INSR itself has also been considered a potential drug target to stimulate INS signaling by using INS ligands that directly bind to and activate the receptor (Kumar, Vizgaudis & Klein-Seetharaman, 2021). Other proteins such as GLUT-4 are also drug targets (Bouché et al., 2004), and one of the most successful drugs to treat diabetes, metformin (Bouché et al., 2004), likely has multiple targets, including the INSR (Bouché et al., 2004).

Survey/search methodology

Our comprehensive literature search was conducted using an array of scientific databases, including but not limited to PubMed, Google Scholar, and Web of Science. This multi-platform approach was implemented to ensure the broadest possible coverage of available literature.

Our search strategy involved the use of key terms and phrases, carefully chosen for their relevance to the subject matter. These included “insulin signaling,” “insulin receptor,” “corals,” “glucose homeostasis in corals,” “coral bleaching,” “coral pharmacology,” and “coral metabolism.” Additionally, we used Boolean operators to refine our searches, combining terms such as “insulin AND corals,” “insulin signaling AND corals,” “insulin receptor in corals,” and “insulin signaling in corals AND diabetes in humans”.

To ensure an unbiased and objective review, we utilized a set of pre-determined inclusion and exclusion criteria. Inclusion criteria encompassed peer-reviewed research articles, reviews, reports, and meta-analyses published in English within the past two decades. A particular emphasis was placed on studies published within the past 5 years to maintain a focus on current and emergent findings. We sought to include a comprehensive range of literature, focusing not only on recent studies but also incorporating seminal works that have significantly contributed to the field, regardless of their publication date. Inclusion criteria encompassed peer-reviewed research articles, reviews, reports, and meta-analyses published in English, with a strong emphasis placed on studies that have had a substantial impact on the field. While a special emphasis was placed on literature published within the past 5 years to highlight the most current and emergent findings, we also included older literature, particularly those fundamental to our understanding of insulin signaling in humans and corals.

Exclusion criteria involved literature that did not directly pertain to insulin signaling in either humans or corals, studies not subjected to peer-review, and non-English publications. Furthermore, we considered the citation count of each study, using it as a metric of its impact within the scientific community. Following the identification of relevant literature, each publication underwent a meticulous review process. The gathered information was then synthesized and critically evaluated to highlight the current understanding of insulin signaling in humans and corals, identify gaps in knowledge, and provide a comprehensive view of potential future research directions.

Systems biology of INS in humans: INS-related signal transduction cascades

The complexity of the INS-related signal transduction pathways is depicted in Fig. 2, and the proteins involved are listed in Table 1. Proteins are separated by pathway involvement based on whether the pathways are initiated by GCG, GLP-1, INS, or SST. Note that GLP-2 is omitted from Fig. 2 due to our gaps in knowledge of how it interfaces with the action of the other hormones and downstream signaling pathways. Full protein names, UniProt entry names, PDAM ID, E-value, P-value, sequence identity, similarity and references regarding biological function are provided and all protein isoforms of a related gene are listed in Tables 1 and 2 are discussed together. A total of 75 proteins (excluding isoform counting) are involved across the three pathways in humans (GCG and GLP-1 receptor binding events are treated as one pathway for simplicity). Of these, 17 proteins function exclusively within the GCG/GLP-1 signaling pathway, while 36 are exclusive to canonical INS signaling, and 10 are exclusive to the SST pathway. Eleven proteins are involved in two of the pathways, while only one protein is ubiquitous to all three pathways AKT (RAC-α/β/γ serine/threonine-protein kinase). Inhibitory signaling is found in GCG and INS pathways, while only stimulatory signaling is maintained in the SST pathway.

Overview of insulin related signaling pathways.

Figure 2: Overview of insulin related signaling pathways.

Conservation of INS-related signaling pathways. Proteins (and their associated isoforms as detailed in Table 1) are represented by their gene name. Proteins exclusive to the GCG signaling pathway are colored in blue and proteins exclusive to INS signaling are colored in orange, while those of the SST signaling pathway are colored pink; proteins involved in two or more pathways are shaded light green. Created with
Table 1:
Proteins related to human insulin signaling.
Full list of proteins involved in INS and INS-related signaling pathways (i.e., GCG and SST signaling), detailing associated pathway, full name, UniProt entry name, and references to biological function.
Gene Protein UniProtKB Reference
ADCY8 Adenylate cyclase type 8 P40145 (ADCY8_HUMAN) Leech, Castonguay & Habener (1999)
CALM* Calmodulin-1
Tsang et al. (2006) and Chattopadhyaya et al. (1992)
CBP CREB-binding protein Q92793 (CBP_HUMAN) Zhang & Bieker (1998)
CREB1 Cyclic AMP-responsive element-binding protein 1 P16220 (CREB1_HUMAN) O’Donovan et al. (1999)
CRTC2 CREB-regulated transcription coactivator 2 Q53ET0 (CRTC2_HUMAN) Iourgenko et al. (2003)
GCG* Pro-glucagon P01275 (GLUC_HUMAN) Orskov, Wettergren & Holst (1993)
GCGR* Glucagon receptor P47871 (GLR_HUMAN) MacNeil et al. (1994)
GLP-1* Glucagon-like peptide 1 P01275 (GLUC_HUMAN) Orskov, Wettergren & Holst (1993)
GLP-1R* Glucagon-like peptide 1 receptor P43220 (GLP1R_HUMAN) Thorens et al. (1993)
GNAQ Guanine nucleotide-binding protein G(q) subunit alpha P50148 (GNAQ_HUMAN) Alvarez-Curto et al. (2016)
GNAS Guanine nucleotide-binding protein G(s) subunit alpha isoforms short
Guanine nucleotide-binding protein G(s) subunit alpha isoforms Xlas
Neuroendocrine secretory protein 55
P63092 (GNAS2_HUMAN)


O95467 (GNAS3_HUMAN)
Pak, Pham & Rotin (2002);
Montrose-Rafizadeh et al. (1999) and Zill et al. (2002)
IP3R Inositol 1,4,5-trisphosphate receptor type 3 Q14573 (ITPR3_HUMAN) Holz et al. (1999)
PFKFB1 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 1 P16118 (F261_HUMAN) Algaier & Uyeda (1988)
PGC-1α Peroxisome proliferator-activated receptor gamma coactivator 1-alpha Q9UBK2 (PRGC1_HUMAN) Knutti, Kaul & Kralli (2000)
PLC 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase gamma-1 P19174 (PLCG1_HUMAN) Rönnstrand (2004)
PYGL Glycogen phosphorylase, liver form P06737 (PYGL_HUMAN) Zhang et al. (2012)
SMEK Serine/threonine-protein phosphatase 4 regulatory subunit 3B
Serine/threonine-protein phosphatase 4 regulatory subunit 3A
Chowdhury et al. (2008)
ACC Acetyl-CoA carboxylase 2
Acetyl-CoA carboxylase 1
Cheng et al. (2007) and Moreau et al. (2006)
AMPK 5′-AMP-activated protein kinase catalytic subunit alpha-2
5′-AMP-activated protein kinase catalytic subunit alpha-1
P54646 (AAPK2_HUMAN)
Q13131 (AAPK1_HUMAN)
Aguan et al. (1994)
Imamura et al. (2001)
GYS Glycogen [starch] synthase, muscle
Glycogen [starch] synthase, liver
P13807 (GYS1_HUMAN)
P54840 (GYS2_HUMAN)
Chan et al. (2003)
Bruno et al. (2004)
PDE3B cGMP-inhibited 3′,5′-cyclic phosphodiesterase B Q13370 (PDE3B_HUMAN) Wilson et al. (2011)
PHK Phosphorylase b kinase gamma catalytic chain, liver/testis isoform
Phosphorylase b kinase gamma catalytic chain, skeletal muscle/heart isoform
P15735 (PHKG2_HUMAN)

Q16816 (PHKG1_HUMAN)
Brushia & Walsh (1999)
PKA cAMP-dependent protein kinase inhibitor alpha
cAMP-dependent protein kinase catalytic subunit PRKX
cAMP-dependent protein kinase type I-alpha regulatory subunit
cAMP-dependent protein kinase type I-beta regulatory subunit
cAMP-dependent protein kinase catalytic subunit alpha
cAMP-dependent protein kinase type II-alpha regulatory subunit
cAMP-dependent protein kinase catalytic subunit beta
cAMP-dependent protein kinase type II-beta regulatory subunit
cAMP-dependent protein kinase catalytic subunit gamma
cAMP-dependent protein kinase inhibitor beta
cAMP-dependent protein kinase inhibitor gamma
P10644 (KAP0_HUMAN)

P31321 (KAP1_HUMAN)
P13861 (KAP2_HUMAN)

P31323 (KAP3_HUMAN)
Semizarov et al. (1998)
Glesne & Huberman (2006)
Diskar et al. (2010)
Guan, Hou & Ricciardi (2005)
Wang et al. (2000)
Wu et al. (2002)
Mayor et al. (2000)
Miki, Nagashima & Seino (1999)
Dabanaka et al. (2012)
Zhao et al. (2006)
AKT RAC-alpha serine/threonine-protein kinase
RAC-beta serine/threonine-protein kinase
RAC-gamma serine/threonine-protein kinase
P31749 (AKT1_HUMAN)
P31751 (AKT2_HUMAN)
Jones et al. (1991)
Zhang et al. (2006)
4EBP1 Eukaryotic translation initiation factor 4E-binding protein 1 Q13541 (4EBP1_HUMAN) Pause et al. (1994)
aPKC Protein kinase C alpha type
Protein kinase C iota type
Protein kinase C zeta type
Finkenzeller, Marmé & Hug (1990)
Selbie et al. (1993)
Schönwasser et al. (1998)
BAD* Bcl2-associated agonist of cell death Q92934 (BAD_HUMAN) Wang et al. (1999)
EiF4E Eukaryotic translation initiation factor 4E P06730 (IF4E_HUMAN) Yanagiya et al. (2012)
Elk1 ETS domain-containing protein Elk-1 P19419 (ELK1_HUMAN) Gille et al. (1995)
FAS Tumor necrosis factor receptor superfamily member 6 P25445 (TNR6_HUMAN) Cascino et al. (1995)
FBP Fructose-1,6-bisphosphatase 1
Fructose-1,6-bisphosphatase isozyme 2
P09467 (F16P1_HUMAN)
O00757 (F16P2_HUMAN)
El-Maghrabi et al. (1993)
Rakus et al. (2005)
FOXO1 Forkhead box protein O1 Q12778 (FOXO1_HUMAN) Shaodong et al. (1999)
G6PC Glucose-6-phosphatase catalytic subunit 1
Glucose-6-phosphatase 2
Glucose-6-phosphatase 3
P35575 (G6PC1_HUMAN)
Pan et al. (1998)
Petrolonis et al. (2004)
Martin et al. (2002)
GK Glycerol kinase
Glycerol kinase 2
Glycerol kinase 3
Q14410 (GLPK2_HUMAN)
Q14409 (GLPK3_HUMAN)
Stepanian et al. (2003)
Chen et al. (2017)
Ohira et al. (2005)
GLUT1 Solute carrier family 2, facilitated glucose transporter member 1 P11166 (GTR1_HUMAN) Mueckler & Makepeace (2008)
GLUT4 Solute carrier family 2, facilitated glucose transporter member 4 P14672 (GLUT4_HUMAN) Kawanishi et al. (2000)
GRB2 Growth factor receptor-bound protein 2 P62993 (GRB2_HUMAN) Lowenstein et al. (1992)
GSK-3 Glycogen synthase kinase-3 alpha
Glycogen synthase kinase-3 beta
P49840 (GSK3A_HUMAN)
P49841 (GSK3B_HUMAN)
Nikoulina et al. (2000)
Boyle et al. (1991)
HSL Hormone-sensitive lipase Q05469 (LIPS_HUMAN) Holst et al. (1996)
INS Insulin P01308 (INS_HUMAN) Bremser et al. (1999)
INSR Insulin receptor P06213 (INSR_HUMAN) Xu, Paxton & Fujita-Yamaguchi (1990)
IRS Insulin receptor substrate 1
Insulin receptor substrate 2
Insulin receptor substrate 4
P35568 (IRS1_HUMAN)
O14654 (IRS4_HUMAN)
Kuo et al. (2007)
Watowich et al. (1999)
Fantin et al. (1998)
MNK MAP kinase-interacting serine/threonine-protein kinase 1
MAP kinase-interacting serine/threonine-protein kinase 2
Fukunaga & Hunter (1997)
Scheper et al. (2001)
mTOR Serine/threonine-protein kinase mTOR P42345 (MTOR_HUMAN) Kim et al. (2002)
p70S6K Ribosomal protein S6 kinase beta-1
Ribosomal protein S6 kinase beta-2
P23443 (KS6B1_HUMAN)
Pullen et al. (1998)
Nguyen et al. (2018)
PDK1/2 3-phosphoinositide-dependent protein kinase 1
[Pyruvate dehydrogenase (acetyl-transferring)] kinase isozyme 2, mitochondrial
O15530 (PDPK1_HUMAN)
Q15119 (PDK2_HUMAN)
Alessi et al. (1997)
Gudi et al. (1995)
PEPCK Phosphoenolpyruvate carboxykinase, cytosolic [GTP]
Phosphoenolpyruvate carboxykinase [GTP], mitochondrial
Zhao et al. (2010)
Lu et al. (2008)
PIP3 Phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase and dual-specificity protein phosphatase PTEN P60484 (PTEN_HUMAN) Li & Sun (1997)
PPI Protein phosphatase inhibitor 2 P41236 (IPP2_HUMAN) Sakashita et al. (2003)
PYG Pygopus homolog 1
Pygopus homolog 2
Fiedler et al. (2008)
Thompson et al. (2002)
PYK Protein-tyrosine kinase 2-beta Q14289 (FAK2_HUMAN) Lev et al. (1995)
Raptor Regulatory-associated protein of mTOR Q8N122 (RPTOR_HUMAN) Kim et al. (2002)
RAS GTPase Eras
GTPase HRas
GTPase KRas
GTPase NRas
Zhang et al. (2010)
Guil et al. (2003)
Yang et al. (2012)
Yin et al. (2019)
Rheb GTP-binding protein Rheb Q15382 (RHEB_HUMAN) Tee et al. (2002)
S6 Ribosomal protein S6 kinase alpha-1
Ribosomal protein S6 kinase alpha-2
Ribosomal protein S6 kinase alpha-3
Ribosomal protein S6 kinase alpha-4
Ribosomal protein S6 kinase alpha-5
Ribosomal protein S6 kinase alpha-6
Ribosomal protein S6 kinase beta-1
Ribosomal protein S6 kinase beta-2
Ribosomal protein S6 kinase delta-1
Q15418 (KS6A1_HUMAN)
Q15349 (KS6A2_HUMAN)
P51812 (KS6A3_HUMAN)
O75676 (KS6A4_HUMAN)
O75582 (KS6A5_HUMAN)
P23443 (KS6B1_HUMAN)
Q96S38 (KS6C1_HUMAN)
Dalby et al. (1998)
Zhao et al. (1995)
Sutherland, Leighton & Cohen (1993)
Pierrat et al. (1998)
Deak et al. (1998)
Berns et al. (2004)
Pullen et al. (1998)
Nguyen et al. (2018)
Hayashi et al. (2002)
SHC SHC-transforming protein 1
SHC-transforming protein 2
SHC-transforming protein 3
SHC-transforming protein 4
P29353 (SHC1_HUMAN)
P98077 (SHC2_HUMAN)
Q92529 (SHC3_HUMAN)
Rönnstrand (2004)
Warner et al. (2000)
Hennige et al. (2000)
Fagiani et al. (2007)
SHIP2 Phosphatidylinositol 3,4,5-trisphosphate 5-phosphatase 2 O15357 (SHIP2_HUMAN) Habib et al. (1998)
SOS Son of sevenless homolog 1
Son of sevenless homolog 2
Q07889 (SOS1_HUMAN)
Q07890 (SOS2_HUMAN)
Chardin et al. (1993)
Umikawa et al. (1999)
SREBP-1c Sterol regulatory element-binding protein 1 P36956 (SRBP1_HUMAN) Yokoyama et al. (1993)
TSC1 Hamartin Q92574 (TSC1_HUMAN) Tee et al. (2002)
TSC2 Tuberin P49815 (TSC2_HUMAN)
ERK1/2 Mitogen-activated protein kinase 3
Mitogen-activated protein kinase 1
P27361 (MK03_HUMAN)
P28482 (MK01_HUMAN)
Marklund et al. (1993)
Sgouras et al. (1995)
JNK Mitogen-activated protein kinase 8
Mitogen-activated protein kinase 9
Mitogen-activated protein kinase 10
P45983 (MK08_HUMAN)
P45984 (MK09_HUMAN)
P53779 (MK10_HUMAN)
Gupta et al. (1996)
Sluss et al. (1994)
Lisnock et al. (2000)
MEK1/2 Dual specificity mitogen-activated protein kinase kinase 1
Dual specificity mitogen-activated protein kinase kinase 2
Q02750 (MP2K1_HUMAN)
P36507 (MP2K2_HUMAN)
Liu et al. (2004)
Mittal, Peak-Chew & McMahon (2006)
P13K Phosphatidylinositol 3-kinase regulatory subunit alpha P27986 (P85A_HUMAN) Vainikka et al. (1994)
RAF RAF proto-oncogene serine/threonine-protein kinase P04049 (RAF1_HUMAN) Dubois et al. (1997)
BAX Apoptosis regulator BAX Q07812 (BAX_HUMAN) Oltval, Milliman & Korsmeyer (1993)
NF-κB Nuclear factor NF-kappa-B p105 subunit
Nuclear factor NF-kappa-B p100 subunit
P19838 (NFKB1_HUMAN)
Q00653 (NFKB2_HUMAN)
Beinke et al. (2004)
Dobrzanski, Ryseck & Bravo (1994)
P21 Cyclin-dependent kinase inhibitor 1 P38936 (CDN1A_HUMAN) Harper et al. (1993)
P27 Cyclin-dependent kinase inhibitor 1B P46527 (CDN1B_HUMAN) Ishida et al. (2000)
P53 Cellular tumor antigen p53 P04637 (P53_HUMAN) Schneider, Montenarh & Wagner (1998)
SHP1 Tyrosine-protein phosphatase non-receptor type 6 P29350 (PTN6_HUMAN) Keilhack et al. (2001)
SHP2 Tyrosine-protein phosphatase non-receptor type 11 Q06124 (PTN11_HUMAN) Miao et al. (2000)
SST* Somatostatin P61278 (SMS_HUMAN) Luque & Kineman (2018)
SSTR Somatostatin receptor type 1
Somatostatin receptor type 2
Somatostatin receptor type 3
Somatostatin receptor type 4
Somatostatin receptor type 5
P30872 (SSR1_HUMAN)
P30874 (SSR2_HUMAN)
P32745 (SSR3_HUMAN)
P31391 (SSR4_HUMAN)
P35346 (SSR5_HUMAN)
Pasquali et al. (2001)
Grant, Collier & Kumar (2004)
Yamada et al. (1992)
Panetta et al. (1994)
Zac1 Zinc finger protein PLAGL1 Q9UM63 (PLAL1_HUMAN) Kas et al. (1998)
DOI: 10.7717/peerj.16804/table-1


No suitable pdam homolog found.
Table 2:
Remote homology detection of candidate insulin signaling related proteins in Pocillopora damicornis.
Full list of proteins involved in INS and INS-related signaling pathways (i.e., GCG and SST signaling), matched to Pdam ID with number of residues overlayed (Cols), P-value, E-value, matched sequence length, probability, query template length and percentage (%) identity retrieved from hhblits.
Gene Uniport ID Protein name Match columns Pdam ID Prob E-value P-value Aligned Cols Query HMM Template HMM % Identity
ADCY8 P40145 Adenylate cyclase type 8 1,251 pdam_00002623 100 2.80E−94 7.20E–98 983 155–1,179 109–1,111 (1,122) 36
CALM P0DP23; P0DP24; P0DP25 Calmodulin-1; Calmodulin-2; Calmodulin-3 149 pdam_00003911 100 6.70E−42 1.70E–45 143 3–147 75–249 (921) 20
CBP Q92793 CREB-binding protein 2,442 pdam_00013067 100 3E−319 7E–323 2,061 1–2,442 1–2,199 (2,199) 47
CREB1 P16220 Cyclic AMP-responsive element-binding protein 1 327 pdam_00005762 100 7.20E−67 1.30E–70 252 63–327 39–319 (319) 52
CRTC2 Q53ET0 CREB-regulated transcription coactivator 2 693 pdam_00014061 100 2.90E−82 5.10E–86 460 17–693 2–506 (506) 34
GCG* P01275 Pro-glucagon 180 pdam_00011985 13 15 0.0022 12 130–141 5–16 (74) 50
GCGR P47871 Glucagon receptor 477 pdam_00008152 100 1.90E−49 4.00E–53 371 25–431 23–410 (765) 22
GLP-1R P43220 Glucagon-like peptide 1 receptor 463 pdam_00008152 100 1.60E−43 3.30E–47 377 13–424 12–401 (765) 22
GNAQ P50148 Guanine nucleotide-binding protein G(q) subunit alpha 359 pdam_00011071 100 7.50E−77 1.90E–80 352 7–359 1–365 (365) 51
GNAS P63092 Guanine nucleotide-binding protein G(s) subunit alpha isoforms short 394 pdam_00011071 100 3.30E−61 8.20E–65 352 1–393 1–364 (365) 44
Q5JWF2 Guanine nucleotide-binding protein G(s) subunit alpha isoforms XLas 1,037 pdam_00011071 100 4.70E−56 1.20E–59 342 662–1,037 12–365 (365) 44
O95467 Neuroendocrine secretory protein 55 245 pdam_00011481 67.4 0.35 5.00E−05 23 33–55 5–27 (973) 26
IP3R Q14573 Inositol 1,4,5-trisphosphate receptor type 3 2,671 pdam_00007499 100 0.00E+00 0.00E+00 2,511 1–2,668 1–2,653 (2,667) 58
PFKFB1 P16118 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 1 471 pdam_00000774 100 1.60E−69 4.00E−73 424 47–471 1–425 (425) 60
PGC-1α Q9UBK2 Peroxisome proliferator-activated receptor gamma coactivator 1-alpha 798 pdam_00012386 99.7 6.90E−22 1.20E−25 134 663–798 413–548 (559) 40
PLC P19174 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase gamma-1 1,290 pdam_00015403 100 2.00E−170 3.00E−174 1,116 24–1,219 19–1,177 (1,293) 48
PYGL P06737 Glycogen phosphorylase, liver form 847 pdam_00018058 100 3.00E−186 5.00E−190 814 1–834 2–818 (826) 68
SMEK Q5MIZ7 Serine/threonine-protein phosphatase 4 regulatory subunit 3B 849 pdam_00021014 100 2.00E−160 4.00E−164 676 1–725 1–683 (753) 62
Q6IN85 Serine/threonine-protein phosphatase 4 regulatory subunit 3A 833 pdam_00021014 100 6.00E−158 1.00E−161 676 1–692 1–684 (753) 63
ACC O00763 Acetyl-CoA carboxylase 2 2,458 pdam_00001946 100 0.00E+00 0.00E+00 2,163 240–2,458 26–2,210 (2,219) 62
Q13085 Acetyl-CoA carboxylase 1 2,346 pdam_00001946 100 0.00E+00 0.00E+00 2,167 96–2,346 24–2,209 (2,219) 64
AMPK P54646 5′-AMP-activated protein kinase catalytic subunit alpha-2 552 pdam_00023206 100 6.00E−106 1.00E−109 518 9–551 9–551 62
Q13131 5′-AMP-activated protein kinase catalytic subunit alpha-1 559 pdam_00023206 100 5.00E−100 1.00E−103 517 19–558 35–568 (569) 62
GYS P13807 Glycogen [starch] synthase, muscle 737 pdam_00011808 100 5.60E−98 1.00E−101 640 3–662 80–720 (727) 59
P54840 Glycogen [starch] synthase, liver 703 pdam_00011808 100 2.30E−99 5.00E−103 640 3–662 80–720 (727) 59
PDE3B Q13370 cGMP-inhibited 3′,5′-cyclic phosphodiesterase 3B 1,112 pdam_00001873 100 1.00E−165 2.00E−169 926 10–1,090 5–984 (1,033) 36
PHK P15735 Phosphorylase b kinase gamma catalytic chain, liver/testis isoform 406 pdam_00008094 100 2.40E−77 5.70E−81 368 7–379 6–376 (420) 53
Q16816 Phosphorylase b kinase gamma catalytic chain, skeletal muscle/heart isoform 387 pdam_00008094 100 7.60E−83 1.80E−86 370 5–381 8–381 (420) 53
PKA P61925 cAMP-dependent protein kinase inhibitor alpha 76 pdam_00011290 99.4 3.10E−18 5.20E−22 56 1–56 1–57 (70) 30
P51817 cAMP-dependent protein kinase catalytic subunit PRKX 358 pdam_00008088 100 3.40E−56 7.10E−60 315 43–358 202–523 (699) 31
P10644 cAMP-dependent protein kinase type I-alpha regulatory subunit 381 pdam_00010058 100 4.00E−61 1.00E−64 367 8–380 6–372 (373) 70
P31321 cAMP-dependent protein kinase type I-beta regulatory subunit 381 pdam_00010058 100 4.30E−59 1.10E−62 363 13–381 11–373 (373) 70
P17612 cAMP-dependent protein kinase catalytic subunit alpha 351 pdam_00024226 100 2.40E−77 5.70E−81 346 6–351 3–348 (348) 82
P13861 cAMP-dependent protein kinase type II-alpha regulatory subunit 404 pdam_00018522 100 5.10E−63 1.20E−66 381 2–396 59–440 (444) 54
P22694 cAMP-dependent protein kinase catalytic subunit beta 351 pdam_00024226 100 4.80E−76 1.20E−79 344 8–351 5–348 (348) 82
P31323 cAMP-dependent protein kinase type II-beta regulatory subunit 418 pdam_00018522 100 3.90E−61 9.40E−65 378 2–407 60–437 (444) 54
P22612 cAMP-dependent protein kinase catalytic subunit gamma 351 pdam_00024226 100 6.30E−78 1.50E−81 340 12–351 9–348 (348) 75
Q9C010 cAMP-dependent protein kinase inhibitor beta 78 pdam_00011290 99.3 7.50E−17 1.30E−20 59 8–66 1–60 (70) 36
Q9Y2B9 cAMP-dependent protein kinase inhibitor gamma 76 pdam_00011290 99.7 3.00E−23 5.10E−27 52 1–52 1–53 (70) 31
AKT P31749 RAC-alpha serine/threonine-protein kinase 480 pdam_00008116 100 2.40E−70 5.20E−74 331 141–477 55–389 (500) 45
P31751 RAC-beta serine/threonine-protein kinase 481 pdam_00008116 100 1.80E−71 4.00E−75 330 144–478 56–389 (500) 46
Q9Y243 RAC-gamma serine/threonine-protein kinase 479 pdam_00001122 100 2.20E−71 5.00E−65 400 22–441 104–516 (1,524) 25
4EBP1 Q13541 Eukaryotic translation initiation factor 4E-binding protein 1 118 pdam_00003235 100 2.10E−39 3.50E−43 116 1–118 1–119 (119) 55
aPKC P17252 Protein kinase C alpha type 672 pdam_00020998 100 8.00E−134 2.00E−137 648 18–665 10–711 (724) 66
P41743 Protein kinase C iota type 596 pdam_00005220 100 1.00E−139 2.00E−143 573 24–596 8–692 (692) 71
Q05513 Protein kinase C zeta type 592 pdam_00005220 100 5.00E−124 1.00E−127 578 9–592 3–692 (692) 66
BAD* Q92934 Bcl2-associated agonist of cell death 168 pdam_00004189 5.3 34 0.0073 42 119–160 24–65 (293) 12
EiF4E P06730 Eukaryotic translation initiation factor 4E 217 pdam_00019745 100 1.10E−43 2.50E−47 186 32–217 37–232 (232) 63
Elk1 P19419 ETS domain-containing protein Elk-1 428 pdam_00014011 100 6.60E−39 1.30E−42 163 4–177 14–181 (204) 41
FAS P25445 Tumor necrosis factor receptor superfamily member 6 335 pdam_00022994 99.9 4.20E−28 8.90E−32 242 60–317 44–399 (409) 17
FBP P09467 Fructose-1,6-bisphosphatase 1 338 pdam_00021399 100 1.80E−41 4.10E−45 239 7–332 4–244 (246) 61
O00757 Fructose-1,6-bisphosphatase isozyme 2 339 pdam_00021399 100 2.40E−40 5.50E−44 240 6–332 3–244 (246) 57
FOXO1 Q12778 Forkhead box protein O1 655 pdam_0001017 100 6.90E−96 1.30E−99 434 154–639 50–546 (557) 37
G6PC P35575 Glucose-6-phosphatase catalytic subunit 1 357 pdam_00002925 100 4.40E−43 1.10E−46 315 5–348 1–324 (505) 29
Q9NQR9 Glucose-6-phosphatase 2 OS=Homo sapiens 355 pdam_00002925 100 1.00E−43 2.40E−47 318 1–350 1–328 (505) 33
Q9BUM1 Glucose-6-phosphatase 3 346 pdam_00002925 100 7.60E−42 1.80E−45 315 1–338 1–327 (505) 31
GK P32189 Glycerol kinase OS=Homo sapiens 559 pdam_00006960 100 2.00E−47 4.90E−51 427 11–474 8–476 (476) 19
Q14410 Glycerol kinase 2 OS=Homo sapiens 553 pdam_00002235 100 6.50E−46 1.60E−49 470 12–507 5–547 (559) 23
Q14409 Glycerol kinase 3 553 pdam_00006960 100 1.00E−46 2.50E−50 424 11–468 8–476 (476) 18
GLUT1 P11166 Solute carrier family 2, facilitated glucose transporter member 1 492 pdam_00006372 100 1.40E−40 4.10E−44 445 15–470 40–484 (495) 45
GLUT4 P14672 Solute carrier family 2, facilitated glucose transporter member 4 509 pdam_00014912 100 3.60E−39 9.90E−43 437 23–485 27–484 (494) 28
GRB2 P62993 Growth factor receptor-bound protein 2 217 pdam_00010914 100 3.50E−36 1.00E−39 213 1–213 1–217 (218) 63
GSK-3 P49840 Glycogen synthase kinase-3 alpha 483 pdam_00001353 100 2.60E−75 6.70E−79 359 89–447 23–388 (421) 81
P49841 Glycogen synthase kinase-3 beta 420 pdam_00001353 100 2.00E−80 5.00E−84 381 1–383 1–387 (421) 84
HSL Q05469 Hormone-sensitive lipase 1,076 pdam_00001853 100 2.40E−96 5.00E−100 709 304–1,058 19–795 (803) 38
INS P01308 Insulin 110 pdam_00006633 98.8 3.20E−13 6.90E−17 101 2–109 5–116 (116) 24
INSR P06213 Insulin receptor 1,382 pdam_00013976 100 1.00E−187 2.00E−191 1,164 28–1,307 8–1,274 (1,306) 42
IRS P35568 Insulin receptor substrate 1 1,242 pdam_00006434 100 2.40E−36 3.90E−40 268 6–275 8–312 (1,427) 21
Q9Y4H2 Insulin receptor substrate 2 1,338 pdam_00006434 99.9 4.90E−34 7.80E−38 292 25–329 9–337 (1,427) 21
O14654 Insulin receptor substrate 4 1,257 pdam_00015468 99.8 1.90E−26 3.30E−30 217 74–334 9–225 (797) 39
MNK Q9BUB5 MAP kinase-interacting serine/threonine-protein kinase 1 465 pdam_00010796 100 8.90E−49 2.10E−52 369 37–451 99–472 (490) 57
Q9HBH9 MAP kinase-interacting serine/threonine-protein kinase 2 465 pdam_00010796 100 3.00E−52 7.20E−56 374 73–454 100–475 (490) 58
mTOR P42345 Serine/threonine-protein kinase mTOR 2,549 pdam_00009963 100 1.00E−280 4.00E−284 2,353 21–2,548 1–2,369 (2,401) 68
p70S6K P23443 Ribosomal protein S6 kinase beta-1 525 pdam_00008116 100 7.80E−87 1.70E−90 421 24–454 1–425 (500) 71
Q9UBS0 Ribosomal protein S6 kinase beta-2 482 pdam_00008116 100 5.30E−85 1.20E−88 376 48–427 45–422 (500) 70
PDK1/2 O15530 3-phosphoinositide-dependent protein kinase 1 556 pdam_00003014- 100 1.20E−78 2.90E−82 302 175–549 54–356 (360) 65
Q15119 [Pyruvate dehydrogenase (acetyl-transferring)] kinase isozyme 2, mitochondrial 407 pdam_0001703 100 2.10E−51 5.30E−55 390 1–398 1–394 (422) 50
PEPCK P35558 Phosphoenolpyruvate carboxykinase, cytosolic [GTP] 622 pdam_00016705 100 1.00E−187 2.00E−191 605 12–621 41–647 (647) 63
Q16822 Phosphoenolpyruvate carboxykinase [GTP], mitochondrial 640 pdam_00016705 100 1.00E−188 2.00E−192 607 28–639 40–647 (647) 62
PIP3 P60484 Phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase and dual-specificity protein phosphatase PTEN 403 pdam_00003212 100 4.50E−60 1.00E−63 340 2–354 18–357 (436) 52
PPI P41236 Protein phosphatase inhibitor 2 205 pdam_00000730 100 2.50E−38 4.40E−42 142 6–199 4–147 (159) 39
PYG Q9Y3Y4 Pygopus homolog 1 419 pdam_00023740 99.2 1.20E−15 2.40E−19 68 332–400 55–124 (345) 28
Q9BRQ0 Pygopus homolog 2 406 pdam_00023740 99.2 9.60E−16 1.70E−19 93 301–394 74–167 (186) 22
PYK Q14289 Protein-tyrosine kinase 2-beta 1,009 pdam_00008953 100 1.00E−144 2.00E−148 954 36–1,002 20–1,118 (1,124) 42
Raptor Q8N122 Regulatory-associated protein of mTOR 1,335 pdam_00003007 100 8.00E−245 2.00E−248 1,295 12–1,332 11–1,333 (1,338) 64
RAS Q7Z444 RASE_HUMAN GTPase ERas 233 pdam_00018296 99.8 1.30E−26 3.40E−30 165 37–201 11–195 (253) 27
P01112 GTPase HRas 189 pdam_00015181 100 5.30E−35 1.60E−38 180 1–181 1–180 (183) 83
P01116 GTPase KRas OS=Homo sapiens 189 pdam_00015181 99.9 1.40E−33 4.30E−37 183 1–189 1–183 (183) 84
P01111 GTPase NRas 189 pdam_00015181 99.9 4.10E−34 1.20E−37 174 1–175 1–174 (183) 84
Rheb Q15382 GTP-binding protein Rheb 184 pdam_00010612 99.9 4.80E−29 1.50E−32 184 1–184 1–185 (185) 65
S6 Q15418 Ribosomal protein S6 kinase alpha-1 735 pdam_00004023 100 5.40E−98 1.00E−101 591 55–730 110–707 (710) 67
Q15349 Ribosomal protein S6 kinase alpha-2 733 pdam_00004023 100 9.00E−100 2.00E−103 589 52–725 110–705 (710) 69
P51812 Ribosomal protein S6 kinase alpha-3 740 pdam_00004023 100 1.60E−98 4.00E−102 588 60–731 109–704 (710) 69
O75676 Ribosomal protein S6 kinase alpha-4 772 pdam_00021026 100 2.50E−99 6.00E−103 697 23–733 24–728 (757) 60
O75582 Ribosomal protein S6 kinase alpha-5 802 pdam_00021026 100 2.00E−110 5.00E−114 706 30–745 14–727 (757) 66
Q9UK32 Ribosomal protein S6 kinase alpha-6 745 pdam_00021026 100 6.40E−95 1.70E−98 635 54–692 15–676 (757) 44
Q96S38 Ribosomal protein S6 kinase delta-1 1,066 pdam_00020764 99.9 3.20E−33 6.10E−37 167 900–1,066 789–955 (958) 51
SHC P29353 SHC-transforming protein 1 583 pdam_00010704 100 2.10E−84 4.50E−88 441 130–582 10–550 (550) 41
P98077 SHC-transforming protein 2 582 pdam_00010704 100 1.30E−77 2.60E−81 448 122–580 11–549 (550) 38
Q92529 SHC-transforming protein 3 594 pdam_00010704 100 1.60E−74 3.40E−78 443 133–593 20–550 (550) 37
Q6S5L8 SHC-transforming protein 4 630 pdam_00010704 100 1.50E−68 3.20E−72 433 183–619 33–549 (550) 41
SHIP2 O15357 Phosphatidylinositol 3,4,5-trisphosphate 5-phosphatase 2 1,258 pdam_00012957 100 3.00E−124 6.00E−128 735 18–897 2–746 (873) 34
SOS Q07889 Son of sevenless homolog 1 1,333 pdam_00007801 100 2.00E−191 4.00E−195 1,061 8–1,076 4–1,079 (1,252) 56
Q07890 Son of sevenless homolog 2 1,332 pdam_00007801 100 1.00E−192 3.00E−196 1,077 8–1,095 4–1,094 (1,252) 56
SREBP-1c P36956 Sterol regulatory element-binding protein 1 1,147 pdam_00001678 100 3.00E−166 5.00E−170 822 292–1,144 411–1,296 (1,297) 42
TSC1 Q92574 Hamartin 1,164 pdam_00004350 100 6.00E−144 1.00E−147 720 7–771 12–845 (857) 34
TSC2 P49815 Tuberin 1,807 pdam_00021002 100 2.00E−216 4.00E−220 1,595 3–1,807 2–1,826 (1,828) 39
ERK1/2 P27361 Mitogen-activated protein kinase 3 379 pdam_00020223 100 2.90E−74 7.50E−78 346 29–374 40–385 (396) 81
P28482 Mitogen-activated protein kinase 1 360 pdam_00020223 100 1.20E−75 3.00E−79 350 7–356 35–384 (396) 84
JNK P45983 Mitogen-activated protein kinase 8 427 pdam_00012090 100 1.60E−61 3.80E−65 364 24–407 35–424 (426) 37
P45984 Mitogen-activated protein kinase 9 424 pdam_00012090 100 1.90E−61 4.70E−65 330 24–364 35–390 (426) 39
P53779 Mitogen-activated protein kinase 10 464 pdam_00012090 100 2.60E−61 6.40E−65 330 62–402 35–390 (426) 39
MEK1/2 Q02750 Dual specificity mitogen-activated protein kinase kinase 1 393 pdam_00000776 100 1.10E−60 2.90E−64 362 3–374 8–373 (373) 69
P36507 Dual specificity mitogen-activated protein kinase kinase 2 400 pdam_00000776 100 9.10E−58 2.30E−61 359 10–382 12–373 (373) 69
P13K P27986 Phosphatidylinositol 3-kinase regulatory subunit alpha 724 pdam_00005911 100 1.10E−69 2.70E−73 532 176–721 344–889 (894) 38
RAF P04049 RAF proto-oncogene serine/threonine-protein kinase 648 pdam_00015444 100 5.90E−46 1.40E−49 246 342–599 377–628 (715) 23
BAX Q07812 Apoptosis regulator BAX 192 pdam_00002763 99.9 2.90E−33 5.90E−37 177 13–190 47–250 (251) 27
NF-κB P19838 Nuclear factor NF-kappa-B p105 subunit 968 pdam_00003205 100 7.00E−113 1.00E−116 790 39–891 40–860 (926) 46
P21 P38936 Cyclin-dependent kinase inhibitor 1 164 pdam_00006472 99.3 1.90E−16 3.40E−20 70 13–82 22–95 (197) 33
P27 P46527 Cyclin-dependent kinase inhibitor 1B 198 pdam_00006472 99.4 1.60E−17 2.90E−21 83 13–95 11–97 (197) 33
P53 P04637 Cellular tumor antigen p53 393 pdam_00016598 100 2.20E−66 4.00E−70 248 95–352 144–397 (439) 37
SHP1 P29350 Tyrosine-protein phosphatase non-receptor type 6 595 pdam_00004172 100 2.00E−86 5.20E−90 508 3–523 5–513 (590) 59
SHP2 Q06124 Tyrosine-protein phosphatase non-receptor type 11 593 pdam_00004172 100 1.10E−94 2.70E−98 515 2–533 2–517 (590) 65
SST* P61278 Somatostatin 116 pdam_00016702 12.1 13 0.0024 50 28–77 131–197 (325) 28
SSTR P30872 Somatostatin receptor type 1 391 pdam_00013387 100 2.10E−44 5.70E−48 287 57–345 214–520 (773) 18
P30874 Somatostatin receptor type 2 369 pdam_00012380 100 1.20E−46 3.20E−50 304 27–332 199–518 (773) 19
P32745 Somatostatin receptor type 3 418 pdam_00019641 100 3.20E−53 7.20E−57 364 45–412 132–573 (976) 19
P31391 Somatostatin receptor type 4 388 pdam_00004106 100 4.80E−42 1.40E−45 295 39–334 35–342 (380) 21
P35346 Somatostatin receptor type 5 364 pdam_00020795 100 6.40E−44 1.80E−47 290 34–325 28–360 (425) 27
Zac1 Q9UM63 Zinc finger protein PLAGL1 463 pdam_00020164 100 1.70E−34 4.70E−38 218 3–220 114–374 (479) 20
DOI: 10.7717/peerj.16804/table-2


No suitable pdam homolog found (bolded rows); E-value refers to the expected number of random hits for a given alignment score; % Identity is the number of identical residues.

Overview of the INS signaling pathway. The INSR is a disulfide-linked tetramer that contains two α and two β subunits located on the cell surface (Xu, Paxton & Fujita-Yamaguchi, 1990; Bremser et al., 1999; Watowich et al., 1999; Kuo et al., 2007; Kumar, Vizgaudis & Klein-Seetharaman, 2021). The α subunits contain four INS binding sites in the extracellular domain (Xu, Paxton & Fujita-Yamaguchi, 1990; Bremser et al., 1999; Kumar, Vizgaudis & Klein-Seetharaman, 2021). The β subunits contain the intracellular tyrosine kinase domains (Xu, Paxton & Fujita-Yamaguchi, 1990; Kumar, Vizgaudis & Klein-Seetharaman, 2021). INS binding to the α subunits activates tyrosine kinase by changing conformations of the β subunits (Xu, Paxton & Fujita-Yamaguchi, 1990; Bremser et al., 1999; Kuo et al., 2007). This causes phosphorylation of insulin receptor substrates (IRS) and SHC which activates kinase cascades such as the PI3K/AKT and the MAPK signaling pathways (Xu, Paxton & Fujita-Yamaguchi, 1990; Jones et al., 1991; Vainikka et al., 1994; Fukunaga & Hunter, 1997; Watowich et al., 1999; Hennige et al., 2000; Zhang et al., 2006; Kuo et al., 2007). IRS activates PI3K to produce the secondary messenger PI-(3,4,5)trisphosphate (PIP3) by accelerating phosphatidylinositol (PI) phosphorylation across the membrane (Vainikka et al., 1994; Li & Sun, 1997; Fantin et al., 1998). IRS-1 integrates signals from different pathways and is considered the master regulator of INS sensitivity (Xu, Paxton & Fujita-Yamaguchi, 1990; Bremser et al., 1999; Kuo et al., 2007). SHIP2 acts as a PI3K antagonist and is involved in the downregulation of the AKT pathway by PIP3 degradation (Jones et al., 1991; Chardin et al., 1993; Habib et al., 1998; Zhang et al., 2006). PDK1/2 is recruited by PIP3 and phosphorylates AKT on serine/threonine residues (Li & Sun, 1997; Fukunaga & Hunter, 1997; Fantin et al., 1998). Subsequently, AKT phosphorylation activates several substrates including FOXO1 proteins that regulate TCF for gene transcription and GSK3 which regulates GLUT4 translocation to the cell membrane (Boyle et al., 1991; Holst et al., 1996; Shaodong et al., 1999; Nikoulina et al., 2000). Activation of IRS-1 also binds to GRB2 and SOS to activate RAS (Lowenstein et al., 1992; Chardin et al., 1993; Umikawa et al., 1999; Guil et al., 2003; Zhang et al., 2010). Activated SHC catalyzes GTP exchange by activating RAS on the plasma membrane (Warner et al., 2000; Hennige et al., 2000; Guil et al., 2003; Rönnstrand, 2004; Zhang et al., 2010; Yin et al., 2019); RAS activation leads to MAPK cascade activation via ERK phosphorylation (Sgouras et al., 1995; Gupta et al., 1996; Tee et al., 2002; Yang et al., 2012; Yin et al., 2019). The AKT pathway also mediates cell survival including growth, differentiation, and inhibiting apoptosis. INS synthesis at the translational level is mediated by mTOR which phosphorylates INS and promotes INS synthesis (Dalby et al., 1998; Kim et al., 2002; Tee et al., 2002). On the other hand, phosphorylation of serine residues on IRS-1 by its downstream effector protein kinase C-ζ (aPKC) which downregulates INS signaling and impairs P13K activity, constitutes negative feedback mechanism in response to INS (Vainikka et al., 1994; Kim et al., 2002; Kuo et al., 2007; Lee et al., 2008). In response to stimuli such as growth factors, IRS-1 phosphorylates multiple serine/threonine kinases such as p70 S6 kinase (P70S6K), mTOR and JNK (Sluss et al., 1994; Pullen et al., 1998; Deak et al., 1998; Watowich et al., 1999; Berns et al., 2004; Kuo et al., 2007; Nguyen et al., 2018).

Overview of GCG signaling pathway. As described above, glucose levels in the body are largely dependent on the coordinated release of GCG by α-cells and INS by β-cells of pancreatic islet, respectively, as shown in Fig. 1 (Orskov, Wettergren & Holst, 1993; MacNeil et al., 1994; Quesada et al., 2008). During hyperglycemia, INS secretion from β-cells is induced; however, during hypoglycemia α-cell secretion of GCG is induced. GCG exerts action via activation of GCG signaling and ADCY8 by coupling to GPCRs such as GCGR and GLP-1R (Orskov, Wettergren & Holst, 1993; MacNeil et al., 1994; Wang, Liang & Wang, 2013). The effects of INS are thus counterbalanced by GCG and the GCG signaling pathway promotes glucose production (Orskov, Wettergren & Holst, 1993; MacNeil et al., 1994; Quesada et al., 2008). GCG binding activates the receptors GNAS and GNAQ of G protein-mediated signaling (Orskov, Wettergren & Holst, 1993; Montrose-Rafizadeh et al., 1999; O’Donovan et al., 1999; Pak, Pham & Rotin, 2002; Alvarez-Curto et al., 2016). GNAS activates the PKA pathway and cAMP production (Orskov, Wettergren & Holst, 1993; MacNeil et al., 1994; Montrose-Rafizadeh et al., 1999). An increase in intracellular cAMP production phosphorylates CREB transcription factor to increase gluconeogenesis (Zhang & Bieker, 1998; O’Donovan et al., 1999). PKA activation also results in the inhibition of glycolysis by the inactivation of PFKFB which is one of the key enzymes in glucose metabolism (Algaier & Uyeda, 1988; Miki, Nagashima & Seino, 1999; Wang et al., 2000; Wu et al., 2002). GNAQ activates the IP3 calcium (Ca2+) signaling pathway and releases Ca2+ intracellularly which results in ERK1/2 phosphorylation causing CREB activation (Marklund et al., 1993; Sgouras et al., 1995; O’Donovan et al., 1999; Alvarez-Curto et al., 2016). Increased Ca2+ in GCG signaling is mediated by activated ADCY coupled to GLP-1R and GCGR. This activates PKA and phosphorylates Ca2+/calmodulin-dependent kinase II (CAMKII) in an IP3R- and Ca2+-dependent manner (Semizarov et al., 1998; Holz et al., 1999; Wang et al., 2000; Wu et al., 2002; Ding et al., 2004; Guan, Hou & Ricciardi, 2005; Glesne & Huberman, 2006; Diskar et al., 2010). Calmodulin (CALM) is a Ca2+ binding messenger activated upon binding of intracellular secondary Ca2+ and primarily transduces the Ca2+ signal in pancreatic cells (Chattopadhyaya et al., 1992; Tsang et al., 2006). Activation of CAMKII promotes FOXO1 nuclear translocation and plays a role in hepatic glucose production in response to fasting (Chattopadhyaya et al., 1992; Shaodong et al., 1999; Tsang et al., 2006). Hepatic expression of SMEK1/2 is also up-regulated during fasting, which is a key regulator of gluconeogenesis and elevates plasma glucose levels (Chowdhury et al., 2008). This causes dephosphorylation of CRTC2 which is responsible for transcriptional activation of gluconeogenic genes (O’Donovan et al., 1999; Iourgenko et al., 2003; Chowdhury et al., 2008).

Overview of SST signaling pathway. SST is a hormone that is involved in the inhibition of endocrine secretions such as INS, GCG, gastrin, and growth hormones as well as cell proliferation (Yamada et al., 1992; Pasquali et al., 2001; Luque & Kineman, 2018). SST binds to GPCRs called somatostatin receptors (SSTRs), of which there are five isoforms (SSTR1 to SSTR5) (Pasquali et al., 2001). Each receptor has distinct functions, and upon activation induce cascades of signaling pathways including protein tyrosine kinase activity (Yamada et al., 1992; Panetta et al., 1994). Upon tyrosine kinase stimulation, cytoplasmic protein-tyrosine phosphatase SHP1 is activated which triggers anti-proliferative and pro-apoptotic signals such as NF-kB, P53/Bax, and JNK (Sluss et al., 1994; Lisnock et al., 2000; Miao et al., 2000; Keilhack et al., 2001). Meanwhile, activation of SHP2 dephosphorylates the P13K/AKT and MEK pathways (Jones et al., 1991; Marklund et al., 1993; Keilhack et al., 2001; Zhang et al., 2006). This causes inhibition of cell proliferation via upregulation of P27, P21 cyclin kinase inhibitors, and the Zac1 tumor suppressor gene (Harper et al., 1993; Schneider, Montenarh & Wagner, 1998; Ishida et al., 2000). Pancreatic δ-cells secrete SST in response to elevated extracellular glucose concentrations (Hauge-Evans et al., 2009) and, within the islets, SST acts as a paracrine inhibitor of INS and GCG secretion (Hauge-Evans et al., 2009). SST is also a hypothalamic peptide known to inhibit somatic growth by inhibiting pituitary growth hormone (Hauge-Evans et al., 2009; Stengel, Rivier & Taché, 2013).

Introduction to corals

Corals are colonial marine invertebrates (cnidarians) that depend on a symbiotic relationship with dinoflagellate algae of the family Symbiodiniaceae (LaJeunesse et al., 2018). The algae harvest light and synthesize nutrients in exchange for shelter and nitrogen sources (Putnam et al., 2017). Coral reefs cover only 0.1% of the ocean floor but are home to the largest density of animals on earth, rivaling rain forest habitats in species diversity (LaJeunesse et al., 2018). The symbiosis, which was originally thought to be restricted to algae, is now known to extend to a much more complex community than anticipated with thousands of bacteria, bacteriophages, viruses, and fungi, in addition to endosymbiotic algae (Bourne et al., 2009). The entirety of the organism community in a coral is referred to as a holobiont, while the individual cnidarian host animals forming the colonies are called polyps.

The holobiont is characterized by balanced host-microbe molecular interactions. The complexity of these interactions in relation to stress and disease resistance, and recovery grow with every new study as questions arise regarding what molecules are responsible for symbiosis establishment and partner coexistence (Ainsworth & Gates, 2016; Kelly et al., 2021). These inter-partner exchanges are still poorly understood, and this is a particularly severe gap in our knowledge, since it is at the heart of the worldwide phenomenon of coral reef bleaching which refers to the breakdown of symbiosis (particularly the cnidarian host and endosymbiotic algae) due to thermal stress and high irradiance, including that brought about by global climate change. A recent study assessed 100 worldwide locations and found that the annual risk of coral bleaching has increased from an expected 8% of locations in the early 1980s to 31% in 2016 (Hughes et al., 2018; IPCC, 2022). Human impacts on coral reef ecosystems threaten fisheries and tourism, industries valued at hundreds of billions of dollars annually (Putnam et al., 2017). We are in urgent need of innovative solutions to increase corals’ resiliency to anthropogenic activities and facilitate their survival.

Climate change driven coral bleaching has now been recognized as the leading cause of the worldwide decline of coral reef cover and, overall, the biggest threat to reef-building coral survival (Hughes et al., 2017). Mass bleaching events have increased both in frequency and severity since the first recorded event in the 1980s (Oliver, Berkelmans & Eakin, 2018) and show no signs of reprieve as ocean warming gets compounded with traditional climate patterns such as the El Niño-Southern Oscillation (McPhaden, Zebiak & Glantz, 2006). Coral bleaching is the common term used to describe dysbiosis in the coral holobiont, specifically, the breakdown of symbiosis (xenophagy and/or expulsion) between the cnidarian host and the dinoflagellate endosymbionts (i.e., dinoflagellates provide most of the coral tissue pigmentation and as dysbiosis progresses, the tissue becomes transparent, thereby revealing the white calcium carbonate skeleton) (Suggett & Smith, 2020). While the full signaling cascade leading to dysbiosis is still poorly defined, we know it leads to damage to cell membranes, lipids, proteins and DNA via nitro-oxidative stress (i.e., the accumulation of free radicals, reactive oxygen species and reactive nitrogen species), a failing antioxidant machinery (e.g., catalase, ascorbate peroxidase, superoxide dismutase) and the organisms’ innate immune response (Weis, 2008; Lesser, 2011; Suggett & Smith, 2020).

Nitro-oxidative stress is common across aerobic systems and, in the case of the coral holobiont, has been associated with heat-damaged chloroplasts (Tolleter et al., 2013; Alderdice et al., 2022) and other damages to the photosynthetic mechanism through heat and light (Gleason & Wellington, 1993; Lesser & Farrell, 2004; Tolleter et al., 2013; Downs et al., 2013; Alderdice et al., 2022), the composition of the thylakoid membrane lipids (Tchernov et al., 2004), the potential for upregulation of ROS scavenging capacity and molecular chaperons during periods of thermal-, light-, or osmotic stress and hypoxia (Gardner et al., 2016; Levin et al., 2016; Ochsenkühn et al., 2017; Aguilar et al., 2019; Alderdice et al., 2021, 2022), seawater trace metal concentrations (Shick et al., 2011; Ferrier-Pagès, Sauzéat & Balter, 2018; Biscéré et al., 2018; Reich et al., 2023) and N:P ratios (Fabricius et al., 2013; Pogoreutz et al., 2017). Furthermore, bleaching has also been associated with the seawater carbonate saturation horizon and dissolved CO2 levels (i.e., ocean acidification) (Anthony et al., 2008; Crawley et al., 2010).

In the context of coral bleaching induced by heat stress, a study involving the tropical sea anemone Aiptasia pallida identified over 500 up-regulated genes, categorized into Cluster I linked to immunity and apoptosis and Cluster II related to protein folding, with potential regulators influenced by transcription factors NFκB and HSF1. A total of 337 genes in symbiotic anemones exhibited declining expression levels before visible bleaching, suggesting their involvement in algal symbiosis loss (Cleves et al., 2020). These findings hint at potential interactions of these genes with the INS signaling pathway, considering known roles of INS signaling in apoptosis and immune responses (Yuyama et al., 2018). Furthermore, experiments inducing ERK activity in corals via UV radiation and thermal stress (Courtial et al., 2017) and heat-shock experiments on Aiptasia (Sloan & Sawyer, 2016) contribute to our understanding of ERK and AKT phosphorylation and MAPK activities in these organisms, potentially implicating the INS signaling pathway in coral bleaching.

Glucose regulation in corals: an opportunity for understanding INS action in non-model organisms

The symbiotic algae provide as much as 90% of the energy corals consume by light harvesting and photosynthesis (Gierz, Forêt & Leggat, 2017). Thus, corals must be able to measure and regulate nutrient balance (Cunning et al., 2017). Given the crucial role of INS signaling for this task in other organisms, we here hypothesize that INS signaling may also exist in corals, although this hypothesis is purely theoretical and remains to be experimentally validated. Support for this hypothesis comes from transcriptomic studies (Yuyama et al., 2018). A comparison between the expression of INS signaling related genes in the presence and absence of the symbiotic algae strongly suggests that INS signaling is induced at the transcriptomic level in response to algal density in the tissue. A likely interpretation of this finding is that corals need to respond to the sugars produced by the algae through light harvesting and perhaps too much sugar could have detrimental effects on corals, similar to the diabetic response through aberrant INS signaling in humans. The symbiotic interaction between algae and coral involves algae entering the host, and the facilitation of energy and metabolite exchange. Algae utilize seawater substrates to synthesize a spectrum of organic compounds, effectively transferring vital nutrients, including amino acids, small peptides, sugars, carbohydrates, and lipids, to coral cells with glucose being a major metabolite transferred in this exchange as demonstrated by Burriesci and colleagues (Burriesci, Raab & Pringle, 2012). It is also possible that the mechanism for bleaching (loss of symbiotic algae from the coral holobiont) involves an imbalance in nutrient regulation and possible involvement of the INS signaling pathway. This raises an interesting speculation: could corals have diabetes, and could insulin resistance be related to the bleaching that is threatening coral species survival? While corals of course do not have Langerhans islets nor blood, the diabetes analogy at the molecular level may stimulate new ways of thinking about coral and human health (see below).

Indeed, there is evidence for INS signaling in corals at the molecular level. First, remote homology detection using HHblits have identified homologues for human IR and INSR in corals (Roger et al., 2022). HHblits is a so-called Hidden Markov Model (HMM)-based alignment approach developed by Remmert et al. (2011). Unlike traditional HMM profiles, in HHblits, both query and template are HMMs. The search for homologues is through an HMM-HMM alignment and the query HMM is generated by using amino acid distributions which makes this method extremely sensitive. It has been shown that, in many instances, HHblits successfully outperforms the identification and alignment of remote homologues, as compared to the traditional profile HMM approach, such as HMMER3 (Remmert et al., 2011). Given the 700 million years of evolution between corals and humans, this enhanced sensitivity of HHblits is instrumental to the comparison between corals and humans. We have already described the sequence alignments of the ligand-receptor pair, INS with INSR for human and for coral (Roger et al., 2022). In both cases, the alignments were identified with high confidence and cover a large fraction of the sequences: 1,164 out of 1,382 amino acids in the case of INSR and 101 out of 110 in the case of INS. The comparison of the sequences of human insulin (UniProt ID P01308) and Pocillopora damicornis (pdam) protein pdam_00006633, and the extracellular domain of the human INSR (UniProt ID P06213) and pdam_00013976 are shown in Tables 3A and 3B, respectively.

Table 3:
Comparison of the sequences of human insulin and coral insulin.
Sequence comparison of human and Pocillopora damicornis insulin and insulin receptor sequences. A. Comparison of the sequences of human and coral INS. B. Matching residues in human INSR (visible in the 6pxv structure) with corresponding residues in coral INSR.
Amino acid sequence (human INS) Amino acid sequence (coral INS)
Domain Amino acid sequence (human INSR) 6pxv Amino acid sequence (coral INSR)
DOI: 10.7717/peerj.16804/table-3


Indicates missing sequence in the structure.

The finding of a human INS homologue in Pocillopora damicornis has prompted us to test the effect of human INS on corals experimentally (Roger et al., 2022). An average 20% reduction in viability at 100 µg/mL INS concentration was observed in line with its proteotoxicity in other systems (Rege et al., 2020). Due to the importance of INS administration in diabetes, its folding and stability has been studied extensively (Weiss & Lawrence, 2018; Liu et al., 2018). High concentrations of salts are known to promote INS aggregation and misfolding (Grudzielanek et al., 2007; Chatani et al., 2014), and the use of seawater in our experiments may induce similar effects, which may be the cause for the observed cytotoxicity.

As shown in Fig. 2, not only INS and INSR, but a total of 75 proteins (excluding isoform counting) are involved across the three INS related pathways in humans. Application of the non-model organism pipeline described above (Kumar et al., 2023) reveals that the majority of downstream signaling proteins, namely 67 of the 75 human proteins, are likely conserved in Pocillopora damicornis. In Fig. 2, all human proteins shown in black have a predicted Pocillopora damicornis homologue, while those shown in red do not. Crosstalk between the SST, CGC and INS pathways is mediated by several proteins that are common to two or even all three pathways. We were not able to identify suitable Pocillopora damicornis homologues for eight proteins: GLP-1, GLP-1R, CGC, CGCR, SST, SSTR, BAD, and CALM, as judged by their poor e-values as well as low percent alignments of amino acids. It is important to realize that GLP-1R, CGCR and SSTR are all GPCR’s and thus it is difficult to differentiate GPCR variation within organisms as compared to across organisms. This complication has been discussed in detail, and it was proposed that the GPCR repertoire of Pocillopora damicornis is 151 as compared to 825 in human (Kumar et al., 2023). The results of the remote homology search can be accessed through supplementary file S4 of that article, where all three human GPCR sequences (CGCR, SSTR and GLP-1R) are never ranked first for any of the coral GCPR candidates. The most closely related GPCR is pdam_00008152-RA, which is more similar to the GLP-2 receptor than those three. Thus, it may be possible that GLP-2 is a more ancient modulation of the INS pathway than the GLP-1, CGC and SST pathways (Amato, Baldassano & Mulè, 2016). This finding suggests that the lack of interest in GLP-2 in previous human studies reviewed above is perhaps unjustified. It is important to note that these new evidences are computational only and await future experimental validation. While SST, GLP-1 and GCG are the ligands initiating their respective signaling pathways through their respective GPCR’s, BAD is located at the effector end of the main INS pathway, indicating that this pathway is mostly functional. Similarly, CALM functions only to stimulate PYGL in the GCG signaling cascade, and TSC1/2 in INS signaling. Importantly, there is a clear homologue of both INS and the INSR present.

Outlook: coral pharmacology

In this review, we have pointed out numerous possible analogies between human and coral INS biology. The enormous pharmacological importance of treating INS resistance in diabetes makes it tempting to speculate that we can translate what we know about human INS pharmacology to corals, coining a new field of “coral pharmacology” which opens the door to thinking about drug discovery and treatments for corals. While at present we do not know if and how we can deliver medicines to corals in the vast ocean in practical terms, ideas include coating surfaces on which coral larvae settle, or feeding corals or dispersing such compounds into the ocean in proximity to coral reefs. This is not unthinkable given that there are many known examples of small molecules secreted into the ocean used in communication between different inhabitants of a reef, e.g., for attracting fish to anemones (Kamio & Derby, 2017; Saha et al., 2019; Kamio, Yambe & Fusetani, 2022; Morgan et al., 2022) or to mediate biological interactions with surfaces during settling of coral larvae (Petersen et al., 2023). Nanocarriers could also assist with this purpose (Roger et al., 2023). Given the fluid nature of the ocean environment, such small molecules can be dispersed easily and thus the environmental impact of treatment of corals with small molecule “coral drugs” will need to be carefully addressed. Nonetheless, the idea of “coral pharmacology” may open new avenues to think about how to tackle the coral bleaching crisis. How might coral drug discovery look like? The high quality of sequence alignments of INS and INSR with respective coral homologues shown in Table 3 provides an opportunity to exploit the large amount of INSR structural data that has become available recently (McKern et al., 2006; Menting et al., 2013; Gutmann et al., 2018; Weis et al., 2018), especially due to the advances in cryoelectron microscopy (Uchikawa et al., 2019). Shown in Fig. 3 are homology models for the various domains in human used to predict coral INSR using the sequences shown in Table 3B. These models open the door to the first step of future exploration of potential drug targets in coral, exemplified here by the INSR as a drug target, extrapolated from its role as a human drug target (Kumar, Vizgaudis & Klein-Seetharaman, 2021). The concept of “coral pharmacology” aims to develop pharmacological approaches towards potentially treating corals who have been harmed by human activities. Using membrane receptors as a proof of concept, we developed a pipeline for establishing the functional similarities between human and coral membrane receptor signaling systems (Kumar et al., 2023). This pipeline extends to the INS-INSR pair and its related signaling pathway (Fig. 2). Given the role of INS signaling for regulation of nutrient concentration in humans, we surmise that the coral homologues will likely carry out a similar function in corals. This suggests that early metazoans such as corals use the INS system despite their simple organization. This may have major implications for coral bleaching and the communication across cnidarian host and symbiotic algae. Transcriptomic analysis has revealed that INS signaling is clearly affected by the establishment of symbiosis between cnidarian host animals and algal symbionts (Yuyama et al., 2018). Given that one of the major benefits of symbiosis is the delivery of sugars obtained through photosynthesis of the algae to the host, we can expect that the role of INS signaling is analogous in corals to that in humans, despite their evolutionary distance. It is tempting to speculate that under high light conditions, when the algae synthesize excess sugars, that the cnidarian host may experience INS resistance, a hypothesis that remains to be validated experimentally. By inference, pharmacological treatment of INS resistance may allow coral rescue. We have already shown that human INS does have an effect on corals (see above), and in fact is cytotoxic (Roger et al., 2022). The presence of receptors such as IR (described here) and GPCR (described in Kumar et al., 2023) suggests that many other functions of corals could potentially be targeted by pharmacological means to help prevent their extinction predicted under current climate trajectories.

Structure prediction of coral insulin receptor.

Figure 3: Structure prediction of coral insulin receptor.

3D reconstruction of coral INSR. (A) Side view. (B) Top view. (C) Bottom view. (D) Individual domains of coral INSR. Created with the PyMOL Molecular Graphics System, Version 2.5 Schrödinger, LLC.
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