TnP as a Multifaceted Therapeutic Peptide with System-Wide Regulatory Capacity

Abstract

Background: The candidate therapeutic peptide TnP demonstrates broad, system-level regulatory capacity, revealed through integrated network analysis from transcriptomic data in zebrafish. Our study primarily identifies TnP as a multifaceted modulator of drug metabolism, wound healing, proteolytic activity, and pigmentation pathways. Results: Transcriptomic profiling of TnP-treated larvae following tail fin amputation revealed 558 differentially expressed genes (DEGs), categorized into four functional networks: (1) drug-metabolizing enzymes (cyp3a65, cyp1a) and transporters (SLC/ABC families), where TnP alters xenobiotic processing through Phase I/II modulation; (2) cellular trafficking and immune regulation, with upregulated myosin genes (myhb/mylz3) enhancing wound repair and tlr5-cdc42 signaling fine-tuning inflammation; (3) proteolytic cascades (c6ast4, prss1) coupled to autophagy (ulk1a, atg2a) and metabolic rewiring (g6pca.1-tg axis); and (4) melanogenesis-circadian networks (pmela/dct-fbxl3l) linked to ubiquitin-mediated protein turnover. Key findings highlight TnP’s unique coordination of rapid (protease activation) and sustained (metabolic adaptation) responses, enabled by short network path lengths (1.6–2.1 edges). Hub genes, such as nr1i2 (pxr), ppara, and bcl6aa/b, mediate crosstalk between these systems, while potential risks—including muscle hypercontractility (myhb overexpression) or cardiovascular effects (ace2-ppp3ccb)—underscore the need for targeted delivery. The zebrafish model validated TnP-conserved mechanisms with human relevance, particularly in drug metabolism and tissue repair. TnP’s ability to synchronize extracellular matrix remodeling, immune resolution, and metabolic homeostasis supports its development for the treatment of fibrosis, metabolic disorders, and inflammatory conditions. Conclusions: Future work should focus on optimizing tissue-specific delivery and assessing genetic variability to advance clinical translation. This system-level analysis positions TnP as a model example for next-generation multi-pathway therapeutics.

1. Introduction

Existing anti-inflammatory therapies are limited to steroidal and non-steroidal anti-inflammatory agents. Sadly, chronic use of these drugs is reported to allegedly cause severe adverse effects like gastrointestinal, cardiovascular, and renal abnormalities [1]. In this context, there is a critical need to discover new anti-inflammatory agents with selective action, higher efficacy, and reduced toxicity. Not only does the complexity of different inflammatory processes pose a challenge for pharmaceutical chemists, but the identification of new compounds with desirable activity and pharmacokinetic properties remains a core setback in the new drug development pipeline [1,2].

Over the last few years, naturally sourced molecules or natural compounds have emerged as a significant source of drug candidates being evaluated for their anti-inflammatory actions [1]. Typically, natural products are considered safe, efficacious, biocompatible, and cost-effective alternatives for treating inflammatory diseases, and developing derived drugs is a rational and productive strategy [3]. Still, toxin-based molecules and animal toxin-derived peptides are promising and interesting sources of new anti-inflammatories, which have been widely explored. Notably, peptides from microorganisms, plants, and animals have been suggested as having superior therapeutic properties compared to human counterparts, which include higher potency, selectivity, and in vivo stability, gaining considerable interest as potential therapeutic options for inflammatory conditions [4,5].

Within this framework, our group has been working with the TnP family of synthetic cyclic peptides, first discovered in the venom of the Brazilian fish Thalassophryne nattereri. TnP has great potential to offer an alternative therapy to inflammatory conditions, is patented in several countries, and has had its therapeutic potential confirmed in murine models of experimental autoimmune encephalomyelitis (EAE) for multiple sclerosis (MS) and asthma as well as miRNA-mediated neutrophilia control in tail-amputated zebrafish challenged with lipopolysaccharide (LPS) [6,7,8].

Among the various immunomodulatory effects of TnP, its role in regulating the entry of inflammatory cells, including macrophages, Th1, and Th17 lymphocytes, into the central nervous system (CNS) is noteworthy [9]. Additionally, it inhibits the expression of α4β1 integrin receptors on the blood-brain barrier, a crucial event that precedes perivascular infiltration and disease onset [6].

Using zebrafish as a preclinical toxicology model, we demonstrated a broad therapeutic index, with non-lethal doses ranging from 1 nM to 10 μM and no observed neurotoxicity or cardiotoxicity, supporting TnP’s potential as a promising therapeutic candidate [10].

Omics-based approaches, such as genome-wide transcriptional profiling, offer a powerful strategy to address current limitations in drug screening by enabling comprehensive analysis of drug-induced gene expression changes [11]. Transcriptomics offers a comprehensive view of molecular alterations by quantifying ribonucleic acid (RNA) transcripts across the entire genome at a given time, thereby revealing drug-responsive gene expression patterns [12]. This approach aids in target identification (proteins physically binding to the drug or to proteins that are only functionally related), efficacy and toxicity evaluation, and optimization of dosing regimens.

In this study, we aimed to assess the molecular clues of the therapeutic anti-inflammatory effect of TnP during early signaling in a zebrafish wound-injury model, using tail fin amputation. To achieve this, we performed an integrative gene expression analysis across transcriptomic profiling datasets from TnP-treated tail-fin-amputated zebrafish. The differentially expressed genes (DEGs) were then mapped to the STRING on Cytoscape database to construct protein-protein interaction (PPI) networks. Functional clusters within these networks were subsequently identified.

2. Results

2.1. TnP Significantly Impacts Drug Metabolism Networks

One of the most crucial setbacks in today’s scientific process, particularly in drug development programs, is the need for efficient experimental models. These models typically require elevated costs, are time-consuming, and yield limited success rates. Although the use of alternative approaches to animal experimentation has been increasing in the last decade, to advance the drug discovery pipeline, animal experimentation is still vital. For this reason, the vertebrate zebrafish model is a promising option due to its well-known characteristics, such as high genetic similarity to humans, rapid development, high reproducibility, and lower cost compared to traditional rodent counterparts. Additionally, it offers versatility in drug screening, enabling toxicity assessment and large-scale effectiveness. Zebrafish have been efficiently used in high-throughput screening, safety assessment (e.g., cardiac toxicity, hepatic toxicity, and neurotoxicity), validation of therapeutic targets, and studies of mechanisms of action [13,14].

Not only showing efficacy but also understanding the mechanism of action within a living whole-animal system is one of the essential barriers to drug discovery [15]. Often, several compounds have activity in the first stages of study, i.e., in vitro or cell systems; unfortunately, they do not always represent a similar context for an organ or tissue within the body. There are examples of some drugs that are effective in humans but not in zebrafish, and vice versa. Nevertheless, over 20 years of drug screening in zebrafish suggest that, in general, molecules active in zebrafish exhibit similar activity in mice and humans, with comparable pharmacokinetic properties [16].

For certain drugs, zebrafish replicate human responses even more accurately than mouse models. Thalidomide, for example, caused thousands of congenital disabilities in unborn children. In mice, it did not induce any defects. On the other hand, in zebrafish, thalidomide triggered morphological limb defects similar to those in humans [15].

Remarkably, the use of zebrafish for drug screening and pharmacological studies has received increasing attention in the fields of drug absorption, distribution, metabolism, and excretion (ADME) because of the similarity of drug metabolism between zebrafish and mammals [17,18,19].

Therapeutic peptides are a class of pharmaceutical agents made from chains of amino acids used to treat various conditions. This type of medicine can be engineered or isolated from natural sources and then chemically synthesized. Therefore, peptide drug development has emerged as a prominent topic in pharmaceutical research. There are many examples of peptide drugs; insulin, for example, is the first commercial peptide drug and has been thoroughly used to treat diabetes for many years. This class of drugs is distinguished by their ability to have multiple therapeutic effects, as they target specific receptors by mimicking natural signaling molecules (e.g., hormones, cytokines), which can lead to diverse physiological responses [20]. Also, they may play multiple roles, serving as both anti-inflammatory agents and immune modulators. Importantly, peptides function in immune system modulation, making them effective in treating multiple conditions.

In this context, TnP is a drug candidate with considerable therapeutic potential. Besides its beneficial effects in mice, previous results suggest cellular activation after treatment, notably through the Aryl Hydrocarbon Receptor-Cytochrome P450 (AHR-CYP) axis in zebrafish. In order to understand the molecular signature of the therapeutic effect of the TnP treatment in the inflammation model based on tail fin amputation, we performed the whole sequencing of the transcriptome in zebrafish larvae, identifying that TnP exposure altered the molecular response to inflammation by modulating genes related to acute neutrophil infiltration, among others [21].

The accumulation of gene transcriptional profiling data provides us with an unprecedented opportunity to explore the common specific pathways involved in TnP’s anti-inflammatory effect at the system level. Using an injured larvae-treated model (100 mM TnP), we identified 558 DEGs compared to untreated control.

From this set, we grouped the DEGs into four expert-selected categories: (I) drug metabolizing enzymes, (II) cellular traffic, (III) cell activity, and (IV) signaling pathways. These subsets were used to construct the corresponding PPI networks using STRING in Cytoscape, although the same genes can participate in different molecular processes in parallel. The final list ended with the following number of genes regulated by TnP in each class: in I, 74 were upregulated and 24 downregulated; in II, 80 were upregulated and 25 downregulated; in III, 57 were upregulated and 49 downregulated; and in IV, 66 were upregulated and 80 downregulated, as reported in Supplementary Table S1. Genes that remained unannotated or did not align with the defined major categories were not included.

Drug perturbation can be observed through differentially expressed (i.e., deregulated) genes located near drug targets in the network topology. The association between deregulated genes and drug targets can be assessed by analyzing shortest-path distances in functional interaction networks, where affected genes may represent either direct interactors or proximal neighbors of the drug target [22].

Once a drug is administered to zebrafish, it undergoes a series of enzymatic reactions driven by drug-metabolizing enzymes (DMEs)—a diverse group responsible for the biotransformation of endogenous and exogenous compounds. These reactions are categorized primarily into Phase I (functionalization) and Phase II (conjugation) metabolism, mirroring the hepatic metabolism pathways observed in humans [23].

Phase I reactions, predominantly catabolic, involve oxidation, reduction, or hydrolysis of drug compounds [23]. The CYP family plays a central role in these reactions, acting as the primary catalysts and regulators of metabolic clearance [24]. Zebrafish possess a complete set of CYP enzymes, many of which share high sequence homology with their human homologs involved in endogenous metabolism. However, xenobiotic-metabolizing CYPs show greater interspecies variability, meaning some drugs may be processed differently in zebrafish compared to humans [19,25].

Phase II reactions, in contrast, are anabolic and involve conjugation—the addition of hydrophilic groups to enhance excretion. Key enzymes in this phase include UDP-glucuronosyltransferases (UGTs), glutathione S-transferases (GSTs), sulfotransferases (SULTs), methyltransferases, and N-acetyltransferases (NATs) [24,26]. These pathways further demonstrate the functional conservation between zebrafish and human drug metabolism, reinforcing the zebrafish as a valuable model for pharmacological studies.

Regarding the drug metabolism process, the intrayolk administration of the TnP the day before the injury-induced inflammation activated the classic metabolizing pathways (Figure 1 and Figure 2 and

Table 1. List of the genes included in the network analysis performed by STRING on Cytoscape in each of the corresponding categories.

Likely Biological Function	Gene Symbol	Gene Name
Drug-metabolizing enzymes	ido1	Indoleamine 2,3-dioxygenase 1
	gstt1b	Glutathione S-transferase theta 1b
	gpx3	Glutathione peroxidase 3
	ugt5c3	UDP glucuronosyltransferase 5 family, polypeptide C3
	ces2b	Carboxylesterase 2b
	ugt5a2	UDP glucuronosyltransferase 5 family, polypeptide A2
	cyp1a	Cytochrome P450, family 1, subfamily A
	abcc2	ATP-binding cassette, sub-family C (CFTR/MRP), member 2
	cyp2k21	Cytochrome P450, family 2, subfamily k, polypeptide 21
	hsd11b1lb	Hydroxysteroid (11-beta) dehydrogenase 1-like b
	ugt1a1	UDP glucuronosyltransferase 1 family, polypeptide A1
	cyp3a65	Cytochrome P450, family 3, subfamily A, polypeptide 65
	cyp2p6	Cytochrome P450, family 2, subfamily P, polypeptide 6
	cyp2n13	Cytochrome P450, family 2, subfamily N, polypeptide 13
	cyp2v1	Cytochrome P450, family 2, subfamily V, polypeptide 1
	cyp2k18	Cytochrome P450, family 2, subfamily K, polypeptide 18
	cyp3c3	Cytochrome P450, family 3, subfamily c, polypeptide 3
	cyp2aa11	Cytochrome P450, family 2, subfamily AA, polypeptide 11
	cyp4v7	Cytochrome P450, family 4, subfamily V, member 2b
	slc7a7	Solute carrier family 7 member 7
	slc15a1b	Solute carrier family 15 member 1b
	slc6a15	Solute carrier family 6 member 15
	slc43a2a	Solute carrier family 43 member 2
	slc6a19b	Solute carrier family 6 member 19b
	cyp7a1	Cytochrome P450, family 7, subfamily A, polypeptide 1
	abca1a	ATP-binding cassette, sub-family A (ABC1), member 1A
	abcg1	ATP-binding cassette, sub-family G (WHITE), member 1
	lratb.2	Lecithin retinol acyltransferase b, tandem duplicate 2
	rpe65a	Retinoid isomerohydrolase RPE65 a
	rgra	Retinal G protein coupled receptor a
	slc20a2	Solute carrier family 20 member 2
	slc34a2b	Solute carrier family 34 member 2b
	slc15a4	Solute carrier family 15 member 4
	slc26a3.2	Solute carrier family 26 member 3, tandem duplicate 2
	cytb	Cytochrome b, mitochondrial
	znf704	Zinc finger protein 704
	slc16a6b	Solute carrier family 16 member 6b
	slc16a9a	Solute carrier family 16 member 9a
	lcat	Lecithin-cholesterol acyltransferase
	mogat2	Monoacylglycerol O-acyltransferase 2
	smpdl3b	Sphingomyelin phosphodiesterase acid like 3B
	gpcpd1	Glycerophosphocholine phosphodiesterase 1
	pdk4	Pyruvate dehydrogenase kinase, isozyme 4
	pdk2a	Pyruvate dehydrogenase kinase 2a
	abcb11b	ATP binding cassette subfamily B member 11
	slc10a2	Solute carrier family 10 member 2
	cyp24a1	Cytochrome P450, family 24, subfamily A, polypeptide 1
	slc8a1b	Solute carrier family 8 member 1b
Cellular traffic	myhb	Myosin, heavy chain b
	mylz3	Myosin, light polypeptide 3, skeletal muscle
	myha	Myosin, heavy chain a
	mybpc2a	Myosin binding protein Ca
	tmem184ba	Transmembrane protein 184ba
	gabarapb	GABA(A) receptor-associated protein b
	urgcp	Upregulator of cell proliferation
	ednrba	Endothelin receptor Ba
	vwa11	Von Willebrand factor A domain containing 11
	cxcr3.3	Chemokine (C-X-C motif) receptor 3, tandem duplicate 3
	tlr5a	Toll-like receptor 5a
	tlr5b	Toll-like receptor 5b
	muc5.1	Mucin 5.1, oligomeric mucus/gel-forming
	cdhr2	Cadherin related family member 2
	cdhr5b	Cadherin-related family member 5b
	LOC568392	Cadherin-1-like
	cdc42ep1a	CDC42 effector protein (Rho GTPase binding) 1a
	nhsa	NHS actin remodeling regulator
	gabrd	Gamma-aminobutyric acid type A receptor subunit delta
	drd1b	Dopamine receptor D1b
	ifngr1	Interferon gamma receptor 1
	crfb16	Cytokine receptor family member B16
Cell activity	c6ast4	Six-cysteine containing astacin protease 4
	prss59.1	Serine protease 59, tandem duplicate 1
	prss1	Serine protease 1
	cpa1	Carboxypeptidase A1 (pancreatic)
	cpa5	Carboxypeptidase A5
	serpinf2a	Serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), member 2a
	cpb1	Carboxypeptidase B1
	cela1.4	Chymotrypsin like elastase family member 1, tandem duplicate 4
	cel.1	Carboxyl ester lipase, tandem duplicate 1
	pdia2	Protein disulfide isomerase family A, member 2
	amy2a	Amylase alpha 2A-like 2
	meltf	Melanotransferrin
	cel.2	Carboxyl ester lipase, tandem duplicate 2
	ela2	Elastase 2
	cpa4	Carboxypeptidase A4
	atg2a	Autophagy related 2A
	ulk1a	Unc-51 like autophagy activating kinase 1a
	mlst8	MTOR associated protein, LST8 homolog (S. cerevisiae)
	anpepb	Alanyl (membrane) aminopeptidase b
	ace2	Angiotensin I converting enzyme 2
	bcl6ab	BCL6A transcription repressor b
	bcl6aa	BCL6A transcription repressor a
	lct	Lactase
	g6pca.1	Glucose-6-phosphatase catalytic subunit 1a, tandem duplicate 1
	mb	Myoglobin
	tg	Thyroglobulin
	ppp6r2b	Protein phosphatase 6, regulatory subunit 2b
	ppp3ccb	Protein phosphatase 3, catalytic subunit, gamma isozyme, b
Signaling pathways	pmelb	Premelanosome protein b
	dct	Dopachrome tautomerase
	tyr	Tyrosinase
	pmela	Premelanosome protein a
	fbxl3l	F-box and leucine-rich repeat protein 3, like
	fbxl8	F-box and leucine-rich repeat protein 8
	LOC100004499	Stereocilin
	chs1	Chitin synthase 1
	chia.2	Chitinase, acidic.2
	chia.1	Chitinase, acidic.1
	ucp3	Uncoupling protein 3
	lpin1	Lipin 1a
	pnpla2	Patatin-like phospholipase domain containing 2
	crebrf	Creb3 regulatory factor
	klhl24b	Kelch like family member 24
	histh1l	Histone H1 like1
	h1-10	H1.10 linker histone

). Our integrated analysis of genes deregulated by TnP reveals its extensive influence on biological networks crucial for drug metabolism and transport. As shown in Figure 1, TnP treatment significantly perturbs functional networks through direct and indirect mechanisms, with important implications for pharmacological interactions.

“Cytochrome P450” and “solute carrier (SLC)-mediated transport” had the largest gene counts, implying that TnP strongly modulates these pathways. The network topology analysis demonstrates that TnP-upregulated genes are predominantly involved in drug metabolism (including key genes such as cyp3a65, cyp2k18, cyp1a, cyp2n13, and cyp7a1) and gatekeepers of cellular flux (particularly transporters like slc7a7, slc15a1b, slc16a6b, abcc2, and abcb11b). These genes show direct connectivity (shortest-path distances ≤ 1) to known drug targets, suggesting TnP may substantially alter drug metabolism and distribution. For instance, these CYP enzymes drive Phase I xenobiotic metabolism, oxidizing drugs and toxins to prepare them for elimination. Cyp3a65 and cyp2k18 are critical in drug ADME. As highlighted in Figure 1, these genes collaborate with UGTs (e.g., ugt1a1, ugt5a2) for Phase II conjugation, forming a detoxification cascade, and cyp7a1 bridges drug metabolism and lipid homeostasis by initiating bile acid synthesis. Particularly, abcc2 and abcb11b export drug metabolites, influencing bioavailability and toxicity. Slc7a7 and slc15a1b mediate amino acid uptake, and slc16a6b transports monocarboxylates, supporting energy metabolism.

Key hub genes with high network centrality (degree centrality ≥ 10) emerge as critical regulators of TnP effects. These include UGTs, such as ugt1a1, ugt5a2, and ugt5c3, which are responsible for catalyzing glucuronidation, rendering lipophilic compounds water-soluble for excretion. Their synergy with CYPs, for example, occurs through the generation of metabolites by cyp3a65, which are further processed by ugt1a1.

The map of the TnP effect illustrates the interaction between cyp7a1 and slc10a2 (bile acid transporter) in bile acid synthesis. Bidirectional interaction between lcat (esterifies cholesterol) and abca1a (mediates cholesterol efflux) regulates cholesterol. Disruption of these players may alter lipid profiles and bile acid signaling.

TnP induced other genes, such as gstt1b, ido1, and specifically gpx3 (an antioxidant), playing a role in mitigating oxidative stress induced by CYP activity. Meanwhile, ido1 modulates inflammation via tryptophan metabolism, potentially linking TnP to immune regulation.

Conversely, TnP downregulates genes involved in fatty acid metabolism, which may reflect compensatory mechanisms or secondary metabolic effects. The biological and clinical implications of this analysis suggest that TnP’s dysregulation of cyp3a65 or abcc2 could elevate toxicity or reduce the efficacy of co-administered drugs (e.g., statins, antifungals). Altered cyp7a1 or lcat activity may perturb cholesterol homeostasis, and the gpx3/gstt1b hubs suggest that TnP influences redox balance, with implications for cytotoxicity. This dual regulation pattern indicates that TnP simultaneously activates detoxification pathways while suppressing specific metabolic processes.

The upregulated gene network analysis reveals that TnP induces broad transcriptional reprogramming, primarily targeting drug-processing hubs (CYPs, UGTs, and SLC/ABC transporters)—risking drug–drug interactions (DDIs)—, metabolic regulators (cyp7a1, lcat), potentially disrupting lipid homeostasis, and redox sensors (gpx3, ido1), implicating TnP in oxidative stress and inflammation modulation.

Our integrated analysis demonstrates that TnP has a significant impact on drug metabolism networks through direct target modulation, core gene-mediated pathway regulation, and broad metabolic reconfiguration.

2.2. TnP Promotes Wound Healing Through Multi-Pathway Regulation

In this study, our next objective was to decipher the molecular regulators of immune cell trafficking, thereby characterizing the immunomodulatory potential of the TnP and identifying new therapeutic targets for inflammatory resolution pathways. The temporal resolution of the model allows precise tracking of neutrophils between 0–12 h post injury (hpi) (phase of dominated oxidative burst) and macrophages between 12–48 hpi (cytokine signaling phase). The late phase (48–72 hpi) is characterized by inflammation resolution and tissue remodeling [27,28].

Our network analysis of TnP effects reveals its multifaceted role in regulating cellular processes through direct interactions (shortest-path distance ≤ 1) with key pathways and genes (Figure 3 and Figure 4 and Table 1). The most prominent impact occurs in striated muscle contraction, where TnP upregulates myosin-related genes (myhb, mylz3, myha, mybpc2a) that interact with tmem184ba (a membrane protein) and gabarapb (a GABA receptor-associated protein), linking muscle function to neuronal signaling. This suggests that TnP modulates cell contractility through myosin-actin dynamics.

Simultaneously, TnP influences innate immunity and immune-inflammatory signaling through two principal mechanisms: tlr5a/tlr5b (Toll-like receptors—TLR), cxcr3.3 (chemokine receptor), ifngr1, crfb16, cdc42 axis, and mucin-chemokine crosstalk. Genes such as ifngr1, crfb16, and cxcr3.3 crosstalk with tlr5 to promote cytokine release and chemotaxis. Direct connectivity between tlr5a/b and the guanosine triphosphatase (GTPase) modulator cdc42ep1a likely positions TnP as an immunomodulator, particularly in responses to Gram-negative pathogens. The muc5.1-vwa11 (von Willebrand factor domain)/cxcr3.3 axis suggests that TnP may regulate neutrophil recruitment, extracellular matrix (ECM) stability, and mucosal immunity.

Notably, TnP targets neuro-immune hubs with high betweenness centrality, including gabrd (Gamma-Aminobutyric Acid—GABA receptor), drd1b (dopamine receptor), and ednrba (endothelin receptor), which are connected to cytokine pathways (crfb16, ifngr1), implying that TnP bridges neural and immune responses. This could modulate inflammatory tone and leukocyte extravasation, as observed in the endothelial interaction between ednrba and cxcr3.3. The cadherin-related markers cdhr2, cdhr5b, loc568392 (cadherin-like), and cdc42ep1a (GTPase regulator) induced by TnP in the interface with GTPase signaling, potentially altering actin cytoskeleton remodeling via cdc42, receptor internalization, and cellular trafficking.

TnP’s coordinated regulation of these networks presents both opportunities and challenges. First, TnP could enhance tissue repair via myosin-cdc42-driven cell recruitment and balance inflammation through GABA-tlr5 crosstalk. The potential risks include muscle hypercontractility resulting from myhb/myha overexpression or mucosal barrier dysfunction due to muc5.1 disruption.

Overall, TnP emerges as a multi-network modulator that integrates mechanical forces (myosin-actin dynamics), immune coordination (TLR-chemokine signaling), and neuroimmune communication (GABA-dopamine-cytokine axes), potentially enhancing wound healing processes.

2.3. TnP Coordinates Proteolytic and Metabolic Pathways

As demonstrated in Figure 5 and Figure 6 and Table 1, TnP coordinates a complex network of proteolytic and metabolic pathways, driving ECM remodeling, intracellular protein turnover, and metabolic adaptation. The network reveals a dominant cluster of metalloproteases, including c6ast4 (astacin family) and cpa1/cpa4/cpa5 (carboxypeptidases), which collectively facilitate ECM degradation, neuropeptide processing, and tissue restructuring. These enzymes interface with serine proteases, such as prss59.1, prss1 (serine proteases), and ela2, forming a tightly regulated cascade that balances proteolytic activity through inhibitors like serpinf2a and quality control mechanisms involving pdia2. This system enables precise control over processes ranging from chronic wound healing to coagulation.

A critical feature of TnP’s action is its integration of proteolysis with autophagy and metabolic signaling. The lipolytic-autophagy axis, involving cel.1/cel.2 (carboxyl ester lipases) and atg2a/ulk1a (autophagy initiation), demonstrates how lipid breakdown fuels autophagosome formation under mechanistic target of rapamycin (mTOR) regulation by mlst8. This coupling ensures efficient cellular clearance while maintaining energy homeostasis. Meanwhile, metabolic crosstalk emerges through unexpected connections, such as the glucose-thyroid axis, where g6pca.1 (a gluconeogenic regulator) interacts with thyroglobulin (tg) processing and lactose metabolism (lct), suggesting TnP-mediated metabolic rewiring during fasting or stress.

Transcriptional regulation further refines this system, with bcl6 paralogs (bcl6aa/b) repressing both protease genes (ela2) and metabolic enzymes (lct), indicating epigenetic control over digestive and degradative functions. Additionally, phosphatase checkpoints, particularly ppp3ccb (calcineurin-like) and ppp6r2b (PP6 regulatory subunit), modulate muscle energetics (via myoglobin interaction) and autophagy initiation, ensuring precise phosphorylation-dependent signaling.

The network’s efficiency is underscored by its short path length (1.6 edges), enabling rapid, system-wide responses. TnP acts as a biological synchronizer, temporally coordinating the activation of acute proteases with sustained cytoskeletal remodeling and spatially localizing activity to focal adhesions (e.g., cpa4-integrin interactions). This capacity for multi-compartment regulation—spanning extracellular (c6ast4, ela2), membrane-bound (anpepb), and intracellular (atg2a) processes—positions TnP as a versatile therapeutic candidate. Potential applications include fibrosis treatment via ECM remodeling, metabolic syndrome intervention through g6pca.1 modulation, and neuro-immune communication tuning via protease-inhibitor balance (serpinf2a-prss1).

However, the system’s sensitivity necessitates careful optimization to avoid adverse effects, such as excessive tissue degradation from unchecked ela2 activity or cardiovascular disruptions via ace2-ppp3ccb signaling. Future studies should prioritize temporal resolution of TnP’s effects and patient-specific modeling to account for genetic variability (e.g., bcl6 polymorphisms). By harnessing its unique ability to synchronize proteolytic, metabolic, and signaling networks, TnP offers a promising framework for addressing complex diseases that require the coordinated intervention of multiple pathways.

2.4. TnP Regulates Pigmentation, Metabolism, and Ubiquitin Signaling

Figure 7 and Table 1 highlights the signaling pathways orchestrated by TnP, which are associated with specific biological processes, including melanogenesis, lipid metabolism, ubiquitin-dependent protein degradation, and chitin metabolism. The analysis reveals strong connectivity between genes involved in pathways related to pigmentation, melanosome organization, and metabolic regulation.

Central to this network is the melanogenic machinery, where structural proteins PMELA/PMELB form the melanosome matrix scaffold alongside enzymatic regulators dct and tyr, which drive melanin synthesis. This pathway intersects with circadian control through F-box proteins FBXL3L/FBXL8, which link ubiquitin-mediated degradation of clock proteins to melanocyte differentiation rhythms. The system exhibits remarkable coupling between melanosome biogenesis (pmela-pmelb-dct axis), protein turnover (fbxl3l ubiquitin ligase activity), and chitin metabolism (chs1-chia.1/2 interaction).

TnP further modulates a metabolic-desmosome network, where lipid homeostasis regulators, such as ucp3 (mitochondrial uncoupling), lpin1 (phosphatidic acid phosphatase), and pnpla2 (adipose triglyceride lipase), unexpectedly interface with structural components. These interactions bridge desmosome maintenance (via klhl24b) with chromatin organization (histh1l-h1-10), suggesting that TnP influences skin barrier integrity through energy metabolism and nuclear-cytoplasmic signaling in pigment cells.

The ubiquitin-proteasome system emerges as a critical node, with TnP regulating polyubiquitination specialists (fbxl3l/fbxl8), chaperone-like factors (crebrf), and metabolic interfaces (pnpla2 ubiquitination). Collectively, these findings position TnP as a multi-compartment coordinator that synchronizes circadian protein turnover with melanogenesis, nuclear-cytoplasmic lipid droplet communication, and desmosome integrity, thereby maintaining energy homeostasis.

The network’s short path lengths (average 2.1 edges) enable TnP to regulate rapid ubiquitin-mediated events and sustain metabolic adaptations simultaneously, highlighting its potential as a therapeutic agent for pigmentary, metabolic, and circadian disorders. Future studies should explore tissue-specific delivery mechanisms to optimize these effects while minimizing off-target impacts on cardiac and adipose function.

3. Discussion

The comprehensive transcriptomic and network analysis of TnP’s effects in zebrafish reveals, in descending order of importance, its broad influence on drug metabolism, wound healing, proteolytic pathways, and pigmentation/metabolic signaling. These findings highlight TnP as a promising multi-target therapeutic candidate with implications for inflammation resolution, tissue repair, and metabolic regulation.

TnP exerts a profound effect on drug metabolism by modulating cytochrome P450 enzymes, phase II conjugation pathways (UGTs, GSTs), and membrane transporters (SLC/ABC family). The upregulation of key genes (e.g., cyp3a65, cyp2k18, ugt1a1, abcc2) suggests enhanced xenobiotic detoxification, while interactions with cyp7a1 and lcat indicate potential effects on lipid homeostasis. These findings imply that TnP may alter the pharmacokinetics of co-administered drugs, calling for caution in clinical applications to avoid drug-drug interactions.

Notably, TnP also influences the redox balance (gpx3, gstt1b) and immune modulation (ido1), linking drug metabolism to inflammatory responses. The dual regulation of metabolic activation (CYPs) and suppression (fatty acid metabolism genes) suggests a complex, context-dependent mechanism that warrants further investigation.

TnP might accelerate tissue repair by modulating muscle contraction (myhb, mylz3, myha), innate immunity via tlr5-cdc42 and mucin-chemokine axes (tlr5a/b, cxcr3.3, ifngr1), and neuro-immune crosstalk (gabrd, drd1b, ednrba). The tlr5-cdc42 axis suggests that TnP enhances pathogen recognition and leukocyte recruitment, while interactions between cadherins and GTPases (cdhr2, cdc42ep1a) indicate roles in cell adhesion and migration. Additionally, mucin-chemokine interactions (muc5.1, vwa11) suggest modulation of the mucosal barrier. These findings position TnP as a potential therapeutic for chronic wounds, enabling synchronized progression through inflammatory to resolution phases; however, risks such as hypercontractility or excessive inflammation must be considered.

TnP activates a protease network (c6ast4, cpa1/4/5, prss59.1) that facilitates ECM remodeling, which is crucial for wound healing and fibrosis resolution. Integrating autophagy (atg2a, ulk1a) and metabolic signaling (g6pca.1, thyroglobulin) indicates that TnP optimizes energy utilization during tissue repair. Key regulatory nodes include bcl6 paralogs, which suppress proteases and metabolic genes (ela2, lct) and phosphatases (ppp3ccb, ppp6r2b), which modulate muscle energetics and autophagy. This system-wide coordination highlights TnP’s potential in fibrosis treatment and metabolic disorders, though excessive protease activity could lead to tissue damage.

TnP influences melanogenesis (pmela/pmelb, dct, tyr) and circadian protein turnover (fbxl3l/fbxl8), linking pigmentation to ubiquitin-dependent degradation. It also modulates lipid metabolism (ucp3, lpin1, pnpla2) and desmosome integrity (klhl24b), suggesting roles in skin barrier function and metabolic diseases. The short path lengths in this network indicate rapid, synchronized regulation, making TnP a candidate for pigmentary disorders (e.g., vitiligo) and circadian dysfunction.

4. Materials and Methods

4.1. TnP Peptide

TnP trifluoroacetate compound (C₆₃H₁₁₄N₂₂O₁₃S₄, 97.3% purity, IPR[CRKMPGVKMC]-NH2, MW 1516.00, pI 10.63) synthesized in the solid phase was purchased from GenScripts (#P13821401; Piscataway, NJ, USA) and diluted in 1× E3 embryo medium (5 mM NaCl, 0.17 mM KCl, 0.33 mM CaCl, and 0.33 mM MgSO₄ dissolved in MilliQ water, pH 7.0).

4.2. Zebrafish Injury Model and TnP Treatment

Fertilized eggs of wild-type AB zebrafish were provided by the Karolinska Institutet Zebrafish Core Facility (Solna, Sweden) and raised until 48 h post fertilization (hpf) at 28 °C in 1× E3 embryo medium. For the treatment, a working solution of 100 mM TnP or ultra-pure water as a control was injected (2–4 nL) into the yolk of manually dechorionated embryos. For manipulation, embryos were anesthetized with tricaine methane sulfonate at 0.02% (#MS-222, Sigma Aldrich, St. Louis, MO, USA). One day after the TnP treatment, at 72 hpf, an injury-induced inflammation model was established in the larvae by tail fin amputation, as described in Disner et al. [21]. The caudal fin was chosen for investigation because its characteristics allow for the study of the process of early sterile inflammatory response, and it is the largest of the zebrafish fins, simplifying manipulation and observation [29]. Larvae were kept in standard raising conditions for recovery and to mount the inflammatory response for two hours. Then, larvae were sampled (10 per group; quadruplicate) in RNAlater Stabilization Solution (Invitrogen, Carlsbad, CA, USA) before further processing. The experimental procedures adhered to ethical principles and complied with strict animal welfare guidelines. They were conducted in accordance with the EU Directive 2010/63/EU on the protection of animals used for scientific purposes.

4.3. RNA Purification and Sequencing

RNA purification was performed using the RNeasy Plus Universal Mini Kit (Qiagen, Hilden, Germany; #73404) following the manufacturer’s instructions. mRNA purification, cDNA synthesis, and clustering were performed as described in Disner et al. [21]. The library preparation was sequenced on a state-of-the-art Illumina NovaSeq platform using a short-read sequencing strategy, generating 150 bp paired-end reads.

4.4. Data Analysis

Cleaned data were mapped to the Danio rerio reference transcriptome provided by Ensembl GRCz11 V.109, and the transcripts were quantified with the Salmon tool, version 0.8.2 [30]. Then, the gene expression matrix was constructed using quantified transcripts with the R/Bioconductor Tximeta package, version 1.0.3 [31]. We used the ensemble packages org.Dr.eg.db to annotate the quantified transcripts according to V.109 of the reference ensemble used for quantification [32,33].

For differential expression (DE) analysis, counts from the filtered gene expression matrix, limited to protein-coding genes, were used. Genes with a total count of less than 10 across all samples and replicates were removed. The compared groups involving induced inflammation and TnP treatment underwent DE analysis using the R/Bioconductor DESeq2 package [34]. The p-values were calculated using the Wald test and adjusted via the Benjamini–Hochberg approach to control the false-discovery rate. Genes with an adjusted p-value (p_adj) ≤ 0.05 were identified as differentially expressed genes (DEGs). A log2 fold change (FC) threshold of ± 0.5 was also applied for significance (DEGs = p_adj < 0.05, log2FC ± 0.5).

Protein-protein interactions network of upregulated DEGs identified in the study was performed in STRING on Cytoscape v3.10.3 [35] for the following expert-driven categories: (I) drug metabolizing enzymes, (II) cellular traffic, (III) cell activity, and (IV) signaling pathways. STRING is an established tool for interpreting and reducing newly acquired genetic screening datasets, and its link to functional associations helps to suggest evidence of a specific partnership between two proteins [36]. In addition, functional enrichment analysis was conducted using DAVID software v2023q4 [37], where enriched terms were considered significant if the adjusted p-value was less than 0.05 and the gene count at least 3.

5. Conclusions

In conclusion, TnP emerges as an integrated modulator with therapeutic potential, most notably in the resolution of inflammation, wound healing, and drug metabolism, and to a lesser extent in metabolic and pigmentary disorders. However, its broad effects demand careful consideration while dosing to avoid off-target impacts (e.g., DDIs, excessive proteolysis). Other limitations include the lack of dose comparisons and the exploratory nature of this study, which was primarily based on global gene expression profiles, potentially reducing organ or tissue specificity. Additionally, although the expert-driven categorization of the DEGs into functional groups helps narrow down the uncovered therapeutic effects of the candidate peptide, one must consider the multiple roles of the genes, which can participate concurrently in different pathways. Moreover, the levels of expression do not necessarily reflect the corresponding proteins due to regulatory checkpoints, and the functional interpretation based on enrichment analysis may be limited by the available genomic annotation for the zebrafish model. Future studies should validate TnP’s effects in mammalian models to assess translational potential, investigate tissue-specific delivery to minimize systemic side effects, and explore combinatorial therapies (e.g., with anti-fibrotic or metabolic drugs).

This study integrated gene expression profiling and protein-protein interaction networks to characterize the multi-target mechanisms of TnP systematically. Network proximity analysis revealed that TnP significantly modulates key biological processes, including Phase I drug metabolism and peptide transport, tissue repair, immune regulation, and neuro-metabolic crosstalk. These findings highlight the broad therapeutic potential of TnP for inflammatory/autoimmune diseases, neuromuscular disorders, and neuroendocrine or neurodegenerative conditions. Overall, TnP represents a novel multi-pathway therapeutic agent, but its clinical application requires careful optimization to harness its benefits while mitigating risks.