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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and <t>MyD88-mediated</t> signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).
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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and <t>MyD88-mediated</t> signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).
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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and <t>MyD88-mediated</t> signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).
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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and <t>MyD88-mediated</t> signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).
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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and <t>MyD88-mediated</t> signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).
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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and <t>MyD88-mediated</t> signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).
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(A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and MyD88-mediated signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).

Journal: bioRxiv

Article Title: An APP-centered molecular gateway integrates innate immunity and retinoic acid signaling to drive irreversible metamorphic commitment

doi: 10.64898/2026.01.22.700939

Figure Lengend Snippet: (A) Venn diagram illustrating the overlap and distinct partitioning of differentially expressed genes (DEGs) at the early stage of metamorphosis, resulting from the comparison of biofilm stimulation (vs unstimulated larva) and retinoic acid (RA) treatment (vs unstimulated larva). The diagram includes both upregulated and downregulated gene sets across the two comparison groups. (B) Protein-protein interaction (PPI) network derived from the biofilm-specific upregulated DEGs (n = 2,233 genes, defined as upregulated by biofilm but not significantly changed by RA). This network is strongly associated with innate immune and MyD88-mediated signaling. (C-E) Subnetworks highlighting central hubs within the biofilm-specific PPI network: (C) APP-, (D) SRC-, and (E) GSK3B-centered subnetworks. (F) PPI network derived from the RA-specific upregulated DEGs (n = 528 genes, defined as upregulated by RA but not significantly changed by biofilm). This network is functionally enriched in developmental and chromatin-related processes. (G) Subnetwork centered on EP300 and PBRM1 within the RA-specific PPI network. (H) Convergent PPI network derived from the upregulated DEGs common to both stimuli (n = 1,163). This network is functionally enriched in MAPK signaling and differentiation pathways. (I) Subnetwork centered on HSP90AA1, which emerges as a major hub integrating the upstream bacterial and RA signaling. In (C-E, G, I), each subnetwork comprises nodes directly connected to the indicated hub protein (black arrowheads).

Article Snippet: The inhibitors were dissolved in DMSO and applied at the indicated concentrations: the MyD88 inhibitor T6167923 (5 or 50 μM; MedChemExpress), the IKKβ inhibitor IKK-16 (0.1 or 1 μM; MedChemExpress), and MAPK inhibitors SP600125 (JNK), SB202190 (p38), and U0126 (ERK) (1 or 10 μM; MedChemExpress or FUJIFILM Wako Pure Chemical Corporation), and the HSP90AA1 inhibitors luminespib (0.1 or 1 μM; Chemscene).

Techniques: Comparison, Derivative Assay

(A) Settlement rate of inhibitor-treated larvae. The box plots with superimposed jitter plots display the larval settlement rate under various inhibitor treatments. The biofilm stimulus condition is used as the positive control. The concentration of each inhibitor is indicated on the horizontal axis. The data represent the settlement rate of larvae remaining attached out of 10 larvae across six independent biological replicates (total n = 60). Statistical significance among treatment groups was assessed using one-way ANOVA followed by Tukey’s HSD post hoc test, with grouping letters indicating significant differences ( p < 0.05); treatments sharing a letter are not significantly different. (B) Quantitative assessment of the functional hierarchy. The box plots with superimposed jitter plots show the Metamorphic Progression Scores (MPS) for larvae treated with various pharmacological inhibitors with or without all-trans retinoic acid (RA). The MPS was calculated based on the metamorphic stage reached by the larvae in the identical assays used for the settlement rate analysis in (A). The concentration of each inhibitor is indicated on the horizontal axis. The MPS represents the average metamorphic stage reached (0 = brachiolaria; 1 = early; 2 = middle; 3 = late; 4 = pre-juvenile; 5 = juvenile). Statistical significance among the treatment groups was assessed using one-way ANOVA followed by Tukey’s HSD post hoc test ( *p < 0.05; n.s., not significant). A significant RA-dependent rescue condition (a statistically significant increase in MPS compared with the inhibitor-alone condition) is highlighted in grey, establishing the functional hierarchy of the pathways relative to the RA commitment signal. (C) Representative image illustrating pathway functional hierarchy. Images show representative larval morphology under the control, inhibitor-only, and inhibitor + RA conditions. These images specifically represent the high-concentration inhibitor treatments (MyD88 inhibitor: 50 µM; MAPK inhibitors: 10 µM; IKKβ and HSP90AA1 inhibitors: 1 µM). MyD88 inhibition completely blocks the behavioral decision of settlement. JNK and p38 inhibition caused a distinct early-stage arrest (low MPS), and the effects of their inhibition were significantly rescued by RA co-treatment. In contrast, ERK inhibition arrested metamorphosis at the middle stage, and this block was not rescued by exogenous RA. Similarly, IKKβ and HSP90AA1 inhibition arrested metamorphosis at later stages, and this block was not rescued by exogenous RA, functionally placing all three pathways (ERK, IKKβ, and HSP90AA1) downstream of the RA commitment signal. Scale bar: 200 µm. Inhibitors used: T6167923 (MyD88 inhibitor), IKK-16 (IKKβ inhibitor), U0126 (ERK inhibitor), SP600125 (JNK inhibitor), SB202190 (p38 inhibitor), and Luminespib (HSP90AA1 inhibitor).

Journal: bioRxiv

Article Title: An APP-centered molecular gateway integrates innate immunity and retinoic acid signaling to drive irreversible metamorphic commitment

doi: 10.64898/2026.01.22.700939

Figure Lengend Snippet: (A) Settlement rate of inhibitor-treated larvae. The box plots with superimposed jitter plots display the larval settlement rate under various inhibitor treatments. The biofilm stimulus condition is used as the positive control. The concentration of each inhibitor is indicated on the horizontal axis. The data represent the settlement rate of larvae remaining attached out of 10 larvae across six independent biological replicates (total n = 60). Statistical significance among treatment groups was assessed using one-way ANOVA followed by Tukey’s HSD post hoc test, with grouping letters indicating significant differences ( p < 0.05); treatments sharing a letter are not significantly different. (B) Quantitative assessment of the functional hierarchy. The box plots with superimposed jitter plots show the Metamorphic Progression Scores (MPS) for larvae treated with various pharmacological inhibitors with or without all-trans retinoic acid (RA). The MPS was calculated based on the metamorphic stage reached by the larvae in the identical assays used for the settlement rate analysis in (A). The concentration of each inhibitor is indicated on the horizontal axis. The MPS represents the average metamorphic stage reached (0 = brachiolaria; 1 = early; 2 = middle; 3 = late; 4 = pre-juvenile; 5 = juvenile). Statistical significance among the treatment groups was assessed using one-way ANOVA followed by Tukey’s HSD post hoc test ( *p < 0.05; n.s., not significant). A significant RA-dependent rescue condition (a statistically significant increase in MPS compared with the inhibitor-alone condition) is highlighted in grey, establishing the functional hierarchy of the pathways relative to the RA commitment signal. (C) Representative image illustrating pathway functional hierarchy. Images show representative larval morphology under the control, inhibitor-only, and inhibitor + RA conditions. These images specifically represent the high-concentration inhibitor treatments (MyD88 inhibitor: 50 µM; MAPK inhibitors: 10 µM; IKKβ and HSP90AA1 inhibitors: 1 µM). MyD88 inhibition completely blocks the behavioral decision of settlement. JNK and p38 inhibition caused a distinct early-stage arrest (low MPS), and the effects of their inhibition were significantly rescued by RA co-treatment. In contrast, ERK inhibition arrested metamorphosis at the middle stage, and this block was not rescued by exogenous RA. Similarly, IKKβ and HSP90AA1 inhibition arrested metamorphosis at later stages, and this block was not rescued by exogenous RA, functionally placing all three pathways (ERK, IKKβ, and HSP90AA1) downstream of the RA commitment signal. Scale bar: 200 µm. Inhibitors used: T6167923 (MyD88 inhibitor), IKK-16 (IKKβ inhibitor), U0126 (ERK inhibitor), SP600125 (JNK inhibitor), SB202190 (p38 inhibitor), and Luminespib (HSP90AA1 inhibitor).

Article Snippet: The inhibitors were dissolved in DMSO and applied at the indicated concentrations: the MyD88 inhibitor T6167923 (5 or 50 μM; MedChemExpress), the IKKβ inhibitor IKK-16 (0.1 or 1 μM; MedChemExpress), and MAPK inhibitors SP600125 (JNK), SB202190 (p38), and U0126 (ERK) (1 or 10 μM; MedChemExpress or FUJIFILM Wako Pure Chemical Corporation), and the HSP90AA1 inhibitors luminespib (0.1 or 1 μM; Chemscene).

Techniques: Positive Control, Concentration Assay, Functional Assay, Control, Inhibition, Blocking Assay

This model illustrates the proposed three-tiered molecular switch that translates external microbial cues into the irreversible developmental fate of sea star metamorphosis, based on Dynamic Network Module (DNM) analysis and comprehensive pharmacological functional assays. This cascade integrates innate immune and developmental signaling pathways across three functional layers: Signal Sensing, Commitment Conversion, and Irreversible Execution. The process is initiated in the Signal Sensing layer, where the environmental cue, microbial biofilms, activates the adapter protein MyD88, which serves as an obligatory first-tier hub. MyD88 transmits signals via the JNK/p38/ERK MAPK pathway to govern the initial settlement behavior. MyD88 exhibits a concentration-dependent dual output: high-dose inhibition abolishes settlement behavior (RA-non-rescuable), while low-dose inhibition permits settlement but causes a late-stage molecular arrest (RA-non-rescuable). Following sensing, the cascade enters the Commitment Conversion layer. JNK/p38 MAPK acts as an essential hybrid adapter that converts immune signals into a Retinoic Acid (RA) hormonal commitment signal (RA-rescuable phenotype). The Amyloid Precursor Protein (APP) functions as the irrevocable commitment gateway, integrating inputs from the upstream MAPK, IKKβ/NFκB, and RA signaling axes to make the final molecular decision. APP ensures irreversibility through “signal focusing,” maintaining its signal strength during the systemic “mass shutdown” of non-essential larval programs. The process culminates in an Irreversible Execution Tier, where the robust execution of the metamorphic program relies on the multi-layered convergence of signals onto the master transcription factor, TFAP2A. The APP commitment decision is translated into transcriptional output via the release of its intracellular domain (AICD), which acts as the final dedicated execution switch by converging to TFAP2A in complex with GSK3β/Src. TFAP2A receives parallel inputs from RA (for launching the program), IKKβ/NFκB (for sustained maintenance and transcriptional output; RA non-rescuable), and ERK (a crucial early execution factor for immediate morphogenesis and physical attachment maintenance; RA non-rescuable). Finally, the RA signal induces the HSP90AA1 chaperone, establishing a positive feedback loop that maintains the structural integrity and function of critical signaling complexes (including MyD88 and APP), thereby ensuring the stability of the executed program.

Journal: bioRxiv

Article Title: An APP-centered molecular gateway integrates innate immunity and retinoic acid signaling to drive irreversible metamorphic commitment

doi: 10.64898/2026.01.22.700939

Figure Lengend Snippet: This model illustrates the proposed three-tiered molecular switch that translates external microbial cues into the irreversible developmental fate of sea star metamorphosis, based on Dynamic Network Module (DNM) analysis and comprehensive pharmacological functional assays. This cascade integrates innate immune and developmental signaling pathways across three functional layers: Signal Sensing, Commitment Conversion, and Irreversible Execution. The process is initiated in the Signal Sensing layer, where the environmental cue, microbial biofilms, activates the adapter protein MyD88, which serves as an obligatory first-tier hub. MyD88 transmits signals via the JNK/p38/ERK MAPK pathway to govern the initial settlement behavior. MyD88 exhibits a concentration-dependent dual output: high-dose inhibition abolishes settlement behavior (RA-non-rescuable), while low-dose inhibition permits settlement but causes a late-stage molecular arrest (RA-non-rescuable). Following sensing, the cascade enters the Commitment Conversion layer. JNK/p38 MAPK acts as an essential hybrid adapter that converts immune signals into a Retinoic Acid (RA) hormonal commitment signal (RA-rescuable phenotype). The Amyloid Precursor Protein (APP) functions as the irrevocable commitment gateway, integrating inputs from the upstream MAPK, IKKβ/NFκB, and RA signaling axes to make the final molecular decision. APP ensures irreversibility through “signal focusing,” maintaining its signal strength during the systemic “mass shutdown” of non-essential larval programs. The process culminates in an Irreversible Execution Tier, where the robust execution of the metamorphic program relies on the multi-layered convergence of signals onto the master transcription factor, TFAP2A. The APP commitment decision is translated into transcriptional output via the release of its intracellular domain (AICD), which acts as the final dedicated execution switch by converging to TFAP2A in complex with GSK3β/Src. TFAP2A receives parallel inputs from RA (for launching the program), IKKβ/NFκB (for sustained maintenance and transcriptional output; RA non-rescuable), and ERK (a crucial early execution factor for immediate morphogenesis and physical attachment maintenance; RA non-rescuable). Finally, the RA signal induces the HSP90AA1 chaperone, establishing a positive feedback loop that maintains the structural integrity and function of critical signaling complexes (including MyD88 and APP), thereby ensuring the stability of the executed program.

Article Snippet: The inhibitors were dissolved in DMSO and applied at the indicated concentrations: the MyD88 inhibitor T6167923 (5 or 50 μM; MedChemExpress), the IKKβ inhibitor IKK-16 (0.1 or 1 μM; MedChemExpress), and MAPK inhibitors SP600125 (JNK), SB202190 (p38), and U0126 (ERK) (1 or 10 μM; MedChemExpress or FUJIFILM Wako Pure Chemical Corporation), and the HSP90AA1 inhibitors luminespib (0.1 or 1 μM; Chemscene).

Techniques: Functional Assay, Protein-Protein interactions, Concentration Assay, Inhibition