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The "match between run" feature was used and the mass search range was set to m/z 400 to 1,000. MS data were processed with Dia-NN (v1.8.1) and searched against an in silico predicted human spectral library (Table S1).

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Specifically, we implemented the GLay algorithm aiming to identify the densely connected clusters within each network. By isolating the clusters with HOXA5 and comparing them using the Dynet plug-in in Cytoscape, we highlighted their common and/or condition-specific interactions. Each cluster’s interactions were used as inputs for enrichment analysis of biological pathways and terms. Following this pipeline, we identified the modulated pathways of HOXA5 due to sildenafil administration. cBOS were generated as previously described.69,144 Briefly, 3 % low melting temperature agarose (Gibco) was diluted in Hank’s Balanced Salt Solution (HBSS, Sigma-Aldrich), heated to 90 °C and slowly cooled down to 40 °C.

Key takeaway

Brain organoids were washed in HBSS, embedded in the agarose, and cooled on ice until the agarose was solid. For slicing, a Vibratome Microm HM 650 V (Thermo Fisher Scientific) was adjusted to the following settings: frequency of 60 Hz, amplitude of 1.0 mm, velocity of 33 mm/s, and slice thickness of 300 μm. The slices were directly transferred to a petri dish filled with HBSS, placed in a cell culture hood and washed four times. Finally, the slices were collected on Millicell-CM inserts (Millipore) and placed in a 6-well plate. 750 μl of cortical differentiation medium IV (CDMIV) were added in each well, so that the membrane was soaked but the top side of the slices was still exposed to air.

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cBOS were cultured at 36 °C and 5 % CO2 for around 30-59 days before starting calcium imaging experiments. For calcium imaging experiments,69 membrane permeable Oregon Green 488 BAPTA-1 AM (OGB-1, Invitrogen) was first solved in 20 % pluronic and 80 % DMSO and diluted to 200 μM in HEPES-buffered saline, which was then injected into cBOS and incubated for 30 minutes. During the incubation and throughout the experiments, cBOS were perfused with artificial cerebrospinal fluid (ACSF), containing 138 mM NaCl, 2.5 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 1.25 mM NaH2PO4, 18 NaHCO3, and 10 glucose. The ACSF was bubbled with 95 % O2 and 5 % CO2, resulting in a pH of 7.4. OGB-1 was excited at 488 nm and signals were detected using the imaging software NIS-Elements and a variable scan digital imaging system (Nikon) attached to an upright microscope (Eclipse FN-1, Nikon). Metabolites were extracted from cells with 500 μl of cold extraction solvent (Acetonitrile:Methanol:MilliQ; 40:40:20, Thermo Fischer Scientific). Subsequently, samples were processed with three cycles of sonication (60 s) and vortexing (120 s) followed by centrifugation at 14,000 rpm at 4 °C for 5 min.

Next, the samples were centrifuged, the supernatants transferred to evaporation tube and evaporated to dry under nitrogen stream. Samples were reconstituted in 40 μl extraction buffer (Acetonitrile:Methanol:MilliQ; 40:40:20) and transferred to LC-MS vials. 2 μl of the samples were analyzed with Thermo Vanquish UHPLC coupled with Q-Exactive Orbitrap mass spectrometer equipped with a heated electrospray ionization (H-ESI) source probe (Thermo Fischer Scientific). A SeQuant ZIC-pHILIC (2.1 × 100 mm, 5 μm particle) column (Merck) was used for chromatographic separation. The gradient elution was carried out with a flow rate of 0.1 ml/min and mobile phase gradient with 20 mM ammonium hydrogen carbonate, adjusted to pH 9.4 with ammonium solution (25 %) as mobile phase A and acetonitrile as mobile phase B, 0-2 min 80 % B, 2-17 min 80-20 % B, 17-24 min 80 % B. The column oven and auto-sampler temperatures were set to 40 ± 3 °C and 5 ± 3 °C, respectively. Following setting were used for MS: full scan range: 55-825 m/z, polarity switching; resolution of 35,000, the spray voltages: 4250 V for positive and 3250 V for negative mode; the sheath gas: 25 arbitrary units (AU); the auxiliary gas: 15 AU; sweep gas flow 0; capillary temperature: 275 °C; S-lens RF level: 50.0.

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We identified metabolites that were differentially present within samples (Table S1). We performed multi-omics integration as previously described.55 Briefly, we integrated bulk transcriptomics, proteomics, and metabolomics datasets derived from LS NPCs and control NPCs (disease signature), as well as transcriptomics and metabolomics datasets from sildenafil-treated LS NPCs and untreated LS NPCs (sildenafil signature). For both cases, we used all sildenafil chewable tablets significantly deregulated molecules (adjusted p-value ≤ 0.05) as input lists for the OmicsNet platform (v.2.0) and retrieved their interactions based on STRING (confidence score 0.7) and Recon3D databases. Molecular interactions were filtered with the Prize-Collecting Steiner Forest (PCSF) algorithm, retaining only the most informative nodes regarding network organization and functionality. For network visualization, we chose the Organic Layout from yFiles plugin in Cytoscape.

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To dissect the rescue mechanism of sildenafil, we searched for molecules with reversed expression in the disease signature and sildenafil signature datasets. Molecules were annotated in the REACTOME and GeneOntology databases for pathway and biological processes enrichment analyses, respectively, using the clusterProfiler package (v4.10.0). To explore the regulatory effect of sildenafil in gene expression levels, we retrieved the drug’s signatures from the L1000 FWD database. Genes that had a consistent pattern of re-regulation across all examined cell lines after sildenafil treatment were considered as literature-indicated drug targets. We evaluated these literature-indicated drug targets in our transcriptomics datasets by filtering those genes that had the same pattern of re-regulation in LS NPCs after sildenafil administration (LS + sildenafil vs.

Animal models

LS + DMSO). A final list of literature-indicated drug targets with a similar regulation pattern in treated LS NPCs was considered a cross-validated set of genes involved in the mechanism of action of sildenafil. To describe the mechanistic effect of sildenafil on HOXA5, we performed two parallel clustering analyses in LS + DMSO vs. controls + DMSO and in LS + sildenafil vs. LS + DMSO networks, respectively. Instrument control was operated with the Xcalibur software (Thermo Fischer Scientific). The metabolite annotation and integration were done with the TraceFinder 5.1 software (Thermo Fischer Scientific) using confirmed retention times by in-house standard library (MSMLS-1EA, Merck) and their m/z. The data quality was monitored throughout the run using pooled QC sample prepared by pooling 5 μL from each suspended sample and interspersed throughout the run every 10 samples. The data was quality controlled for peak quality (poor chromatography), prefiltered with 20 % RSD cutoff of the pooled QC and noise. We identified metabolites that were differentially present within samples (Table S1). We performed multi-omics integration as previously described.55 Briefly, we integrated bulk transcriptomics, proteomics, and metabolomics datasets derived from LS NPCs and control NPCs (disease signature), as well as transcriptomics and metabolomics datasets from sildenafil-treated LS NPCs and untreated LS NPCs (sildenafil signature). For both cases, we used all sildenafil chewable tablets significantly deregulated molecules (adjusted p-value ≤ 0.05) as input lists for the OmicsNet platform (v.2.0) and retrieved their interactions based on STRING (confidence score 0.7) and Recon3D databases. Molecular interactions were filtered with the Prize-Collecting Steiner Forest (PCSF) algorithm, retaining only the most informative nodes regarding network organization and functionality. For network visualization, we chose the Organic Layout from yFiles plugin in Cytoscape. To dissect the rescue mechanism of sildenafil, we searched for molecules with reversed expression in the disease signature and sildenafil signature datasets. Molecules were annotated in the REACTOME and GeneOntology databases for pathway and biological processes enrichment analyses, respectively, using the clusterProfiler package (v4.10.0). To explore the regulatory effect of sildenafil in gene expression levels, we retrieved the drug’s signatures from the L1000 FWD database.

• Sildenafil can cause side effects such as headaches, flushing, or nasal congestion.
• At high doses, the risk of side effects and adverse reactions increases significantly.
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Genes that had a consistent pattern of re-regulation across all examined cell lines after sildenafil treatment were considered as literature-indicated drug targets. We evaluated these literature-indicated drug targets in our transcriptomics datasets by filtering those genes that had the same pattern of re-regulation in LS NPCs after sildenafil administration (LS + sildenafil vs. LS + DMSO). A final list of literature-indicated drug targets with a similar regulation pattern in treated LS NPCs was considered a cross-validated set of genes involved in the mechanism of action of sildenafil. To describe the mechanistic effect of sildenafil on HOXA5, we performed two parallel clustering analyses in LS + DMSO vs. controls + DMSO and in LS + sildenafil vs.

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The "match between run" feature was used and the mass search range was set to m/z 400 to 1,000. MS data were processed with Dia-NN (v1.8.1) and searched against an in silico predicted human spectral library (Table S1). Metabolites were extracted from cells with 500 μl of cold extraction solvent (Acetonitrile:Methanol:MilliQ; 40:40:20, Thermo Fischer Scientific). Subsequently, samples were processed with three cycles of sonication (60 s) and vortexing (120 s) followed by centrifugation at 14,000 rpm at 4 °C for 5 min. Next, the samples were centrifuged, the supernatants transferred to evaporation tube and evaporated to dry under nitrogen stream.

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Samples were reconstituted in 40 μl extraction buffer (Acetonitrile:Methanol:MilliQ; 40:40:20) and transferred to LC-MS vials. 2 μl of the samples were analyzed with Thermo Vanquish UHPLC coupled with Q-Exactive Orbitrap mass spectrometer equipped with a heated electrospray ionization (H-ESI) source probe (Thermo Fischer Scientific). A SeQuant ZIC-pHILIC (2.1 × 100 mm, 5 μm particle) column (Merck) was used for chromatographic separation. The gradient elution was carried out with a flow rate of 0.1 ml/min and mobile phase gradient with 20 mM ammonium hydrogen carbonate, adjusted to pH 9.4 with ammonium solution (25 %) as mobile phase A and acetonitrile as mobile phase B, 0-2 min 80 % B, 2-17 min 80-20 % B, 17-24 min 80 % B. The column oven and auto-sampler temperatures were set to 40 ± 3 °C and 5 ± 3 °C, respectively.

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Following setting were used for MS: full scan range: 55-825 m/z, polarity switching; resolution of 35,000, the spray voltages: 4250 V for positive and 3250 V for negative mode; the sheath gas: 25 arbitrary units (AU); the auxiliary gas: 15 AU; sweep gas flow 0; capillary temperature: 275 °C; S-lens RF level: 50.0. Instrument control was operated with the Xcalibur software (Thermo Fischer Scientific). The metabolite annotation and integration were done with the TraceFinder 5.1 software (Thermo Fischer Scientific) using confirmed retention times by in-house standard library (MSMLS-1EA, Merck) and their m/z. The data quality was monitored throughout the run using pooled QC sample prepared by pooling 5 μL from each suspended sample and interspersed throughout the run every 10 samples. The data was quality controlled for peak quality (poor chromatography), prefiltered with 20 % RSD cutoff of the pooled QC and noise. LS + DMSO networks, respectively. Specifically, we implemented the GLay algorithm aiming to identify the densely connected clusters within each network.

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The microscope was equipped with a Fluor 40x/ 0.8 DIC M/N2 ∞ /0 WD 2.0 water immersion objective (Nikon) and an orca FLASH 4.0 LT camera (Hamamatsu Photonics). Images were routinely obtained at 1 Hz and emission was collected at >500 nm. Regions of interest (ROIs) representing cell somata were identified, and their signals were background-corrected. For calculating ΔF/F0, sildenafil citrate tablets 150 mg the traces were normalized to their initial baseline (first 30 s of measurement). Additionally, the fluorescence signals were corrected for bleaching and analysed with OriginPro Software (OriginLab Corporation).

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To probe for the cellular response to acute metabolic stress, ACSF was switched to glucose-free ACSF containing 5 mM sodium azide (Honeywell) and 2 mM 2-Deoxy-D-glucose (Apollo Scientific) for 2 min. Then, it was switched back to ACSF for 20-30 min until cellular calcium levels recovered to their original baseline. For each calcium signal, the area under the curve (AUC) and the peak amplitudes ΔF/F0 (in %) were analyzed. After washing with Tyrode’s solution, the cells were incubated for 10 min at room temperature (RT) in Tyrode’s solution to allow fura-2 de-esterification and equilibration. Next, the Tyrode’s solution was replaced by a calcium-free Tyrode’s solution (129 mM NaCl, 1 mM MgCl2, 5 mM KCl, 30 mM D-glucose, 25 mM HEPES, 0.5 mM EGTA, pH 7.4), and immediately placed in a temperature- and CO2-controlled (37 °C, 5 % CO2, and ∼20 % O2) sample holder attached to the stage of an Axio Observer 7 inverted microscope (Zeiss, Jena, Germany) equipped with a x 40 objective (F-Fluar M27; NA 1.3; oil immersion; Zeiss) and x 1 magnification changer (Tubelens Optovar; Zeiss).

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Fura-2 was alternatingly excited at 340 nm and 380 nm using a Sutter Lambda DG5 wavelength switcher (Sutter Instruments, Novato, CA, USA), FT 430 dichroic mirror, and BP525/50 emission filter. Fura-2 emission signals were captured in the dark using an Axiocam 702 camera (Zeiss), applying an exposure time of 20 ms and image acquisition interval of 1 s. Microscopy hardware was controlled by Zen Pro software (version 3.2; Zeiss). During time lapse recordings, 1 μM thapsigargin (TG) (Thermo Fisher Scientific) was added to the extracellular medium by gentle pipetting. Numerical fluorescence intensity data was extracted from the fura-2 images using FIJI software (version 1.53q; ROIs were manually defined for each time lapse recording in the cytosol of individual cells and extracellular background. By isolating the clusters with HOXA5 and comparing them using the Dynet plug-in in Cytoscape, we highlighted their common and/or condition-specific interactions. Each cluster’s interactions were used as inputs for enrichment analysis of biological pathways and terms.

Following this pipeline, we identified the modulated pathways of HOXA5 due to sildenafil administration.

• Sildenafil 100g refers to a high dosage of the medication used to treat erectile dysfunction.
• This dosage is significantly higher than the common 50mg or 25mg tablets.
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cBOS were generated as previously described.69,144 Briefly, 3 % low melting temperature agarose (Gibco) was diluted in Hank’s Balanced Salt Solution (HBSS, Sigma-Aldrich), heated to 90 °C and slowly cooled down to 40 °C. Brain organoids were washed in HBSS, embedded in the agarose, and cooled on ice until the agarose was solid. For slicing, a Vibratome Microm HM 650 V (Thermo Fisher Scientific) was adjusted to the following settings: frequency of 60 Hz, amplitude of 1.0 mm, velocity of 33 mm/s, and slice thickness of 300 μm. The slices were directly transferred to a petri dish filled with HBSS, placed in a cell culture hood and washed four times. Finally, the slices were collected on Millicell-CM inserts (Millipore) and placed in a 6-well plate. 750 μl of cortical differentiation medium IV (CDMIV) were added in each well, so that the membrane was soaked but the top side of the slices was still exposed to air.

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cBOS were cultured at 36 °C and 5 % CO2 for around 30-59 days before starting calcium imaging experiments.

• Storage of sildenafil should be in a cool, dry place away from direct sunlight.
• Common side effects include dizziness, upset stomach, or vision changes.
• The dosage of sildenafil should be tailored to individual health needs.
• Sildenafil can interact with other medications, affecting its safety and efficacy.
• Always seek medical guidance before using sildenafil, especially at high doses.

For calcium imaging experiments,69 membrane permeable Oregon Green 488 BAPTA-1 AM (OGB-1, Invitrogen) was first solved in 20 % pluronic and 80 % DMSO and diluted to 200 μM in HEPES-buffered saline, which was then injected into cBOS and incubated for 30 minutes. During the incubation and throughout the experiments, cBOS were perfused with artificial cerebrospinal fluid (ACSF), containing 138 mM NaCl, 2.5 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 1.25 mM NaH2PO4, 18 NaHCO3, and 10 glucose. The ACSF was bubbled with 95 % O2 and 5 % CO2, resulting in a pH of 7.4. OGB-1 was excited at 488 nm and signals were detected using the imaging software NIS-Elements and a variable scan digital imaging system (Nikon) attached to an upright microscope (Eclipse FN-1, Nikon). The microscope was equipped with a Fluor 40x/ 0.8 DIC M/N2 ∞ /0 WD 2.0 water immersion objective (Nikon) and an orca FLASH 4.0 LT camera (Hamamatsu Photonics).

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Next, in each image fura-2 emission signals were quantified for multiple cells at both excitation wavelengths. All cytosolic ROIs were of identical size and remained inside the cytosol during the full duration of the recording. Cytosolic fura-2 signals were first individually background-corrected for each excitation wavelength, after which the ratio value (340/380 nm) was calculated. 10 μM ROCK inhibitor was added to the final media after splitting to promote neuron survival. Experiments and quantification were performed as previously described.81 Neurons generated for neurite outgrowth quantification were treated with 10 μM sildenafil in 0.1 % DMSO or 0.1 % DMSO alone following media changes on days 8, 10, and 12. Images were routinely obtained at 1 Hz and emission was collected at >500 nm. Regions of interest (ROIs) representing cell somata were identified, and their signals were background-corrected. For calculating ΔF/F0, sildenafil citrate tablets 150 mg the traces were normalized to their initial baseline (first 30 s of measurement). Additionally, the fluorescence signals were corrected for bleaching and analysed with OriginPro Software (OriginLab Corporation). To probe for the cellular response to acute metabolic stress, ACSF was switched to glucose-free ACSF containing 5 mM sodium azide (Honeywell) and 2 mM 2-Deoxy-D-glucose (Apollo Scientific) for 2 min. Then, it was switched back to ACSF for 20-30 min until cellular calcium levels recovered to their original baseline. For each calcium signal, the area under the curve (AUC) and the peak amplitudes ΔF/F0 (in %) were analyzed. After washing with Tyrode’s solution, the cells were incubated for 10 min at room temperature (RT) in Tyrode’s solution to allow fura-2 de-esterification and equilibration. Next, the Tyrode’s solution was replaced by a calcium-free Tyrode’s solution (129 mM NaCl, 1 mM MgCl2, 5 mM KCl, 30 mM D-glucose, 25 mM HEPES, 0.5 mM EGTA, pH 7.4), and immediately placed in a temperature- and CO2-controlled (37 °C, 5 % CO2, and ∼20 % O2) sample holder attached to the stage of an Axio Observer 7 inverted microscope (Zeiss, Jena, Germany) equipped with a x 40 objective (F-Fluar M27; NA 1.3; oil immersion; Zeiss) and x 1 magnification changer (Tubelens Optovar; Zeiss). Fura-2 was alternatingly excited at 340 nm and 380 nm using a Sutter Lambda DG5 wavelength switcher (Sutter Instruments, Novato, CA, USA), FT 430 dichroic mirror, and BP525/50 emission filter. Fura-2 emission signals were captured in the dark using an Axiocam 702 camera (Zeiss), applying an exposure time of 20 ms and image acquisition interval of 1 s.

• Sildenafil may cause temporary visual disturbances; report any persistent changes to a doctor.
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Microscopy hardware was controlled by Zen Pro software (version 3.2; Zeiss). During time lapse recordings, 1 μM thapsigargin (TG) (Thermo Fisher Scientific) was added to the extracellular medium by gentle pipetting. Numerical fluorescence intensity data was extracted from the fura-2 images using FIJI software (version 1.53q; ROIs were manually defined for each time lapse recording in the cytosol of individual cells and extracellular background. Next, in each image fura-2 emission signals were quantified for multiple cells at both excitation wavelengths. All cytosolic ROIs were of identical size and remained inside the cytosol during the full duration of the recording. Cytosolic fura-2 signals were first individually background-corrected for each excitation wavelength, after which the ratio value (340/380 nm) was calculated. 10 μM ROCK inhibitor was added to the final media after splitting to promote neuron survival. Experiments and quantification were performed as previously described.81 Neurons generated for neurite outgrowth quantification were treated with 10 μM sildenafil in 0.1 % DMSO or 0.1 % DMSO alone following media changes on days 8, 10, and 12.