RRID:AB_2336864
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2336864
RRID:AB_2336864
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2336864
RRID:AB_626618
DOI: 10.1016/j.cell.2025.11.010
Resource: (Santa Cruz Biotechnology Cat# sc-1657, RRID:AB_626618)
Curator: @scibot
SciCrunch record: RRID:AB_626618
RRID:AB_2336871
DOI: 10.1016/j.cell.2025.11.010
Resource: (Vector Laboratories Cat# RL-1022, RRID:AB_2336871)
Curator: @scibot
SciCrunch record: RRID:AB_2336871
RRID:AB_2783797
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab140601, RRID:AB_2783797)
Curator: @scibot
SciCrunch record: RRID:AB_2783797
RRID:AB_2057020
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2057020
RRID:AB_10974262
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab125011, RRID:AB_10974262)
Curator: @scibot
SciCrunch record: RRID:AB_10974262
RRID:AB_1080271
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_1080271
RRID:AB_2192954
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2192954
RRID:AB_2533554
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2533554
RRID:AB_2340610
DOI: 10.1016/j.cell.2025.11.010
Resource: (Jackson ImmunoResearch Labs Cat# 711-205-152, RRID:AB_2340610)
Curator: @scibot
SciCrunch record: RRID:AB_2340610
RRID:AB_261982
DOI: 10.1016/j.cell.2025.11.010
Resource: (Sigma-Aldrich Cat# P0372, RRID:AB_261982)
Curator: @scibot
SciCrunch record: RRID:AB_261982
RRID:AB_2340607
DOI: 10.1016/j.cell.2025.11.010
Resource: (Jackson ImmunoResearch Labs Cat# 711-175-152, RRID:AB_2340607)
Curator: @scibot
SciCrunch record: RRID:AB_2340607
RRID:AB_1163659
DOI: 10.1016/j.cell.2025.11.010
Resource: (Sigma-Aldrich Cat# I5006, RRID:AB_1163659)
Curator: @scibot
SciCrunch record: RRID:AB_1163659
RRID:AB_10549419
DOI: 10.1016/j.cell.2025.11.010
Resource: (Synaptic Systems Cat# 163 004, RRID:AB_10549419)
Curator: @scibot
SciCrunch record: RRID:AB_10549419
RRID:AB_2336066
DOI: 10.1016/j.cell.2025.11.010
Resource: (Thermo Fisher Scientific Cat# ICN790191, RRID:AB_2334870)
Curator: @scibot
SciCrunch record: RRID:AB_2334870
RRID:AB_2149550
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2149550
RRID:AB_2299684
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2299684
RRID:AB_2148611
DOI: 10.1016/j.cell.2025.11.010
Resource: (Santa Cruz Biotechnology Cat# sc-41, RRID:AB_2148611)
Curator: @scibot
SciCrunch record: RRID:AB_2148611
RRID:AB_2904121
DOI: 10.1016/j.cell.2025.11.010
Resource: (Progen Cat# GP-N2, RRID:AB_2904121)
Curator: @scibot
SciCrunch record: RRID:AB_2904121
RRID:AB_310325
DOI: 10.1016/j.cell.2025.11.010
Resource: (Millipore Cat# 06-984, RRID:AB_310325)
Curator: @scibot
SciCrunch record: RRID:AB_310325
RRID:AB_3081283
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3081283
RRID:AB_477154
DOI: 10.1016/j.cell.2025.11.010
Resource: (Sigma-Aldrich Cat# L0668, RRID:AB_477154)
Curator: @scibot
SciCrunch record: RRID:AB_477154
RRID:AB_303708
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab3329, RRID:AB_303708)
Curator: @scibot
SciCrunch record: RRID:AB_303708
RRID:AB_2716838
DOI: 10.1016/j.cell.2025.11.010
Resource: (Cell Signaling Technology Cat# 9482, RRID:AB_2716838)
Curator: @scibot
SciCrunch record: RRID:AB_2716838
RRID:AB_3084202
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3084202
RRID:AB_2936858
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2936858
RRID:AB_722493
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab46544, RRID:AB_722493)
Curator: @scibot
SciCrunch record: RRID:AB_722493
RRID:AB_2337748
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2337748
RRID:AB_2796681
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2796681
RRID:AB_2339080
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2339080
RRID:AB_2920282
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2920282
RRID:AB_2340541
DOI: 10.1016/j.cell.2025.11.010
Resource: (Jackson ImmunoResearch Labs Cat# 709-225-149, RRID:AB_2340541)
Curator: @scibot
SciCrunch record: RRID:AB_2340541
RRID:AB_2883328
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2883328
RRID:AB_2796691
DOI: 10.1016/j.cell.2025.11.010
Resource: (SouthernBiotech Cat# 9200-05, RRID:AB_2796691)
Curator: @scibot
SciCrunch record: RRID:AB_2796691
RRID:AB_3413698
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3413698
RRID:AB_2687127
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2687127
RRID:AB_2234687
DOI: 10.1016/j.cell.2025.11.010
Resource: (R and D Systems Cat# AF1197, RRID:AB_2234687)
Curator: @scibot
SciCrunch record: RRID:AB_2234687
RRID:AB_10918981
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_10918981
RRID:AB_398140
DOI: 10.1016/j.cell.2025.11.010
Resource: (BD Biosciences Cat# 610821, RRID:AB_398140)
Curator: @scibot
SciCrunch record: RRID:AB_398140
RRID:AB_3355459
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_3355459
RRID:AB_3076642
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab216130, RRID:AB_3076642)
Curator: @scibot
SciCrunch record: RRID:AB_3076642
RRID:AB_3675235
DOI: 10.1016/j.cell.2025.11.010
Resource: (Thermo Fisher Scientific Cat# H3570, RRID:AB_3675235)
Curator: @scibot
SciCrunch record: RRID:AB_3675235
RRID:AB_2943420
DOI: 10.1016/j.cell.2025.11.010
Resource: (Aurion Cat# 800.333, RRID:AB_2943420)
Curator: @scibot
SciCrunch record: RRID:AB_2943420
RRID:AB_10561589
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab92726, RRID:AB_10561589)
Curator: @scibot
SciCrunch record: RRID:AB_10561589
RRID:AB_314204
DOI: 10.1016/j.cell.2025.11.010
Resource: (BioLegend Cat# 302004, RRID:AB_314204)
Curator: @scibot
SciCrunch record: RRID:AB_314204
RRID:AB_2335698
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2334502
RRID:AB_879748
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab55811, RRID:AB_879748)
Curator: @scibot
SciCrunch record: RRID:AB_879748
RRID:AB_2067162
DOI: 10.1016/j.cell.2025.11.010
Resource: (Agilent Cat# M0777, RRID:AB_2067162)
Curator: @scibot
SciCrunch record: RRID:AB_2067162
RRID:AB_2609527
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2609527
RRID:AB_476744
DOI: 10.1016/j.cell.2025.11.010
Resource: (Sigma-Aldrich Cat# A5441, RRID:AB_476744)
Curator: @scibot
SciCrunch record: RRID:AB_476744
RRID:AB_2490474
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2490474
RRID:AB_302747
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab1997, RRID:AB_302747)
Curator: @scibot
SciCrunch record: RRID:AB_302747
RRID:AB_2253046
DOI: 10.1016/j.cell.2025.11.010
Resource: (Santa Cruz Biotechnology Cat# sc-166205, RRID:AB_2253046)
Curator: @scibot
SciCrunch record: RRID:AB_2253046
RRID:AB_354381
DOI: 10.1016/j.cell.2025.11.010
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_354381
RRID:AB_301438
DOI: 10.1016/j.cell.2025.11.010
Resource: (Abcam Cat# ab14730, RRID:AB_301438)
Curator: @scibot
SciCrunch record: RRID:AB_301438
RRID:CVCL_0Q73
DOI: 10.1016/j.cej.2025.171649
Resource: (RRID:CVCL_0Q73)
Curator: @scibot
SciCrunch record: RRID:CVCL_0Q73
RRID:AB_2799074
DOI: 10.1016/j.brainres.2025.150086
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2799074
RRID:AB_2841532
DOI: 10.1016/j.brainres.2025.150086
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2841532
RRID:AB_2836514
DOI: 10.1016/j.brainres.2025.150086
Resource: (Affinity Biosciences Cat# DF4149, RRID:AB_2836514)
Curator: @scibot
SciCrunch record: RRID:AB_2836514
RRID:SCR_021139
DOI: 10.1016/j.brainres.2025.150086
Resource: ggpubr (RRID:SCR_021139)
Curator: @scibot
SciCrunch record: RRID:SCR_021139
RRID:SCR_017677
DOI: 10.1016/j.brainres.2025.150086
Resource: cytoHubba (RRID:SCR_017677)
Curator: @scibot
SciCrunch record: RRID:SCR_017677
RRID:AB_2799066
DOI: 10.1016/j.brainres.2025.150086
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2799066
RRID:SCR_015505
DOI: 10.1016/j.brainres.2025.150086
Resource: glmnet (RRID:SCR_015505)
Curator: @scibot
SciCrunch record: RRID:SCR_015505
RRID:SCR_018685
DOI: 10.1016/j.brainres.2025.150086
Resource: Monocle3 (RRID:SCR_018685)
Curator: @scibot
SciCrunch record: RRID:SCR_018685
RRID:SCR_010943
DOI: 10.1016/j.brainres.2025.150086
Resource: LIMMA (RRID:SCR_010943)
Curator: @scibot
SciCrunch record: RRID:SCR_010943
RRID:SCR_022211
DOI: 10.1016/j.brainres.2025.150086
Resource: None
Curator: @scibot
SciCrunch record: RRID:SCR_022211
RRID:SCR_016341
DOI: 10.1016/j.brainres.2025.150086
Resource: Seurat (RRID:SCR_016341)
Curator: @scibot
SciCrunch record: RRID:SCR_016341
RRID:SCR_021046
DOI: 10.1016/j.brainres.2025.150086
Resource: Foredom (RRID:SCR_021046)
Curator: @scibot
SciCrunch record: RRID:SCR_021046
RRID:AB_476744
DOI: 10.1016/j.brainres.2025.150086
Resource: (Sigma-Aldrich Cat# A5441, RRID:AB_476744)
Curator: @scibot
SciCrunch record: RRID:AB_476744
RRID:AB_2099233
DOI: 10.1016/j.brainres.2025.150086
Resource: (Cell Signaling Technology Cat# 7074, RRID:AB_2099233)
Curator: @scibot
SciCrunch record: RRID:AB_2099233
RRID:CVCL_9Q53
DOI: 10.1016/j.biopha.2024.117641
Resource: (ATCC Cat# CRL-4053, RRID:CVCL_9Q53)
Curator: @scibot
SciCrunch record: RRID:CVCL_9Q53
RRID:CVCL_0493
DOI: 10.1016/j.biopha.2024.117641
Resource: (ATCC Cat# TIB-71, RRID:CVCL_0493)
Curator: @scibot
SciCrunch record: RRID:CVCL_0493
RRID:CVCL_0214
DOI: 10.1016/j.bcp.2025.117603
Resource: (IZSLER Cat# BS CL 15, RRID:CVCL_0214)
Curator: @scibot
SciCrunch record: RRID:CVCL_0214
RRID:CVCL_0182
DOI: 10.1007/s12035-025-05378-3
Resource: (KCB Cat# KCB 200770YJ, RRID:CVCL_0182)
Curator: @scibot
SciCrunch record: RRID:CVCL_0182
RRID:SCR_002798
DOI: 10.1007/s12035-025-05378-3
Resource: GraphPad Prism (RRID:SCR_002798)
Curator: @scibot
SciCrunch record: RRID:SCR_002798
RRID:AB_262011
DOI: 10.1007/s12035-025-05378-3
Resource: (Sigma-Aldrich Cat# A3854, RRID:AB_262011)
Curator: @scibot
SciCrunch record: RRID:AB_262011
RRID:SCR_003070
DOI: 10.1007/s12035-025-05378-3
Resource: ImageJ (RRID:SCR_003070)
Curator: @scibot
SciCrunch record: RRID:SCR_003070
RRID:AB_3094483
DOI: 10.1007/s12035-025-05378-3
Resource: (Abcam Cat# ab279654, RRID:AB_3094483)
Curator: @scibot
SciCrunch record: RRID:AB_3094483
RRID:CVCL_0027
DOI: 10.1007/s11262-025-02206-7
Resource: (KCLB Cat# 88065, RRID:CVCL_0027)
Curator: @scibot
SciCrunch record: RRID:CVCL_0027
RRID:CVCL_0030
DOI: 10.1007/s11262-025-02206-7
Resource: (TKG Cat# TKG 0331, RRID:CVCL_0030)
Curator: @scibot
SciCrunch record: RRID:CVCL_0030
RRID:CVCL_0045
DOI: 10.1007/s11262-025-02206-7
Resource: (DSMZ Cat# ACC-305, RRID:CVCL_0045)
Curator: @scibot
SciCrunch record: RRID:CVCL_0045
RRID:CVCL_0059
DOI: 10.1007/s11262-025-02206-7
Resource: (IZSLER Cat# BS CL 86, RRID:CVCL_0059)
Curator: @scibot
SciCrunch record: RRID:CVCL_0059
RRID:CVCL_VR66
DOI: 10.1007/s11262-025-02206-7
Resource: (ATCC Cat# CCL-185IG-LUC2, RRID:CVCL_VR66)
Curator: @scibot
SciCrunch record: RRID:CVCL_VR66
RRID:CVCL_RB14
DOI: 10.1007/s11262-025-02206-7
Resource: (ATCC Cat# 55-X, RRID:CVCL_RB14)
Curator: @scibot
SciCrunch record: RRID:CVCL_RB14
RRID:AB_11097477
DOI: 10.1007/s00418-025-02447-5
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_11097477
RRID:AB_11042077
DOI: 10.1007/s00418-025-02447-5
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_11042077
RRID:AB_2545704
DOI: 10.1007/s00210-025-04870-w
Resource: None
Curator: @scibot
SciCrunch record: RRID:AB_2545704
RRID:AB_2127596
DOI: 10.1007/s00210-025-04870-w
Resource: (Santa Cruz Biotechnology Cat# sc-57315, RRID:AB_2127596)
Curator: @scibot
SciCrunch record: RRID:AB_2127596
RRID:AB_630341
DOI: 10.1007/s00210-025-04870-w
Resource: (Santa Cruz Biotechnology Cat# sc-52746, RRID:AB_630341)
Curator: @scibot
SciCrunch record: RRID:AB_630341
RRID:AB_331284
DOI: 10.1007/s00210-025-04870-w
Resource: (Cell Signaling Technology Cat# 3033, RRID:AB_331284)
Curator: @scibot
SciCrunch record: RRID:AB_331284
RRID:AB_10917259
DOI: 10.1007/s00210-025-04870-w
Resource: (Santa Cruz Biotechnology Cat# sc-365970, RRID:AB_10917259)
Curator: @scibot
SciCrunch record: RRID:AB_10917259
RRID:AB_2797421
DOI: 10.1007/s00210-025-04870-w
Resource: (Sigma-Aldrich Cat# SAB4503940, RRID:AB_2797421)
Curator: @scibot
SciCrunch record: RRID:AB_2797421
RRID:AB_10693922
DOI: 10.1007/s00210-025-04870-w
Resource: (Cell Signaling Technology Cat# 2117, RRID:AB_10693922)
Curator: @scibot
SciCrunch record: RRID:AB_10693922
RRID:AB_2315112
DOI: 10.1007/s00210-025-04870-w
Resource: (Cell Signaling Technology Cat# 4370, RRID:AB_2315112)
Curator: @scibot
SciCrunch record: RRID:AB_2315112
RRID:SCR_011847
DOI: 10.1007/s00018-025-05964-7
Resource: Trim Galore (RRID:SCR_011847)
Curator: @scibot
SciCrunch record: RRID:SCR_011847
RRID:SCR_006525
DOI: 10.1007/s00018-025-05964-7
Resource: Picard (RRID:SCR_006525)
Curator: @scibot
SciCrunch record: RRID:SCR_006525
RRID:SCR_022444
DOI: 10.1002/smll.202507451
Resource: University of Pennsylvania Penn Vet Extracellular Vesicle Core Facility (RRID:SCR_022444)
Curator: @scibot
SciCrunch record: RRID:SCR_022444
RRID:Addgene_105003
DOI: 10.1002/ptr.70136
Resource: RRID:Addgene_105003
Curator: @scibot
SciCrunch record: RRID:Addgene_105003
RRID:SCR_017874
DOI: 10.1002/jbma.70002
Resource: Northwestern University Integrated Molecular Structure Education and Research Center Core Facility (RRID:SCR_017874)
Curator: @scibot
SciCrunch record: RRID:SCR_017874
RRID:SCR_022718
DOI: 10.1002/glia.70103
Resource: University of Warsaw Center of New Technologies Genomics Core Facility (RRID:SCR_022718)
Curator: @scibot
SciCrunch record: RRID:SCR_022718
RRID:SCR_002963
DOI: 10.1002/cpe.70467
Resource: NEST (RRID:SCR_002963)
Curator: @scibot
SciCrunch record: RRID:SCR_002963
RRID:SCR_008394
DOI: 10.1002/cpe.70467
Resource: Python Programming Language (RRID:SCR_008394)
Curator: @scibot
SciCrunch record: RRID:SCR_008394
RRID:CVCL_0320
DOI: 10.1002/cbdv.202502550
Resource: (RRID:CVCL_0320)
Curator: @scibot
SciCrunch record: RRID:CVCL_0320
RRID:CVCL_0125
DOI: 10.1002/cbdv.202502436
Resource: (ATCC Cat# CRL-2539, RRID:CVCL_0125)
Curator: @scibot
SciCrunch record: RRID:CVCL_0125
RRID:CVCL_0030
DOI: 10.1002/cbdv.202502436
Resource: (TKG Cat# TKG 0331, RRID:CVCL_0030)
Curator: @scibot
SciCrunch record: RRID:CVCL_0030
RRID:SCR_021758
DOI: 10.1002/anbr.202500161
Resource: Colorado State University Analytical Resources Core Facility (RRID:SCR_021758)
Curator: @scibot
SciCrunch record: RRID:SCR_021758
RRID:CVCL_0019
DOI: 10.1002/advs.202520444
Resource: (BCRJ Cat# 0223, RRID:CVCL_0019)
Curator: @scibot
SciCrunch record: RRID:CVCL_0019
plasmid_52
DOI: 10.1002/advs.202519698
Resource: RRID:Addgene_52
Curator: @scibot
SciCrunch record: RRID:Addgene_52
RRID:CVCL_0493
DOI: 10.1002/advs.202518196
Resource: (ATCC Cat# TIB-71, RRID:CVCL_0493)
Curator: @scibot
SciCrunch record: RRID:CVCL_0493
RRID:CVCL_0063
DOI: 10.1002/advs.202512725
Resource: (RRID:CVCL_0063)
Curator: @scibot
SciCrunch record: RRID:CVCL_0063
RRID:CVCL_0062
DOI: 10.1002/advs.202512725
Resource: (RRID:CVCL_0062)
Curator: @scibot
SciCrunch record: RRID:CVCL_0062
RRID:CVCL_0291
DOI: 10.1002/advs.202512074
Resource: (RRID:CVCL_0291)
Curator: @scibot
SciCrunch record: RRID:CVCL_0291
RRID:CVCL_0547
DOI: 10.1002/advs.202512074
Resource: (BCRC Cat# 60343, RRID:CVCL_0547)
Curator: @scibot
SciCrunch record: RRID:CVCL_0547
RRID:CVCL_0504
DOI: 10.1002/advs.202512074
Resource: (ATCC Cat# CRL-2577, RRID:CVCL_0504)
Curator: @scibot
SciCrunch record: RRID:CVCL_0504
RRID:CVCL_5112
DOI: 10.1002/advs.202512074
Resource: (RRID:CVCL_5112)
Curator: @scibot
SciCrunch record: RRID:CVCL_5112
RRID:CVCL_1724
DOI: 10.1002/advs.202512074
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Curator: @scibot
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RRID:SCR_018673
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RRID:SCR_021758
DOI: 10.1002/adma.202518259
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RRID:CVCL_J409
DOI: 10.1002/adhm.202503382
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RRID:CVCL_0059
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Resource: (IZSLER Cat# BS CL 86, RRID:CVCL_0059)
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RRID:CVCL_0422
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RRID:CVCL_0291
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RRID:CVCL_0027
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AB_6640
DOI: 10.1186/s13058-025-02176-6
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Curator: @dhovakimyan1
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RRID:SCR_01
DOI: 10.1113/JP288411
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DOI: 10.1113/JP288411
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DOI: 10.1113/JP288011
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DOI: 10.1113/JP288011
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RRID:Addgene_61
DOI: 10.1111/tpj.70622
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DOI: 10.1111/jnc.70310
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RRID:Addgene_177
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RRID:CDCL-1720
DOI: 10.1016/j.jncc.2025.11.003
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RRID:CDCL-1531
DOI: 10.1016/j.jncc.2025.11.003
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RRID:CDCL-1055
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RRID:SCR_003070w
DOI: 10.1016/j.celrep.2025.116660
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Black Americans hoped that the end of the Civil War would create an entirely new world, while white southerners tried to restore the antebellum order as much as they could.
This shows how the end of a major war isn’t always guaranteed to bring the results it has promised, former slaves were still forced into labor.
We do not fully understand yet the complex causal mechanisms between how something happens in one person's mind moves through neural networks then moves through social ecological networks um and actually may create change in entire sector or give rise to systems
for - anthropocene - signalling - intrabrain - interbrain - SRG comment - individual / collective gestalt - SRG comment - how information flows from one brain to another - networked language!
Christopher Broom's work on in hierarchy in the forest
for - book - Hierarchy in the Forest - shared struggle against inequality - the most important part of human heritage, intelligence and history - SRG comment - recognizing the sacred in all beings - adjacent to Michel Bauwens and the oscillation of the commons - to - book - publisher's page - Hierarchy in the Forest - The Evolution of Egalitarianism - 2001 - Christopher Boehm - https://hyp.is/_w4TEtZoEfCcjmPIvOEOaQ/www.hup.harvard.edu/books/9780674006911
book Goliath's Curse, the history and future of societal collapse
for - to - book - Goliath's Curse: the History and Future of Societal Collapse - Luke Kemp
democracy can basically help save the world. That the use of things like citizen assemblies and citizens juries would lead to far better governance outcomes.
for - citizen assemblies & juries - lead to better governance outcomes - can save the world
Edward Tellella, another physicist, had naughty calculation that there's a nonzero chance that detonating the bomb would ignite the entire atmosphere of Earth, killing not just all humans, but every single shred of life. By that time, the US also knew that the Nazis were no longer capable of making the bomb nor even pursuing their own project anymore. They still went ahead and took the risk.
for - progress trap - technology - nuclear - psychopathic behavior - Edward Teller calculation - decision to go ahead anyways!
killing large groups of people who often at the prime of their working age means suddenly you're losing often decades or centuries of working hours as well. In every single case, it's a wasteful use of energy. Conspicuous consumption or as a way of saying I am more important than you. I have higher status than you do.
for - status competition - conspicuous consumption - war - waste in general
boardrooms and parliaments, it's somewhere between 3 to 21%. Now, again, numbers are very disputed
for - stats - psychopathy - 3 to 21% in boardrooms and parliaments - more likely to find psychopath in boardroom and parliament than grocery store - SRG comment - stats- shadow side of leadership - high percentage of leaders have dark triad
the dark triad
for - definition - dark triad - Narcissism (grandiosity, entitlement, self-adoration), - Machiavellianism (manipulative, strategic self-interest, callousness), and - Psychopathy (impulsivity, lack of empathy/remorse, antisocial behavior). - SRG comment - dark triad - useful for Deep Humanity profile
And why does this happen? How do we have such a huge shift in human social relations? One of the big reasons is status competition
for - reason for - social shift - from egalitarianism - to power hierarchy - status competition - SRG comment - Goliath's Curse - status competition - Deep Humanity antidote
Some call it civilization, I prefer to call Goliath.
for - definition - Goliath - the anthropological shift from egalitarianism to power hierarchy over the holocene - to - book publisher's page - Goliath's Curse - Luke Kemp - from - youtube - The Anthropocene Paradigm Shift
optimal foraging theory
for - definition - optimal foraging theory - our ancestors minimized energy expended for gathering food and maximized leisure time
we also need know that when you start pushing systems you will get a resistance and right now we talk about a transformation backlash in the in in the research
for - definition - transformation backlash - resistance experienced when pushing against an existing system - progress trap - polycrisis - climate crisis - transformation backlash
we need to educate general practitioners, not just specialists, right? We need to to look at the anthroposine geoysiology and say, okay, we need some GPS for anthroposine geoysiology.
for - metaphor - medical - anthropocene - beyond experts, we need GPs for Anthropocene geophysiology - SRG comment - Is SRG GP for anthropocene?
I think we need to concentrate more on the feedbacks between all of those nodes than on the nodes themselves. And that's tough because I might be an expert on one of those nodes and you might be an expert on one of the other nodes. And and it's not that that's needed. It's the feedbacks between the nodes.
for - wicked problems - feedback between nodes is the priority - wicked problems - SRG comment - feedback between nodes - indicates progress traps COLLECCT ecosystem design
one of the things that I find really interesting that's not talked about very much is the impacts of nitrogen fixing and the production of artificial fertilizers which contributed to the number one issue which is human population growth
for - progress trap - nitrogen for fertilizers - anthropocene research - releases lots of methane - climate crisis - leverage point - replacing nitrogen fertilizers
deeply problematic which is based on this idea of technological substitution and which does not feed the facts of the material growth of everything despite all the innovations.
for - green growth - still continues MATERIAL growth
this idea of backstop technology was taken up by all sorts of neocclassical economies to talk about climate change and it start with this hypothesis there is a back stop technology which is a zero emitting uh technology which is available at a certain price and then of course all the models is about you know how can we make this technology appear quicklier.
for - climate crisis - green growth- illusion?
I'm currently curating an exhibition on planetary health and that's exactly this big challenge to get this planetary big abstract concept >> into parts that are digestible for the public and that are like that they can really feel it or can connect to it and I think that's also a very big challenge
for - museum - planetary health - communications - big challenge
there's still so many people outside who just don't know or it's so abstract to them this big dimension. I'm and in the I'm working in a museum
for - climate communications - difficulty of communicating anthropocene - SRG comment - climate crisis as hyperobject - apply Deep Humanity for impactful climate education
we don't have leverage to uh counter what um John Baptist was and talking about at the end the more and more and more
for - infinite economic growth - more more more - climate crisis - infinite growth of capitalism problem - antidote - targeted degrowth
energy forecasting from uh from the most expert institution like the uh international energy agency, well, they don't see any energy transition coming and it shouldn't be a surprise because energy transition is a radically strange notion,
for - climate crisis - energy transition - IEA - none coming - old energy forms still persist
At the beginning of the 20th century most of the people would use petrol petroleum lamps to produce light kerosene lamps and of course then came electrification and electricity made kerosene lamps obsolid. Nevertheless, during the 20th century, we are burning more and more oil to produce light. And today, just the the headlights of the automobiles burn more oil than the whole economy, the whole world economy did in the early 20th century
for - stats - fossil fuels - kerosene lamps at beginning of 20th century for lighting - today more oil to produce electricity for lighting SRG comment - climate crisis - science communication - TPF - contact - Fabian Will
Now compare that for instance with another kind of biologically built structure where we're getting comparable amounts of morphological change of morphos species or technos species uh uh you know which have developed just over a few decades
for - stats - speed - cultural (technological) evolution - cell phone - 35 years to touchscreen phones - comparison - speed of cultural vs biological evolution - progress trap
what we've done since then uh uh is to increase the number of crystalline inorganic compounds that is minerals in every but formal sense at the earth's surface um uh by orders of magnitude so now more than 300,000 most of those have been made since 1950
for - stats - minerals - since 1950, 300,000 new minerals - only 5,000 up til modernity - planetary boundary - novel entities
life comes in and not very much happens until life decides to excrete oxygen into the atmosphere when you get a whole raft of hydroxides and hydrox oxides and hydroxides coming in
for - geology - history - minerals - when life starts excreting oxygen - many new minerals - planetary boundary novel entities boundary
Why is accumulation linked to success and power? And will there be ways to escape that vicious circle?
for - greed - game A - linked to success - can we escape from game A? - SRG comment - accumulation perspective of capitalism - climate crisis - Deep Humanity interventions
for - book - Hierarchy in the Forest - The Evolution of Egaliterian Behavior - author - Christopher Boehm - from - youtube - The Anthropocene Paradigm Shift
eLife Assessment
This study resolves a cryo-EM structure of the GPCR, human GPR30, which responds to bicarbonate and regulates cellular responses to pH and ion homeostasis. Understanding the ligand and the mechanism of activation is important to the field of receptor signaling and potentially facilitates drug development targeting this receptor. Structures and functional assays provide solid evidence for a potential bicarbonate binding site.
Reviewer #1 (Public review):
Summary:
This study resolves a cryo-EM structure of the GPCR, GPR30, in the presence of bicarbonate, which the author's lab recently identified as the physiological ligand. Understanding the ligand and the mechanism of activation is of fundamental importance to the field of receptor signaling. This solid study provides important insight into the overall structure and suggests a possible bicarbonate binding site.
Strengths:
The overall structure, and proposed mechanism of G-protein coupling are solid. Based on the structure, the authors identify a binding pocket that might accommodate bicarbonate. Although assignment of the binding pocket is speculative, extensive mutagenesis of residues in this pocket identifies several that are important to G-protein signaling. The structure shows some conformational differences with a previous structure of this protein determined in the absence of bicarbonate (PMC11217264). To my knowledge, bicarbonate is the only physiological ligand that has been identified for GPR30, making this study an important contribution to the field. However, the current study provides novel and important circumstantial evidence for the bicarbonate binding site based on mutagenesis and functional assays.
Weaknesses:
Bicarbonate is a challenging ligand for structural and biochemical studies, and because of experimental limitations, this study does not elucidate the exact binding site. Higher resolution structures would be required for structural identification of bicarbonate. The functional assay monitors activation of GPR30, and thus reports on not only bicarbonate binding, but also the integrity of the allosteric network that transduces the binding signal across the membrane. However, biochemical binding assays are challenging because the binding constant is weak, in the mM range.
The authors appropriately acknowledge the limitations of these experimental approaches, and they build a solid circumstantial case for the bicarbonate binding pocket based on extensive mutagenesis and functional analysis. However, the study does fall short of establishing the bicarbonate binding site.
Reviewer #2 (Public review):
Summary:
In this manuscript, "Cryo-EM structure of the bicarbonate receptor GPR30," the authors aimed to enrich our understanding of the role of GPR30 in pH homeostasis by combining structural analysis with a receptor function assay. This work is a natural development and extension of their previous work on Nature Communications (PMID: 38413581). In the current body of work, they solved the cryo-EM structure of the human GPR30-G-protein (mini-Gsqi) complex in the presence of bicarbonate ions at 3.15 Å resolution. From the atomic model built based on this map, they observed the overall canonical architecture of class A GPCR and also identified 3 extracellular pockets created by ECLs (Pockets A-C). Based on the polarity, location, size, and charge of each pocket, the authors hypothesized that pocket A is a good candidate for the bicarbonate binding site. To identify the bicarbonate binding site, the authors performed an exhaustive mutant analysis of the hydrophilic residues in Pocket A and analyzed receptor reactivity via calcium assay. In addition, the human GPR30-G-protein complex model also enabled the authors to elucidate the G-protein coupling mechanism of this special class A GPCR, which plays a crucial role in pH homeostasis.
Strengths:
As a continuation of their recent Nature Communications publication, the authors used cryo-EM coupled with mutagenesis and functional studies to elucidate bicarbonate-GPR30 interaction. This work provided atomic-resolution structural observations for the receptor in complex with G-protein, allowing us to explore its mechanism of action, and will further facilitate drug development targeting GPR30. There were 3 extracellular pockets created by ECLs (Pockets A-C). The authors were able to filter out 2 of them and hypothesized that pocket A was a good candidate for the bicarbonate binding site based on the polarity, location, and charge of each pocket. From there, the authors identified the key residues on GPR30 for its interaction with the substrate, bicarbonate. Together with their previous work, they mapped out amino acids that are critical for receptor reactivity.
Weaknesses:
When we see a reduction of a GPCR-mediated downstream signaling, several factors could potentially contribute to this observation: 1) a reduced total expression of this receptor due to the mutation (transcription and translation issue); 2) a reduced surface expression of this receptor due to the mutation (trafficking issue); and 3) a dysfunctional receptor that doesn't signal due to the mutation. In the current revision, based on the gating strategy, the surface expression of the HA-positive WT GPR30-expressing cells is only 10.6% of the total population, while the surface expression levels of the mutants range from 1.89% (P71A) to 64.4% (D111A). Combining this information with the functional readout in Figure 3F and G, as well as their previous work, the authors concluded that mutations at P71, E115, D125, Q138, C207, D210, and H307 would decrease bicarbonate responses. Among those sites,
E115, Q138, and H307 were from their previous Nature Comm paper.
Authors claim P71 and C207 make a structural-stability contribution, as their mutations result in a significant reduction in surface expression: P71A (1.89%) and C207A (2.71%). However, compared to 10.6% of the total population in the WT, (P71A is 17.8% of the WT, and C207A is 25.6% of the WT), this doesn't rule out the possibility that the mutated receptor is also dysfunctional: at 10 mM NaHCO3, RFU of WT is ~500, RFU of P71 and C207 are ~0.
The authors also interpret "The D125ECL1A mutant has lost its activity but is located on the surface" and only mention "D125 is unlikely to be a bicarbonate binding site, and the mutational effect could be explained due to the decreased surface expression". Again, compared to 10.6% of the total population in the WT, D125A (3.94%) is 37.2% of the WT. At 10 mM NaHCO3, the RFU of the WT is ~500, the RFU of D125 is ~0. This doesn't rule out the possibility that the mutated receptor is also dysfunctional. It is not clear why D125A didn't make it to the surface.
Other mutants that the authors didn't mention much in their text: D111A (64.4%, 607.5% of WT surface expression), E121A (50.4%, 475.5% of WT surface expression), R122 (41.0%, 386.8% of WT surface expression), N276A (38.9%, 367.0% of WT surface expression) and E218A (24.6%, 232.1% of WT surface expression) all have similar RFU as WT, although the surface expression is about 2-6 times more. On the other hand, Q215A (3.18%, 30% of WT surface expression) has similar RFU as WT, with only a third of the receptor on the surface.
Altogether, the wide range of surface expression across the different cell lines, combined with the different receptor function readouts, makes the cell functional data only partially support their structural observations.
Reviewer #3 (Public review):
Summary
GPR30 responds to bicarbonate and plays a role in regulating cellular pH and ion homeostasis. However, the molecular basis of bicarbonate recognition by GPR30 remains unresolved. This study reports the cryo-EM structure of GPR30 bound to a chimeric mini-Gq in the presence of bicarbonate, revealing mechanistic insights into its G-protein coupling. Nonetheless, the study does not identify the bicarbonate-binding site within GPR30.
Strengths
The work provides strong structural evidence clarifying how GPR30 engages and couples with Gq.
Weaknesses
Several GPR30 mutants exhibited diminished responses to bicarbonate, but their expression levels were also reduced. As a result, the mechanism by which GPR30 recognizes bicarbonate remains uncertain, leaving this aspect of the study incomplete.
Author response:
The following is the authors’ response to the original reviews.
The parts of the text that have been changed.The major changes are as follows:
We re-analyzed the dataset and improved the local resolution of the extracellular region (Author response image 1).
We re-modeled based on the improved density and canceled the bicarbonate model based on comments from all reviewers.
We performed calcium assay using cell lines stably expressing the mutants, whose surface expression levels were analyzed by fluorescence-activated cell sorting (FACS)<br /> (Figure 3F, G and Figure 3–figure supplement 1-3).
Thus, we significantly revised our discussion of the extracellular binding pocket and the result of the mutational study. In the revised manuscript, we speculate that H307 is a candidate for the bicarbonate binding site.
Author response image 1.
Figure Comparison of local resolution between re-analyzed and previous maps.A Side and top view of the re-analyzed receptor-focused map of GPR30 colored by local resolution. B Side and top view of the previous receptor-focused map of GPR30 colored by local resolution
Reviewer #1 (Public Review):
Summary:
This study resolves a cryo-EM structure of the GPCR, GPR30, which was recently identified as a bicarbonate receptor by the authors' lab. Understanding the ligand and the mechanism of activation is of fundamental importance to the field of receptor signaling. However, the main claim of the paper, the identification of the bicarbonate binding site, is only partly supported by the structural and functional data, leaving the study incomplete.
Strengths:
The overall structure, and proposed mechanism of G-protein coupling seem solid. The authors perform fairly extensive unbiased mutagenesis to identify a host of positions that are important to G-protein signaling. To my knowledge, bicarbonate is the only physiological ligand that has been identified for GPR30, making this study a particularly important contribution to the field.
Weaknesses:
Without higher resolution structures and/or additional experimental assessment of the binding pocket, the assignment of the bicarbonate remains highly speculative. The local resolution is especially poor in the ECL loop region where the ligand is proposed to bind (4.3 - 4 .8 Å range). Of course, sometimes it is difficult to achieve high structural resolution, but in these cases, the assignment of ligands should be backed up by even more rigorous experimental validation.The functional assay monitors activation of GPR30, and thus reports on not only bicarbonate binding, but also the integrity of the allosteric network that transduces the binding signal across the membrane. Thus, disruption of bicarbonate signaling by mutagenesis of the putative coordinating residues does not necessarily mean that bicarbonate binding has been disrupted. Moreover, the mutagenesis was apparently done prior to structure determination, meaning that residues proposed to directly surround bicarbonate binding, such as E218, were not experimentally validated. Targeted mutagenesis based on the structure would strengthen the story.
Moreover, the proposed bicarbonate binding site is surprising in a chemical sense, as it is located within an acidic pocket. The authors cite several other structural studies to support the surprising observation of anionic bicarbonate surrounded by glutamate residues in an acidic pocket (references 31-34). However, it should be noted that in general, these other structures also possess a metal ion (sodium or calcium) and/or a basic sidechain (arginine or lysine) in the coordination sphere, forming a tight ion pair. Thus, the assigned bicarbonate binding site in GPR30 remains an anomaly in terms of the chemical properties of the proposed binding site.
Thank you for your insightful comments. Based on the weaknesses you pointed out, we reconstructed the receptor based on the improved density and removed the bicarbonate model. We performed calcium assays using cell lines stably expressing the variant based on the structure.
Reviewer #2(Public Review):
Summary:
In this manuscript, "Cryo-EM structure of the bicarbonate receptor GPR30," the authors aimed to enrich our understanding of the role of GPR30 in pH homeostasis by combining structural analysis with a receptor function assay. This work is a natural development and extension of their previous work (PMID: 38413581). In the current body of work, they solved the first cryo-EM structure of the human GPR30-G-protein (mini-Gsqi) complex in the presence of bicarbonate ions at 3.21 Å resolution. From the atomic model built based on this map, they observed the overall canonical architecture of class A GPCR and also identified 4 extracellular pockets created by extracellular loops (ECLs) (Pockets A-D). Based on the polarity, location, and charge of each pocket, the authors hypothesized that pocket D is a good candidate for the bicarbonate binding site. To verify their structural observation, on top of the 10 mutations they generated in the previous work, the authors introduced another 11 mutations to map out the essential residues for the bicarbonate response on hGPR30. In addition, the human GPR30-G-protein complex model also allowed the authors to untangle the G-protein coupling mechanism of this special class A GPCR that plays an important role in pH homeostasis.
Strengths:
As a continuation of their recent Nature Communication publication (PMID: 38413581), this study was carefully designed, and the authors used mutagenesis and functional studies to confirm their structural observations. This work provided high-resolution structural observations for the receptor in complex with G-protein, allowing us to explore its mechanism of action, and will further facilitate drug development targeting GPR30. There were 4 extracellular pockets created by ECLs (Pockets A-D). The authors were able to filter out 3 of them and identified that pocket D was a good candidate for the bicarbonate binding site based on the polarity, location, and charge of each pocket. From there, the authors identified the key residues on GPR30 for its interaction with the substrate, bicarbonate. Together with their previous work, they carefully mapped out nine amino acids that are critical for receptor reactivity.
Weaknesses:
It is unclear how novel the aspects presented in the new paper are compared to the most recent Nature Communications publication (PMID: 38413581). Some areas of the manuscript appear to be mixed with the previous publication. The work is still impactful to the field. The new and novel aspects of this manuscript could be better highlighted.
I also have some concerns about the TGFα shedding assay the authors used to verify their structural observation. I understand that this assay was also used in the authors' previous work published in Nature Communications. However, there are still several things in the current data that raised concerns:
Thank you for your insightful comments. Based on the weaknesses you pointed out, we highlighted the new and novel aspects of this manuscript could be better highlighted.l. We performed calcium assays using cell lines stably expressing the variant based on the structure.
(1) The authors confirmed the "similar expression levels of HA-tagged hGPR30" mutants by WB in Supplemental Figure 1A and B. However, compared to the hGPR30-HA (~6.5 when normalized to the housekeeping gene, Na-K-ATPase), several mutants of the key amino acids had much lower surface expression: S134A, D210A, C207A had ~50% reduction, D125A had ~30% reduction, and Q215A and P71A had ~20% reduction. This weakens the receptor reactivity measured by the TGFα shedding assay.
Since the calcium assay data is included in the main figure, the TGFα shedding assay and WB expression quantification data are Figure 3. –– supplement figure 1-4, but we included an explanation of the expression levels in the figure caption.
(2) In the previous work, the authors demonstrated that hGPR30 signals through the Gq signaling pathway and can trigger calcium mobilization. Given that calcium mobilization is a more direct measurement for the downstream signaling of hGPR30 than the TGFα shedding assay, pairing the mutagenesis study with the calcium assay will be a better functional validation to confirm the disruption of bicarbonate signaling.
According to the suggestion, we performed calcium assay using cell lines stably expressing the mutants (Figure 3F, G and Figure 3–figure supplement 1-3).
(3) It was quite confusing for Figure 4B that all statistical analyses were done by comparing to the mock group. It would be clearer to compare the activity of the mutants to the wild-type cell line.
Thank you for your comment. As you mentioned, the comparisons are made between wild-type GPR30 and mutants in the revised manuscript (Figure 3G, Figure 3.—figure supplement 4B)
Additional concerns about the structural data include
(1) E218 was in close contact with bicarbonate in Figure 4D. However, there is no functional validation for this observation. Including the mutagenesis study of this site in the cell-based functional assay will strengthen this structural observation.
We cancelled the bicarbonate model, and we performed mutation analysis targeting all residues facing the binding pocket using cell lines that stably express variants including E218A.
(2) For the flow chart of the cryo-EM data processing in Supplemental data 2, the authors started with 10,148,422 particles after template picking, then had 441,348 Particles left after 2D classification/heterogenous refinement, and finally ended with 148,600 particles for the local refinement for the final map. There seems to be a lot of heterogeneity in this purified sample. GPCRs usually have flexible and dynamic loop regions, which explains the poor resolution of the ECLs in this case. Thus, a solid cell-based functional validation is a must to assign the bicarbonate binding pocket to support their hypothesis.
We re-analyzed the dataset and improved the local resolution of the extracellular region (Author response image 1) and cancelled the bicarbonate model. Yet, as suggested by the reviewer, solid cell-based functional validation is efficient to analyze the receptor function response to bicarbonate. Thus, we performed mutation analysis targeting all residues facing the binding pocket using cell lines stably expressing the mutants, whose surface expression levels were analyzed by FACS (Figure 3F, G and Figure 3.––figure supplement 1-3).
Reviewer #3 (Public Review):
Summary:
GPR30 responds to bicarbonate and regulates cellular responses to pH and ion homeostasis. However, it remains unclear how GPR30 recognizes bicarbonate ions. This paper presents the cryo-EM structure of GPR30 bound to a chimeric mini-Gq in the presence of bicarbonate. The structure together with functional studies aims to provide mechanistic insights into bicarbonate recognition and G protein coupling.
Strengths:
The authors performed comprehensive mutagenesis studies to map the possible binding site of bicarbonate.
Weaknesses:
Owing to the poor resolution of the structure, some structural findings may be overclaimed.
Based on EM maps shown in Figure 1a and Figure Supplement 2, densities for side chains in the receptor particularly in ECLs (around 4 Å) are poorly defined. At this resolution, it is unlikely to observe a disulfide bond (C130ECL1-C207ECl2) and bicarbonate ions. Moreover, the disulfide between ECL1 and ECL2 has not been observed in other GPCRs and the published structure of GPR30 (PMID: 38744981). The density of this disulfide bond could be noise.
The authors observed a weak density in pocket D, which is accounted for by the bicarbonate ions. This ion is mainly coordinated by Q215 and Q138. However, the Q215A mutation only reduced but not completely abolished bicarbonate response, and the author did not present the data of Q138A mutation. Therefore, Q215 and Q138 could not be bicarbonate binding sites. While H307A completely abolished bicarbonate response, the authors proposed that this residue plays a structural role. Nevertheless, based on the structure, H307 is exposed and may be involved in binding bicarbonate. The assignment of bicarbonate in the structure is not supported by the data.
Thank you for your insightful comments. Based on the weaknesses you pointed out, we reconstructed the receptor based on the improved density and removed the bicarbonate model. We performed calcium assays using cell lines stably expressing the variant based on the structure.
Reviewer #1 (Recommendations For The Authors):
(1) The experimental validation of the bicarbonate binding could be strengthened by developing an assay that directly monitors bicarbonate binding (rather than GPCR signaling)
We agree that a direct binding assay for bicarbonate would be highly attractive (i.e. Filter binding assay using 14C-HCO₃⁻). However, the weak affinity of bicarbonate ions (in the mM range) would make reliable radioisotope-based detection impossible due to minimal specific receptor occupancy and high non-specific background and thus it is highly challenging and there are limitations to what can be done in this structural paper.
and determining a structure at comparable resolution in the absence of bicarbonate. In addition, all residues that are proposed to be located adjacent to the bicarbonate should be mutated and functionally validated.
We re-modeled the receptor based on the improved density and canceled the bicarbonate model. We performed calcium assay using cell lines stably expressing the mutants (Figure 3F, G and Figure 3.–figure supplement 1-3).
(2) What are the maps contoured in Figure 4D? The legend should describe this. Is 218 within the map region shown, or is there no density for its sidechain?
We removed the corresponding figure and cancelled the bicarbonate model.
(3) The contour level of the maps in Figure 1 - Figure Supplement 2 should also be indicated. Are these all contoured at the same level?
Thank you for your comment. We re-analyzed the same data set and obtained new density maps and models. We reworked Figure 1 and Figure 1. figure supplement 2; the contour level of the map for Figure 1 and composite map for the Figure 1. figure supplement 2 is the same, 7.65.
(4) Regarding the cited structures of bicarbonate-binding proteins, for three of the four cited structures, the bicarbonate is actually coordinated by positive ligands, with the Asp/Glu playing a more peripheral role:
Capper et al: Overall basic cavity with tight bidentate coordination by Arg. The Glu is 5-6 Å away.
Koropatkin et al: Two structures. The first, solved at pH 5, is proposed to have carbonic acid bound. The second, solved at pH 8, shows carbonate in a complex with calcium, with the calcium coordinated by carboxylates.
Wang et al: The bicarbonate is coordinated by a lysine and a sodium ion. The sodium is coordinated by carboxylates.
The authors should more thoughtfully discuss the unusual properties of this binding site with regard to the previous literature. Is it possible that bicarbonate binds in complex with a metal ion? Could this possibility be experimentally tested?
We cancelled the bicarbonate model.
(5) As a structure of GPR30 has been recently published by another group (PMID: 38744981), it would be valuable to discuss structural similarities and differences and discuss how bicarbonate activation and activation by the chloroquine ligand identified by the other group might both be accommodated by this structure.
Thank you for your valuable comment. We compared the structure presented by another group and added our discussion, as “During the revision of this manuscript, the structures of apo-GPR30-G<sub>q</sub> (PDB 8XOG) and the exogenous ligand Lys05-bound GPR30-G<sub>q</sub> (PDB 8XOF) were reported [42]. We compared our structure of GPR30 in the presence of bicarbonate with these structures. In the extracellular region, the position of TM5 in GPR30 in the presence of bicarbonate is similar to that in apo-GPR30. In contrast, the position of TM6 is shifted outward relative to that of apo-GPR30, resembling the conformation observed in Lys05-bound GPR30 (Figure 6A, B). Additionally, the position of ECL1 is also shifted outward compared to that of apo-GPR30 (Figure 6B). In the GPR30 structure in the presence of bicarbonate, ECL2 was modeled, suggesting differences in structural flexibility. These findings indicate that the structure of GPR30 in the presence of bicarbonate is different from both the apo structure and the Lys05-bound structure, demonstrating that the structure and the flexibility of the extracellular domain of GPR30 change depending on the type of ligand. Furthermore, focusing on the interaction with G<sub>q</sub>, the αN helix of G<sub>q</sub> is not rotated in the structure bound to Lys05, in contrast to the characteristic bending of the αN helix in our structure (Figure 6C, D). Although it is necessary to consider variations in experimental conditions, such as salt concentration, the differences in the G<sub>q</sub> binding modes suggest that the downstream signals may change in a ligand-dependent manner.” (lines 249-266).
Reviewer #2 (Recommendations For The Authors):
(1) It is highly recommended that the authors carefully go through the "insights into bicarbonate binding" section. The results of the new findings in this paper were blended in with the results from the previous work: the importance of E115, Q138, and H307 in the receptor-bicarbonate interaction was shown in the Nature Communication paper but the authors didn't make it clear, which added a little confusion.
We emphasized this fact in the main text (lines 130-132).
(2) It would be nice for the authors to add some content about the physiological concentration of HCO3 or refer more to their previous work about the rationale for selecting the bicarbonate dose in their functional assay.
Thank you for your comment. The physiological concentration of bicarbonate is 22-26 mM in the extracellular fluid, including interstitial fluid and blood, and 10-12 mM in the intracellular fluid. The bicarbonate concentration alters in various physiological and pathological conditions – metabolic acidosis in chronic kidney disease causes a drop to 2-3 mM, and metabolic alkalosis induced by severe vomiting increases HCO<sub>3</sub><sup>-</sup> concentrations more than 30 mM. Thus, our present and previous works clearly show that GPR30 is activated by physiological concentrations of bicarbonate, whether it is localized intracellularly or on the membrane, and that GPR30 can be deactivated or reactivated in various pathophysiological conditions. We added this in the discussion section (lines 267-278).
(3) In Figure 3A, in the legend, the authors mentioned: "black dashed lines indicate hydrogen bonds". No hydrogen bond was noted in the figure.
We totally corrected Figure 3.
(4) Figure 3B, it would be helpful for the authors to denote the meaning of the blue-white-red color coding in the legend.
We removed the figure.
(5) Supplemental Figure 3: since AF3 was released on May 3rd, it would be awesome in the revision version if the authors would update this to the AF3 model.
The AF2 model has been replaced with the AF3. (Figure 2–figure supplement 2A-C). The AF2 and AF3 models are almost identical, and they form incorrect disulfide bonds. This confirms the usefulness of the experimental structural determination in this study.
(6) Supplemental Figure 4: it wasn't clear to me if the expression experiments were repeated multiple times or if there was any statistical analysis for the expression level was done in this study.
We performed the expression experiment by western blotting once and did not perform statistical analyses. We performed repeated FACS analyses of HEK cells stably expressing N-terminally HA-tagged wild-type or mutant GPR30s to analyze their membrane and whole-cell expressions during revision (Figure 3.–figure supplement 1-3). Using these stable cells, we performed calcium assays using cell lines stably expressing the mutants (Figure 3F, G and Figure 3–figure supplement 1-3).
(7) Supplemental Figure 4: Also, is there a reason for the authors to compare the expression level of hGPR30 to the housekeeping gene NA-K-ATPase rather than the total loaded protein? Traditionally housekeeping genes have been used as loading controls to semiquantitatively compare the expression of target proteins in western blots. However, numerous recent studies show that housekeeping proteins can be altered due to experimental conditions, biological variability across tissues, or pathologies. A consensus has developed for using total protein as the internal control for loading. An editorial from the Journal of Biological Chemistry reporting on "Principles and Guidelines for Reporting Preclinical Research" from the workshop held in June 2014 by the NIH Director's Office, Nature Publishing Group, and Science stated, "It is typically better to normalize Western blots using total protein loading as the denominator".
Thank you for your instructive comment. We evaluated western blotting with the same amount of total protein loaded 20 µg for whole-cell lysate and 1.5 µg for cell surface protein (Figure 3.–figure supplement 3C-F).
Reviewer #3 (Recommendations For The Authors):
The claim about this disulfide should be removed unless the authors can provide mass spec evidence.
Thank you for your crucial comments. Firstly, C130 is a residue of TM3, not ECL1, so our misprint has been corrected to C130<sup>3.25</sup>. C207<sup>ECL2</sup>, located at position 45.50, is the most conserved residue in ECL2, and it forms a disulfide bond with cysteine at position 3.25 (PMID: 35113559). The paper was additionally cited regarding the preservation of the bond of C130<sup>3.25</sup>-C207<sup>ECL2</sup> (line 103). Indeed, disruption of this disulfide bond by the C207<sup>ECL2</sup> A mutation resulted in a marked reduction in receptor activity. In addition, the data set was re-analyzed to improve the local resolution of the extracellular region, and it was shown that the density of ECL2 is not noise (Figure 2. ––figure supplement 2). We are confident about the presence of the disulfide bond, based on the structural analysis data and the conservation.
The highly flexible extracellular region is greatly affected by experimental conditions and ligands, so we speculate that the ECL2 and the disulfide bond was not observed in other reported structures of GPR30. Then, we have added the following content to the discussion, as “In the GPR30 in the presence of bicarbonate, ECL2 was modelled, suggesting differences in structural flexibility.” (lines 256-257).
The authors should remove the assignment of bicarbonate in the structure, and tone down the binding site of bicarbonate.
We cancelled the bicarbonate model.
Minor:
(1) The potency of bicarbonate for GPR30 is in the mM range. Although the concentration of bicarbonate in the serum can reach mM range, how about its concentration in the tissues? Given its low potency, it may be not appropriate to claim GPR30 is a bicarbonate receptor at this point, but the authors can claim that GPR30 can be activated by or responds to bicarbonate.
The physiological concentration of bicarbonate is 22-26 mM in the extracellular fluid, including interstitial fluid and blood, and 10-12 mM in the intracellular fluid. Therefore, GPR30 is activated by physiological concentrations of bicarbonate in the tissues. Also, the bicarbonate concentration alters in various physiological and pathological conditions – metabolic acidosis in chronic kidney disease causes a drop to 2-3 mM, and metabolic alkalosis induced by severe vomiting increases HCO3- concentrations more than 30 mM. Thus, our work clearly shows that GPR30 is activated by physiological concentrations of bicarbonate, whether it is localized intracellularly or on the membrane, and that GPR30 can be deactivated or reactivated in various pathophysiological conditions. According to the reasons above, we claim GPR30 is a bicarbonate receptor (lines 267-278).
(2) The description that there is no consensus on a drug that targets GPR30 is not accurate, since lys05 has been reported as an agonist of GPR30 and their structure is published (PMID: 38744981). The published structures of GPR30 should be introduced in the paper.
We added the discussion about the structural comparison with the Lys05-bound structure (Figure 6, lines 249-266)
(3) BW numbers in Figure 4A should be shown.
We added BW numbers in the figures of the mutational studies.
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Your professors are much more likely to find a self-consciously highbrow writing style tedious than impressive
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Producing and reading elegant writing is a pleasure, but what really matters in academic writing is precision.
This sentence stands out to me because it challenges the idea that academic writing must sound fancy to be good. I sometimes worry that my writing isn’t “academic” enough, but this chapter reminds me that precision is more important than sounding sophisticated. Clear writing shows clear thinking, and readers care more about understanding the ideas than being impressed by complicated sentences.
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Le livre classique n’est plus la seule forme de transmission du savoir, ni peut-être la principale
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R0:
Reviewer #1:
This sub study was nested in a factorial randomized controlled trial (RCT) in women aged 18–30 years. Participants included in this study were randomized to receive either a preconception intervention package or routine care until early childhood. The design strategy involved a reasonable sample size justification to show superiority. The sample needed for the study objectives was well justified with power considerations. However, the investigators do note that the sample size, while adequate for detecting moderate effect sizes, may have been insufficient to identify smaller but clinically meaningful differences. The descriptives are informative as seen in Tables 1 and 2.
Generalized linear models (GLMs) with a Gaussian family and identity link function were used to estimate mean differences in CRP, AGP, IGF-1, and IGFBP3 concentrations. To estimate risk ratios for inflammatory status between infants in the intervention and routine care groups, GLMs with a binomial family and log link function were employed. Final models were adjusted for place of birth. There are several considerations needing clarification.
There are four endpoints. Therefore,
Also, with respect to model content,
The overall conclusions follow from the analyses performed and results seen in Table 3. The strengths and limitations are reasonably described in the ‘Discussion’ section. As an added point, however,
4.There is a gap between the manuscript text and the supplement supporting information proposal Version 2.0. Was there any attempt to explore the mediation analysis discussed in that proposal?
Reviewer #2:
Recommendation: Minor Revision.
Reviewer #3:
This study is a secondary analysis of the WINGS factorial randomized controlled trial evaluating the effects of a multidomain, integrated intervention delivered from preconception through early childhood on infant biomarkers of inflammation and growth (CRP, AGP, IGF-1, IGFBP3) at 3 and 6 months of age. This study links the integrated intervention to specific changes in inflammatory and growth-related biomarkers like CRP, AGP, IGF-1 and IGFBP3. The study addressed the biologically relevant and policy-important question related to early-life interventions in low-resource settings The findings indicate no significant differences in these biomarkers between the intervention and control groups, except for a transient decrease in IGFBP3 at 3 months, which was not sustained at 6 months. The authors conclude that while the intervention improved growth outcomes in the parent trial, it did not significantly influence early-life inflammation or IGF axis biomarkers. The manuscript is well-written, clearly articulated and follows the required CONSORT Guidelines. Major Comments 1. Rationale and Framing • Biological rationale connecting integrated maternal–child interventions (nutrition, WASH, psychosocial care) with the specific biomarkers studied (CRP, AGP, IGF-1, IGFBP3), needs clarity • Clarify why these markers and 3- and 6-month time points were selected, especially since primary growth outcomes were reported at 24 months in the main WINGS paper. • A concise conceptual model or figure showing hypothesized pathways could help readers follow the mechanistic logic. 2. Study Power and Sample • The power calculation is based on CRP only. Please justify the adequacy of the sample size for detecting meaningful differences in IGF-1 and IGFBP3, given their biological variability in infancy. • Power calculations are based on LAZ outcomes from the primary WINGS study rather than biomarker data. This needs justification. 3. Statistical Analysis and results • Tables 2 and 3 could be simplified to highlight group comparisons more effectively. • Adjustment only for the place of delivery seems limited. • The author may consider other covariates, such as mothers’ BMI, socioeconomic indicators, or exposure to infections, in the analysis. In case they are intentionally excluded from the analysis, explain their exclusion. • It would be useful to include effect size interpretation (e.g., percentage change or standardized mean difference) to better convey the biological relevance of null findings. 4. Interpretation of Findings • However, cautious interpretation of the null findings is needed. Aspects such as biological plausibility, contextual limitations, and future implications for longitudinal research require further elaboration. • The discussion acknowledges the absence of significant effects, but can be deepened if the authors discuss the following issues o Address low baseline inflammation as a potential ceiling effect. o Note that intervention effects might appear later in life (after 6 months). o Acknowledge that non-inflammatory mechanisms (caregiving, infection prevention, psychosocial stimulation) might explain the positive growth outcomes in the primary trial. • Expand the comparison with similar trials—such as SHINE (Zimbabwe), ELICIT (Tanzania), and MAL-ED studies—that examined inflammation and growth factor pathways. • The trial was conducted in a single urban Indian setting, which limits extrapolation to rural or diverse socioeconomic contexts. The discussion should acknowledge this limitation more explicitly and suggest strategies for replication in varied environments. 5. Policy and Program Implications • The conclusion is based on the non-significant findings of biomarkers. Whereas the short duration of biomarker assessment may oversimplify complex biological processes. More elaborate discussion is needed on possible confounders like infections, duration, and type of breastfeeding.
Minor Comments 1. Abstract: Conclude with a stronger statement about contribution: e.g., “These findings add to the understanding of biological mechanisms underlying integrated early-life interventions in LMICs.” 2. Tables: Present only adjusted results in the main text; unadjusted data may be submitted as supplementary files. Ensure all tables include units (mg/L, ng/mL) and consistent decimal formatting. 3. CONSORT Diagram: Please include the number of exclusions, losses to follow-up, and reasons for non-participation in Figure 1 for transparency. 4. Discussion: Add a short note acknowledging that biomarker variability in early infancy is high and may obscure subtle intervention effects. 5. References: Consider citing more recent literature (published within the last 3 years) that links microbiome–inflammation–growth relationships in infants. 6. Language and Formatting: Ensure consistency in abbreviations (e.g., IGFBP3 vs IGF-BP3). Use consistent phrasing for “preconception, pregnancy, and early childhood interventions, growth-related biomarkers, and growth factor profiles” throughout.
Overall Recommendations: Minor–to–Moderate Revision This is a robust, well-implemented study addressing an important mechanistic question within global child health. Although the results are null, they offer valuable insights into early-life biology and integrated program evaluation. Strengthening the biological framing, contextual discussion, and presentation of adjusted analyses will substantially enhance the manuscript’s impact and readability.