Keywords: human brain evolution, gene duplicates, neuronal excitability, LRRC37, FGF13, voltage-gated channels, axon initial segment, cerebral cortex, SCN1B

LRRC37 gene family displays selective genomic amplification and gene expression in simian and human species

We previously identified >30 hominid-specific genes expressed during human corticogenesis,³⁹ including theLRRC37 gene family encoding putative membrane receptors.⁴⁶ The number ofLRRC37 genes increased through independent segmental duplications in simian and hominid species, leading to many paralogs.⁴⁶ The human genome carries at least 15 partial duplications that encode several pseudogenes, and at least 4 protein-encoding genes, compared with 2 in the mouse genome (Figure 1A).⁴⁶LRRC37 genes encode two types of proteins, A- and B-types. Both A- and B-types are transmembrane proteins that contain an extracellular LRR domain (Figure 1B). The B-type proteins carry an additional specific domain, hereafter referred to as LB domain, located near the extracellular N-terminal part of the protein (Figure 1B).LRRC37B types emerged in the simian genomes and are thus not found in the mouse (Figures 1A,S1A, and S1B). Alignment of the amino acid sequences of LRRC37B-types found in hominids revealed strong conservation between orthologous human and other hominid (chimpanzee, bonobo, gorilla, and orangutan) proteins, especially at the level of the LB and LRR domains (89%–99% of identity;Figure S1A). The macaque genome contains a singleLRRC37B-type paralog (LRRC37-M2), which displays lower levels of homology with human LRRC37B at the amino acid level (65%;Figures S1A and S1B) and does not seem to possess a human orthologous counterpart.

TheLRRC37B gene studied here thus appears to be present only in hominid genomes. Many hominid-specific genes may be of little functional relevance, which is typically associated with variable copy number (CN), indicative of relaxed evolutionary constraints. We examined CN variation ofLRRC37 human paralogs using whole-genome sequencing⁴⁹ across thousands of diverse humans from the 1000 Genomes Project.⁵⁰ This revealed thatLRRC37B, shared between hominids, andLRRC37A3, for which no ortholog could be found in the chimpanzee, were nearly fixed in the tested population (diploid CN = 2) (Figure S1C), strongly suggesting conservation and functionality, whileLRRC37A andLRRC37A2 exhibit CN polymorphism (diploid CN between 0 and 5).

We next examined the pattern of expression ofLRRC37 genes, first in the human cerebral cortex, then in comparison with other species. Inspection of postnatal developmental expression in the human prefrontal cortex (PFC)⁵¹ revealed that all fourLRRC37 genes are expressed throughout development until adulthood (Figure S1D for upper-layer neurons). Inspection of single-cell RNA sequencing (scRNA-seq) data in the human adult middle temporal gyrus (MTG)³⁵ and in the dorsolateral PFC (dlPFC)⁴⁸ revealed thatLRRC37 genes were expressed in most subclasses of CPNs and gamma-aminobutyric acid (GABA)ergic interneurons, but in a fraction of neurons in each subclass (Figures 1C, 1D, andS1E).LRRC37B transcript levels were higher in CPNs compared with GABAergic interneurons (1.47-fold higher, adjusted p value < 10⁻⁸¹, Wilcoxon ranked sum test) (Figures 1C andS1E;Table S1). AllLRRC37 genes were expressed at lower levels in non-neuronal cells (at least 1.4-fold lower for the four paralogs, adjusted p values < 10⁻³¹; Wilcoxon rank-sum test) (Figures 1C andS1E;Table S1).

Bulk RNA-seq data⁵² revealed expression ofLRRC37 paralogs in the adult human and macaque cerebral cortex, while noLrrc37 transcripts were detected in the mouse cortex in any cell type at any stage (Figure S2A), as previously described.⁴⁶ snRNA-seq of human and chimpanzee dlPFC⁴⁸ revealed species differences in the levels of expression of theLRRC37 paralogs.LRRC37B RNA levels were consistently higher in the human than in the chimpanzee cortical neurons (Figures 1D, 1E, andS2B). For instance, in upper-layer CPNs (L2/3 IT),LRRC37B was expressed at 1.9-fold higher levels in human than in chimpanzee counterparts (Deseq2 test with pseudo-bulk approach, adjusted p value < 6.9 × 10⁻⁸) (Figure 1E). Conversely,LRRC37A andLRRC37A2 were expressed at higher levels in the chimpanzee than in the human neurons (Figures 1D and 1E; Deseq2 tests with pseudo-bulk approach, adjusted p values <0.01 for L2/3 IT neurons).

Overall, these data indicate that within simians theLRRC37 gene family members display divergent genomic amplification and gene expression in the cerebral cortex. Among them,LRRC37B is only present in the hominid genomes, with a fixed CN in the human modern population, and enriched at the transcript level in human cortical neurons (including CPNs) compared with chimpanzee cortical neurons.

LRRC37B is localized to the AIS of human CPNs

We next examined LRRC37B at the protein level, using a specific antibody raised against the LB domain (seeSTAR Methods). This antibody recognizes LRRC37B-type proteins encoded in human, chimpanzee, and macaque, but none of the LRRC37A types (Figures S2C and S2D). Using this antibody, we confirmed that LRRC37B can be targeted to the cellular membrane with the expected topology in heterologously transfected HEK293T cells (Figure S2C).

We looked at the pattern of endogenous LRRC37B protein expression in the adult human cerebral cortex. This revealed that LRRC37B is mostly localized at the level of the AIS (marked with ankyrin-G) in a subset (>40%) of CPNs (Figures 1F–1I;Table S2). Similar patterns were observed throughout all cortical areas tested (frontal, temporal, occipital, parietal, and in both upper layer;Figures 1F–1I andS2E;Table S2) and deep-layer CPNs (data not shown). The AIS subcellular compartment is the main site of generation of AP through the opening of voltage-gated sodium channels (Nav channels) concentrated at this location.²⁹ Time course analysis from early postnatal ages to >60 years old human specimens, revealed an absence of AIS immunoreactivity in neonates while the proportion of CPNs displaying LRRC37B at the AIS sharply increased from childhood to stabilize at puberty (Figure 1I;Table S2). Finally, we examined the cortical white matter, in which ankyrin-G and Nav channels are co-localized at the nodes of Ranvier.⁵³ Ankyrin-G was moderately co-localized with Nav1.6 (r = 0.33 ± 0.07), as expected, but it was not co-localized with LRRC37B (r = 0.09 ± 0.04) (Figure S1F).

We next examined LRRC37B expression in other species, using the same antibody (directed against the LB domain;Figure S1A) on similarly prepared cryosections of adult cerebral cortex of mouse (barrel cortex), macaque, and chimpanzee (temporal cortex) (Figures 1H andS2E;Table S3). This failed to reveal any immunoreactivity in the mouse, as expected given the absence of the gene in this species. More surprisingly, there was no detectable immunoreactivity at the AIS levels in macaque or chimpanzee samples, although a weak, diffuse punctate pattern of expression could be detected in the chimpanzee cerebral cortex (Figures 1H andS2E). The species-specific targeting of LRRC37B at the AIS level could be related to the higher levels of RNA expression in human CPNs (Figures 1D, 1E, andS2B), or to differential post-transcriptional control of LRRC37B in human CPNs.

Thus, LRRC37B is an AIS protein selectively expressed in human CPNs (Figure 1J).

LRRC37B negatively regulates CPN excitability

We next performed gain of function of LRRC37B in mouse CPNs throughin utero electroporation (IUE) in the barrel cortex (at embryonic day 15.5, thereby targeting mostly cortical layer II/III CPNs). We electroporated vectors leading to a cre-dependent bicistronic expression of LRRC37B and EGFP (Enhanced Green Fluorescent Protein) (LRRC37B-expressing neurons), or EGFP alone (control neurons), followed by analysis at postnatal day (P)28. We found that the human LRRC37B protein (hLRRC37B) was enriched at the AIS, as in human CPNs (Figures 2A andS3A), while control neurons displayed no LRRC37B immunoreactivity, as expected (Figure S3A). We detected no differences in the AIS length and localization in LRRC37B-expressing neurons compared with control neurons (Figures S3B and S3C). IUE ofLRRC37A2, belonging to the more ancestral LRRC37 A-type, did not reveal a selective localization at the AIS (Figure S3D). On the other hand, IUE of chimpanzee LRRC37B (cLRRC37B) led to similar results of AIS subcellular localization (Figures S3A and S3B), further suggesting that the absence of protein detection of LRRC37B in the chimpanzee cerebral cortex (Figures 1H andS2E) is not solely due to sequence differences between human and chimpanzee orthologous proteins.

Given the importance of the AIS in neuronal excitability, we next compared the electrophysiological properties of control and LRRC37B-expressing mouse cortical CPNs, using patch-clamp recordings inex vivo cortical slices (barrel cortex, cortical layer II/III CPNs) of P24–P32 electroporated mice (Figures 2B–2F andS3E–S3G). LRRC37B gain of function led to a sharp decrease in neuronal excitability, characterized by a lower AP firing rate and a higher rheobase (Figures 2B–2D). It also led to a decreased input resistance and an increased capacitance (Figure S3E), which could in principle contribute to changes in the AP firing rates. Furthermore, LRRC37B-expressing neurons also displayed specific changes in two critical features of APs, risetime and width, pointing to changes in intrinsic excitability of the neurons (Figure 2E). Phase plot analyses^27,54—used to study the temporal profile of single evoked APs (using 3 independent approaches; see “Methods 1–3” inSTAR Methods for details)—revealed that LRRC37B-expressing neurons display a selective decrease in the AIS component of APs (between −16% and −20%), while the somatic and repolarization components remained unchanged (Figures 2F andS3F–S3H). Current-voltage IV-curve-based sodium and potassium ionic currents that reflect mostly currents at the level of the cell body⁵⁵ (Figure S3I) also remained unchanged.

Finally, we examined the synaptic properties of LRRC37B-expressing neurons. As the AIS is the synaptic target of chandelier GABAergic interneurons that regulate CPN output,⁵⁶ we quantified GABAergic synapses at the level of the AIS. This revealed no difference between LRRC37B-expressing and control mouse CPNs in the density of VGAT (Vesicular GABA Transporter) or Gephyrin puncta (Figures S3J and S3K). Whole-cell voltage clamp recordings revealed no difference in frequency or amplitude of spontaneous excitatory and inhibitory postsynaptic currents compared with control neurons (Figure S3L).

These data indicate that LRRC37B can act as a negative regulator of intrinsic excitability when overexpressed in mouse CPNs, acting specifically on AP generation at the AIS level.

LRRC37B is a receptor for extracellular FGF13A

To identify the molecular mechanisms underlying the function of LRRC37B, we searched for its endogenous ligands. We first performed an ELISA-based interactome screen.^57,58 We used as a bait the predicted extracellular sequence of LRRC37B (LRRC37B_ECTO) fused with alkaline phosphatase (ALP).⁵⁹ Using LRRC37B_ECTO-ALP immobilized in each well of 384-well plates, 920 transmembrane or secreted proteins (including 24 proteins enriched at the AIS or in chandelier interneurons; see STAR Methods), fused to an Fc domain, were used as preys.

The screen led to a single reproducible hit from three independent experiments: FGF13A (Figure S4A). This result first came as a surprise, as FGF13 is as a member of the non-canonical FGF (Fibroblast Growth Factor) FHF (FGF Homologous Factor) family, previously reported to encode non-secreted proteins.^60,61,62 FGF13 encodes several splice isoforms (FGF13A, FGF13B, FGF13V, FGF13Y, and FGF13VY) that share a C-terminal domain (encoded by coding exons 2–5, hereafter named “core domain”) but differ by their first coding exon (Figure 3A).⁶³ We hypothesized that alternatively spliced mRNAs could encode secreted or non-secreted isoforms of FGF13. We tested this using heterologous expression in HEK293T cells of all major FGF13 isoforms, followed by analysis of cell lysates vs. medium. Only FGF13A could be detected as a secreted protein in the culture medium, but none of the other tested isoforms, nor the core domain (Figure 3A). We next tested whether FGF13A could bind to LRRC37B using co-immunoprecipitation (coIP). LRRC37B could be coIP only with FGF13A, and not with any of the other tested isoforms, nor with the FGF13 core domain (Figure 3B). Adding recombinant FGF13A protein to the culture medium of cells expressing LRRC37B also resulted in coIP of FGF13A with LRRC37B (Figure 3C). Similar binding results were obtained with a synthetic peptide corresponding to the first exon of FGF13A (ExonS;Figure 3C), indicating that the ExonS-encoded domain alone is sufficient to bind to LRRC37B.

These data indicate that FGF13A is an extracellular ligand of LRRC37B, to which it binds to through its isoform-specific N-terminal domain, henceforth referred to as F13ExonS.

In order to identify the domains of LRRC37B receptor responsible for the interaction with FGF13A, we generated a series of LRRC37B constructs containing deletions in the extracellular domain of LRRC37B, fused at the N-terminal with the prolactin leader peptide and an hemagglutinin (HA) tag, and at the C-terminal with the transmembrane domain of PDGF-R (Platelet-Derived Growth Factor Receptor) (Figure 3D). We performed IPs of the different LRRC37B deletion mutants transfected in HEK293T cells, following application of FGF13A to the culture medium. This revealed that the LRR domain (amino acids 468–841) was necessary and sufficient to bind to FGF13A (Figure 3E). Similar coIPs were observed following co-transfection of LRRC37B and FGF13A cDNAs and FGF13A IP (Figure S4B). We also compared the molecular properties of human LRRC37B with macaque and chimpanzee LRRC37B proteins. This revealed that the chimpanzee protein could bind to FGF13A, while the macaque LRRC37B did not (Figure S4C), in line with its shorter LRR domain structure (Figure S1B). Similarly, human LRRC37A2, which displays an LRR domain very similar to LRRC37B (Figure S1A), could bind to FGF13A (Figure S4C). To assess the specificity of this interaction, we performed the same approach with the extracellular domains of other membrane receptors (GPR158, SLITRK2, LRRTM1, and CD4), including several LRR receptors. None of them coIPed FGF13A (Figure S4D).

We next performed interaction measurements between the purified recombinant LRR domain (amino acids 468–841) fused at its N terminus with a FLAG tag (Figure S4E) and a synthetic peptide corresponding to F13ExonS. As negative controls, we used synthetically produced random peptides, and the ExonU of FGF13B (F13ExonU;Figure 3A). Fluorescent polarization (FP) assays showed that LRR binds strongly to F13ExonS (dissociation constant, K_d = 530 nM), whereas no binding was observed for the negative controls, including F13ExonU (Figure 3F). The affinity of the interaction between F13ExonS and LRRC37B was also estimated by performing cell-surface-binding assays using a biotin-labeled F13ExonS synthetic peptide and HEK293T cells expressing the extracellular domain of LRRC37B and deletion mutants (Figure S4F). This revealed a specific binding of F13ExonS to the extracellular domain of LRRC37B (K_d = 1.105 ± 0.261 nM) and to the LRR domain alone (K_d = 1.179 ± 0.280 nM), while no binding was detected with LRRC37B mutant devoid of LRR (Figure S4F).

Overall, these experiments indicate that the LRR domain of LRRC37B interacts directly and with high affinity with F13ExonS.

Extracellular FGF13A and F13ExonS bind to Nav channel SCN8A/Nav1.6

FGF13 was previously reported to modulate the function of Nav channels through binding of its core domain to an intracellular domain of the channel.^64,65,66,67 Given our data above, we hypothesized that extracellular FGF13A could potentially bind to Nav channels. We first tested whether FGF13A and F13ExonS could bind to the Nav channel Nav1.6 (encoded bysodium-voltage-gated channel alpha subunit 8,SCN8A), a major Nav channel that initiates AP at the AIS of CPNs.^29,68,69 FGF13A and F13ExonS, when applied in the medium of HEK293T cells transfected for Nav1.6, could be coIPed with Nav1.6 (Figure 3G). Moreover, binding assays using a biotin-labeled F13ExonS peptide and HEK293T cells expressing Nav1.6 revealed specific binding of F13ExonS to Nav1.6 (K_d = 49.826 ± 0.261 nM) (Figure S4G).

Finally, co-transfecting the three proteins in HEK293T cells revealed that LRRC37B could not be coIP with Nav1.6 alone, while it could be found in the same complex in the presence of FGF13A (Figure 3H).

These data indicate that FGF13A when applied extracellularly can bind directly to LRRC37B and to the Nav channel Nav1.6, allowing the three proteins to form a complex when co-expressed together (Figure 3I).

Extracellular FGF13A and F13ExonS decrease the intrinsic excitability of CPNs

We next tested whether extracellular FGF13A may affect the physiological properties of mouse CPNsin vivo. We performed patch-clamp recordings of mouse non-electroporated cortical slices (barrel cortex at P24–P32) combined with extracellular bath application of recombinant protein FGF13A (Figures 4 andS5A–S5D;Table S4). This revealed a dose-dependent effect of FGF13A on neuronal excitability at 10–50 nM, leading to decreased AP firing rate, increased rheobase, increased AP risetime and width, as observed following LRRC37B gain of function (Figures 4A–4E,S5A, and S5B;Table S4). FGF13A addition had no effect on membrane resistance and capacitance (Figure S5B;Table S4). Phase plot analyses on multiple trains of AP revealed that FGF13A extracellular application led to a decrease in the AIS compartment (−17.8%), as observed following LRRC37B gain of function (Figures 4F andS5D). However, unlike for LRRC37B, we also detected effects on the soma (−9.4%) and during repolarization phases (Figure 4F). Moreover, we observed a global decrease in ionic currents, reflecting mostly cell body currents (Figure S5C),⁵⁵ two effects not seen following LRRC37B gain of function alone (Figure S3I). F13ExonS elicited the same effects as FGF13A except for the AP width (Figures 4A andS5A–S5C;Table S4).

In contrast, the same experiments performed with intracellular application of FGF13A at the same concentration (50 nM) did not lead to detectable effects on neuronal excitability, except a small decrease in AP amplitude and sodium currents (Figures S5E–S5I), which could be due to leakage of internal medium from the recording pipette during the cellular approach phase. These results further indicate that at this concentration, FGF13A exerts its effects essentially at the extracellular level.

Thus, extracellular FGF13A can decrease mouse CPN excitability, but at global levels not restricted to the AIS, unlike LRRC37B.

LRRC37B concentrates FGF13A function at the AIS of CPNs

We next examined the functional interaction between LRRC37B, Nav1.6, and FGF13Ain vivo in LRRC37B-expressing mouse CPNs versus control CPNs. We performed coIP of LRRC37B from electroporated cortex, which confirmedin vivo the interaction between LRRC37B and FGF13A (Figure S6A). We then examined the distribution of the proteins by immunofluorescence. This revealed that FGF13A was present also at the level of the AIS (Figures 5A and 5B), but more abundantly in LRRC37B-expressing CPNs than in control CPNs, in distinct patches along the AIS (Figures 5B andS6B). STED (stimulated emission depletion) microscopy confirmed that LRRC37B was expressed at the level of the AIS in the vicinity of Nav1.6 and FGF13A, with a high co-occurrence between LRRC37B and Navα (r = 0.57 ± 0.17), and moderate co-occurrence between LRRC37B and FGF13A (r = 0.32 ± 0.17) (Figure 5A). We measured autocorrelation and periodicity of LRRC37B, FGF13A, and Navα signals. We obtained similar periodicity values for all proteins in the range of 190 nm (Figure S6C), as typically found for AIS protein clusters.^29,70

To test the impact of FGF13A-LRRC37B on neuronal function, we combined FGF13A extracellular application (50 nM) with LRRC37B gain of function in mouse CPNsin vivo. The effects of FGF13A application and LRRC37B overexpression were similar but non-additive, leading to similarly decreased AP firing rate, increased rheobase, increased AP risetime and width, and decreased AP generation at the AIS level (Figures 5C–5G andS6D–S6F). The effects of FGF13A on ionic currents were unaffected by LRRC37B overexpression (Figure S6G), consistent with global effects of FGF13A on all neuronal compartments (Figures 4F,5G,S5C, andS6G), and those of LRRC37B restricted to the AIS (Figures 2F and5G).

Altogether, these data indicate that LRRC37B interacts with FGF13A at the AIS and thereby concentrates its effects on neuronal excitability at this level.

LRRC37B binds to the Navβ subunit 1 (SCN1B)

To identify additional binding partners of LRRC37B, we performed affinity purification of rat brain extracts using as a bait the ectodomain of LRRC37B fused to the Fc portion of human IgG (LRRC37B_ECTO-Fc),⁷¹ followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, compared with Fc alone. Several membrane proteins of the AIS were detected uniquely in the LRRC37B_ECTO-Fc condition, at low levels, including the Nav channel Nav1.1 (encoded bySCN1A [sodium voltage-gated channel alpha subunit 1]), but also the regulatory Navβ subunit SCN1B (encoded bysodium voltage-gated channel beta subunit 1) (Figure S7A). AIS proteins are resistant to detergents, which makes their extraction challenging,⁷² hence the generally low number of spectral counts.

Nav β-subunits are not channels but cell adhesion molecules that can directly bind to and positively regulate the trafficking and function of Nav channels, and are thereby critically involved in neuronal excitability.^73,74 We therefore tested their potential interactions with LRRC37B. Using heterologous co-expression in HEK193T cells, we found that the extracellular part of LRRC37B could coIP SCN1B (Figures 6A–6C). We next tested for the interaction of SCN1B with several LRRC37B deletion mutants. We found that the LB domain (amino acids 133–186 of LRRC37B) was necessary to mediate the binding between LRRC37B and SCN1B (Figures 6A and 6B). Consistent with the importance of the LB domain for SCN1B interaction, we detected no interaction between SCN1B and LRRC37A2 that lacks this domain, while macaque and chimpanzee LRRC37B receptors both displayed binding to SCN1B (Figure S7B).

Overall, these data show that the LB domain of LRRC37B is necessary and sufficient to mediate the binding to SCN1B.

Finally, we tested the interactions between LRRC37B and its binding partners FGF13A and SCN1B, as well as Nav1.6. We found that LRRC37B, SCN1B, and FGF13A could be coIPed in the same complex, while SCN1B alone could not bind to FGF13A (Figure 6C). SCN1B was found to bind to Nav1.6, as expected,⁷³ but this interaction was abolished when co-transfecting LRRC37B (Figure 6D).

These results indicate that LRRC37B binds to SCN1B through its specific LB domain and that LRRC37B and Nav1.6 can compete for their binding to SCN1B, the functional consequence of which remains to be explored.

LRRC37B regulates human CPN excitability

Could LRRC37B interactions with Nav1.6 regulators FGF13A and SCN1B be physiologically relevant in the human cerebral cortexin vivo?

By examining scRNA-seq databases³⁶ we found that FGF13, SCN1B, SCN8A (Nav1.6), and LRRC37B were co-expressed in most types of human cortical neurons (Figure S7C). FGF13 was expressed at higher levels in GABAergic interneurons compared with CPN (>2-fold, adjusted p value < 10⁻⁷, Wilcoxon rank-sum test) (Figure S7C). SCN8A and SCN1B were expressed at higher levels in cortical neurons compared with non-neuronal cells (>3-fold for each, adjusted p values < 2 × 10⁻⁵⁶, Wilcoxon rank-sum tests). We next performed co-IP experiments from human cortical tissue, which revealed that Navα subunits (Nav channels), LRRC37B, SCN1B, and FGF13A were found in the same IP complex (Figure 7A).

Finally, we performed acute patch-clamp recordings on humanex vivo temporal cortex biopsies (focusing on cortical layer II/III CPNs) (Figure 7B;Table S2). We confirmed that human L2/3 CPNs display a lower excitability compared with mouse counterparts, as previously reported (Figure S7D).¹⁵ Next, taking advantage of the fact that only a subset (>40%) of human L2/3 CPNs express LRRC37B (Figure 1I), we compared the properties of LRRC37B-positive versus LRRC37B-negative neurons. Cells were filled with biocytin during electrophysiological recordings, followed by LRRC37B immunostainings (Figure 7C).

This revealed that LRRC37B-positive neurons display lower excitability compared with LRRC37B-negative neurons, with a decreased AP firing rate, an increased rheobase and increased AP risetime and width (Figures 7D–7G), while we observed no differences in input resistance, capacitance, ionic currents (Figures S7E and S7F). Phase plot analysis of single APs (measured through 2 different independent approaches—see “Methods 2 and3”) revealed that LRRC37B-positive neurons display a decrease in the AIS compartment (between −22% and −29%) compared with LRRC37B-negative neurons, while other compartments remained unchanged (Figures 7H,S7G, and S7H). Finally, as the cortical depth, size of the soma, and length of the AIS have been associated with changes in neuronal excitability,^19,30,36 we examined these parameters but detected no differences between LRRC37B-positive and LRRC37B-negative neurons (Figures S7I–S7K).

Overall, these data indicate that endogenous expression of LRRC37B in human CPNs is associated with decreased intrinsic excitability at the level of the AIS.

Limitations of the study

Because of limited chimpanzee sample availability, we could test only chimpanzee temporal cortex at the protein level, and the PFC at the RNA level: it remains to be determined whether and how LRRC37B is expressed and functional in the chimpanzee in other brain/cortical areas. The impact of LRRC37B on membrane resistance and capacitance in mouse but not human neurons should be clarified further. The exact contribution of SCN1B to LRRC37B/Nav functions remains to be elucidated.

Key resources table

Resource availability

Experimental model and study participant details

Method details

Quantification and statistical analysis

Data are represented as mean + standard error of the mean (SEM), mean ± standard deviation (SD), individual values with median, individual values with mean+SEM, median ± quartiles or median + SE median (see Main text,Figures 1,2,3,4,5,6, and7 legends,Figures S1–S7 legends, andSTAR Methods sections). Unpaired Mann-Whitney test or paired Wilcoxon tests have been used for assessing the significance of differences in the analyses containing two conditions using GraphPad (see Main text;Figures 2,4,5, and7 legends;Figures S3,S5,S6, andS7 legends; andSTAR Methods sections as well as for n description). Differential gene expression between human and chimpanzee was assessed with Deseq2 test with pseudo-bulk approach and between human clusters using Wilcoxon ranked sum test using R (see Main text,Figures 1 andS2 legends, andSTAR Methods sections). We selected unpaired Mann-Whitney tests because we assumed that we selected randomly neurons analysed, that the two samples tested (e.g. LRRC37B vs control) were independent, and because we measured continuous or ordinal variables that can be ranked. We selected paired Wilcoxon tests because we assumed that pairs (e.g. a neuron before and after application) were selected randomly, because we measured continuous variables that can be ranked, and because we used >5 pairs per test.

For transcriptomic analysis, data from Hodge et al.³⁵ originate from 5 human individuals (29 years old male, 42 years old male, 43 years old female, 50 years old male, 60 years old female), Ma et al.⁴⁸ from 4 individuals for each species (for human: 19 years old male, 36 years old male, 50 years old female, 64 years old male; for chimpanzee: 27 years old male, 31 years old male, 45 years old female, 50 years old female) and Herring et al.⁵¹ from 25 individuals (2 days old to 40 years old, 11 females and 14 males).

For stainings on primate cortical sections, details are indicated inTable S3. Data for human white matter are from 3 pictures per individual from 2 individuals (30, 54 yo). For human AIS intensity profile data we analysed 60 neurons per patient, 3 patients (7-38 years old, seeTable S2); and for electrophysiology, 4-6 neurons per patient and 12 patients (4-62 years old, seeTable S2).

For mouse image quantification data, we used at least 3 neurons per animal, 3 animals per litter (littermates comparison) and at least 3 litters. For mouse IUE electrophysiological datasets we used 9-15 animals per group from at least four litters except forFigure S3G in which we used 2 animals per group from 1 litter. Peptide application was done on 2-7 animals per condition. Single AP properties (risetime, decaytime, width, amplitude, single AP phase plots) were recorded as a single AP per neuron.

For co-IPs, experiments with HEK-293T cells have been performed >3 times, experiments from mouse in vivo samples > 2 times and human in vivo samples >3 times. Fluorescent polarization measures have been performed 9 times with the same LRR protein batch.

Author contributions

Conceptualization and methodology, B.L.-P. and P.V.; formal analysis, B.L.-P., A.L., K.W., N.L., E.E., I.V., M.D.V., D.C.S., and M.Y.D.; investigation, B.L.-P., A.L., K.W., N.L., E.K., I.V., K.K., K.M.V., N.V., T.W.B., D.C.S., M.Y.D., D.C., J.S., J.d.W., and P.V.; transcriptome analysis, E.E. and B.L.-P.; copy-number analysis, D.C.S. and M.Y.D.; electrophysiological recording and analysis, K.W., I.V., and A.L.;in utero electroporations and mouse cortex processing for immunostaining, B.L.-P., A.L., and S.B.; molecular cloning assistance, A.L., V.G., and K.M.V.; cryosections, A.B. and B.L.-P.; recruitment and informed consent of human subjects and surgical resection of human cortical tissue, T.T.; human biopsy processing assistance, A.L., I.V., and H.N.; ELISA assay, T.W.B. and D.C.; recombinant protein production and SEC-MALS, B.L.-P., T.J., M.D., and M.D.V.; fluorescent polarization measures, N.L., K.K., F.R., and J.S.; protein pull-down experiment, K.M.V. and J.d.W.; affinity estimation assays, B.L.-P. and N.V.; all other experimental work and analyses, B.L.-P. and A.L.; writing, B.L.-P. and P.V.; funding acquisition, P.V.; resources, P.V.; supervision, J.d.W. and P.V.

Declaration of interests

B.L.-P., P.V., J.d.W., A.L., K.W., J.S., F.R., N.L, and K.K. are inventors on a PCT application related to this work.

• 1.Richerson P.J., Gavrilets S., de Waal F.B.M. Modern theories of human evolution foreshadowed by Darwin’s Descent of Man. Science. 2021;372:eaba3776. doi: 10.1126/science.aba3776. [DOI] [PubMed] [Google Scholar]
• 2.Buckner R.L., Krienen F.M. The evolution of distributed association networks in the human brain. Trends Cogn. Sci. 2013;17:648–665. doi: 10.1016/j.tics.2013.09.017. [DOI] [PubMed] [Google Scholar]
• 3.Herculano-Houzel S. The human brain in numbers: a linearly scaled-up primate brain. Front. Hum. Neurosci. 2009;3:31. doi: 10.3389/neuro.09.031.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 4.Vanderhaeghen P., Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat. Rev. Neurosci. 2023;24:213–232. doi: 10.1038/s41583-023-00675-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 5.Sousa A.M.M.M., Meyer K.A., Santpere G., Gulden F.O., Sestan N. Evolution of the human nervous system function, structure, and development. Cell. 2017;170:226–247. doi: 10.1016/j.cell.2017.06.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 6.Libé-Philippot B., Vanderhaeghen P. Cellular and molecular mechanisms linking human cortical development and evolution. Annu. Rev. Genet. 2021;55:555–581. doi: 10.1146/annurev-genet-071719-020705. [DOI] [PubMed] [Google Scholar]
• 7.Fair T., Pollen A.A. Genetic architecture of human brain evolution. Curr. Opin. Neurobiol. 2023;80:102710. doi: 10.1016/j.conb.2023.102710. [DOI] [PubMed] [Google Scholar]
• 8.Roberts R.J.V., Pop S., Prieto-Godino L.L. Evolution of central neural circuits: state of the art and perspectives. Nat. Rev. Neurosci. 2022;23:725–743. doi: 10.1038/s41583-022-00644-y. [DOI] [PubMed] [Google Scholar]
• 9.Sherwood C.C., Lee P.W.H.H., Rivara C.B., Holloway R.L., Gilissen E.P.E.E., Simmons R.M.T.T., Hakeem A., Allman J.M., Erwin J.M., Hof P.R. Evolution of specialized pyramidal neurons in primate visual and motor cortex. Brain Behav. Evol. 2003;61:28–44. doi: 10.1159/000068879. [DOI] [PubMed] [Google Scholar]
• 10.Sherwood C.C., Miller S.B., Karl M., Stimpson C.D., Phillips K.A., Jacobs B., Hof P.R., Raghanti M.A., Smaers J.B. Invariant synapse density and neuronal connectivity scaling in primate neocortical evolution. Cereb. Cortex. 2020;30:5604–5615. doi: 10.1093/cercor/bhaa149. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 11.Molnár G., Oláh S., Komlósi G., Füle M., Szabadics J., Varga C., Barzó P., Tamás G. Complex events initiated by individual spikes in the human cerebral cortex. PLoS Biol. 2008;6:e222. doi: 10.1371/journal.pbio.0060222. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 12.Molnár G., Rózsa M., Baka J., Holderith N., Barzó P., Nusser Z., Tamás G. Human pyramidal to interneuron synapses are mediated by multi-vesicular release and multiple docked vesicles. eLife. 2016;5:1–12. doi: 10.7554/eLife.18167. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 13.Szegedi V., Paizs M., Csakvari E., Molnar G., Barzo P., Tamas G., Lamsa K. Plasticity in single axon glutamatergic connection to GABAergic interneurons regulates complex events in the human neocortex. PLoS Biol. 2016;14:e2000237. doi: 10.1371/journal.pbio.2000237. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 14.Testa-Silva G., Verhoog M.B., Linaro D., de Kock C.P.J., Baayen J.C., Meredith R.M., De Zeeuw C.I., Giugliano M., Mansvelder H.D. High bandwidth synaptic communication and frequency tracking in human neocortex. PLoS Biol. 2014;12 doi: 10.1371/journal.pbio.1002007. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 15.Beaulieu-Laroche L., Toloza E.H.S., van der Goes M.S., Lafourcade M., Barnagian D., Williams Z.M., Eskandar E.N., Frosch M.P., Cash S.S., Harnett M.T. Enhanced dendritic compartmentalization in human cortical neurons. Cell. 2018;175:643–651.e14. doi: 10.1016/j.cell.2018.08.045. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 16.Kalmbach B.E., Buchin A., Long B., Close J., Nandi A., Miller J.A., Bakken T.E., Hodge R.D., Chong P., de Frates R., et al. h-Channels contribute to divergent intrinsic membrane properties of supragranular pyramidal neurons in human versus mouse cerebral cortex. Neuron. 2018;100:1194–1208.e5. doi: 10.1016/j.neuron.2018.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 17.Gidon A., Zolnik T.A., Fidzinski P., Bolduan F., Papoutsi A., Poirazi P., Holtkamp M., Vida I., Larkum M.E. Dendritic action potentials and computation in human layer 2/3 cortical neurons. Science. 2020;367:83–87. doi: 10.1126/science.aax6239. [DOI] [PubMed] [Google Scholar]
• 18.Geirsdottir L., David E., Keren-Shaul H., Weiner A., Bohlen S.C., Neuber J., Balic A., Giladi A., Sheban F., Dutertre C.A., et al. Cross-species single-cell analysis reveals divergence of the primate microglia program. Cell. 2019;179:1609–1622.e16. doi: 10.1016/j.cell.2019.11.010. [DOI] [PubMed] [Google Scholar]
• 19.Beaulieu-Laroche L., Brown N.J., Hansen M., Toloza E.H.S., Sharma J., Williams Z.M., Frosch M.P., Cosgrove G.R., Cash S.S., Harnett M.T. Allometric rules for mammalian cortical layer 5 neuron biophysics. Nature. 2021;600:274–278. doi: 10.1038/s41586-021-04072-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 20.Schwarz N., Uysal B., Welzer M., Bahr J.C., Layer N., Löffler H., Stanaitis K., Pa H., Weber Y.G., Hedrich U.B.S., et al. Long-term adult human brain slice cultures as a model system to study human CNS circuitry and disease. eLife. 2019;8:1–26. doi: 10.7554/eLife.48417. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 21.Deitcher Y., Eyal G., Kanari L., Verhoog M.B., Atenekeng Kahou G.A., Mansvelder H.D., De Kock C.P.J., Segev I. Comprehensive morpho-electrotonic analysis shows 2 distinct classes of L2 and L3 pyramidal neurons in human temporal cortex. Cereb. Cortex. 2017;27:5398–5414. doi: 10.1093/cercor/bhx226. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 22.Eyal G., Verhoog M.B., Testa-Silva G., Deitcher Y., Lodder J.C., Benavides-Piccione R., Morales J., Defelipe J., de Kock C.P.J., Mansvelder H.D., et al. Unique membrane properties and enhanced signal processing in human neocortical neurons. eLife. 2016;5:e16553. doi: 10.7554/eLife.16553. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 23.Kalmbach B.E., Hodge R.D., Jorstad N.L., Owen S., de Frates R., Yanny A.M., Dalley R., Mallory M., Graybuck L.T., Radaelli C., et al. Signature morpho-electric, transcriptomic, and dendritic properties of human layer 5 neocortical pyramidal neurons. Neuron. 2021;109:2914–2927.e5. doi: 10.1016/j.neuron.2021.08.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 24.Wilbers R., Metodieva V.D., Duverdin S., Heyer D.B., Galakhova A.A., Mertens E.J., Versluis T.D., Baayen J.C., Idema S., Noske D.P., et al. Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling. Sci. Adv. 2023;9:eade3300. doi: 10.1126/sciadv.ade3300. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 25.Ferguson K.A., Cardin J.A. Mechanisms underlying gain modulation in the cortex. Nat. Rev. Neurosci. 2020;21:80–92. doi: 10.1038/s41583-019-0253-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 26.Beck H., Yaari Y. Plasticity of intrinsic neuronal properties in CNS disorders. Nat. Rev. Neurosci. 2008;9:357–369. doi: 10.1038/nrn2371. [DOI] [PubMed] [Google Scholar]
• 27.Bean B.P. The action potential in mammalian central neurons. Nat. Rev. Neurosci. 2007;8:451–465. doi: 10.1038/nrn2148. [DOI] [PubMed] [Google Scholar]
• 28.Debanne D., Inglebert Y., Russier M. Plasticity of intrinsic neuronal excitability. Curr. Opin. Neurobiol. 2019;54:73–82. doi: 10.1016/j.conb.2018.09.001. [DOI] [PubMed] [Google Scholar]
• 29.Leterrier C. The axon initial segment, 50 years later: a nexus for neuronal organization and function. Curr. Top. Membr. 2016;77:185–233. doi: 10.1016/bs.ctm.2015.10.005. [DOI] [PubMed] [Google Scholar]
• 30.Grubb M.S., Burrone J. Activity-dependent relocation of the axon initial segment fine-tunes neuronal excitability. Nature. 2010;465:1070–1074. doi: 10.1038/nature09160. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 31.Kole M.H.P., Ilschner S.U., Kampa B.M., Williams S.R., Ruben P.C., Stuart G.J. Action potential generation requires a high sodium channel density in the axon initial segment. Nat. Neurosci. 2008;11:178–186. doi: 10.1038/nn2040. [DOI] [PubMed] [Google Scholar]
• 32.Tosches M.A. From cell types to an integrated understanding of brain evolution: the case of the cerebral cortex. Annu. Rev. Cell Dev. Biol. 2021;37:495–517. doi: 10.1146/annurev-cellbio-120319-112654. [DOI] [PubMed] [Google Scholar]
• 33.Lein E.S., Belgard T.G., Hawrylycz M., Molnár Z. Transcriptomic perspectives on neocortical structure, development, evolution, and disease. Annu. Rev. Neurosci. 2017;40:629–652. doi: 10.1146/annurev-neuro-070815-013858. [DOI] [PubMed] [Google Scholar]
• 34.Berg J., Sorensen S.A., Ting J.T., Miller J.A., Chartrand T., Buchin A., Bakken T.E., Budzillo A., Dee N., Ding S.L., et al. Human neocortical expansion involves glutamatergic neuron diversification. Nature. 2021;598:151–158. doi: 10.1038/s41586-021-03813-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 35.Hodge R.D., Bakken T.E., Miller J.A., Smith K.A., Barkan E.R., Graybuck L.T., Close J.L., Long B., Johansen N., Penn O., et al. Conserved cell types with divergent features in human versus mouse cortex. Nature. 2019;573:61–68. doi: 10.1038/s41586-019-1506-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 36.Bakken T.E., Jorstad N.L., Hu Q., Lake B.B., Tian W., Kalmbach B.E., Crow M., Hodge R.D., Krienen F.M., Sorensen S.A., et al. Comparative cellular analysis of motor cortex in human, marmoset and mouse. Nature. 2021;598:111–119. doi: 10.1038/s41586-021-03465-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 37.Jorstad N.L., Song J.H.T., Exposito-Alonso D., Suresh H., Castro-Pacheco N., Krienen F.M., Yanny A.M., Close J., Gelfand E., Long B., et al. Comparative transcriptomics reveals human-specific cortical features. Science. 2023;382:eade9516. doi: 10.1126/science.ade9516. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 38.Dennis M.Y., Eichler E.E. Human adaptation and evolution by segmental duplication. Curr. Opin. Genet. Dev. 2016;41:44–52. doi: 10.1016/j.gde.2016.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 39.Suzuki I.K., Gacquer D., Van Heurck R., Kumar D., Wojno M., Bilheu A., Herpoel A., Lambert N., Cheron J., Polleux F., et al. Human-specific NOTCH2NL genes expand cortical neurogenesis through delta/Notch regulation. Cell. 2018;173:1370–1384.e16. doi: 10.1016/j.cell.2018.03.067. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 40.Florio M., Albert M., Taverna E., Namba T., Brandl H., Lewitus E., Haffner C., Sykes A., Wong F.K., Peters J., et al. Human-specific gene ARHGAP11B promotes basal progenitor amplification and neocortex expansion. Science. 2015;347:1465–1470. doi: 10.1126/science.aaa1975. [DOI] [PubMed] [Google Scholar]
• 41.Fiddes I.T., Lodewijk G.A., Mooring M., Bosworth C.M., Ewing A.D., Mantalas G.L., Novak A.M., van den Bout A., Bishara A., Rosenkrantz J.L., et al. Human-specific NOTCH2NL genes affect Notch signaling and cortical neurogenesis. Cell. 2018;173:1356–1369.e22. doi: 10.1016/j.cell.2018.03.051. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 42.Van Heurck R., Bonnefont J., Wojno M., Suzuki I.K., Velez-Bravo F.D., Erkol E., Nguyen D.T., Herpoel A., Bilheu A., Beckers S., et al. CROCCP2 acts as a human-specific modifier of cilia dynamics and mTOR signaling to promote expansion of cortical progenitors. Neuron. 2023;111:65–80.e6. doi: 10.1016/j.neuron.2022.10.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 43.Charrier C., Joshi K., Coutinho-Budd J., Kim J.E., Lambert N., De Marchena J., Jin W.L., Vanderhaeghen P., Ghosh A., Sassa T., et al. Inhibition of SRGAP2 function by its human-specific paralogs induces neoteny during spine maturation. Cell. 2012;149:923–935. doi: 10.1016/j.cell.2012.03.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 44.Hou Q.Q., Xiao Q., Sun X.Y., Ju X.C., Luo Z.G. TBC1D3 promotes neural progenitor proliferation by suppressing the histone methyltransferase G9a. Sci. Adv. 2021;7:eaba8053. doi: 10.1126/sciadv.aba8053. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 45.Schmidt E.R.E., Zhao H.T., Park J.M., Dipoppa M., Monsalve-Mercado M.M., Dahan J.B., Rodgers C.C., Lejeune A., Hillman E.M.C., Miller K.D., et al. A human-specific modifier of cortical connectivity and circuit function. Nature. 2021;599:640–644. doi: 10.1038/s41586-021-04039-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 46.Giannuzzi G., Siswara P., Malig M., Marques-Bonet T., NISC Comparative Sequencing Program. Mullikin J.C., Ventura M., Eichler E.E. Evolutionary dynamism of the primate LRRC37 gene family. Genome Res. 2013;23:46–59. doi: 10.1101/gr.138842.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 47.De Wit J., Hong W., Luo L., Ghosh A. Role of leucine-rich repeat proteins in the development and function of neural circuits. Annu. Rev. Cell Dev. Biol. 2011;27:697–729. doi: 10.1146/annurev-cellbio-092910-154111. [DOI] [PubMed] [Google Scholar]
• 48.Ma S., Skarica M., Li Q., Xu C., Risgaard R.D., Tebbenkamp A.T.N., Mato-Blanco X., Kovner R., Krsnik Ž., de Martin X., et al. Molecular and cellular evolution of the primate dorsolateral prefrontal cortex. Science. 2022;377:eabo7257. doi: 10.1126/science.abo7257. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 49.Shen F., Kidd J.M. Rapid, paralog-sensitive CNV analysis of 2457 human genomes using quick-mer2. Genes (Basel) 2020;11 doi: 10.3390/genes11020141. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 50.1000 Genomes Project Consortium. Auton A., Brooks L.D., Durbin R.M., Garrison E.P., Kang H.M., Korbel J.O., Marchini J.L., McCarthy S., McVean G.A., et al. A global reference for human genetic variation. Nature. 2015;526:68–74. doi: 10.1038/nature15393. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 51.Herring C.A., Simmons R.K., Freytag S., Poppe D., Moffet J.J.D., Pflueger J., Buckberry S., Vargas-Landin D.B., Clément O., Echeverría E.G., et al. Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution. Cell. 2022;185:4428–4447.e28. doi: 10.1016/j.cell.2022.09.039. [DOI] [PubMed] [Google Scholar]
• 52.Cardoso-Moreira M., Halbert J., Valloton D., Velten B., Chen C., Shao Y., Liechti A., Ascenção K., Rummel C., Ovchinnikova S., et al. Gene expression across mammalian organ development. Nature. 2019;571:505–509. doi: 10.1038/s41586-019-1338-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 53.Tian C., Wang K., Ke W., Guo H., Shu Y. Molecular identity of axonal sodium channels in human cortical pyramidal cells. Front. Cell. Neurosci. 2014;8:297. doi: 10.3389/fncel.2014.00297. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 54.Jenerick H. Phase plane trajectories of the muscle spike potential. Biophys. J. 1963;3:363–377. doi: 10.1016/s0006-3495(63)86827-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 55.Bakkum D.J., Obien M.E.J., Radivojevic M., Jäckel D., Frey U., Takahashi H., Hierlemann A. The axon initial segment is the dominant contributor to the neuron’s extracellular electrical potential landscape. Adv. Biosyst. 2019;3:e1800308. doi: 10.1002/adbi.201800308. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 56.Gallo N.B., Paul A., Van Aelst L. Shedding light on chandelier cell development, connectivity, and contribution to neural disorders. Trends Neurosci. 2020;43:565–580. doi: 10.1016/j.tins.2020.05.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 57.Ranaivoson F.M., Turk L.S., Ozgul S., Kakehi S., von Daake S., Lopez N., Trobiani L., De Jaco A., Denissova N., Demeler B., et al. A proteomic screen of neuronal cell-surface molecules reveals IgLONs as structurally conserved interaction modules at the synapse. Structure. 2019;27:893–906.e9. doi: 10.1016/j.str.2019.03.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 58.Ozgul S., von Daake S., Kakehi S., Sereni D., Denissova N., Hanlon C., Huang Y.J., Everett J.K., Yin C., Montelione G.T., et al. An ELISA-based screening platform for ligand–receptor discovery. Methods Enzymol. 2019;615:453–475. doi: 10.1016/bs.mie.2018.10.001. [DOI] [PubMed] [Google Scholar]
• 59.Apóstolo N., Smukowski S.N., Vanderlinden J., Condomitti G., Rybakin V., ten Bos J., Trobiani L., Portegies S., Vennekens K.M., Gounko N.V., et al. Synapse type-specific proteomic dissection identifies IgSF8 as a hippocampal CA3 microcircuit organizer. Nat. Commun. 2020;11:5171. doi: 10.1038/s41467-020-18956-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 60.Dover K., Solinas S., D’Angelo E., Goldfarb M. Long-term inactivation particle for voltage-gated sodium channels. J. Physiol. 2010;588:3695–3711. doi: 10.1113/jphysiol.2010.192559. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 61.Smallwood P.M., Munoz-Sanjuan I., Tong P., Macke J.P., Hendry S.H.C., Gilbert D.J., Copeland N.G., Jenkins N.A., Nathans J. Fibroblast growth factor (FGF) homologous factors: new members of the FGF family implicated in nervous system development. Proc. Natl. Acad. Sci. USA. 1996;93:9850–9857. doi: 10.1073/pnas.93.18.9850. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 62.Wang C., Chung B.C., Yan H., Lee S.Y., Pitt G.S. Crystal structure of the ternary complex of a NaV C-terminal domain, a fibroblast growth factor homologous factor, and calmodulin. Structure. 2012;20:1167–1176. doi: 10.1016/j.str.2012.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 63.Munoz-Sanjuan I., Smallwood P.M., Nathans J. Isoform diversity among fibroblast growth factor homologous factors is generated by alternative promoter usage and differential splicing. J. Biol. Chem. 2000;275:2589–2597. doi: 10.1074/jbc.275.4.2589. [DOI] [PubMed] [Google Scholar]
• 64.Wittmack E.K., Rush A.M., Craner M.J., Goldfarb M., Waxman S.G., Dib-Hajj S.D. Fibroblast growth factor homologous factor 2B: association with Nav1.6 and selective colocalization at nodes of Ranvier of dorsal root axons. J. Neurosci. 2004;24:6765–6775. doi: 10.1523/JNEUROSCI.1628-04.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 65.Goetz R., Dover K., Laezza F., Shtraizent N., Huang X., Tchetchik D., Eliseenkova A.V., Xu C.F., Neubert T.A., Ornitz D.M., et al. Crystal structure of a fibroblast growth factor homologous factor (FHF) defines a conserved surface on FHFs for binding and modulation of voltage-gated sodium channels. J. Biol. Chem. 2009;284:17883–17896. doi: 10.1074/jbc.M109.001842. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 66.Wang C., Wang C., Hoch E.G., Pitt G.S. Identification of novel interaction sites that determine specificity between fibroblast growth factor homologous factors and voltage-gated sodium channels. J. Biol. Chem. 2011;286:24253–24263. doi: 10.1074/jbc.M111.245803. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 67.Barbosa C., Xiao Y., Johnson A.J., Xie W., Strong J.A., Zhang J.M., Cummins T.R. FHF2 isoforms differentially regulate Nav1.6-mediated resurgent sodium currents in dorsal root ganglion neurons. Pflugers Arch. 2017;469:195–212. doi: 10.1007/s00424-016-1911-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 68.Lorincz A., Nusser Z. Cell-type-dependent molecular composition of the axon initial segment. J. Neurosci. 2008;28:14329–14340. doi: 10.1523/JNEUROSCI.4833-08.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 69.Hu W., Tian C., Li T., Yang M., Hou H., Shu Y. Distinct contributions of Na(v)1.6 and Na(v)1.2 in action potential initiation and backpropagation. Nat. Neurosci. 2009;12:996–1002. doi: 10.1038/nn.2359. [DOI] [PubMed] [Google Scholar]
• 70.Vassilopoulos S., Gibaud S., Jimenez A., Caillol G., Leterrier C. Ultrastructure of the axonal periodic scaffold reveals a braid-like organization of actin rings. Nat. Commun. 2019;10:5803. doi: 10.1038/s41467-019-13835-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 71.Savas J.N., De Wit J., Comoletti D., Zemla R., Ghosh A., Yates J.R. Ecto-Fc MS identifies ligand-receptor interactions through extracellular domain Fc fusion protein baits and shotgun proteomic analysis. Nat. Protoc. 2014;9:2061–2074. doi: 10.1038/nprot.2014.140. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 72.Hamdan H., Lim B.C., Torii T., Joshi A., Konning M., Smith C., Palmer D.J., Ng P., Leterrier C., Oses-Prieto J.A., et al. Mapping axon initial segment structure and function by multiplexed proximity biotinylation. Nat. Commun. 2020;11:100. doi: 10.1038/s41467-019-13658-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 73.Namadurai S., Yereddi N.R., Cusdin F.S., Huang C.L.H., Chirgadze D.Y., Jackson A.P. A new look at sodium channel β subunits. Open Biol. 2015;5:140192. doi: 10.1098/rsob.140192. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 74.O’Malley H.A., Isom L.L. Sodium channel β subunits: emerging targets in channelopathies. Annu. Rev. Physiol. 2015;77:481–504. doi: 10.1146/annurev-physiol-021014-071846. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 75.Martín-Sánchez C., Alés E., Balseiro-Gómez S., Atienza G., Arnalich F., Bordas A., Cedillo J.L., Extremera M., Chávez-Reyes A., Montiel C. The human-specific duplicated α7 gene inhibits the ancestral α7, negatively regulating nicotinic acetylcholine receptor-mediated transmitter release. J. Biol. Chem. 2021;296:100341. doi: 10.1016/j.jbc.2021.100341. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 76.Moradi Chameh H., Rich S., Wang L., Chen F.D., Zhang L., Carlen P.L., Tripathy S.J., Valiante T.A. Diversity amongst human cortical pyramidal neurons revealed via their sag currents and frequency preferences. Nat. Commun. 2021;12:2497. doi: 10.1038/s41467-021-22741-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 77.Rabouille C. Pathways of unconventional protein secretion. Trends Cell Biol. 2017;27:230–240. doi: 10.1016/j.tcb.2016.11.007. [DOI] [PubMed] [Google Scholar]
• 78.Abrams J., Roybal D., Chakouri N., Katchman A.N., Weinberg R., Yang L., Chen B.X., Zakharov S.I., Hennessey J.A., Avula U.M.R., et al. Fibroblast growth factor homologous factors tune arrhythmogenic late NaV1.5 current in calmodulin binding-deficient channels. JCI Insight. 2020;5:e141736. doi: 10.1172/jci.insight.141736. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 79.Effraim P.R., Huang J., Lampert A., Stamboulian S., Zhao P., Black J.A., Dib-Hajj S.D., Waxman S.G. Fibroblast growth factor homologous factor 2 (FGF-13) associates with Nav1.7 in DRG neurons and alters its current properties in an isoform-dependent manner. Neurobiol. Pain. 2019;6:100029. doi: 10.1016/j.ynpai.2019.100029. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 80.Yang J., Wang Z., Sinden D.S., Wang X., Shan B., Yu X., Zhang H., Pitt G.S., Wang C. FGF13 modulates the gating properties of the cardiac sodium channel Nav1.5 in an isoform-specific manner. Channels (Austin) 2016;10:410–420. doi: 10.1080/19336950.2016.1190055. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 81.Effraim P.R., Estacion M., Zhao P., Sosniak D., Waxman S.G., Dib-Hajj S.D. Fibroblast growth factor homologous factor 2 attenuates excitability of DRG neurons. J. Neurophysiol. 2022;128:1258–1266. doi: 10.1152/jn.00361.2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 82.Fry A.E., Marra C., Derrick A.V., Pickrell W.O., Higgins A.T., te Water Naude J., McClatchey M.A., Davies S.J., Metcalfe K.A., Tan H.J., et al. Missense variants in the N-terminal domain of the A isoform of FHF2/FGF13 cause an X-linked developmental and epileptic encephalopathy. Am. J. Hum. Genet. 2021;108:176–185. doi: 10.1016/j.ajhg.2020.10.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 83.Pablo J.L., Wang C., Presby M.M., Pitt G.S. Polarized localization of voltage-gated Na+ channels is regulated by concerted FGF13 and FGF14 action. Proc. Natl. Acad. Sci. USA. 2016;113:E2665–E2674. doi: 10.1073/pnas.1521194113. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 84.Favuzzi E., Deogracias R., Marques-Smith A., Maeso P., Jezequel J., Exposito-Alonso D., Balia M., Kroon T., Hinojosa A.J., F Maraver E.F., et al. Distinct molecular programs regulate synapse specificity in cortical inhibitory circuits. Science. 2019;363:413–417. doi: 10.1126/science.aau8977. [DOI] [PubMed] [Google Scholar]
• 85.Jamann N., Dannehl D., Lehmann N., Wagener R., Thielemann C., Schultz C., Staiger J., Kole M.H.P., Engelhardt M. Sensory input drives rapid homeostatic scaling of the axon initial segment in mouse barrel cortex. Nat. Commun. 2021;12:23. doi: 10.1038/s41467-020-20232-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 86.Meisler M.H., Hill S.F., Yu W. Author correction: sodium channelopathies in neurodevelopmental disorders. Nat. Rev. Neurosci. 2021;22:256. doi: 10.1038/s41583-021-00449-5. [DOI] [PubMed] [Google Scholar]
• 87.Narayanan D.L., Majethia P., Shrikiran A., Siddiqui S., Dalal A., Shukla A. Further evidence of affected females with a heterozygous variant in FGF13 causing X-linked developmental and epileptic encephalopathy 90. Eur. J. Med. Genet. 2022;65:104403. doi: 10.1016/j.ejmg.2021.104403. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 88.Devinsky O., Vezzani A., O’Brien T.J., Jette N., Scheffer I.E., de Curtis M., Perucca P. Epilepsy. Nat. Rev. Dis. Primers. 2018;4:18024. doi: 10.1038/nrdp.2018.24. [DOI] [PubMed] [Google Scholar]
• 89.Wimmer V.C., Reid C.A., So E.Y.-W., Berkovic S.F., Petrou S. Axon initial segment dysfunction in epilepsy. J. Physiol. 2010;588:1829–1840. doi: 10.1113/jphysiol.2010.188417. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 90.Zhang L., Vijg J. Somatic mutagenesis in mammals and its implications for human disease and aging. Annu. Rev. Genet. 2018;52:397–419. doi: 10.1146/annurev-genet-120417-031501. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 91.Byrska-Bishop M., Evani U.S., Zhao X., Basile A.O., Abel H.J., Regier A.A., Corvelo A., Clarke W.E., Musunuri R., Nagulapalli K., et al. High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios. Cell. 2022;185:3426–3440.e19. doi: 10.1016/j.cell.2022.08.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 92.Iwata R., Casimir P., Vanderhaeghen P. Mitochondrial dynamics in postmitotic cells regulate neurogenesis. Science. 2020;369:858–862. doi: 10.1126/science.aba9760. [DOI] [PubMed] [Google Scholar]
• 93.DeKeyser J.M., Thompson C.H., George A.L. Cryptic prokaryotic promoters explain instability of recombinant neuronal sodium channels in bacteria. J. Biol. Chem. 2021;296:100298. doi: 10.1016/j.jbc.2021.100298. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 94.Hand R., Bortone D., Mattar P., Nguyen L., Heng J.I.-T., Guerrier S., Boutt E., Peters E., Barnes A.P., Parras C., et al. Phosphorylation of Neurogenin2 specifies the migration properties and the dendritic morphology of pyramidal neurons in the neocortex. Neuron. 2005;48:45–62. doi: 10.1016/j.neuron.2005.08.032. [DOI] [PubMed] [Google Scholar]
• 95.Nurk S., Koren S., Rhie A., Rautiainen M., Bzikadze A.V., Mikheenko A., Vollger M.R., Altemose N., Uralsky L., Gershman A., et al. The complete sequence of a human genome. Science. 2022;376:44–53. doi: 10.1126/science.abj6987. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 96.Wolf F.A., Angerer P., Theis F.J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 2018;19:15. doi: 10.1186/s13059-017-1382-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 97.Cunningham F., Allen J.E., Allen J., Alvarez-Jarreta J., Amode M.R., Armean I.M., Austine-Orimoloye O., Azov A.G., Barnes I., Bennett R., et al. Ensembl 2022. Nucleic Acids Res. 2022;50:D988–D995. doi: 10.1093/nar/gkab1049. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 98.Love M.I., Huber W., Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. doi: 10.1186/s13059-014-0550-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 99.Gross G.G., Junge J.A., Mora R.J., Kwon H.B., Olson C.A., Takahashi T.T., Liman E.R., Ellis-Davies G.C.R., McGee A.W., Sabatini B.L., et al. Recombinant probes for visualizing endogenous synaptic proteins in living neurons. Neuron. 2013;78:971–985. doi: 10.1016/j.neuron.2013.04.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 100.Schroeder A., Vanderlinden J., Vints K., Ribeiro L.F., Vennekens K.M., Gounko N.V., Wierda K.D., de Wit J. A modular organization of LRR protein-mediated synaptic adhesion defines synapse identity. Neuron. 2018;99:329–344.e7. doi: 10.1016/j.neuron.2018.06.026. [DOI] [PubMed] [Google Scholar]
• 101.Condomitti G., Wierda K.D., Schroeder A., Rubio S.E., Vennekens K.M., Orlandi C., Martemyanov K.A., Gounko N.V., Savas J.N., de Wit J. An input-specific orphan receptor GPR158-HSPG interaction organizes hippocampal mossy fiber-CA3 synapses. Neuron. 2018;100:201–215.e9. doi: 10.1016/j.neuron.2018.08.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 102.Raissi A.J., Staudenmaier E.K., David S., Hu L., Paradis S. Sema4D localizes to synapses and regulates GABAergic synapse development as a membrane-bound molecule in the mammalian hippocampus. Mol. Cell. Neurosci. 2013;57:23–32. doi: 10.1016/j.mcn.2013.08.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 103.Costes S.V., Daelemans D., Cho E.H., Dobbin Z., Pavlakis G., Lockett S. Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophys. J. 2004;86:3993–4003. doi: 10.1529/biophysj.103.038422. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 104.Cordelières F.P., Zhang C. Bioimage Data Analysis Workflows. Springer; 2020. 3D quantitative colocalisation analysis; pp. 33–66. [Google Scholar]
• 105.Manders E.M.M., Verbeek F.J., Aten J.A. Measurement of co-localization of objects in dual-colour confocal images. J. Microsc. 1993;169:375–382. doi: 10.1111/j.1365-2818.1993.tb03313.x. [DOI] [PubMed] [Google Scholar]
• 106.Carravilla P., Chojnacki J., Rujas E., Insausti S., Largo E., Waithe D., Apellaniz B., Sicard T., Julien J.P., Eggeling C., et al. Molecular recognition of the native HIV-1 MPER revealed by STED microscopy of single virions. Nat. Commun. 2019;10:78. doi: 10.1038/s41467-018-07962-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 107.Nichols M.R., Moss M.A., Reed D.K., Lin W.L., Mukhopadhyay R., Hoh J.H., Rosenberry T.L. Growth of β-amyloid(1 − 40) protofibrils by monomer elongation and lateral association. Characterization of distinct products by light scattering and atomic force microscopy. Biochemistry. 2002;41:6115–6127. doi: 10.1021/bi015985r. [DOI] [PubMed] [Google Scholar]
• 108.Savas J.N., Ribeiro L.F., Wierda K.D., Wright R., DeNardo-Wilke L.A., Rice H.C., Chamma I., Wang Y.Z., Zemla R., Lavallée-Adam M., et al. The sorting receptor SorCS1 regulates trafficking of neurexin and AMPA receptors. Neuron. 2015;87:764–780. doi: 10.1016/j.neuron.2015.08.007. [DOI] [PMC free article] [PubMed] [Google Scholar]

Supplementary Materials

Data Availability Statement

• •

  All data are available in the manuscript or thesupplemental information.

• •

  This paper does not report original code.

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  Any additional information required to reanalyse the data reported in this work paper is available from thelead contact upon request.