Functional Dysregulation of CDC42 Causes Diverse Developmental Phenotypes
2018; Elsevier BV; Volume: 102; Issue: 2 Linguagem: Inglês
10.1016/j.ajhg.2017.12.015
ISSN1537-6605
AutoresSimone Martinelli, Oliver H.F. Krumbach, Francesca Pantaleoni, Simona Coppola, Ehsan Amin, Luca Pannone, Kazem Nouri, Luciapia Farina, Radovan Dvorský, Francesca Romana Lepri, Marcel Buchholzer, Raphael Konopatzki, Laurence E. Walsh, Katelyn Payne, Mary Ella Pierpont, Samantha A. Schrier Vergano, Katherine G. Langley, Douglas P. Larsen, Kelly D. Farwell, Sha Tang, Cameron Mroske, Ivan Gallotta, Elia Di Schiavi, Matteo Della Monica, Licia Lugli, Cesare Rossi, Marco Seri, Guido Cocchi, Lindsay B. Henderson, Berivan Baskin, Mariëlle Alders, Roberto Mendoza‐Londono, Lucie Dupuis, Deborah A. Nickerson, Jessica X. Chong, Naomi Meeks, Kathleen Brown, Tahnee N. Causey, Megan T. Cho, Stephanie Demuth, M. Cristina Digilio, Bruce D. Gelb, Michael J. Bamshad, Martin Zenker, Mohammad Reza Ahmadian, Raoul C. M. Hennekam, Marco Tartaglia, Ghayda Mirzaa,
Tópico(s)Congenital heart defects research
ResumoExome sequencing has markedly enhanced the discovery of genes implicated in Mendelian disorders, particularly for individuals in whom a known clinical entity could not be assigned. This has led to the recognition that phenotypic heterogeneity resulting from allelic mutations occurs more commonly than previously appreciated. Here, we report that missense variants in CDC42, a gene encoding a small GTPase functioning as an intracellular signaling node, underlie a clinically heterogeneous group of phenotypes characterized by variable growth dysregulation, facial dysmorphism, and neurodevelopmental, immunological, and hematological anomalies, including a phenotype resembling Noonan syndrome, a developmental disorder caused by dysregulated RAS signaling. In silico, in vitro, and in vivo analyses demonstrate that mutations variably perturb CDC42 function by altering the switch between the active and inactive states of the GTPase and/or affecting CDC42 interaction with effectors, and differentially disturb cellular and developmental processes. These findings reveal the remarkably variable impact that dominantly acting CDC42 mutations have on cell function and development, creating challenges in syndrome definition, and exemplify the importance of functional profiling for syndrome recognition and delineation. Exome sequencing has markedly enhanced the discovery of genes implicated in Mendelian disorders, particularly for individuals in whom a known clinical entity could not be assigned. This has led to the recognition that phenotypic heterogeneity resulting from allelic mutations occurs more commonly than previously appreciated. Here, we report that missense variants in CDC42, a gene encoding a small GTPase functioning as an intracellular signaling node, underlie a clinically heterogeneous group of phenotypes characterized by variable growth dysregulation, facial dysmorphism, and neurodevelopmental, immunological, and hematological anomalies, including a phenotype resembling Noonan syndrome, a developmental disorder caused by dysregulated RAS signaling. In silico, in vitro, and in vivo analyses demonstrate that mutations variably perturb CDC42 function by altering the switch between the active and inactive states of the GTPase and/or affecting CDC42 interaction with effectors, and differentially disturb cellular and developmental processes. These findings reveal the remarkably variable impact that dominantly acting CDC42 mutations have on cell function and development, creating challenges in syndrome definition, and exemplify the importance of functional profiling for syndrome recognition and delineation. The rate of identification of genes implicated in human disorders has dramatically increased with the use of second-generation sequencing technologies. In particular, exome sequencing has emerged as a feasible and efficient strategy to uncover the molecular basis of Mendelian disorders, particularly for individuals with a rare clinical presentation or for whom a unifying clinical diagnosis is not discerned.1Bamshad M.J. Ng S.B. Bigham A.W. Tabor H.K. Emond M.J. Nickerson D.A. Shendure J. Exome sequencing as a tool for Mendelian disease gene discovery.Nat. Rev. Genet. 2011; 12: 745-755Crossref PubMed Scopus (1261) Google Scholar Mutations affecting the same gene but resulting in substantial phenotypic differences is a very well-known phenomenon, but the wide use of exome sequencing has led to the recognition that this event occurs much more commonly than previously appreciated.2Chong J.X. Buckingham K.J. Jhangiani S.N. Boehm C. Sobreira N. Smith J.D. Harrell T.M. McMillin M.J. Wiszniewski W. Gambin T. et al.Centers for Mendelian GenomicsThe genetic basis of Mendelian phenotypes: discoveries, challenges, and opportunities.Am. J. Hum. Genet. 2015; 97: 199-215Abstract Full Text Full Text PDF PubMed Scopus (419) Google Scholar, 3Menke L.A. van Belzen M.J. Alders M. Cristofoli F. Ehmke N. Fergelot P. Foster A. Gerkes E.H. Hoffer M.J. Horn D. et al.DDD StudyCREBBP mutations in individuals without Rubinstein-Taybi syndrome phenotype.Am. J. Med. Genet. A. 2016; 170: 2681-2693Crossref PubMed Scopus (29) Google Scholar, 4Lee C.S. Fu H. Baratang N. Rousseau J. Kumra H. Sutton V.R. Niceta M. Ciolfi A. Yamamoto G. Bertola D. et al.Baylor-Hopkins Center for Mendelian GenomicsMutations in fibronectin cause a subtype of spondylometaphyseal dysplasia with “corner fractures”.Am. J. Hum. Genet. 2017; 101: 815-823Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar In the last few years, it has been recognized that the variable clinical manifestation of allelic mutations can often result from their differential impact on protein function, although the consequences of specific variants can be difficult to predict and may require substantial efforts to be fully understood.5Niceta M. Stellacci E. Gripp K.W. Zampino G. Kousi M. Anselmi M. Traversa A. Ciolfi A. Stabley D. Bruselles A. et al.Mutations impairing GSK3-mediated MAF phosphorylation cause cataract, deafness, intellectual disability, seizures, and a Down syndrome-like facies.Am. J. Hum. Genet. 2015; 96: 816-825Abstract Full Text Full Text PDF PubMed Scopus (78) Google Scholar, 6Reijnders M.R.F. Ansor N.M. Kousi M. Yue W.W. Tan P.L. Clarkson K. Clayton-Smith J. Corning K. Jones J.R. Lam W.W.K. et al.Deciphering Developmental Disorders StudyRAC1 missense mutations in developmental disorders with diverse phenotypes.Am. J. Hum. Genet. 2017; 101: 466-477Abstract Full Text Full Text PDF PubMed Scopus (82) Google Scholar, 7Martinelli S. Torreri P. Tinti M. Stella L. Bocchinfuso G. Flex E. Grottesi A. Ceccarini M. Palleschi A. Cesareni G. et al.Diverse driving forces underlie the invariant occurrence of the T42A, E139D, I282V and T468M SHP2 amino acid substitutions causing Noonan and LEOPARD syndromes.Hum. Mol. Genet. 2008; 17: 2018-2029Crossref PubMed Scopus (64) Google Scholar Here, we report that missense mutations in cell division cycle 42 (CDC42 [MIM: 116952]), a gene encoding a member of the RAS superfamily of low-molecular-weight GTP/GDP-binding proteins functioning as a major node in intracellular signaling, underlie a clinically heterogeneous group of developmental phenotypes. Our in silico, in vitro, and in vivo dissection of the structural and functional impact of disease-causing mutations documents that they variably perturb CDC42 biochemical behavior and differentially affect cellular and developmental processes, highlighting the variable impact of the functional dysregulation of this GTPase in cell physiology and development. Our findings also exemplify the importance of functional profiling for syndrome recognition and delineation. A total of 15 subjects from 13 unrelated families were included in the study. Clinical data and DNA samples were collected from the participating families (after written informed consent was obtained) and stored and used under research projects approved by the Review Boards of the participating institutions. Investigators studying the affected individuals described here were connected via the MatchMaker Exchange (MME) network of web-based tools8Philippakis A.A. Azzariti D.R. Beltran S. Brookes A.J. Brownstein C.A. Brudno M. Brunner H.G. Buske O.J. Carey K. Doll C. et al.The Matchmaker Exchange: a platform for rare disease gene discovery.Hum. Mutat. 2015; 36: 915-921Crossref PubMed Scopus (293) Google Scholar GeneMatcher and MyGene2.9Sobreira N. Schiettecatte F. Valle D. Hamosh A. GeneMatcher: a matching tool for connecting investigators with an interest in the same gene.Hum. Mutat. 2015; 36: 928-930Crossref PubMed Scopus (821) Google Scholar, 10Chong J.X. Yu J.H. Lorentzen P. Park K.M. Jamal S.M. Tabor H.K. Rauch A. Saenz M.S. Boltshauser E. Patterson K.E. et al.Gene discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features.Genet. Med. 2016; 18: 788-795Abstract Full Text Full Text PDF PubMed Scopus (63) Google Scholar Nine affected individuals (subjects 1 to 5 and 8 to 11), who exhibited a molecularly unexplained and clinically unrecognized multi-systemic disorder, were investigated by whole-exome sequencing (WES) using DNA samples obtained from either leukocytes or saliva specimens, and a child-parent trio-based strategy. Exome capture was carried out using the SureSelect Clinical Research Exome (Agilent) (subjects 1 and 8), SureSelect Human All Exon v.1, v.3, and v.5 (Agilent) (subjects 2, 10, and 5, respectively), Nextera Exome Enrichment Kit (Illumina) (subject 3), SeqCap EZ VCRome 2.0 (Roche) (subject 4), and SeqCap EZ MedExome v2 (Roche) (subjects 9 and 11) target enrichment kits, and sequencing was performed on a HiSeq 2000 platform (Illumina), using paired-end. WES data processing, sequence alignment to GRCh37, and variant filtering and prioritization by allele frequency, predicted functional impact, and inheritance models were performed as previously described.11Homsy J. Zaidi S. Shen Y. Ware J.S. Samocha K.E. Karczewski K.J. DePalma S.R. McKean D. Wakimoto H. Gorham J. et al.De novo mutations in congenital heart disease with neurodevelopmental and other congenital anomalies.Science. 2015; 350: 1262-1266Crossref PubMed Scopus (436) Google Scholar, 12Tanaka A.J. Cho M.T. Millan F. Juusola J. Retterer K. Joshi C. Niyazov D. Garnica A. Gratz E. Deardorff M. et al.Mutations in SPATA5 are associated with microcephaly, intellectual disability, seizures, and hearing loss.Am. J. Hum. Genet. 2015; 97: 457-464Abstract Full Text Full Text PDF PubMed Scopus (111) Google Scholar, 13Farwell Hagman K.D. Shinde D.N. Mroske C. Smith E. Radtke K. Shahmirzadi L. El-Khechen D. Powis Z. Chao E.C. Alcaraz W.A. et al.Candidate-gene criteria for clinical reporting: diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases.Genet. Med. 2017; 19: 224-235Abstract Full Text Full Text PDF PubMed Scopus (39) Google Scholar Mean coverage of target regions and average reads depth for individual samples are provided in Table S1. Subjects 12 (simplex case subject) and 13 to 15 (affected members of family 30153) (Figure S1) belonged to a cohort of 235 unrelated individuals with clinical features fitting Noonan syndrome (MIM: 163950) or overlapping with this disorder, followed at three participating genetic centers (Rome, Bologna, and Magdeburg),14Roberts A.E. Allanson J.E. Tartaglia M. Gelb B.D. Noonan syndrome.Lancet. 2013; 381: 333-342Abstract Full Text Full Text PDF PubMed Scopus (494) Google Scholar, 15Tartaglia M. Gelb B.D. Disorders of dysregulated signal traffic through the RAS-MAPK pathway: phenotypic spectrum and molecular mechanisms.Ann. N Y Acad. Sci. 2010; 1214: 99-121Crossref PubMed Scopus (153) Google Scholar who did not harbor mutations in previously identified genes implicated in RASopathies. Based on the hypothesis that mutations in CDC42 might be linked causally to Noonan syndrome (or a clinically related RASopathy), the entire CDC42 coding sequence was analyzed by targeted resequencing, using genomic DNA from blood, skin fibroblasts, hair bulbs, and/or epithelial cells from the oral mucosa. Target enrichment was performed using the Nextera Rapid Capture kit (Illumina), and sequencing was carried out on a NextSeq550 (Illumina) with a 2 × 150 bp paired-end read protocol. Alignment and variant calling were performed with the BWA Enrichment BaseSpace App (Illumina), and VCF output files were annotated using Variant Studio v.2.2 (Illumina). Finally, Sanger sequencing was used to screen the CDC42 coding exons in subjects 6 and 7, who showed clinical features suggestive for the condition associated with CDC42 group I mutations (see below). Overall, nine different missense mutations distributed across the entire CDC42 coding sequence were identified (Table 1). Two amino acid substitutions affected the N-terminal α helix (residues Ile21 and Tyr23), three involved adjacent residues within the switch II motif (Tyr64, Arg66, and Arg68), two mapped to the fourth β strand (Cys81 and Ser83), and the remaining two were located close to the C terminus (Ala159 and Glu171) (Figure 1A). Four variants were recurrent, and all occurred as a de novo event in at least one family. Of note, the c.511G>A substitution (p.Glu171Lys) was shared by the four affected subjects with clinical features resembling Noonan syndrome, occurring de novo in subject 12, and co-segregating with the phenotype in family 30153 (subjects 13 to 15), consistent with dominant inheritance. None of these variants had been reported in ExAC/gnomAD, and all were predicted to be pathogenic and met the American College of Medical Genetics (ACMG) criteria to be considered disease causing (Table S2).19Richards S. Aziz N. Bale S. Bick D. Das S. Gastier-Foster J. Grody W.W. Hegde M. Lyon E. Spector E. et al.ACMG Laboratory Quality Assurance CommitteeStandards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.Genet. Med. 2015; 17: 405-424Abstract Full Text Full Text PDF PubMed Scopus (14622) Google Scholar One variant, c.191A>G (p.Tyr64Cys), had previously been reported in two subjects with syndromic thrombocytopenia (MIM: 616737).20Takenouchi T. Kosaki R. Niizuma T. Hata K. Kosaki K. Macrothrombocytopenia and developmental delay with a de novo CDC42 mutation: Yet another locus for thrombocytopenia and developmental delay.Am. J. Med. Genet. A. 2015; 167A: 2822-2825Crossref PubMed Scopus (61) Google Scholar, 21Takenouchi T. Okamoto N. Ida S. Uehara T. Kosaki K. Further evidence of a mutation in CDC42 as a cause of a recognizable syndromic form of thrombocytopenia.Am. J. Med. Genet. A. 2016; 170A: 852-855Crossref PubMed Scopus (44) Google ScholarTable 1List of the Germline CDC42 Missense Mutations Identified in This StudyExonNucleotide ChangeAmino Acid ChangeDomainMutation GroupSubjectsOriginMetaSVMaScores > 0 (MetaSVM), > 15 (CADDphred) or > 0.5 (REVEL) predict that the sequence change has a significant impact on protein structure and function.CADD phredaScores > 0 (MetaSVM), > 15 (CADDphred) or > 0.5 (REVEL) predict that the sequence change has a significant impact on protein structure and function.REVELaScores > 0 (MetaSVM), > 15 (CADDphred) or > 0.5 (REVEL) predict that the sequence change has a significant impact on protein structure and function.ACMG1c.62T>Cp.Ile21Thrα1III1de novo0.372927.10.901pathogenic1c.68A>Gp.Tyr23Cysα1III2de novo0.775227.10.937pathogenic3c.191A>Gp.Tyr64Cysswitch III3de novo0.797623.40.834pathogenic3c.196A>Gp.Arg66Glyswitch III4, 5de novo0.532626.90.836pathogenic3c.203G>Ap.Arg68Glnswitch III6, 7de novo0.658626.30.827pathogenic3c.242G>Tp.Cys81Pheβ4II8de novo0.628030.00.840pathogenic3c.247T>Cp.Ser83Proβ4II9, 10de novo0.828327.80.853pathogenic4c.476C>Tp.Ala159ValNBPII11de novo1.017934.00.916pathogenic5c.511G>AbThis change affects transcript variant 1 (GenBank: NM_001791.3) and isoform 1 (GenBank: NP_001782.1), while it does not affect transcript variant 2 (GenBank: NM_044472.2) and isoform 2 (GenBank: NP_426359.1). The two isoforms have the same amino acid length but are characterized by a different C terminus.p.Glu171LysCBRIII12, 13–151 de novo, 1 familial0.015824.70.768pathogenicNucleotide numbering reflects cDNA numbering with 1 corresponding to the A of the ATG translation initiation codon in the CDC42 reference sequence (GenBank: NM_001791.3). No variants were reported in the public databases ExAC and GnomAD. All variants were predicted to be “deleterious” by Combined Annotation Dependent Depletion (CADD) v.1.3, Database for Nonsynonymous SNPs’ Functional Predictions (dbNSFP) Support Vector Machine (SVM) v.3.0, and REVEL algorithms.16Kircher M. Witten D.M. Jain P. O’Roak B.J. Cooper G.M. Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants.Nat. Genet. 2014; 46: 310-315Crossref PubMed Scopus (3676) Google Scholar, 17Dong C. Wei P. Jian X. Gibbs R. Boerwinkle E. Wang K. Liu X. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies.Hum. Mol. Genet. 2015; 24: 2125-2137Crossref PubMed Scopus (635) Google Scholar, 18Ioannidis N.M. Rothstein J.H. Pejaver V. Middha S. McDonnell S.K. Baheti S. Musolf A. Li Q. Holzinger E. Karyadi D. et al.REVEL: an ensemble method for predicting the pathogenicity of rare missense variants.Am. J. Hum. Genet. 2016; 99: 877-885Abstract Full Text Full Text PDF PubMed Scopus (864) Google Scholar All changes satisfied the necessary criteria to be classified as pathogenic according to the American College of Medical Genetics guidelines.19Richards S. Aziz N. Bale S. Bick D. Das S. Gastier-Foster J. Grody W.W. Hegde M. Lyon E. Spector E. et al.ACMG Laboratory Quality Assurance CommitteeStandards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.Genet. Med. 2015; 17: 405-424Abstract Full Text Full Text PDF PubMed Scopus (14622) Google Scholar Abbreviations: NBP, nucleotide binding pocket; CBR, CRIB motif binding region.a Scores > 0 (MetaSVM), > 15 (CADDphred) or > 0.5 (REVEL) predict that the sequence change has a significant impact on protein structure and function.b This change affects transcript variant 1 (GenBank: NM_001791.3) and isoform 1 (GenBank: NP_001782.1), while it does not affect transcript variant 2 (GenBank: NM_044472.2) and isoform 2 (GenBank: NP_426359.1). The two isoforms have the same amino acid length but are characterized by a different C terminus. Open table in a new tab Nucleotide numbering reflects cDNA numbering with 1 corresponding to the A of the ATG translation initiation codon in the CDC42 reference sequence (GenBank: NM_001791.3). No variants were reported in the public databases ExAC and GnomAD. All variants were predicted to be “deleterious” by Combined Annotation Dependent Depletion (CADD) v.1.3, Database for Nonsynonymous SNPs’ Functional Predictions (dbNSFP) Support Vector Machine (SVM) v.3.0, and REVEL algorithms.16Kircher M. Witten D.M. Jain P. O’Roak B.J. Cooper G.M. Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants.Nat. Genet. 2014; 46: 310-315Crossref PubMed Scopus (3676) Google Scholar, 17Dong C. Wei P. Jian X. Gibbs R. Boerwinkle E. Wang K. Liu X. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies.Hum. Mol. Genet. 2015; 24: 2125-2137Crossref PubMed Scopus (635) Google Scholar, 18Ioannidis N.M. Rothstein J.H. Pejaver V. Middha S. McDonnell S.K. Baheti S. Musolf A. Li Q. Holzinger E. Karyadi D. et al.REVEL: an ensemble method for predicting the pathogenicity of rare missense variants.Am. J. Hum. Genet. 2016; 99: 877-885Abstract Full Text Full Text PDF PubMed Scopus (864) Google Scholar All changes satisfied the necessary criteria to be classified as pathogenic according to the American College of Medical Genetics guidelines.19Richards S. Aziz N. Bale S. Bick D. Das S. Gastier-Foster J. Grody W.W. Hegde M. Lyon E. Spector E. et al.ACMG Laboratory Quality Assurance CommitteeStandards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.Genet. Med. 2015; 17: 405-424Abstract Full Text Full Text PDF PubMed Scopus (14622) Google Scholar Abbreviations: NBP, nucleotide binding pocket; CBR, CRIB motif binding region. CDC42 encodes a small GTPase of the RHO family modulating multiple signaling pathways controlling cell polarity and migration, endocytosis, and cell cycle progression, by cycling between an active (GTP-bound) and an inactive (GDP-bound) state.22Etienne-Manneville S. Cdc42--the centre of polarity.J. Cell Sci. 2004; 117: 1291-1300Crossref PubMed Scopus (564) Google Scholar, 23Heasman S.J. Ridley A.J. Mammalian Rho GTPases: new insights into their functions from in vivo studies.Nat. Rev. Mol. Cell Biol. 2008; 9: 690-701Crossref PubMed Scopus (1433) Google Scholar It is characterized by five major highly conserved motifs, G1 to G5, which mediate GTP binding and hydrolysis (G4 and G5), phosphate binding (G1 and G3), and effector binding (G2) (Figure 1A).24Colicelli J. Human RAS superfamily proteins and related GTPases.Sci. STKE. 2004; 2004: RE13Crossref PubMed Scopus (576) Google Scholar, 25Dvorsky R. Ahmadian M.R. Always look on the bright site of Rho: structural implications for a conserved intermolecular interface.EMBO Rep. 2004; 5: 1130-1136Crossref PubMed Scopus (124) Google Scholar Based on clinical heterogeneity (see below) and location of affected residues, we predicted that the mutations would have a variable functional impact. The structural consequences of the identified disease-causing mutations on CDC42 structure and function were assessed by Pymol molecular viewer (see Web Resources), using available PDB structures. This allowed us to inspect CDC42 interactions with ARHGAP1 (p50GAP/CDC42GAP; PDB: 1grn), ARHGAP18 (MacGAP; PDB: 5c2j), and ITSN1 (PDB: 1ki1) and WAS (WASP; PDB: 1cee), as representatives for CDC42’s GTPase activating proteins (GAPs), guanine nucleotide exchange factors (GEFs), and effectors, respectively, and to classify them structurally and functionally into three different groups. A first group of mutations affected the switch II region (p.Tyr64Cys, p.Arg66Gly, and p.Arg68Gln; group I), which mediates CDC42 binding to effectors and regulators (Figures 1B–1D).25Dvorsky R. Ahmadian M.R. Always look on the bright site of Rho: structural implications for a conserved intermolecular interface.EMBO Rep. 2004; 5: 1130-1136Crossref PubMed Scopus (124) Google Scholar Tyr64 and Arg66 are located on the surface of CDC42 and directly participate in interactions with regulatory proteins and effectors. These changes were predicted to affect these interactions and, as a consequence, the catalytic activity of the GTPase and/or its capability to transduce signaling. Similarly, Arg68 is embedded in the protein interior and stabilizes the conformation of the switch II region via intramolecular interactions with multiple residues (Ala59, Gln61, and Glu100). The Arg-to-Gln change was assumed to strongly destabilize the switch II loop and the interaction with signaling partners. Group II included substitutions involving residues located within (Ala159) or close to (Cys81 and Ser83) the nucleotide-binding pocket (Figures 1B, 1C, and 1E). Ala159 faces the guanine base and replacement by valine was predicted to promote fast GDP/GTP cycling, favoring a GEF-independent active, GTP-bound state of the protein. A similar hyperactive behavior has been reported in RAS proteins.26Janakiraman M. Vakiani E. Zeng Z. Pratilas C.A. Taylor B.S. Chitale D. Halilovic E. Wilson M. Huberman K. Ricarte Filho J.C. et al.Genomic and biological characterization of exon 4 KRAS mutations in human cancer.Cancer Res. 2010; 70: 5901-5911Crossref PubMed Scopus (221) Google Scholar, 27Gremer L. Merbitz-Zahradnik T. Dvorsky R. Cirstea I.C. Kratz C.P. Zenker M. Wittinghofer A. Ahmadian M.R. Germline KRAS mutations cause aberrant biochemical and physical properties leading to developmental disorders.Hum. Mutat. 2011; 32: 33-43Crossref PubMed Scopus (100) Google Scholar, 28Chang M.T. Asthana S. Gao S.P. Lee B.H. Chapman J.S. Kandoth C. Gao J. Socci N.D. Solit D.B. Olshen A.B. et al.Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity.Nat. Biotechnol. 2016; 34: 155-163Crossref PubMed Scopus (482) Google Scholar Similarly, Ser83 binds to Gln116, which interacts with the guanine base, predicting indirect perturbation of nucleotide binding properties of CDC42. Cys81 is an invariant residue among RHO GTPases located in proximity of the phosphate-binding loop, and its substitution to phenylalanine was expected to cause favorable hydrophobic interactions with this loop, dislocation of Gly12, and consequently defective GTP hydrolysis. Finally, group III (CRIB mutations) included variants at Ile21, Tyr23, and Glu171, which are exposed residues predicted to affect interactions with effectors containing a CDC42/RAC-interacting binding (CRIB) motif (Figures 1B, 1C, and 1F).29Pirone D.M. Carter D.E. Burbelo P.D. Evolutionary expansion of CRIB-containing Cdc42 effector proteins.Trends Genet. 2001; 17: 370-373Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar Glu171 binds to Lys235 of WAS (WASP, hereafter) and plays a major role in the electrostatic binding network stabilizing the WASP-CDC42 association,30Abdul-Manan N. Aghazadeh B. Liu G.A. Majumdar A. Ouerfelli O. Siminovitch K.A. Rosen M.K. Structure of Cdc42 in complex with the GTPase-binding domain of the ‘Wiskott-Aldrich syndrome’ protein.Nature. 1999; 399: 379-383Crossref PubMed Scopus (283) Google Scholar, 31Hemsath L. Dvorsky R. Fiegen D. Carlier M.F. Ahmadian M.R. An electrostatic steering mechanism of Cdc42 recognition by Wiskott-Aldrich syndrome proteins.Mol. Cell. 2005; 20: 313-324Abstract Full Text Full Text PDF PubMed Scopus (105) Google Scholar which was predicted to be disrupted by the Glu-to-Lys change. Tyr23 lies at the CDC42 surface implicated in PAK1 binding and stabilizes proper orientation of helix α5 mediating WASP binding.32Morreale A. Venkatesan M. Mott H.R. Owen D. Nietlispach D. Lowe P.N. Laue E.D. Structure of Cdc42 bound to the GTPase binding domain of PAK.Nat. Struct. Biol. 2000; 7: 384-388Crossref PubMed Scopus (159) Google Scholar, 33Gizachew D. Guo W. Chohan K.K. Sutcliffe M.J. Oswald R.E. Structure of the complex of Cdc42Hs with a peptide derived from P-21 activated kinase.Biochemistry. 2000; 39: 3963-3971Crossref PubMed Scopus (38) Google Scholar Ile21 is located near the switch I region contributing to the hydrophobic pocket of helix α1 participating in WASP binding.30Abdul-Manan N. Aghazadeh B. Liu G.A. Majumdar A. Ouerfelli O. Siminovitch K.A. Rosen M.K. Structure of Cdc42 in complex with the GTPase-binding domain of the ‘Wiskott-Aldrich syndrome’ protein.Nature. 1999; 399: 379-383Crossref PubMed Scopus (283) Google Scholar The Ile-to-Thr substitution was predicted to perturb CDC42 binding to signaling partners. We assessed the effects of the disease-causing mutations on CDC42 GTPase activity, GDP/GTP exchange, and binding to effectors in vitro, using recombinant proteins. The p.Tyr23Cys, p.Tyr64Cys, p.Arg66Gly, p.Arg68Gln, p.Ser83Pro, p.Ala159Val, and p.Glu171Lys amino acid substitutions were selected as representative of the three mutation groups that were predicted to perturb differentially CDC42 function. pGEX vectors were used for bacterial overexpression of GST-tagged wild-type and mutant CDC42 proteins, and the GTPase-binding domains (GBD) of WASP (residues 154–321), PAK1 (residues 57–141), FMNL2 (residues 1–379), and IQGAP1 (residues 863–1657) in E. coli BL21 (DE3). Proteins were purified after cleavage of the GST tag (Superdex 75 or 200, GE Healthcare).31Hemsath L. Dvorsky R. Fiegen D. Carlier M.F. Ahmadian M.R. An electrostatic steering mechanism of Cdc42 recognition by Wiskott-Aldrich syndrome proteins.Mol. Cell. 2005; 20: 313-324Abstract Full Text Full Text PDF PubMed Scopus (105) Google Scholar Nucleotide-free and fluorescent nucleotide-bound CDC42 variants were prepared using alkaline phosphatase (Roche) and phosphodiesterase (Sigma Aldrich) at 4°C.31Hemsath L. Dvorsky R. Fiegen D. Carlier M.F. Ahmadian M.R. An electrostatic steering mechanism of Cdc42 recognition by Wiskott-Aldrich syndrome proteins.Mol. Cell. 2005; 20: 313-324Abstract Full Text Full Text PDF PubMed Scopus (105) Google Scholar, 34Hemsath L. Ahmadian M.R. Fluorescence approaches for monitoring interactions of Rho GTPases with nucleotides, regulators, and effectors.Methods. 2005; 37: 173-182Crossref PubMed Scopus (42) Google Scholar First, GTPase activity was measured basally and following ARHGAP1 (p50GAP, hereafter) stimulation by fluorescent experiments using tetramethylrhodamine (tamra-) GTP as substrate with a Hi-Tech Scientific (SF-61) stopped-flow instrument (Figures 2A and S2). The assays documented a variably increased basal GTP hydrolysis for CDC42Tyr64Cys, CDC42Arg68Gln, and CDC42Ala159Val. Each of these mutants, however, exhibited robust GAP insensitivity, showing respectively a 4,700-fold (CDC42Tyr64Cys), 392-fold (CDC42Arg68Gln), and 366-fold (CDC42Ala159Val) reduction in GAP-stimulated GTPase activity, compared to wild-type CDC42. A mildly decreased GAP-stimulated GTP hydrolysis was documented for CDC42Tyr23Cys and CDC42Arg66Gly. By using the same experimental approach, release of methylanthraniloyl (mant-) GDP was used to assess the basal and GEF-catalyzed nucleotide exchange reactions (Figures 2B and S3). The assays documented an increase of GDP release for CDC42Ala159Val and a slightly increased nucleotide exchange for CDC42Arg68Gln and CDC42Ser83Pro. By contrast, p.Tyr64Cys resulted in an almost completely abolished response to GEF. No substantial difference in GDP/GTP exchange behavior was observed for the other mutants. Then, fluorescence experiments were performed by using increasing amounts of the CDC42 interacting domains of WASP, PAK1, FMNL2, and IQGAP1 titrated to CDC42 proteins bound to mant-GppNHp, a non-hydrolyzable GTP analog, to assess the binding of mutants to four major CDC42 effectors and evaluate their ability to transduce signaling (Figures 2C and S4). Experiments were performed using a Fluoromax 4 fluorimeter in polarization mode, and the dissociation constants (Kd) were calculated by fitting the concentration-dependent binding curve using a qua
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