Synapse formation is induced by transsynaptic interaction of neuronal cell-adhesion molecules termed synaptic organizers. Type IIa receptor protein tyrosine phosphatases (IIa RPTPs) function as presynaptic organizers. The cytoplasmic domain of IIa RPTPs consists of two phosphatase domains, and the membrane-distal one (D2) is essential for synapse formation. Liprin-α, which is an active zone protein critical for synapse formation, interacts with D2 via its C-terminal domain composed of three tandem sterile alpha motifs (tSAM). Structural mechanisms of this critical interaction for synapse formation remain elusive. Here, we report the crystal structure of the complex between mouse PTPδ D2 and Liprin-α3 tSAM at 1.91 Å resolution. PTPδ D2 interacts with the N-terminal helix and the first and second SAMs  of Liprin-α3. Structure-based mutational analyses in vitro and in cellulo demonstrate that the interactions with Liprin-α SAM1 and SAM2 are essential for the binding and synaptogenic activity. Synaptic organizers are cell-adhesion molecules capable of inducing synaptic differentiation through transsynaptic interactions. Here the authors present the crystal structure of the intracellular interaction between the synaptic organizer PTPδ and Liprin-α to reveal the structural mechanism of intracellular molecular interactions for IIa-RPTP-mediated synapse formation. Type IIa receptor protein tyrosine phosphatases (IIa RPTPs) function as presynaptic organizers. Dysfunctions of IIa RPTPs and their postsynaptic partners are associated with neurodevelopmental disorders, such as autism spectrum disorders (ASD), intellectual disability, or schizophrenia4. The vertebrate IIa RPTP family consists of three members, PTPδ, PTPσ, and LAR, which share the same domain architecture with a large N-terminal extracellular domain, a single transmembrane segment, and a cytoplasmic domain  domains and four or eight fibronectin type III (FN) domains5. The extracellular domain mediates a heterophilic, transsynaptic interaction with various postsynaptic organizers such as Netrin-G ligand 3 (NGL-3)7, Tropomyosin kinase C (TrkC)8, Interleukin-1 receptor accessory protein-like 1 (IL1RAPL1)9, Interleukin-1 receptor accessory protein (IL-1RAcP)10, Slit- and Trk-like family protein (Slitrk) 1–Slitrk612, synaptic adhesion-like molecule (SALM) 313, and SALM514. All of these postsynaptic organizers except NGL-3 interact with the Ig domains of IIa RPTPs20. Their selective interactions are controlled by two mini-exon-derived peptides (meA and meB peptides), which are located within the Ig2 domain and in the junction between the Ig2 and Ig3 domains, respectively.Synaptic organizers are a class of neuronal adhesion or secretory proteins capable of inducing synaptic differentiation, and play important roles in formation and maturation of neuronal synapsesain Fig. 3,4. The 4. The membrane-proximal phosphatase domain (D1) is catalytically active, whereas the membrane-distal one (D2) is inactive. The D2 domain of IIa RPTPs directly interacts with several synaptic proteins including Liprin-α22, Caskin23, and Trio24. In heterologous synaptogenic co-culture assays using short hairpin RNA (shRNA)-mediated PTPσ knockdown neurons and HEK293T cells expressing TrkC or Slitrk1, re-expression of phosphatase-dead PTPσ mutants could partially recover the synaptogenic activity in PTPσ-knockdown neurons but that of a D2-lacking mutant could not25. The intracellular interactions of PTPσ with synaptic proteins via the D2 domain likely play more critical roles in synaptogenesis than the phosphatase activity catalyzed by the D1 domain.The cytoplasmic domain of IIa RPTPs comprises two tandem phosphatase domains21. Liprin-α belongs to the Liprin family, which is highly conserved from invertebrates to mammals26. The vertebrate Liprin family is classified into three groups: Liprin-α, Liprin-β, and KazrinE27. Mammals possess four Liprin-α isoforms (Liprin-α1–Liprin-α4), two Liprin-β isoforms (Liprin-β1 and -β2), and KazrinE. On the other hand, invertebrates possess a single set of Liprin-α, -β, and -γ28. Liprin-γ is the closest homolog of KazrinE. Among them, Liprin-α and -γ can reportedly bind to the D2 domain of IIa RPTPs. The existence of only a single liprin-α gene in invertebrates makes it simpler to assess in vivo function of Liprin-α in the nervous system. A loss of function in syd-2 gene (Liprin-α homolog in Caenohabiditis elegans) alters the size and shape of presynaptic termini32. Deletion of the IIa RPTP homolog, ptp-3, resulted in mislocalization of SYD-2. In Drosophila, Dliprin-α, a homolog of Liprin-α, is required for normal synaptic morphology at neuromuscular junction and for photoreceptor target selection34.Liprin-α is an active zone protein and the first protein identified as an intracellular binding partner of IIa RPTPs36. Knockdown of Liprin-α2 by shRNA alters synaptic vesicle pool size and presynaptic ultrastructure. Liprin-α2 regulates the turnover of the active zone proteins, calcium/calmodulin-dependent serine kinase (CASK) and RIM1/2, to facilitate synaptic transmission37. Superresolution microscopy revealed substantial difference in the localization of Liprin-α2 and -α3 inside the presynapse38. Liprin-α3 is substantially colocalized with the active zone proteins, whereas Liprin-α2 is localized to more internal region of the nerve terminals. Liprin-α3-knockout mice generated by CRISPR/Cas9 gene editing show impaired exocytosis of synaptic vesicles, although they survive and develop mostly normally, possibly due to a complementary function of Liprin-α238. In fact, the depletion of Liprin-α3 causes the translocation of Liprin-α2 to the acive zone, though their functions may not be completely overlapped38.Although all four isoforms of Liprin-α are expressed in the brain with differential distribution and increase the complexity of their neuronal functions, Liprin-α2 and -α3 are predominantly and specifically expressed in the brain39, GIT140, RIM37, KIF1A41, and mDia43. The tSAM domain of Liprin-α interacts with the D2 domain of IIa RPTPs22 and CASK44. In addition, Liprin-α and -β form a heterodimer through the interaction between Liprin-α SAM1 and Liprin-β SAM345. A wide variety of binding partners for Liprin-α imply its broad synaptic functions.The Liprin family shares similar domain architecture comprising an N-terminal coiled-coil domain and three tandem sterile alpha motifs , SAM1, and SAM2 in the tSAM domain of Liprin-α3. The structure-based mutational analyses in vitro and in cellulo demonstrate that the interaction with the SAM1 and SAM2 domains of Liprin-α3 is essential for the binding and synaptogenic activity.The complex structure between the tSAM domain of Liprin-α2 and CASK revealed that the insertion loop between SAM1 and SAM2 in Liprin-α2 interacts with CASK45 and the phosphatase domains of IIa RPTPs46. Consequently, the combination of PTPδ D2 and Liprin-α3 tSAM yielded diffraction-quality crystals. The crystal structure of the PTPδ D2–Liprin-α3 tSAM complex was determined by the molecular replacement method using PTPσ D2 (PDB 2FH7 [10.2210/pdb2FH7/pdb])46 and Liprin-α2 tSAM 45 as the search models. The asymmetric unit contains one complex, and no obvious molecular contact suggestive of higher-order assembly was found in the crystal , which contains four FN domains with the 9-residue meA and meB peptide insertions (A9B+).To reveal the structural basis of the interaction between IIa RPTPs and Liprin-α, we sought to determine the crystal structure of the complex between the intracellular domain of IIa RPTPs and the tSAM domain of Liprin-α. The D1–D2 and D2 domains of mouse PTPδ and PTPσ and the tSAM domains of mouse Liprin-α1, -α2, -α3, and -α4 were purified and subjected to co-crystallization screening. Their expression constructs were designed, based on the structures of Liprin-α2 tSAM08 Table . The res47. The pseudoactive site of PTPδ D2 retains the catalytic cysteine residue (Cys1440). However, the tyrosine residue in the phosphorylated Tyr recognition loop and the aspartate residue in the WPD motif, which are critical for the phosphatase activity49, are replaced with Leu and Glu, respectively. These replacements synergistically reduce the phosphatase activity50. The interface between Liprin-α3 and PTPδ D2 is located on the opposite side of the pseudoactive site . SAM2 and SAM3 are connected by the short linker helix Fig. . The eleThe D2 domain of PTPδ interacts with αN, SAM1, and SAM2 of Liprin-α3 but not with SAM3 in the present crystal structure of the PTPδ D2–Liprin-α3 tSAM complex Fig. . At the To assess the contribution of these intermolecular interactions to the binding affinity between PTPδ D2 and Liprin-α3 tSAM, site-directed mutants of PTPδ D2 or Liprin-α3 tSAM were analyzed by surface plasmon resonance (SPR) spectroscopy Table .Table 2M21, despite their some sequence similarity . Superposition of the structures of mouse Liprin-α3 and Liprin-β1 highlights that Trp856 and Leu978 of Liprin-α3, which are critical for binding to PTPδ and conserved in the Liprin-α family, are replaced with Ser and Arg in Liprin-β1, respectively , and a complete shutdown of Liprin-α-mediated signaling likely requires a multiple gene knockout approach. In Liprin-α3-null mice, Liprin-α2 possibly compensates for the lack of Liprin-α3.Essential roles of Liprin-α in synapse formation have been demonstrated by knockout experiments of 10. The IL1RAPL1–PTPδ interaction requires two short peptide inserts (meA-peptide and meB-peptide) within the Ig-like domains of PTPδ, which are derived from mini-exons A and B of Ptprd gene encoding PTPδ protein18. We then generated a mutant mouse line that lacks meB-peptide-containing PTPδ splice variants capable of binding to IL1RAPL1 by inserting a stop codon into mini-exon B (exon 9) of Ptprd gene. The Ptprd allele with the mini-exon B mutation is referred to as PtprdmeB* in this study. When cocultured with wild-type cortical neurons, beads conjugated with the recombinant extracellular domain of IL1RAPL1 strongly induced the accumulation of presynaptic reporter proteins, synaptophysin-mCherry and EGFP-Rab3, in contacting axons  completely lacked the presynapse-inducing activity , while deletion of the D2 domain and C-terminal tail of PTPδ (ΔD2C) completely lacked the ability to rescue the defect in the presynaptic differentiation  restored presynaptic differentiation like wild type, in agreement with the fact that αN does not contribute to the binding to PTPδ D2 52 onto that of Liprin-α3 bound to PTPδ D2 using SAM1 as the reference, the position of the SAM2 domain is completely different between Caskin-1 and Liprin-α3  onto the present PTPδ D2–Liprin-α3 tSAM structure using Liprin-α tSAM as the reference, no steric hindrance occurs between CASK and PTPδ D2  and pmCherry-N1 (Clontech) vectors, respectively.For the structural and SPR analyses, the genes encoding mouse PTPδ D2 (residues 1213–1508) and mouse Liprin-α3 tSAM (residues 808–1114) were PCR amplified from cDNAs and cloned into the pET21a (Millipore) and pGEX-6P1 vectors , respectively. For pull-down assay, the genes encoding mouse CASK N-terminal kinase domain (residues 1–323) was cloned into the pET21a vector. PTPδ D2 (residues 1213–1508) and D1-D2 (residues 891–1508) were cloned into the pGEX-6P1 vector. For synaptogenic assay, the coding sequences of preprotrypsin signal peptide followed by FLAG tag from pFLAG-CMV-1 vector (Sigma), mouse PTPδ lacking signal peptide, porcine teschovirus-1 P2A peptideEscherichia coli Rosetta (DE3) cells (Millipore). The cells were disrupted by sonication. For the purification of PTPδ D2, the cell lysate containing PTPδ D2 fused with the C-terminal His6-tag (PTPδ D2-His6) was applied onto a Ni-NTA (Qiagen) column. After washing with 20 mM Tris-HCl buffer (pH 8.0) containing 300 mM NaCl and 50 mM imidazole, PTPδ D2-His6 was eluted with 20 mM Tris-HCl buffer (pH 8.0) containing 300 mM NaCl and 250 mM imidazole. For crystallography, PTPδ D2-His6 was further purified by size-exclusion chromatography using Superdex 200  column with 20 mM Tris-HCl buffer (pH 7.5) containing 150 mM NaCl. For the purification of Liprin-α3 tSAM, the cells expressing Liprin-α3 tSAM fused with the N-terminal glutathione-S-transferase (GST-Liprin-α3 tSAM) was disrupted by sonication. The cell lysate was applied onto a Glutathione Sepharose FF column . After washing by phosphate-buffered saline (PBS), GST-Liprin-α3 was eluted with 50 mM Tris-HCl buffer (pH 8.0) containing 200 mM NaCl and 15 mM reduced glutathione. The eluted sample was further purified by anion-exchange chromatography using a Resource Q column , which was pre-equilibrated with 20 mM Tris-HCl buffer (pH 7.5) containing 50 mM NaCl. GST-Liprin-α3 was eluted with a linear gradient of 50–500 mM NaCl. The GST tag was cleaved off by HRV3c protease and removed by a Glutathione Sepharose FF column. The sample was purified again by anion-exchange chromatography in the same manner as GST-Liprin-α3. Finally, the sample was purified by size-exclusion chromatography using a Superdex 200  column with 20 mM Tris-HCl buffer (pH 7.5) containing 150 mM NaCl.All proteins were expressed in 6-tag (His6-CASK) was purified by Ni-affinity chromatography in the same manner as PTPδ D2-His6. His6-CASK was further purified by anion-exchange chromatography using a HiTrap Q HP or Resource Q column .For pull-down assay, PTPδ D2 or D1-D2 fused with an N-terminal GST tag was purified using a Glutathione Sepharose FF column, followed by size-exclusion chromatography using a Superdex 200  column or anion-exchange chromatography using a Resource Q  column, respectively. The CASK N-terminal kinase domain fused with the N-terminal His6 (90 µM) and Liprin-α3 tSAM (70 µM) were mixed. Initial crystallization screening was performed using the sitting drop vapor diffusion method at 20 °C with a Mosquito liquid-handling robot (TTP Lab Tech). About 500 conditions were tested with crystallization reagent kits supplied by Hampton Research and Qiagen. After optimization of the crystallization condition, diffraction-quality crystals of the complex were obtained with the reservoir solution containing 15% PEG 3350 and 0.1 M Tris-HCl (pH 8.5). The crystals were soaked in the reservoir solution supplemented with 30% PEG 400 and then flash-frozen in liquid N2.For crystallization of the PTPδ D2–Liprin-α3 tSAM complex, PTPδ D2-His57 and the CCP4 program suite58. The structure of the PTPδ D2–Liprin-α3 tSAM complex was determined by molecular replacement with the program Molrep59 using PTPσ D2 (PDB 2FH7[10.2210/pdb2FH7/pdb])46 and Liprin-α2 tSAM (PDB 3TAD[10.2210/pdb3TAD/pdb])45 as the search models. The atomic model was manually improved using the program Coot60, and refined using the program Phenix61 with good stereochemistry . Data collection and refinement statistics are summarized in Table 62. Sequence alignment was performed using ClustalX software63. All structure figures were prepared using the program PyMOL .Diffraction data sets were collected at 100 K at BL41XU in SPring-8 and processed with HKL20006 was immobilized on a CM5 sensor chip by the amine-coupling method. The amount of the immobilized ligand for each experiment is shown in response units in Table –1, followed by a 600-s dissociation phase. The PTPδ D2-immobilized sensor chip was regenerated by 20 mM Hepes-NaOH buffer (pH 7.5) containing 1 M NaCl. All mutants examined by SPR analysis were confirmed to behave as wild type in size-exclusion chromatography  were calculated using Biacore T200 software. Data are shown as mean ± standard deviation from at least three independent experiments for each sample.SPR experiments were performed using Biacore T200  at 25 °C in 10 mM Hepes-NaOH buffer (pH 7.5) containing 150 mM NaCl, and 0.005% Tween-20. Wild-type or mutant PTPδ D2-His6-CASK were mixed with GST-PTPδ D2 at an equimolar ratio (20 µM) in PBS with 0.1% Triton X-100 (PBS-T), and then immobilized onto Glutathione Sepharose FF  beads. The beads were washed with PBS-T three times. The bound protein complexes were then eluted with 50 mM Tris-HCl buffer (pH 8.0) containing 200 mM NaCl and 15 mM reduced glutathione. The eluted sample was separated from beads by centrifuge and subjected to SDS-PAGE analysis with Coomassie brilliant blue staining. For Supplementary Fig. 6-CASK in PBS-T with or without 29 µM Liprin-α3 tSAM. The beads were washed with PBS-T twice. The bound protein complexes were then eluted with 2xSDS loading buffer and subjected to SDS-PAGE analysis with Coomassie brilliant blue staining.For Fig. 64. The sequences of guide RNA (gRNA-meB) and ssODN (meB*-ssODN) were 5′-CAUCCCUCAGAGCUGCGAGA-3′ and, 5′-CCTTTTCCTCATTTCATTGTGTTCTGCATCAAACCCCCCTACATCCCTCAGAGCTCTGAGAAGGTTGGTGTGTTTTTTACTTTTTACCCACCTTTACAAAACTACTACTT-3′, respectively. The genomic DNAs from the F0 mice were subjected to cleaved amplified polymorphic sequence analyses using primer set, 5′-ATGGTGACCTCCTTTGCTG-3′ and 5′-TCATGCATTGCATTTGGACG-3′, and restriction enzyme SacI for the detection of the ssODN-mediated knock-in of the stop codon into meB. The F0 mosaic mice were crossed with wild-type C57BL/6N mice to generate heterozygous (Ptprd+/meB*) F1 mice. The strain was maintained by crossing Ptprd+/meB* females with wild-type C57BL/6N mice. The F3 heterozygous male and female mice were mated to generate homozygous mutant mice for preparation of neuronal cultures. All experimental protocols for animal studies were approved by the Animal Experiment Committee of the University of Toyama (Authorization No. A2016med-140) and conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals of the University of Toyama.The electroporation of guide RNA, Cas9 protein, and ssODN into C57BL/6N mouse zygotes was performed as previously describedPtprdmeB*/meB*) mutant mice at embryonic day 18 as previously described9. The cultured neurons were transfected with expression vectors for wild-type or mutated forms of PTPδ linked to EGFP-Rab3 by P2A peptide at days in vitro (DIV) 8, and cocultured with Fc- or IL1RAPL1-Fc-coated magnetic beads at DIV9. The cocultures were fixed and mounted for confocal microscopy at DIV10.Cerebral cortical neurons were prepared from homozygous  in a blinded manner with regard to the expression vectors transfected. Fc- or IL1RAPL1-coated beads on the EGFP-Rab3-expressing axons were randomly imaged. Z series optical sections were projected by the brightest point method and the accumulation of EGFP-Rab3 around the beads were quantified using ImageJ softwareF value = 76.49; Fig. F value = 17.95; Supplementary Fig. F value = 35.98).Two independent experiments were included in the statistical analysis for Fig. Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


JMTV nucleic acids were detected in 3.9% of the tick pools, including those from several tick species from the genera Rhipicephalus and Haemaphysalis, and Hyalomma marginatum, the main vector of CCHFV in Turkey. Phylogenetic analysis supported two separate clades, independent of host or location, suggesting ubiquitous distribution in ticks. JMTV was not recovered from any human, animal or bird specimens tested. Near-complete viral genomes were sequenced from the prototype isolate and from three infected tick pools. Genome topology and functional organization were identical to the members of Jingmen group viruses. Phylogenetic reconstruction of individual viral genome segments and functional elements further supported the close relationship of the strains from Kosovo. We further identified probable recombination events in the JMTV genome, involving closely-related strains from Anatolia or China.We obtained a Jingmen tick virus (JMTV) isolate, following inoculation of a tick pool with detectable Crimean-Congo hemorrhagic fever virus (CCHFV) RNA. We subsequently screened 7223 ticks, representing 15 species in five genera, collected from various regions in Anatolia and eastern Thrace, Turkey. Moreover, we tested specimens from various patient cohorts ( Arachnida, subclass Acari) are hematophagous ectoparasites of vertebrates, acting as biological vectors responsible for the transmission of several viruses to humans and animals [Ticks , initially detected from ticks in the Jingmen region of Hubei province in China , is amoniviridae .The detection of a JMTV variant in a red colobus monkey in Uganda demonstrated primate infections in nature and highlighted the potential relevance of these viruses to animal and human health . The dishttps://hsgm.saglik.gov.tr/tr/zoonotikvektorel-kkka/zoonotikvektorel-kkka-istatistik). Furthermore, we have detected Tamdy orthonairovirus, chuviruses, flavi-like viruses, rhabdoviruses and novel phleboviruses in ticks from various regions of Turkey, mostly with unexplored human or animal health impact [Turkey is located in the Asia Minor and Eastern Thrace region of the Balkan Peninsula and maintains a natural transmission zone for vector-borne infections between Asia, Africa and Europe. Diverse ecological and climatic conditions observed in Anatolia and Thrace provides suitable habitats for several tick species . Many tih impact ,20,21. TAnimal sera were obtained at local veterinary clinics and animal shelters or during tick removal, with full compliance with the national regulations on the operation and procedure of animal experiments ethics committees  and approved study protocols by Ankara University local ethics committee (AULEC/201-96-346). The tick specimens included in the study comprised field-collected host-seeking or ambusher ticks and those removed from domesticated animals, performed with informed consent and cooperation of the owners or caretakers, for which local or regional ethics committee approval was not required. Stored human sera and cerebrospinal fluid specimens were included for testing with previous approval from local or institutional ethics committees . Collection and testing of avian specimens were undertaken with approval from the Republic of Turkey ministry of forestry and water affairs, general directorate of nature conservation and national parks (20.04.2016/86035) and Ankara University animal experiments local ethics committee (10.02.2016/2016-3-22).Bos taurus), sheep (Ovis aries), goats (Capra aegagrus hircus) and dogs (Canis familiaris), or collected by flagging, using a 75 × 100 cm cloth over low and high vegetation. Upon collection, the ticks were stored in vials, transferred in dry ice, and identified morphologically to the species level using suitable taxonomic keys [The tick specimens were collected at 59 locations in Istanbul , Edirne, Kırklareli and Tekirdağ (Thrace region), Mersin , Van (eastern Anatolia), Adıyaman, Diyarbakır and Şanlıurfa (southeastern Anatolia) provinces, between 2013–2018 . The spemic keys ,24,25,26The detection of JMTV was performed by polymerase chain reaction (PCR). We used two primer sets, targeting the NS3-like protein gene, located on the genome segment 3 . Having Specimens positive for JMTV nucleic acids were further screened for tick-borne phleboviruses, flaviviruses and nairoviruses using previously-described assays based on generic amplification. For phleboviruses, single-round amplification by the ppL1 and ppL2 primer sets, targeting the viral polymerase functional motifs located on the L-segment, were employed . A nesteSpecimens from wild birds were collected at wildlife rehabilitation centers of the Ministry of forestry and water affairs in Samsun and Hatay provinces during necropsy. The centers are located in the convergence zone of the known bird migration routes from the Balkans and Asia to Africa over Anatolia. Canine sera were collected at local veterinary clinics and animal shelters during medical interventions by local veterinarians in Mersin and Adana provinces. Sera from cattle were collected from infested animals during tick removal in Şanlıurfa province. We further tested previously collected human specimens for JMTV infections. The specimens comprised sera from individuals with laboratory diagnosis of Crimean-Congo hemorrhagic fever, cerebrospinal fluid (CSF) and/or sera from individuals with febrile disease or meningoencephalitic symptoms of unknown etiology with/without tick bite history. The specimens were stored at −80 °C and available as aliquots of the original sample, purified RNA or cDNA, processed using a High Pure Viral Nucleic Acid Kit  and a RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific). Nucleic acid purification and/or cDNA synthesis in unprocessed specimens were carried out as described for tick pools. All specimens were screened for JMTV using both sets of primers, as described above.2 atmosphere at 37 °C and monitored daily for cytopathic effects. Weekly blind passages were performed, and culture supernatants were tested for viral nucleic acids at each passage.Processed tick homogenates were inoculated onto semi-confluent monolayers of African green monkey kidney  cells. The cells were obtained from the cell culture collection of the Department of Virology, Faculty of Veterinary Medicine, Ankara University. Briefly, the specimens (400–500 μL) were filtered through 0.22 μm sterile membrane filters  and inoculated onto cells in T25 flasks , following dilution in equal volumes of Dulbecco’s modified Eagle’s medium (DMEM). Allowing cell adsorption for an hour, 5 mL of DMEM, supplemented with 5% fetal bovine serum, l-glutamine, 100 U/mL penicillin and 100 ug/mL streptomycin, was added. The cells were incubated in 5% COA 100 μL aliquot of cell culture supernatants or tick pools was initially treated with Ambion DNase I and RNase Cocktail  and unencapsidated nucleic acids were removed using the Agencourt AMPure XP purification system . RNA was purified using the QIAmp Viral RNA Mini Kit  and reverse transcribed into double-stranded cDNA using random hexamers SuperScript IV Reverse Transcriptase  and the NEBNext mRNA Second Strand Synthesis Module . The cDNA was cleaned up using the Agencourt AMPure XP reagent  and total yield and size distribution were optimized via the Agilent 2100 Bioanalyzer . Fragmentation, adaptor ligation and amplification were carried out using Nextera XT DNA Library Prep kit , using standard protocols provided by the manufacturer. The sequencing runs were performed in the paired-end mode, using the Illumina HiSeq 2000 .The raw data were de-multiplexed and extracted in fastq format. Adaptor removal and trimming for quality and length (phred score of 33 and 30 base pairs (bp) minimum length) were carried out using Trimmomatic (version 0.35) ,32. VelvObtained sequences were handled using Geneious . BLASTn, BLASTn optimized for highly similar sequences (MEGABLAST) and BLASTp algorithms were used for nucleotide and deduced amino acid similarity searches in the public databases . Nucleothttps://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) and MOTIF Search (http://www.genome.jp/ tools/motif/) in the PFAM database [http://www.cbs.dtu.dk/services/SignalP-5.0/) and PROSPER  [https://embnet.vital-it.ch/software/TMPRED_form.html) [http://www.cbs.dtu.dk/services/NetOGlyc/) was used for identifying potential N-linked glycosylation sites [Protein domain and motif searches were performed using the NCBI conserved domain search tool  ,42. Predrm.html) . NetNGlyon sites .Rhipicephalus bursa collected from sheep in Van province, was initially positive in generic nairovirus PCR during screening. Following cell culture inoculation, cytopathic effects, observed as cell elongation and vacuolization without prominent plaque formation, become visible, while no amplification could be attained in nairo-, flavi- or phlebo-virus assays. Finally, positive results and sequence confirmation were obtained using prototype JMTV primers, and cell culture supernatant of the second passage was used for genome sequencing.The initial isolation of the JMTV strain T36 was carried out by the inoculation of a processed tick specimen onto Vero E6 cells. The specimen, a female n = 3443, 47.7%), Istanbul , Tekirdağ , Mersin , Edirne , Diyarbakır , Adıyaman , Van  and Şanlıurfa  provinces in Turkey. Collections comprised adult ticks , larvae  and nymphs  , followed by Hyalomma scupense , Haemaphysalis parva  and others. The complete list of the tick cohort is provided in We collected and screened 7223 ticks, representing 5 genera and 15 species. The specimens originated from Kırklareli  . The mosR. bursa (7/25), Rhipicephalus turanicus (5/25), H. marginatum (4/25), Hae. parva (4/25), Rhipicephalus sanguineus sensu lato (3/25) and Haemaphysalis inermis (2/25) species, originating from Kırklareli (12/25), Mersin (5/25), Tekirdağ (4/25) and Van (4/25) provinces. Pools with detectable virus sequences comprised adult female and male ticks as well as nymphs (The screening was performed in 630 tick pools and JMTV nucleic acids were detected in 25 (3.9%). Positive pools comprised s nymphs . We did Amplicon sequencing in tick pools with detectable JMTV provided 260-bp amplicons of the viral genome segment 3. The sequences showed up to 19.3% and 7% intramural diversity on nucleotide and putative amino acid levels, respectively. In the maximum likelihood analysis, they formed two well-demarcated clusters, with a shared common ancestor . The fir3 − 3.4 × 107 genome copies. In total, 103 specimens from 87 individuals were screened, all with negative results for JMTV.We tested different patient cohorts for JMTV infections. One included 21 sera from individuals with febrile disease of unknown etiology (no tick bites) and 23 sera from individuals with a history of tick bites. Serum-CSF pairs from 16 patients with acute onset central nervous system infections without identifiable etiology were also evaluated. We further assessed sera from 27 CCHFV-infected individuals with viral loads of 9.8 × 10Anas platyrhynchos , Coturnix coturnix , Perdix perdix , Pernis apivorus , Clanga pomarina , Phoenicopterus roseus , Ardea herodias , Ciconia ciconia , Chroicocephalus ridibundus , Columba livia , Corvus cornix  and Pelecanus onocrotalus . The tissues comprised specimens from liver (n = 53), lung (n = 15), spleen (n = 7) and heart (n = 7). A total of 65 tissues from 53 birds were screened. Finally, canine sera from Mersin (n = 30) and Adana (n = 30) and bovine sera from Şanlıurfa province (n = 20) were assessed for JMTV. All non-tick specimens were negative.A number of tissues from avian species were screened for JMTV. The species included 6 with JMTV sequences comprising 1.3%–16.7% of the reads. The complete coding regions of the four genomic segments of the JMTV genome were obtained with incomplete non-coding ends, via NGS and Sanger sequencing (Direct NGS of the cell culture supernatant (T36) and PCR-positive tick pools  provided total read numbers of 1.56–2.35 × 10quencing . Each gequencing . The seqRhipicephalus-associated flavi-like virus, Amblyomma virus, Kindia tick virus and Yanggou tick virus sequences  is observed in the N-terminal. The mature VP1s contain 5–7 predicted transmembrane regions in various strains, with a potential signal peptidase cleavage site (GS(F)S-QE). The mature glycoprotein also carries two potential N-glycosylation sites (NTTF and NCTV) at varying positions (on residues 162 and 215 in JMTVs with 744 amino acid VP1).Viral genome segment 3 encodes for the second putative nonstructural protein (NSP2), that comprise 808 amino acids, with sequence and functional similarities to the flavivirus NS2b–NS3 complex, with essential roles in viral polyprotein processing and genome replication . NS3 is Amblyomma virus, as well as JMTV strains from Kosovo and Turkey, an adenylate kinase or related kinase motif (COG0563), involved in nucleotide transport and metabolism, was detected, encompassing residues 30–119 of the VP3. In addition, a predicted membrane protein motif  was detected in VP3 90–238th positions in MGTV, Rhipicephalus-associated flavi-like virus and JMTV strains from Kosovo and Turkey. These motifs are lacking in the remaining JMTV genomes.The fourth viral genome segment is distinct in the way that it is bicistronic and comprises two ORFs with overlapping reading frames . The VP2Rhipicephalus and Haemaphysalis were infected, as well as Hyalomma marginatum, the main vector for CCHFV transmission in Turkey. Pairwise comparison of the partial segment 3 sequences showed significant diversity and the sequences grouped into two separate clades in phylogeny reconstruction, regardless of the host tick species or location  viruses shown to produce animal infections . Moreovenfection . Similarnfection . Despite viruses ,13. ThroIxodes ricinus ticks but lacking in over 900 individuals with suspected tick-borne encephalitis, tested for viral nucleic acids as well as immunoglobulins [Among Jingmenviruses, JMTV and ALSV have been recently documented to cause human infections ,16. Initlobulins . JMTV inJMTV infections in vertebrates other than humans is likely, as supported by virus detection in primates, rodents and host-removed ticks ,8,13,15.Aves) are involved in the transmission of several viruses, owing to the biodiversity, adaptive immune response enabling asymptomatic infections and opportunities for virus acquisition from various sources [Ixodes, Hyalomma, and Haemaphysalis ticks [Birds (class  sources . They ma sources . Consideis ticks ,50. To iIn conclusion, we isolated for the first time, a JMTV strain in Anatolia, and carried out screening of ticks, canine, bovine and avian specimens, and people with clinical symptoms. Despite lack of detection in human and animal specimens, we identified JMTV in several tick species, including vectors of CCHFV. Moreover, we sequenced viruses originating from ticks and cell cultures. Structural and functional aspects of the genomes were similar to global JMTV isolates, with the highest identities to viruses from the Balkan Peninsula. We further provided evidence for genetic exchange among local JMTVs. JMTV must be considered in diagnosis of febrile diseases of unknown etiology.


Drosophila photoreceptor neurons and in human neuroblastoma cells in culture as a direct substrate of UBE3A. Here, we further characterize this regulation, by identifying the UBE3A-dependent ubiquitination sites and ubiquitin chains formed on DDI1. Additionally, we found one deubiquitinating enzyme that is capable of reversing the action of UBE3A on DDI1. The complete characterization of the ubiquitination pathway of an UBE3A substrate is important due to the role of this E3 ligase in rare neurological disorders as Angelman syndrome.The ubiquitin E3 ligase UBE3A has been widely reported to interact with the proteasome, but it is still unclear how this enzyme regulates by ubiquitination the different proteasomal subunits. The proteasome receptor DDI1 has been identified both in  The lack of functional UBE3A E3 ubiquitin ligase in the brain is responsible for a rare neurodevelopmental disorder called Angelman syndrome (AS). With an incidence of 1:15.000 births , the disN-terminal amide group (M1) by which additional ubiquitin moieties can be attached, forming a wide range of poly-ubiquitin chains  is transferred to an E2 ubiquitin-conjugating enzyme, and subsequently to an E3 ubiquitin ligase, which is the ultimate responsible for attaching the ubiquitin moiety to the substrate . UBE3A in chains . Linkagein vitro studies have demonstrated that UBE3A ubiquitin ligase mainly forms K48 chains and hence, likely targets proteins to the proteasome  enzymes that are responsible for removing the ubiquitin moiety from substrates. The human genome codes for almost a hundred DUBs that based on sequence similarity and likely mechanisms of action are divided into six groups: UCH, USP, OTU, JAMM, MJD, and the most recently discovered MINDY . It coulIn the present study, we have characterized the UBE3A-dependent ubiquitination of the proteasomal shuttling protein DDI1. From six ubiquitination sites detected on DDI1, we have discovered that the presence of K133 is necessary for DDI1 to be ubiquitinated by UBE3A. Additionally, investigation of the ubiquitin linkages has shown that UBE3A forms K11- and K48-linked ubiquitin chains on DDI1. We also screened a siRNA library to search for the DUB involved in the deubiquitination of UBE3A substrates, and found that USP9X has the capacity to regulate DDI1 ubiquitination levels. Overall, our data shed light into the molecular mechanisms underlying Angelman syndrome, and reveal USP9X as a potential therapeutic target that may help restoring the non-pathological ubiquitination pattern on Angelman syndrome patients, and hence, ameliorate their symptoms.C-terminally GFP-tagged DDI1 (DDI1-GFP) vector was generated using the commercial pEGFP-N1 vector (Clontech), while N-terminally GFP-tagged DDI1 (GFP-DDI1) was cloned into a PM-cherry-C1 vector kindly provided by Dr. Daniel Abankwa (see section “Cloning Procedures”). The plasmids used to express the N-terminally FLAG-tagged versions of the wild type  and catalytically inactive  human UBE3A (an UBE3A  were a gan UBE3A . A previan UBE3A  was usedan UBE3A .Gene for human DDI1 protein (Uniprot Q8WTU0) was synthesized by GenScript and further amplified using 5′-TATAGGTACCATGCTGATCACCGTG-3′ forward primer and 5′-TATAACCGGTATGCTCTTTTCGTCC-3′ reverse primer and inserted between the Acc65I and AgeI sites of the pEGFPN1 vector. For the generation of GFP-DDI1, human DDI1 sequence was amplified using 5′-CGCGTGTACAGTATGAATATAGCGATA-3′ forward primer and 5′-CGCAAGCTTTCAATGCTCTTTTCG-3′ reverse primer. Amplified DDI1 was then inserted between BsrGI and HindIII sites of the PM-cherry-C1 where mCherry had been previously replaced by GFP. All PCR reactions were carried out with Phusion High-Fidelity DNA polymerase (Thermo Scientific). PCR product gel extractions and plasmid purifications were performed with the E.Z.N.A. Gel Extraction Kit and E.Z.N.A. plasmid mini and midi kits (Omega Bio-tek), respectively. Correct sequence for all plasmids was confirmed by sequencing either by the Eurofins GATC Biotech Company  or the SGIKER Unit of Sequencing and Genotyping at the University of the Basque Country .6 cells). After 24 h from seeding, cells were co-transfected with 12,5 μg of DDI1-GFP and 12,5 μg of UBE3AWT or UBE3ALD for 72 h using Lipofectamine 3000 transfection reagent (Invitrogen) and according to manufacturer’s instructions. For the DUB silencing experiment, HEK293T cells were seeded the previous day in six-well plates (6 × 105 cells). Each well was then transfected with 10 nM siRNA targeting specific DUBs . For that purpose Lipofectamine RNAiMAX transfection reagent (Thermo Fischer) was used according to manufacturer’s instructions. After 24 h incubation, 1,5 μg of DDI1-GFP and 1,5 μg of FLAG-Ub were co-transfected for another 48 h using again Lipofectamine 3000 transfection reagent (Invitrogen). For all experiments, cells were washed twice in PBS after the transfection periods and stored at -20°C until required.Human Embryonic Kidney cells (HEK293T) were cultured under standard conditions  using Dulbecco’s modified Eagle medium/nutrient mixture F-12 (DMEM/F-12) with GlutaMAX (Thermo Scientific) and supplemented with 10% fetal bovine serum (Thermo Scientific), 100 U/ml of penicillin (Invitrogen) and 100 mg of streptomycin (Invitrogen). For ubiquitination sites and chain-types experiments by mass spectrometry, HEK293T cells were seeded in 100 mm plates  and centrifuged at 14 000 g for 10 min. Supernatants were mixed with 25 μl/well (6-well plate) and 50 μL/well (100 mm plates) of GFPTrap-A agarose beads suspension (Chromotek GmbH), which had been previously washed twice with a Dilution buffer . After incubation for 3 h at room temperature with gentle rolling, samples were centrifuged at 2700 g for 2 min to separate the beads from the unbound material. GFP beads were then subjected to three washing steps; once with the dilution buffer, thrice with washing buffer  and once with 1% SDS in PBS. GFP-tagged proteins bound to the beads were eluted by incubating at 95°C for 10 min with 25 μl elution buffer .Transfected HEK293T cells were lysed with 500 μl of lysis buffer in six-well plates and with 2 mL in 100 mm dishes  were used. Proteins were then transferred to PVDF membranes using the iBlot system (Invitrogen). Membranes were blocked using 5% powdered milk in PBS-Tween (PBS-T). Following primary and secondary antibody incubation, membranes were developed with an ECL kit (Biorad Clarity). To create dual-color westerns independent color channels were assigned to two independent westerns that were developed in the same membrane. The amount of material loaded for western blot analysis was between 10–30% of neat inputs and 30–50% of neat elution samples. The following primary antibodies were used at 1/1000 concentration: mouse monoclonal anti-GFP antibody ; mouse monoclonal anti-FLAG M2-HRP conjugated antibody ; mouse monoclonal anti-UBE3A (clone E6AP-300) antibody , rabbit monoclonal anti-UCHL-5 , rabbit polyclonal anti-USP9X , anti-USP7 (kindly provided by Dr. Emilio Lecona), rabbit polyclonal anti-USP42 . The following secondary antibodies were used at 1/4000 concentration: goat anti-mouse-HRP-labeled antibody  and goat anti-rabbit-HRP labeled antibody .Prior to MS analysis, the efficiency of GFP pull-downs was evaluated by silver staining. Briefly, the 10% of each neat elution was resolved by SDS–PAGE , and after fixing the proteins within the gel with 40% methanol/10% acetic acid, gel bands were visualized using the SilverQuest kit following manufacturer’s instructions (Invitrogen).Ninety percent of the neat elution from each GFP pull-down was resolved by SDS–PAGE  and visualized with Colloidal Blue (Invitrogen) following manufacturer’s instructions. Aiming to isolate mono- and poly-ubiquitinated DDI1, each gel lane was excised into two slices above the clear band of approximately 75 KDa that corresponds to non-modified DDI1 . Subsequ-1. The mass spectrometer was operated in positive ion mode. Full MS scans were acquired from m/z 375 to 1800 with a resolution of 120,000 at m/z 200. The 10 most intense ions were fragmented by higher energy C-trap dissociation with normalized collision energy of 28 and MS/MS spectra were recorded with a resolution of 15,000 at m/z 200. The maximum ion injection time were 100 ms and 120 ms, whereas AGC target values were 3 × 106 and 5 × 105 for survey and MS/MS scans, respectively. In order to avoid repeat sequencing of peptides, dynamic exclusion was applied for 12 s. Singly charged ions or ions with unassigned charge state were also excluded from MS/MS. Data were acquired using Xcalibur software (Thermo Scientific).Mass spectrometric analyses were performed on an EASY-nLC 1200 liquid chromatography system interfaced with a Q Exactive HF-X mass spectrometer (Thermo Scientific) via a nanospray flex ion source. Dried peptides were dissolved in 0.1% formic acid and loaded onto an Acclaim PepMap100 pre-column  connected to an Acclaim PepMap RSLC C18  analytical column. Peptides were eluted from the column using the following gradient: 18 min from 2.4 to 24%, 2 min from 24 to 32% and 12 min at 80% of acetonitrile in 0.1% formic acid at a flow rate of 300 nl minHomo sapiens entries  where the sequences of FLAG_UBIQUITIN and DDI1_GFP proteins were manually added. To assess ubiquitin chains types present on DDI1, only raw files corresponding to poly-ubiquitinated DDI1 were processed. By contrast, to infer the DDI1 ubiquitination sites, raw files corresponding to both mono- and poly-ubiquitinated DDI1 were processed together. Carbamidomethylation (C) was set as fixed modification whereas Met oxidation, protein N-terminal acetylation and Lys GlyGly (not C-term) were defined as variable modifications. Mass tolerance was set to 8 and 20 ppm at the MS and MS/MS level, respectively. Enzyme specificity was set to trypsin, allowing for a maximum of three missed cleavages. Match between runs option was enabled with 1.5 min match time window and 20 min alignment window to match identification across samples. The minimum peptide length was set to seven amino acids. The false discovery rate for peptides and proteins was set to 1%. For the analysis of ubiquitination sites, a minimum localization probability of 0.75 was used. Normalized spectral protein label-free quantification (LFQ) intensities were calculated using the MaxLFQ algorithm.Acquired raw data files were processed with the MaxQuant  softwareLD) does not increase the ubiquitination of GFP-tagged DDI1. By contrast, wild type UBE3A (UBE3AWT) enhances the ubiquitination of DDI1 while the level of non-modified DDI1 remains unchanged . Then, DDI1 was isolated from both experimental conditions by GFP pull-down procedure, and subsequently resolved by SDS–PAGE. Coomassie staining revealed a band just below 75 kDa corresponding to GFP-tagged DDI1, as earlier identified by western blotting  domain; K133, K161 and K213 within the helical domain (HDD); K291, that resides in the aspartyl protease-like RVP domain; and K382, on the C-terminal end of the protein  enzymes. Having demonstrated that UBE3A ubiquitinates DDI1, we next aimed to discover the DUB capable of deubiquitinating it. We screened an RNAi library in order to identify the DUB whose silencing would enhance DDI1 ubiquitination. For that purpose, we used HEK293T cells expressing DDI1-GFP and FLAG-Ub, in which 41 different DUBs were silenced individually. More precisely, we silenced 36 members of the USP family, as well as 3 and 2 members, respectively, of the UCH and OTU families . To measWe then silenced the above mentioned four DUBs separately, and used a scramble siRNA as a control for this validation experiment that was performed in triplicate . The silDUB inhibition has been considered as a potential therapeutic strategy for those diseases on which the function of a given E3 ligase is lost, and certain essential substrates are ubiquitinated at levels below their physiological requirement. A compound termed WP1130 has been previously used to experimentally inhibit USP9X , even ifOverall, our data indicate that UBE3A and USP9X are the E3 ligase and DUB, respectively, involved in modulating the ubiquitination of DDI1.Saccharomyces cerevisiae  domain that interacts with the 26S proteasome  that binds to ubiquitin or poly-ubiquitin chains , including protein ubiquitination and phosphorylation, play a critical role in essentially all cellular processes by regulating the activity, localization or interactions of proteins. For example, it has been shown that the interaction between the proteasome and the proteasomal shuttle Rad23 is regulated by a phosphorylation occurring on the UBL domain of Rad23 , 23. In C-terminal of the protein. It is likely that ubiquitination of different residues on specific domains may affect differentially DDI1 function. Hence, future work will be necessary to elucidate the biological significance of each modification.Furthermore, our mass spectrometry-based approach revealed five novel ubiquitination sites in human DDI1: K77 on the UBL domain, K133, K161 and K213 in the HDD domain and K382 in the WT and UBE3ALD, we found that peptides bearing ubiquitinated K77, K133 and K161 appeared more abundant upon overexpression of UBE3AWT. Altogether, these results pointed to the N-terminal region of DDI1, including the ubiquitin-like domain and the double helical domain (HDD), as a ubiquitination hotspot region, where UBE3A mostly acts.We are interested in elucidating the molecular mechanisms underlying Angelman syndrome, a rare neurological disease caused by the lack of functional E3 ubiquitin ligase UBE3A in the brain. For that reason, among the six DDI1 ubiquitination sites detected in the present study, our interest focused on the ones mediated by UBE3A, as it is likely that UBE3A-dependent ubiquitination events are altered in Angelman syndrome patients. Comparing the intensity of the diGly-modified peptides corresponding to DDI1 in samples overexpressing UBE3AOut of the three putative UBE3A-dependent DDI1 ubiquitination sites detected, K133- and K161-containing peptides reached statistical significance. However, to further corroborate previous results, DDI1 K77, K133 and K161 were individually mutated to arginines. UBE3A-dependent ubiquitination of DDI1 was only significantly reduced when residue K133 was mutated, indicating that undoubtedly UBE3A is responsible for modifying this residue. It has been postulated that the HDD domain, which contains the K133 residue, may play a role in substrate recognition . TherefoWT overexpression, a detailed MS-based analysis of the DDI1 ubiquitinated fraction revealed K48 and K11 as the chain types most prominently induced by overexpression of this E3 ligase, suggesting that the increase in ubiquitin signal most likely corresponds to the formation of those chain types.The fate of an ubiquitinated protein does not only depend on the specific residue that is modified, but also on the type of ubiquitin linkage that is formed in such residue . A largein vivo is likely to provide more light in this issue.K48-linked ubiquitin chains have been widely described to direct proteins to degradation via the proteasome . Indeed,Most PTMs, including ubiquitination, are reversible modifications modulated by the co-ordinated action of two opposing enzymes: one adding a given chemical group to the protein, the other one removing it. In particular, protein ubiquitination is modulated by E3/DUB pairs. The regulation of the enzymes modulating protein PTMs is crucial for maintaining the appropriate balance of protein modification required for cellular homeostasis. In fact, as already mentioned, deregulation of these enzymes is implicated in a number of diseases, including cancer and rare neurological diseases . TherefoSo far, there are few studies showing that E3/DUB pairs act in a highly co-ordinated manner to regulate the ubiquitination and, hence, the activity of common substrates . It has NE, JAR, JMA, and UM designed the experiments. NE, JB, and KA performed the experiments. NE, NO, JR, BL, KA, and UM analyzed the experiments. NE, NO, and UM wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The discovery of vulnerable regions on norovirus particles is instrumental in the development of effective inhibitors, particularly for GI noroviruses that are genetically diverse. Analysis of these GI.1-specific Nanobodies has shown that similar to GII norovirus particles, the GI particles have vulnerable regions. The only known cofactor region, the HBGA binding pocket, represents the main target for inhibition. With a combination treatment, i.e., the addition of Nano-7 or Nano-94 with 2′FL, the effect of inhibition was increased. Therefore, combination drug treatments might offer a better approach to combat norovirus infections, especially since the GI genotypes are highly diverse and are continually changing the capsid landscape, and few conserved epitopes have so far been identified. Human norovirus infections are a major disease burden. In this study, we analyzed three new norovirus-specific Nanobodies that interacted with the prototype human norovirus . We showed that the Nanobodies bound on the side (Nano-7 and Nano-62) and top (Nano-94) of the capsid-protruding (P) domain using X-ray crystallography. Nano-7 and Nano-62 bound at a similar region on the P domain, but the orientations of these two Nanobodies clashed with the shell (S) domain and neighboring P domains on intact particles. This finding suggested that the P domains on the particles should shift in order for Nano-7 and Nano-62 to bind to intact particles. Interestingly, both Nano-7 and Nano-94 were capable of blocking norovirus virus-like particles (VLPs) from binding to histo-blood group antigens (HBGAs), which are important cofactors for norovirus infection. Previously, we showed that the GI.1 HBGA pocket could be blocked with the soluble human milk oligosaccharide 2-fucosyllactose (2′FL). In the current study, we showed that a combined treatment of Nano-7 or Nano-94 with 2′FL enhanced the blocking potential with an additive (Nano-7) or synergistic (Nano-94) effect. We also found that GII Nanobodies with 2′FL also enhanced inhibition. The Nanobody inhibition likely occurred by different mechanisms, including particle aggregation or particle disassembly, whereas 2′FL blocked the HBGA binding site. Overall, these new data showed that the positive effect of the addition of 2′FL was not limited to a single mode of action of Nanobodies or to a single norovirus genogroup.IMPORTANCE The discovery of vulnerable regions on norovirus particles is instrumental in the development of effective inhibitors, particularly for GI noroviruses that are genetically diverse. Analysis of these GI.1-specific Nanobodies has shown that similar to GII norovirus particles, the GI particles have vulnerable regions. The only known cofactor region, the HBGA binding pocket, represents the main target for inhibition. With a combination treatment, i.e., the addition of Nano-7 or Nano-94 with 2′FL, the effect of inhibition was increased. Therefore, combination drug treatments might offer a better approach to combat norovirus infections, especially since the GI genotypes are highly diverse and are continually changing the capsid landscape, and few conserved epitopes have so far been identified. Caliciviridae family. The genome contains three open reading frames (ORFs), where ORF1 encodes nonstructural proteins, ORF2 encodes the major capsid protein (VP1), and ORF3 encodes the minor capsid protein (VP2). Based on the capsid gene sequences, noroviruses can be divided into at least seven genogroups (GI to GVII), with GI, GII, and GIV causing infections in humans. Each human genogroup is further subdivided into numerous genotypes  35 to 45 nm in diameter , 4. The 5–A recent study showed that human monoclonal antibodies (MAbs) targeting the GI.1 HBGA pocket inhibited norovirus VLPs from binding to HBGAs by steric interference with the HBGA pocket . In our 14–in vitro  in complex with the GI.1 P domain. We showed that Nano-7 and Nano-62 bound on the side of the P domain, whereas Nano-94 bound on the top. Our data suggest that Nano-7 and Nano-62 might clash with the S domain and neighboring P domains, which would mean that the P domains on particles would need to shift to accommodate Nanobody binding. Interestingly, Nano-7 and Nano-94 also blocked VLPs from binding to HBGAs. More importantly, we discovered that a combination of either Nano-7 or Nano-94 with 2′FL improved HBGA binding inhibition.490) signal. Nevertheless, the three Nanobodies bound at a similar cutoff dilution . The three GI Nanobodies bound to the P domain in a dose-dependent manner and with a comparable cutoff dilution . Likewisdilution . These rdK (dissociation constant) of 4.58 × 10−9 M and Nano-94 − dK was 4.34 × 10−8 M. Nano-7 showed a subnanomolar dK of 1.63 × 10−10 M. The binding reaction of Nano-7 to the P domain was exothermic and driven by a very large enthalpy change, while unfavorable entropy input was less significant. The exothermic binding of Nano-62 was characterized by a large enthalpy change coupled with favorable entropy of the binding reaction (n = ∼1). Overall, the thermodynamic properties of these GI Nanobodies resembled those of previously characterized GII Nanobodies.The thermodynamic properties of Nanobody binding to the GI.1 P domain were analyzed using isothermal titration calorimetry (ITC) . Two Nanreaction . On the In order to determine the precise binding sites, the structure of Nanobodies in complex with the GI.1 P domain was determined using X-ray crystallography. Data statics of the complexes are shown in The crystal structure of GI.1 P domain–Nano-7 complex was solved to 1.58-Å resolution. Nano-7 bound on the side of the P domain in a grove between two P domain monomers . Nano-7 The structure of GI.1 P domain–Nano-62 complex was solved to 2.09-Å resolution. Similar to Nano-7, we found that Nano-62 bound on the side of the P domain and in the grove between two P domain monomers . HoweverThe structure of GI.1 P domain–Nano-94 complex was solved to 2.31-Å resolution. Nano-94 bound on the top of the P domain and interacted with one P domain monomer . Direct In order to better understand why the GI.1 Nanobodies were genotype specific, we aligned capsid sequences of other GI genotypes . Overall50s) of 0.4 μg/ml and 9.2 μg/ml, respectively. These results were similar to those with GII Nanobodies, where not all Nanobodies were capable of blocking, despite binding at similar regions on the P domain (Our previous study showed that GII Nanobodies could block attachment to porcine gastric mucin (PGM) . ConsequP domain . It is tP domain .In order to evaluate if the GI Nanobodies might alter the stability of intact VLPs, we measured the diameters of Nanobody-treated VLPs using dynamic light scattering (DLS). The untreated VLPs exhibited a single peak, indicating a homogenous sample with VLP diameter of 42 nm . IncubatTo directly observe the effects, the Nanobody-treated VLPs were examined using EM . After t50 of 50 mM (P ≤ 0.05), as determined by paired t test and two-way analysis of variance (ANOVA).Our earlier study showed that 2′FL inhibited GI.1 VLPs from binding to PGM, with an ICof 50 mM . Therefoof 50 mM . The comof 50 mM  to C. Thof 50 mM  was usedof 50 mM  and E. AFor Nano-7, the observed inhibition of the combinations ranging from 100 to 1.6 μg/ml Nano-7 combined with 10 to 50 mM 2′FL closely matched the expected value for addition of the two single effects  to J. Th50 of 2′FL for GII.10 VLPs was 5.5 mM. Serially diluted Nano-85 was mixed with 1.0, 2.5, 5.0, and 10 mM 2′FL. The combination of Nano-85 and 1.0 mM 2′FL did not increase the inhibition effect compared to that with Nano-85 alone, suggesting that this concentration of 2′FL was too low. The combination of Nano-85 and 2.5, 5, and 10 mM 2′FL inhibited the attachment of VLPs to PGM to a greater extent than with Nano-85 or 2′FL alone, indicating a positive cooperative effect. For most combinations, the observed effects matched the calculated expected additivity. According to the Bliss independence criterion, the effects were determined to be additive. Overall, these results showed that the positive effect of a combination of Nanobody and 2′FL was not genogroup specific.To analyze whether the positive effects of a Nanobody and 2′FL combination were genogroup dependent, we repeated the combination inhibition assay with GII VLPs treated with GII-specific Nano-85  and 2′FLIn this study, we analyzed three new GI.1-specific Nanobodies that bound on the side and top of the P domain. We showed that Nano-7 and Nano-62 bound in such a way that the opposite end of the CDRs clashed with the S domain and neighboring P domains when modeled on the VLP structure  and 6. IOnly two human norovirus VLP structures have been determined at a resolution that can clearly distinguish the P and S domains, i.e., GI.1 (an X-ray structure) and GII.10 (a cryo-EM structure) , 35. TheThe notion that GI and GII particles conceal vulnerable epitopes at occluded regions raises several new lines of questions. For example, is the P domain movement an advantage or disadvantage for the virus? And, what is the function of the P domain movement? We have shown that GII VLPs treated with citrate increased in particle diameter, which might make the virus noninfectious , 38. We In our previous study, we identified several GII.10-specific Nanobodies that bound to occluded epitopes, but these were still able to efficiently inhibit VLP attachment to PGM. Similarly, the GI Nanobodies Nano-7 and Nano-62 also bound to an occluded region  to 6. NaA comparison of the binding of Nano-62 to GI.1 and Nano-26 to GII.10 showed that the binding sites were similar, yet the inhibitory properties were rather different. Nano-62 did not influence the particle structure or inhibit HBGA binding; in contrast, Nano-26 was shown to induce particle disassembly upon binding to GII.10 VLPs, therefore effectively inhibiting HBGA binding . These rG). Since only minor structural rearrangements in the P domain occurred upon Nanobody binding, the structures of the respective complexes could be fitted very well to the X-ray structure of the GI.1 VLP  was produced as previously described   for 18 h at 22°C. Cells were harvested by centrifugation and disrupted by sonication on ice. The His-tagged fusion-P domain protein was purified from a Ni column (Qiagen) and digested with HRV-3C protease (Novagen) overnight at 4°C. The cleaved P domain was separated on the Ni column and dialyzed in gel filtration buffer  overnight at 4°C. The P domain was further purified by size-exclusion chromatography, concentrated to 4 mg/ml in GFB, and then stored at 4°C. For the production of norovirus VLPs, VP1 of GI.1 , GI.2 , GI.2 , GI.3 , GI.4 , and GI.11  was expressed in insect cells (1IHM).The GI.1 P domain  in the dark for 30 min at room temperature. Finally, the reaction was stopped with 6% (vol/vol) HCl, and absorption at 490 nm (OD490) was measured. A cutoff limit was set at OD490 of >0.15, which was ∼3 times the value of the PBS negative control  were coated with 100 μl/well (5 μg/ml) of GI.1 P domain or VLPs for 1 h at 37°C. Plates were washed three times with phosphate-buffered saline (pH 7.4) containing 0.1% Tween 20 (PBS-T) and subsequently blocked with 5% skimmed milk in PBS for 1 h at room temperature. Nano-62 or Nano-94 was serially diluted (1:1) with PBS, starting at 100 μg/ml, applied to the washed ELISA plates, and incubated for 1 h at 37°C. Nanobodies were detected with horseradish peroxidase-conjugated monoclonal antibody against polyhistidine (Sigma) at a dilution of 1:4,000 in PBS. Plates were washed and then developed with  control .AK, and the binding parameters, N and ΔH . Binding sites were assumed to be identical.Isothermal titration calorimetry (ITC) experiments were performed using an ITC-200 . Samples were dialyzed into PBS and filtered prior to the titration experiments. Titrations were performed at 35°C (Nano-7), 30°C (Nano-62), or 25°C (Nano-94) by injecting consecutive (0.5 μl for Nano-7 and 2 μl for both Nano-62 and Nano-94) aliquots of Nanobody (150 μM) into GI.1 P domain (15 μM) with 150-s intervals. The binding data were corrected for the heat of dilution and fit to a one-site binding model to calculate the equilibrium binding constant, The GI.1 P domain was mixed separately at a 1:1.4 molar ratio with the Nano-7, Nano-62, and Nano-94, and the complexes were incubated for 2 h at 25°C. Each complex was purified by size-exclusion chromatography using a Superdex-200 column and concentrated to 4.6 mg/ml. The complex crystals were grown using the hanging-drop vapor diffusion method. For GI.1 Nano-62 and GI.1 Nano-94, the mother solution contained 0.1 M sodium citrate (pH 5.5) and 20% (wt/vol) polyethylene glycol 3000 (PEG-3000) for 3 to 7 days at 18°C. For GI.1 Nano-7, crystals were grown in mother solution containing 0.17 M ammonium acetate, 0.085 M sodium citrate (pH 5.6), 15% (vol/vol) glycerol, and 25.5% (wt/vol) PEG-4000. Prior to flash-freezing in liquid nitrogen, single crystals were transferred to a cryoprotectant containing the mother liquor with or without 30% ethylene glycol.XDS (2ZL5) and a previously determined Nanobody (PDB ID 4KRN) as search models in Phaser (Coot (Phenix (Coot and MolProbity (https://pymol.org).X-ray diffraction data were collected at the European Synchrotron Radiation Facility, France, at beamlines ID23-1, ID29, and ID30A-3 and processed with XDS . The GI.n Phaser . The comer  with a Zetasizer Nano S system . The VLPs and Nanobodies (10 μl/10 μl) were incubated for 10 min at room temperature, diluted in 1 ml of distilled water, and then measured. Measurements were performed at 25°C in three runs with 15 measurement cycles.The norovirus VLP morphology (treated and untreated) was analyzed using negative-stain electron microscopy (EM), as previously described . Nanobodo-phenylenediamine dihydrochloride (OPD) and H2O2 in the dark for 30 min at room temperature. Finally, the reaction was stopped with 3 N HCl, and the absorbance at 490 nm (OD490) was measured. Nano-62 (GI negative control) and 2′FL (GI positive control) were used as controls in each experiment. The OD490 value of the untreated VLPs was set as the reference value corresponding to 100% binding. The percentage of inhibition was calculated as [1 − (treated VLP mean OD490/mean reference OD490)] × 100. The half-maximal inhibitory concentration (IC50) was determined using the Prism software (version 6.0) (The binding of GI.1 VLPs to porcine gastric mucin (PGM) type III (containing HBGAs) was previously determined . For theion 6.0) . All expIn a similar assay, blocking of GII.10 attachment to PGM by a combination of Nano-85 and 2′FL was examined. In this assay, incubation times and temperatures differed slightly due to the different VLPs used. Coating was performed for 4 h at room temperature, blocking was done at 4°C overnight, and the treated VLPs with Nano-85–2′FL were incubated for 2 h at room temperature. The GII.10 VLPs were detected using polyclonal anti-GII.10 rabbit antibodies (1 h at room temperature) and polyclonal anti-rabbit-HRP conjugate (1 h at room temperature) .To evaluate the interaction of Nano-7 and Nano-94 with 2′FL, Bliss independence was employed for data analysis of the HBGA-blocking assays , 53. Thit test for all single data points and two-way ANOVA.A comparison of the calculated expected additive effect to the observed results demonstrates how the drugs interact with each other. If zero interaction applies, the effects of the two drugs are additive, and as a consequence, the measured values of drug combination are close to the calculated theoretical additivity values. If the observed combination values are 20% above the expected additivity values, synergistic effects are implied, and if the observed values are 20% below the expected additivity, antagonism is implied. To determine if the difference between the expected additivity and our observed inhibition was statistically significant, we performed a paired two-tailed 6H6Y for the GI.1 P domain–Nano-7 complex, 6H6Z for the GI.1 P domain–Nano-62 complex, and 6H71 for the GI.1 P domain–Nano-94 complex.Atomic coordinates and structure factors of the complexes were deposited in the Protein Data Bank with the accession numbers


We develop a machine learning tool useful for predicting the instantaneous dynamical state of sub-monomer features within long linear polymer chains, as well as extracting the dominant macromolecular motions associated with sub-monomer behaviors of interest. We employ the tool to better understand and predict sub-monomer A2 domain unfolding dynamics occurring amidst the dominant large-scale macromolecular motions of the biopolymer von Willebrand Factor (vWF) immersed in flow. Results of coarse-grained Molecular Dynamics (MD) simulations of non-grafted vWF multimers subject to a shearing flow were used as input variables to a Random Forest Algorithm (RFA). Twenty unique features characterizing macromolecular conformation information of vWF multimers were used for training the RFA. The corresponding responses classify instantaneous A2 domain state as either folded or unfolded, and were directly taken from coarse-grained MD simulations. Three separate RFAs were trained using feature/response data of varying resolution, which provided deep insights into the highly correlated macromolecular dynamics occurring in concert with A2 domain unfolding events. The algorithm is used to analyze results of simulation, but has been developed for use with experimental data as well. These changes occur on multiple length scales. First, vWF unravels from a compact globule to an unraveled configuration on a macromolecular length scale, after which a second conformational change may take place on a sub-monomer length scale whereby the A2 domain of vWF is able to unfold if hydrodynamic force is sufficient9.von Willebrand Factor (vWF) is a large multimeric protein found in blood plasma. vWF plays an indispensable role in the blood clotting process by initiation of clot formation that stops bleeding due to vessel hemorrhagepN10, where larger unfolding forces were observed for faster pulling rates. Thus, under the action of hydrodynamic forces in shearing flows, it is expected that A2 domains unfold when subject to forces in the range reported from single-molecule pulling experiments. The partial or complete unfolding of the A2 domain is required for molecular scission by the enzyme ADAMTS1312, because the vWF cleavage site is deeply buried in the folded A2 domain structure and must be revealed by force-induced A2 domain unfolding in order for vWF proteolysis to occur14. A2 domain cleavage is crucial for preventing excessive thrombus formation. Large hemostatically active vWF multimers must be cleaved to functional lengths upon secretion into the vasculature in order to avoid adverse blood clotting17.This study focuses on the A2 domain of the vWF monomer. Single-molecule pulling experiments have demonstrated that the A2 domain unfolds due to internal tensile forces in the range of 7–15 18. Macromolecular unravelling reveals binding sites in the A1 domain for the platelet receptor GpIbα, which enables vWF to act as a bridge molecule in the binding of platelets to damaged blood vessels7. It has been reported that autoinhibition of vWF-platelet binding exists, and is mediated by a force-sensitive interaction of the A1 and A2 domains19. The dissociation of the A1-A2 complex is caused by a stretching force that was found to be coupled with A2 domain unfolding, such that A1-A2 dissociation occurred just before exposure of the cleavage site within the A2 domain. The exact biochemical basis for A1-A2 interaction was recently quantified more precisely20. Some of the current authors have advanced simulation data that invoked A2 domain mediation of A3-collagen binding as a mechanism for observing shear-induced binding trends that are in agreement with experiment21. While A2 domain mediation of A3-collagen binding has not been confirmed or refuted by experiment, data that have been advanced clarifying A2 mediation of A1-platelet binding were obtained from a number of different experimental methods. It is clear, then, that A2 domain distortion and eventual unfolding are behaviors that are critical to healthy vWF functionality.Besides vWF proteolysis, it has been reported that the A2 also plays an important role in the platelet binding process24, and the characteristics of internal tensile force within sheared multimers has also been studied extensively26. However, the large-scale behaviors and essential macromolecular dynamics of vWF multimers occurring in concert with A2 domain unfolding events is not fully understood.Hydrodynamic force induced A2 domain unfolding is an important aspect of vWF functionality. Naturally, the ability to predict A2 domain dynamics would open the door to many possible scientific and medical advancements. However, A2 domain unfolding is made possible after macromolecular unravelling from a globular to a more unraveled conformation occurs, which subsequently exposes A2 domains to hydrodynamic loading. So, before any sort of predictions about the state of constituent A2 domains can be made, the dominant behaviors of the macromolecule occurring in tandem with A2 domain unfolding events must first be characterized. The mechanism responsible for the initiation of macromolecular unraveling in the bulk has been well characterized by a recent protrusion nucleation theory27. One technique extracts dominant conformational motions by means of a correlation analysis using contact matrices, which may be effective in examining the concerted dynamics of the macromolecule and individual A2 domains.Characterization of conformational changes on multiple length scales presents numerous hurdles related to the nature of vWF dynamics, as well as their measurement techniques. vWF is a flexible polymer that is capable of undergoing extreme conformational changes on multiple length scales in relatively short periods of time. Traditional methods of extracting the dominant motions from an ensemble of molecular conformations, such as correlation analyses by way of principle component analysis, Cartesian covariance matrices, distance-covariance matrices, or quasi-harmonic analyses, illuminate the “vibrational” motions of the polymer. These methods are often useful for cases where the protein architecture is very structured and the collection of molecular conformations represent samples from short periods of time so that the variance is minimal29. A recent RFA application to polymer physics identified that the weakest dihedral angle of a bulk polymer is the most influential molecular feature for determining polymer chain radius of gyration30. Another study applied the RFA to account for molecular flexibility of proteins in order to achieve more accurate predictions of protein-protein associations using Monte-Carlo based simulation methods31.The Random Forest Algorithm (RFA) is a purely data-driven machine-learning tool frequently used to classify and predict system behavior in a wide variety of disiplinesIn this study, we utilize the RFA to develop a tool capable of predicting the instantaneous A2 domain state based on macromolecular conformational feature information. In doing so, we simultaneously characterize the essential macromolecular dynamics occurring in concert with A2 domain unfolding events by exploiting the nature of the RFA. Further, we identify the most important macromolecular conformational features for the prediction of A2 domain state. The methodological foundations set forth in this work will be extended in a forthcoming study, which will utilize the technique developed here to analyze experimentally obtained data.10. Each bead represents the collection of domains on either side of the A2, and adjacent monomers are connected by stiff harmonic springs that represent disulfide bonds. In this work, we simulated vWF multimers comprised of N = 100 beads, which represent proteins 50 monomers in length. Note that this size multimer is in the physiological range of sizes observed for functional vWF in blood, for which the upper limit has been reported to be around 40–200 monomers1. 22 non-interacting chains were considered in order to obtain sufficient statistical sampling. Further details and parameters for the molecular model and BD simulations can be found in our previous works32 and in the Supplemental Materials.We performed coarse-grained molecular dynamics (MD) simulations using an experimentally parameterized coarse-grain model of vWF in a simple one-dimensional bulk shearing flow, where the flow is in the x-direction and shearing occurs in the z-direction. Data obtained from coarse grained MD simulations were used as input to the RFA. The physical model  considers a single vWF monomer as a system of two beads connected by a Finitely Extensible Nonlinear Elastic (FENE) spring. The FENE spring represents the A2 domain of the vWF monomer, and has a spring constant and maximum extensible length that were obtained by fitting experimental force-extension data33. The RFA is an aggregation of a large number of decision trees, where each tree is constructed from a bootstrapped sample over the original data. A final decision made by the RFA, or prediction, is based on a majority-wins system among the ensemble of decision trees, where each tree casts one vote. This process introduces a randomness that reduces issues related to overfitting data, and results in increased prediction performance on unseen datasets. As opposed to many other methods, the RFA is capable of providing both an accurate prediction rule and an assessment for the relative importance of predictors34. The latter makes this method more appealing for problems related to bioinformatics applications36.Machine learning encompasses a wide variety of algorithms capable of recognizing structures and patterns in a given dataset. An accurate algorithm for a learning task depends on the biases within the dataset, as well as the type of features to be used as input variables . One major bias is the availability of the true response label, which is the RFA output corresponding to the prescribed input features. This type of bias describes what is called supervised machine learning. The Random Forest Algorithm (RFA) is a tree-based method of supervised learningC is the number of unique labels and fi is the frequency of label i at a node. This criterion also enables the importance of each feature to be ranked based on decreased node impurity. We implemented the RFA from the Scikit-learn module37.An essential part of decision tree construction is the splitting criteria that determines features to be used in a hierarchal order. In the current study, the Gini impurity criteria is used and is given by,In this study, we trained the RFA with a set of input variables obtained from data generated by coarse-grained MD simulations of vWF in shear flows. These input variables are macromolecular conformational features listed in Table pN10, although A2 domain unfolding events in experiment were observed over a range of force values between 7–15 pN. Accordingly, we define A2 domain unfolding to be any force excursion event of FENE spring tension past the experimentally-motivated value of 11 pN, which is in the middle of the range reported by experiment.The instantaneous A2 domain state was used as the response for training, which was either 1 or 0 for an unfolded or folded A2 domain, respectively. A single response was given for the chain-level resolution, whereas 5 and 10 binary responses were used for the 5- and 10-segment resolution levels, respectively. The physical model employed two beads and one FENE spring to describe the vWF monomer, so a partition within the 5-segment resolution comprised of 20 beads had 10 connecting FENE springs capable of unfolding. If any of the A2 domain represented FENE springs within a given partition were found to be unfolded, then the response assigned to this partition was 1. If instead all constituent A2 domains were folded at an instant, then the response assigned to that partition was 0. Results obtained from single-molecule pulling experiments found that the most likely unfolding force for the A2 domain is approximately 11 We were motivated to examine three partition resolutions for a few reasons. Firstly, we suspected that prediction performance of the RFA could be increased if feature/response information was more finely resolved along the multimer contour, which encouraged us to partition the chain into many segments. However, we desired to develop a procedure relevant to both simulation and experiment, which limited the number of possible partitions to avoid being devoid of experimental applicability. Various regions of a polymer exhibit different fundamental behavior that is dependent upon their location along the chain contour, which we knew a priori. Accordingly, we partitioned the multimer into numerous segments in an attempt to extract these position-dependent dynamics from within the data using the RFA. Further, we desired to identify possible correlations in macromolecular behavior among these segments, which necessitated the RFA to distinguish features and responses from the various segments.24. The protrusion is subsequently exposed to hydrodynamic force, which may lead to complete macromolecular unraveling if the protrusion continues to elongate due to a sufficiently strong local flow field. In the case of protrusion nucleation, the behavior at the multimer termini is what causes macromolecular unraveling, whereas the dynamical behavior near the multimer center is what follows in effect. Another location dependent behavior is exemplified by shielding effects induced by hydrodynamic interactions among members of the chain. Shielding effects describe a situation where one bead shields another so that the presence of one bead mitigates the hydrodynamic force felt by another. These hydrodynamic interactions are actually disturbance velocities propagated through the flow field due to the forced motion of beads39. The effect of such disturbances depends on the separation distance between the hydrodynamically interacting beads, and can manifest different behaviors along the mutlimer contour as a result.The notion of position-dependent dynamics is well-illustrated by two examples: protrusion nucleation and hydrodynamic shielding. Macromolecular unraveling is initiated when a small thermally-nucleated protrusion emerges from an otherwise globular multimerConformational feature information listed in Table 40.Figure 25, and therefore any A2 unfolding event can be associated with subsequent cleavage of the vWF multimer. In this case, a practitioner may only be concerned if A2 domain unfolding occurs whatsoever, and the location of the unfolded A2 domain(s) may be of less importance.Correct prediction of folded A2 domains for the 5- and 10-segment resolutions is highly accurate at the multimer termini (∼98–100%), and diminishes slightly nearer to the chain center (∼96–97%). The opposite trend is observed for correct prediction of unfolded A2 domains. Partitioning with 10-segments yielded 7% and 10% accuracy in unfolded A2 domain predictions for the outermost segments. This dramatically increased for their neighbors to 69% and 71%, and was maximal near the multimer center at 86% accuracy. Prediction accuracy at the multimer center is nearly identical for both the 5- and 10-segment resolutions (∼86–87%). However, unfolded A2 domain predictions in the outermost partitions for the 5-segment case exhibit tremendous improvement compared to the 10-segment case with 60% and 61% prediction accuracy. Prediction performance at the chain-level resolution is high for folded and unfolded A2 domain states at 91% and 94% accuracy, respectively. The accuracy of predictions at the chain-level resolution are considerably high, but at a cost to knowledge of A2 domain state location along the multimer contour. However, prior authors have advanced that unfolding of the A2 domain is the rate-limiting mechanism in vWF cleavage by the enzyme ADAMTS13et al. analyzed fluorescence distributions along unraveled vWF multimer contours, and estimated the average extension per monomer with a resolution of tens of nanometers41. Molecular tension sensors with single piconewton sensitivity have been developed for use in living cells by fluorescence force spectroscopy43. Scanning angle interface microscopy permits for the measurement of molecular height in the direction normal to the scanning plane, and can determine the inclination of unraveled surface-bound polymer chains relative to the shearing lamina with nanometer resolution44. Finally, A2 domain state can be probed using a fluorescent molecular tag capable of specifically binding to the scissile bond site within the A2 domain structure. Theoretically, a series of microfluidic flow experiments using fluorescence microscopy imaging techniques could be devised that estimate A2 domain state and the values of predetermined features characterizing flow-induced conformational changes and internal stresses, which occur on length scales as little as tens of nanometers and as large as ten microns. This feature/response data could be analyzed using a RFA to better understand the configurational landscape of the macromolecule associated with sub-monomer A2 domain unfolding events, and in theory, make predictions about such multi-scale behaviors.Figure The low prediction accuracy for unfolded A2 domains in the outermost partitions, shown in Fig. 8), which is parabolic with little force at the termini and peak force at the center. In this work, we have defined A2 domain unfolding to be any force excursion event of FENE spring tension past the experimentally-motivated value of 11 pN. While this definition is certainly a gross simplification of what is actually a sudden, probabilistic, and dramatic unfolding event, the FENE spring model reliably captures smoothed force-extension correlations of unfolded A2 domain dynamics21. In light of the parabolic tension distribution and definition for unfolding, it is intuitive that the probability for A2 domain unfolding (i.e. significant force excursion events) also exhibits a quasi-parabolic distribution along the chain contour . Hydrodynamic forces induce little internal tension near the polymer termini so that the probability of unfolding is small there, however force magnitude and the likelihood of unfolding increase towards the multimer center. Among the 140,00 observations used for training in the 10-segment case, only 0.4% of the data represented conformations with unfolded A2 domains in the terminal segments, whereas this value was over 20% for the two central segments. The 50-fold difference in A2 domain unfolding statistics between terminal and central segments justifies the low prediction accuracy for unfolded A2 domain states at the 5- and 10-segment resolution levels, as compared to the chain-level resolution.This is evidenced by the ensemble average FENE spring tension distribution along the multimer contour . Alternatively, 4 out of the 14 most important features for the first and last segments characterize information pertaining to neighboring segments. Correlated segment dynamics and their implications will be discussed further throughout the remainder of this work.Table cumulative feature importance, which treated the sums of ensemble position components as single features for each segment. However, Fig. Figure where to look for important macromolecular conformational information, which reduced the task to merely determining what that information is. Our domain knowledge of the underlying polymer physics combined with a backwards working approach revealed the nature of the underlying large scale motions that facilitate A2 domain unfolding as a function along the chain.Our motivation for the explicit inclusion of each position component is made evident by the results illustrated in Fig. Based on analysis of feature values and visualization of polymer conformations, we found that the inhomogeneous distributions of positional importance are easily corroborated by elementary polymer physics principles. Two types of behavior are evident in the x-direction position importance distributions in the first column of Fig. less important than the position of beads in neighboring segments 2 and 4. An A2 domain was considered to be unfolded if the internal tensile force within the connecting FENE spring was greater than 11 pN, and the FENE force value was determined solely by the bead-bead separation distance that defines the FENE spring extension. Therefore, one may falsely assume that our choice to explicitly include each bead position component as an input feature to the RFA would ensure highly accurate predictions merely because the response is a sort of non-linear transformation of the features. However, the x-direction distribution for segment 3 shows that this is certainly not true; rather, the position of distant beads that are not physically connected to the unfolding domain are dramatically more important for predicting A2 domain dynamics. As we have shown in Fig. Correlated segment dynamics are readily observable in the distributions of Fig. Figure configuration), we showed that correlations among individual segment dynamics have stronger influence in the outermost partitions as compared to centrally-located regions. Here, a procedure has been advanced that permits significant dimensionality reduction from an entire coarse-grain simulation ensemble to a small collection of key observables at the macromolecular scale, which permit for high accuracy prediction of sub-monomer response. To further demonstrate the impact of such dimensionality reduction, in a forthcoming work, the procedure developed here will be implemented to analyze macromolecular conformation information from experimentally generated data45.We have shown that the instantaneous state of sub-monomer A2 domains can be accurately predicted based on features that characterize macromolecular conformation information of von Willebrand Factor multimers in shear flows. Our method employed a purely data-driven machine learning technique, whereby the Random Forest Algorithm was trained using three data sets of feature/response information of varying resolution detail. Post-training predictions were made using an unseen data set. The accuracy of these predictions for unfolded A2 domains ranged from 86–94% at the multimer center, depending on the feature/response resolution level considered, with a certainty of their location resolved to as little as 5 out of 50 possible A2 domains along the vWF multimer contour. The high accuracy of predictions made indicates that the feature information used as input variables to the RFA sufficiently describes the behavior of vWF in shearing flows. We identified the most important features for prediction of A2 domain state, and found that a small fraction of the total features considered account for the majority of the prediction importance – the 14 most important features out of 88 total features for the 5-segment resolution level accounts for 87–94% of the total prediction importance, depending on segment location. By exploiting the nature of the Random Forest Algorithm, we extracted the dominant motions of the vWF multimer occurring in tandem with A2 domain unfolding events from an ensemble of macromolecular conformations. We observed that these essential large-scale molecular motions manifest in strongly correlated dynamics among various segments of the vWF chain, which occur in concert to facilitate A2 domain unfolding. We found that neighboring regions of the multimer adjacent to an A2 domain unfolding event are required to assume elevation differences in the shearing direction, which causes a local hydrodynamic loading that induces elongation in the flow-direction. Accordingly, we found that A2 domain unfolding requires neighboring regions of the chain on either side to “pull” on it in the flow-direction. Aside from the strong correlations observed among bead position features (or equivalently the chain Supplemental Materials


TRAF-interacting protein (TRAIP), a negative regulator of TNF-induced-nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation, inhibits adaptor protein TRAF2 by direct interaction and is critical in apoptosis, cell proliferation, antiviral response, and embryonic development. Although the critical function of TRAIP in NF-κB signaling is well-known, the molecular inhibitory mechanism of TRAIP remains unclear. We found that the TRAIP coiled-coil domain altered its stoichiometry between dimer and trimer in a concentration-dependent manner. Additionally, the TRAIP RING domain induced even higher-ordered assembly, which was necessary for interacting with the TRAF-N domain of TRAF2 but not TRAF1. Characterization of the TRAF-N domains of TRAF1 and TRAF2, the tentative TRAIP-binding region of TRAFs, suggested the molecular basis of the inhibitory effect of TRAIP on TRAF2 in NF-κB signaling. Tumor necrosis factor (TNF)-receptor associated factor (TRAF) proteins, TRAF1–TRAF7, are major signaling molecules that transduce signals for the TNF receptor (TNFR) and interleukin-1 receptor/Toll like receptor family signaling pathways in mammals and play critical roles in the regulation of the immune system and apoptosis ,3. The mTRAF-interacting protein (TRAIP) was initially identified as a negative regulator of TNF-induced nuclear factor (NF)-κB activation. The inhibitory function of TRAIP is mediated via a direct interaction with TRAF2 and possibly TRAF1 . In addiAlthough the main inhibitory function of TRAIP in TNF-induced NF-κB activation was introduced a few decades ago, the molecular mechanism of TRAIP-TRAF2 interaction-mediated inhibition of TRAF2 function is not fully understood. In this study, we found that the TRAIP coiled-coil domain forms stable dimers or trimers in solution, and the RING domain at the N-terminus of TRAIP participates in the formation of even higher-ordered oligomers. Although it has been suggested that the coiled-coil domain of TRAIP interacts with the TRAF2 coiled-coil domain (TRAF-N) to inhibit TRAF2 function , we founHuman TRAIP (53 kDa) is composed of 469 amino acids with annotated domains including an N-terminal RING domain followed by coiled-coil (CC) and leucine zipper (LZ) domains A. The moFor biochemical studies in vitro, we generated two expression constructs (TRAIP CC: residues 72–167 and TRAIP RING-CC: residues 1–157). Both proteins were well-expressed and purified by two quick-step chromatography processes, affinity and size-exclusion. The size-exclusion chromatography profile showed that the RING domain containing the coiled-coil domain of TRAIP (TRAIP RING-CC) was eluted from 12 to 19 mL, indicating the existence of a more highly oligomerized form, while only the coiled-coil domain of TRAIP (TRAIP CC) appeared as one single peak eluted at approximately 17 mL, indicating a homogeneous population of TRAIP CC in solution B. To anaThe TRAF family contains a common TRAF domain at the C-terminus; six TRAF proteins, from TRAF1 to TRAF6, have been identified in mammals . The C-tTo investigate the mechanism exerted by TRAIP on TRAF using structural and biochemical methods in vitro, we purified the TRAF-N domains of TRAF1 and TRAF2, which are known to interact with TRAIP. Size-exclusion chromatography showed that both TRAF-N domains eluted at approximately 17 mL, indicating the formation of a trimer in solution D,E. ThesBased on previous structural and biochemical studies of the TRAF1 TRAF domain, the TRAF-N domain is critical for trimer stabilization of TRAF1 and this trimerization is functionally important ,20. To fThe interactions between the various constructs of TRAIP, which included CC, RING-CC, and CC-LZ, and TRAF-N domains of TRAF1 and TRAF2, were analyzed by Native PAGE. Although the mixtures of many combinations between TRAIP and TRAF did not produce new complex bands, the mixture of the TRAIP RING-CC and TRAF2 TRAF-N domain produced a complex band that was not detected for either TRAIP RING-CC alone or TRAF2 TRAF-N alone A. This rIn conclusion, the specific interaction between TRAIP and TRAF2 was observed in vitro, and the minimal binding region of TRAIP was analyzed. The RING domain of TRAIP contributed to homo-oligomerization, which is critical for binding to the TRAF2 TRAF-N domain. This interaction strategy may be important for the inhibitory activity of TRAIP against the function of adaptor molecule TRAF. The loosely packed TRAF2 TRAF-N domain may determine the specificity of TRAIP. Collectively, based our results, TRAIP can be homo-oligomerized via the RING domain and the main form of dimeric TRAIP can hijack monomeric TRAF2 (loosely packed into trimer in certain cases) via the coiled-coil domain to inhibit assembly of the functional unit of trimeric TRAF2 during cellular signaling .Escherichia coli BL21 (DE3) cells. The TRAF4 TRAF-C domain, which does not contain a coiled-coil domain, corresponding to amino acids 304–470 and two TRAF-N CC domains of TRAF1 (corresponding to amino acids 181–244) and TRAF2 (corresponding to amino acids 264–329) cloned into the pET24a vector were expressed in E. coli BL21 (DE 3) by overnight induction at 20 °C. Expressed target proteins contained a carboxyl terminal His-tag and were purified by affinity chromatography followed by size-exclusion chromatography. A superdex 200 gel filtration column 10/30  that had been pre-equilibrated with a solution of 20 mM Tri-HCl at pH 8.0 and 150 mM NaCl was used for size-exclusion chromatography. Cloning, protein expression, and purification of the TRAF domains of human TRAF2 and TRAF4 were conducted as described previously [To obtain C-terminally His-tagged protein samples of TRAIP, the full-length cDNA of human TRAIP (residues 1–280) was used as a template for polymerase chain reaction (PCR). Human TRAIP CC (residues 72–167), TRAIP RING-CC (residues 1–157), and TRAIP CC-LZ (residues 66–280) were amplified and cloned into the pET24a vector at the NdeI and XhoI cloning sites. The plasmid was then transformed into eviously ,23.The molar masses of the TRAIP CC, TRAIP RING-CC, and TRAF-C domains of TRAF2 and TRAF4 were determined by multi-angle light scattering (MALS). Purified target proteins were re-loaded onto a Superdex 200 HR 10/30 gel-filtration column  that is connected to the AKTA pure FPLC machine  and mini-DAWN treos MLAS detector . The gel-filtration column had been pre-equilibrated with proper buffer.AUC data were collected at 20 °C using an XL-A analytical ultracentrifuge . A concentration of 2 mg/mL of TRAIP CC for the TRAF-N domains of TRAF1 and TRAF2 in 20 mM Tris-HCl pH 8.0 and 150 mM NaCl and the reference buffer were loaded onto a dual sector Epon centerpiece . Both protein samples were centrifuged at 45,000 rpm and the movements of a boundary formed by the high centrifugal force were monitored over time at a wavelength of 280 nm. The experimental data were analyzed, and c(s) was calculated using the program SEDFIT .The oligomeric states of TRAIP CC and TRAIP RING-CC, as well as the complex formation of various TRAIP proteins with TRAF, were monitored by Native (non-denaturing) PAGE using a Phast System  with pre-made 8–25% acrylamide gradient gels . Purified protein samples obtained by affinity and size-exclusion chromatography were loaded onto the gel. Coomassie Brilliant Blue was used for staining.http://www.ebi.ac.uk/Tools/msa/clustalo/).The amino acid sequences of the TRAF domains of TRAF1 and TRAF2 were analyzed using Clustal Omega . A 20-µL sample mixture of protein, thermal shift dye, and buffer was tested. The fluorescent signal was detected as a function of temperature using a CFX96 Real-Time PCR Detection System . Raw data were retrieved using the Transcriptic webapp, and melt curves were generated by plotting the first derivative of the fluorescent signal as a function of temperature.TRAF CC and various TRAIP proteins purified from affinity chromatography were mixed in a molar ratio of approximately 1:1 and pre-incubated at 25 °C for 1 h. The mixture was then passed through a Superdex 200 gel filtration column HR 10/30  that had been pre-equilibrated with buffer containing 20 mM Tris-HCl at pH 8.0 and 150 mM NaCl.