HHsearch , which can detect remote homologies that are missed by tools used to annotate databases. Here we have applied HHsearch to study a single structural fold in a single model organism as proof of principle. In the entire clan of protein domains sharing the pleckstrin homology domain fold in yeast, systematic application of HHsearch accurately identified known PH‐like domains. It also predicted 16 new domains in 13 yeast proteins many of which are implicated in intracellular traffic. One of these was Vps13p, where we confirmed the functional importance of the predicted PH‐like domain. Even though such predictions require considerable work to be corroborated, they are useful first steps. HHsearch should be applied more widely, particularly across entire proteomes of model organisms, to significantly improve database annotations.Advances in membrane cell biology are hampered by the relatively high proportion of proteins with no known function. Such proteins are largely or entirely devoid of structurally significant domain annotations. Structural bioinformaticians have developed profile‐profile tools such as  Even more sensitive tools carry out profile‐profile searches, which extract family‐wide information for both query and target.Protein Databank of solved structures (PDB). Profiles can implicitly encode aspects of secondary structure,HHsearch is a powerful profile‐profile alignment toolAn important way to determine the function of an unknown protein is to identify homology to a protein with known function. However, a significant minority ~20%) of protein sequences shows no obvious homology at the level of primary structure  to any other protein.0% of proclan.Pleckstrin homology (PH) domains and their structural homologues, PH‐like domains, are one of the most common folds in eukaryotes.S. cerevisiae is one of the most highly studied, especially in systems biology. Yet for 10%‐13% of yeast proteins there is no functionally or structurally relevant domain information . Progress in finding functions for yeast proteins with no recognizable domain is slower than expected.The model organism 22.1PH‐like domains are defined by a combination of structure and sequence alignment Box . DiffereBox 1PH‐like domains are the fourth most common fold in the human proteome.either (1): by structural similarity to the region occurring twice in pleckstrin. The peptide backbone follows the characteristic βββββββα‐pattern closely; or (2) by significant sequence homology to any domain that fits the structural definition. This may require indirect alignment (profile‐sequence) rather than just sequence‐sequence. Both the classical PH domain in PEPP1 and the GRAM domain in MTMR2 meet definition 1  made from seed plus hits. The profile is then used to initiate another round of searching, and because it contains more sequence information than the previous round it may detect more hits. The whole process iterates through multiple rounds until no more sequences are added.All profile‐sequence tools are seeded with one or multiple sequences to find new SuperFamily only uses seeds with solved structure, while Pfam starts with any recognizable domain.HMM), which codes insertions or deletions at each position in a profile‐specific way.Profile‐sequence tools differ in choice of seeds, in particular how broad a net to cast. For example, the tool pfam.xfam.org/clan/CL0266), but new discoveries are not disseminated to databases instantly.Domain definitions are updated regularly  is annotated by InterProScan, which is a resource from the European Bioinformatics Institute . InterProScan incorporates all of Pfam, SuperFamily, Gene3D and many other profile‐sequence tools.33.1Defining PH‐like domains starts with mining the literature, the PDB for solved structures, and sequence databases. For a standard definition of the PH‐like clan we used PSI‐BLAST to study PDB, which contains >200 different PH‐like domains. We described the minimal set of 39 PH‐like sequences that identified the complete set of PH‐like domains in PDB as strong hits in PSI‐BLAST searches. This minimal set indicates the presence of 39 families in the PH‐like clan  include both “knowns” such as PDB, and curated domains from Pfam, SuperFamily, Gene3D(CATH) and other profile tools, and also “unknowns,” ie, proteomes, both prokaryotes (>30) and eukaryotes (x9): human, mouse, fruit fly, nematode, malarial parasite, thale cress and 3 fungi: budding yeast (S. cerevisiae), fission yeast (S. pombe) and maize blast (U. maydis). The 2 libraries used mostly for this study are PDB, which contains ~35 000 entries (non‐redundant at 70% sequence identity) updated weekly, and yeast, which has 5870 entries. A third library constructed in‐house was used for off‐line searches .HHsearch has 3 stagesnumber of iterations. The defaults number of iterations for building the query MSA is 3. Libraries of targets have been built with 2 iterations. Iterating more times (maximum number = 8) enhances sensitivity, but takes longer. Searches designed specifically to identify only orthologues within a large family of homologues may benefit from using 1 iteration, deliberately reducing sensitivity.scoring secondary structure. There is an option to not score secondary structure at all. Run off‐line, it is also possible to vary the proportion of the overall alignment weighted to secondary structure. Default is 11%, ie, sequence alignment dominates.using solved structure. If the PDB is being used as either query or target, the user can choose to use solved secondary structure states (reduced to 3 states) instead of predicted structure.Important variables that can be set by the user for each of the 3 stages are:probability of shared structure (prob[SS]) with the query sequence. For each hit, apart from the prob[SS] value, there is a precise alignment  that can be summarized by 3 important values: (i) the statistical expectation  of achieving the hit in terms of sequence alone given the size of the library, equivalent to the HHblits E‐value; (ii) the 2° structural similarity (2Ssim), which is independent of sequence homology; and (iii) the number of columns aligned between query and target (COLs), which can be as few as 6. We applied a length threshold that the alignment should cover 20% of the domain, ie, 20 aligned columns, and we found that shorter hits were often to a single structural element . Hits that can be detected by PSI‐BLAST typically have a prob[SS] ≥ 99% and an E‐value of 10−10, which reflects the greater sensitivity of HHblits than PSI‐BLAST.HHsearch returns up to ~20 000 hits ordered in terms of descending 44.1Specificity : HHsearch provides a list of alignments with decreasing probability of shared structure : To compare the sensitivities of HHsearch and PSI‐BLAST, we compared their ability to join the PH‐like clan together. The 39 searches with HHsearch produced 1200 hits to PH‐like domains in PDB with prob[SS] ≥ 85%, which is many more positive hits than PSI‐BLAST produced (n = 350). While 20 families were unlinked by PSI‐BLAST, HHsearch left just 4 unlinked families  of these domains (Table S2A).We used HHsearch to search a target HMM library containing all yeast proteins with the 39 PH‐like sequences defined above. Among hits with prob[SS] ≥85%, there were 71 of the 73 known yeast PH‐like domains  makes no difference. On the other hand profile‐sequence tools are dependent on where they start because the profile represents a large group of sequences centred on the query. Thus, a profile‐sequence tool searching in 1 direction  will probably not make the same hits as the same tool searching in the other direction .One way to overcome the problem of profile bias in favor of where it starts is to manipulate the growing MSA to attempt to eradicate any trace of its origin. HHblits does this by filtering an MSA (thousands of sequences) to only pick a small group (~100) that are chosen to maximize diversity.HHalign . This confirmed that only the 4 new regions in Caf120p, Lam1p, Sip3p and Vid27p are PH‐like domains . Therefore, it is a false positive hit. We next investigated how such a strong false positive arose . We then used each of the yeast MSAs in turn to search the PDB library. This identified 88 yeast regions where the top hit was both (1) a solved >200 PH‐like domain and (2) had a prob[SS] ≥ 85%. This group contained 72 of the 73 known yeast PH‐like domains (sensitivity = 99%). The 73rd known domain also matched PH‐like domains in PDB, but at prob[SS] = 79%. The 16 other regions included all 4 of the new regions found above and 12 further candidate PH‐like domains, with matches in the range of prob[SS] 88%‐100%. We tested if these were true positives by carrying out pairwise alignments. These showed strong hits to known PH‐like domains for 11 of the regions. One other region, in Pib2p, was a false positive for the same reasons as Age1p, in that matches to PH‐like domains were only obtained with longer segments  not the domain alone (data not shown). We predict that the remaining 11 matches are all PH‐like domains . Whether this involved offline use of HHsearch, or a combination of strategies for the online server HHpred  are worth considering further.Seed searches with domain only to exclude false positives .For every interesting region, confirm the significance of the hit by comparing its strength to that obtained by the strongest false positives in PDB‐to‐PDB searches (set to detect predicted structure only).Use PSI‐BLAST to identify one representative sequence per family within the overall clan.Use the representative sequences in PDB to PDB searches by HHsearch to set a threshold for prob[SS] that avoids false positives .Seed PDB‐to‐unknown HHsearch searches with these sequences, looking in the proteome of choice, identifying positive hits with the threshold obtained above.Investigate non‐significant hits, especially those with relatively high COLs and 2Ssim Box , by carrMake more links between non-significant hits and PDB entries by indirect searches in related organisms. First, use unknown‐to‐related proteome searches to identify homologous regions in the related proteome. Use these hits to carry out related proteome‐to‐PDB searches.Confirm all new matches with domain only searches.A more complex alternative for the confirmatory steps (A2 and B6) is to create HMMs for the query and target regions with 8 iterations, and align them pairwise with HHalign.The final option we explored was to test different settings within HHsearch. To identify conserved folds with highly diverged sequence, we raised the secondary structure weighting (ssw) within each alignment. In HHsearch, this has a default of 11% Box . Increas2.6One of the most typical functions of PH‐like domains is organelle targeting, binding proteins or lipids. In a previous survey of 33 yeast classical PH domains, only 9 had this function,Full‐length Vps13p (3144 aa) has intracellular localisations to multiple membrane contact sites, including vacuole and mitochondrial patches (vCLAMP), endosome‐mitochondrial contacts and nucleus vacuole junctions (NVJ),We next studied the effect of the two Vps13 mutations on intracellular distribution. Vps13‐EGFP showed a complex intracellular distribution: in log phase it was largely diffuse, with the majority of cells containing puncta, some of which were close to the vacuole Figure A; by comvacuolar protein sorting (vps) defect (and hence is secreted) in Δvps13 cells.Δvps13 produced significantly stronger signals than wild‐type Vps13‐EGFP, stronger for Vps13ΔPH‐EGFP than Vps13LIAA, although both were significantly weaker than empty plasmid , a vacuolar enzyme that is subject to a strong d Figure G. Thus, d Figure H.722.7Is the increase in domain discovery seen for PH‐like domains likely to apply to other domains? To begin to examine this we surveyed 132 contiguous open reading frames on the right arm of yeast chromosome IV, representing 2% of the yeast proteome. MSAs for all ORFs were used to search PDB, and regions not previously known to contain domains were examined. Twenty‐one new domains were predicted in 16 (12%) of the proteins . As with PH‐like domains, many of these new domains would also be discoverable by systematically initiating PSI‐BLAST with the yeast sequence (prob[SS] ≥ 99% n = 9). Although some of the newly discovered domains do not strongly determine function , other predictions are more functionally significant . Seven newly predicted domains were found in the 19 proteins that had no prior structural/functional information, a discovery rate of 37%. Rolled out across the entire yeast proteome HHsearch could identify ~900 new domains, and 250–300 of these would be in the proteins that currently have no structural/functional information.39 years, so homologues can be found at different evolutionary distances to provide information about functionally critical residues in yeast proteins. In the future we plan to analyze the yeast proteome systematically, annotating all the knowns and predicting many unknowns. Meanwhile HHpred is an extremely powerful online resource for discovering remote homologies.Current protein domain annotations can be significantly improved with profile‐profile tools, to catch up with advances in the literature, to focus searches on proteins of unknown function, and to maximize sensitivity. For the PH‐like clan, HHsearch identified the known domains and also extended their number by 20%. Elsewhere in yeast, application of HHsearch may be particularly good for proteins of unknown function. Yeast proteins are very good subjects for this tool because many organisms exist that diverged from it at different times in the last 104Database files: Files downloaded : InterProScan , HHsuite 2.0.15  including yeast template HMMs (May 2008), PDB , and Interpro 34.0.PSI‐BLAST: Searches were carried out in 2 stages at Tuebingen Toolkit. Firstly the PDB sequence was seeded in searches of sequences from NCBI . If new sequences were still added in the final iteration, a further round of 10 was initiated, until no more sequences were added . Aligned sequences were then submitted to a single round of BLAST using PDB as the target database.HHblits: This was run on its own or as part of HHsearch with up to 8 iterations and an e‐value threshold for inclusion in MSA = 0.001–0.01.HHsearch: Use was both online (“HHpred”) at http://toolkit.tuebingen.mpg.defmin))/0.45–3.0hit.score_aass = ))/0.45–To allow secondary structure to be weighted higher than the standard 11%, we edited line 853 of “hhhitlist.C”:lamda*hit.score_ss/0.45–3.0hit.score_aass = ))/0.45–The underlined term was reduced to:This change removed a cap on the contribution of secondary structure.HHalign: Domain sequences from both PDB and yeast proteins with 3‐5 flanking residues where available were submitted to HHblits, and the resulting “representative alignments,” deleting the secondary structure prediction and confidence entries, were compared in HHalign run with standard settings.Yeast HMM library (Ychunk200): Total yeast protein sequence was obtained from downloads.yeast-genome.org/sequence/S288C_reference/orf_protein/. The problem highlighted by Age1p  was addressed by dividing proteins into regions of 200 residues (overlapping by 100), producing ~26 000 “chunks.” MSAs and HMMs were created for all chunks  to create a “Ychunk200” library that is available as an FTP download on request.Yeast‐to‐PDB searches: All HMMs in Ychunk200 were submitted as queries for HHsearch using the PDB library (June 2013) as target. Top hits to PDB entries that contain PH‐like domains were then filtered for the presence of multiple domains, and if these were found alignments were curated by hand to include only those hits where the alignment includes the PH‐like domain.Residue conservation across the C‐terminus of Vps13p: ConSurf was used with standard settings for the final 1095 aa of Vps13p.Plasmids: All plasmids were based on pRS416 , and used the 168 bp fragment from the promoter of PHO5 for moderately strong, constitutive expression. PH domains were cloned as monomers in the form GFP—LGSAPVMAS—cloned sequence—SR*, and dimers were separated by either SR or SS. Residues used were Bud2p‐1 = 1‐163, Bud2p‐2 = 168‐319, Gyp7p = 1‐182, Pkh1p = 562‐674, Pkh2p = 833‐966, Tph3p‐1 = 1‐177, Tph3p‐2 = 180‐561, Vps13p = 3028‐3144, and Ysp1p‐2 = 568‐717. Full length and truncated Vps13p constructs were cloned by gap repair to clone either Vps13‐EGFP (1–3144 aa), Vps13ΔPH‐EGFP (1–3028 aa), or Vps13LIAA‐EGFP . All PCR products and non‐gap repaired segments were checked by sequencing.Microscopy: Cells grown at 30°C to mid log phase, or 16 h thereafter for early stationary phase, were immobilized between slide and coverslip, and visualized on an AOBS SP2 confocal microscope  at room temperature, using identical settings for images comparing different constructs.Vacuolar Protein Sorting of CPY: Haploid BY4741 yeast lacking VPS13 were transformed with full length and mutated Vps13‐EGFP plasmids, as well as a plasmid expressing GFP‐GFP. The parent wild‐type strain, also carrying GFP‐GFP, was included as positive control. Ten‐fold dilutions of cells were spotted on selective medium  and grown for 24 h before being overlaid with a nitrocellulose membrane for 16 h. This was washed extensively, and then processed to detect CPY,The authors declare that they have no conflicts of interest.Clan: a group of domain families that share the same fold but cannot be linked by standard sequence alignment tools  alone. Sometimes called superfamilies.E‐value: each alignment between query and target is assigned an e‐value, which is the number of hits as good as the one obtained that would be expected to occur randomly given the size of the database being searched. A threshold is chosen, (here 0.01) so that alignments more statistically unlikely than this are considered significant.HHalign: pairwise application of HHsearch for direct comparison of 2 MSAs.HHblits: Builds profiles from a single query via multiple rounds of searching, differing from PSI‐BLAST in several ways that increase speed and sensitivity.HHpred: online server for HHsearch.HHsearch: profile‐profile tool that explicitly weights a proportion of an alignment to aligned (predicted) secondary structure. MSAs can be built by either PSI‐BLAST or HHblits.Hit: target in database that aligns with an e‐value more statistically significant  than the chosen threshold.HMM: Hidden Markov Model: a way to represent MSAs, coding features including penalizing insertions and deletions in a profile‐specific way; more computationally complex than a simple profile.MSA: multiple sequence alignment: sequences with multiple small regions of local homology are aligned across a large region by inserting gaps. MSAs can be dominated by large numbers of highly related sequences . This problem can be addressed by filtering MSAs for redundancy, reducing non‐diversity.Pfam: a tool that identifies domains broadly, even without known structure/function. Pfam domains are constructed as HMMs. They are curated, reliable, and when structurally related families are found, they are grouped into clans on the basis of structural homology confirmed by HHsearch.Profile: statistical representation of the residues across an MSA, sometimes represented as a protein “logo.” Simple profiles apply inflexible, standard rules, for example for insertions/deletions.PSI‐BLAST:Position‐specific iterated basic local alignment search tool. Builds profiles from a single query via multiple rounds of BLAST.Query: (or seed) sequence from which searches are initiated.SuperFamily: a narrow specificity tool for identifying domains similar to known structures, similar to SCOP.Target: group of sequences curated into a database among which homologs are being sought. Database size varies from relatively small  to very large . Size can be reduced by excluding redundant sequences sharing more than a pre‐determined level of sequence identity (20%‐90%).DRF adapted the program hhhitlist.C, constructed Ychunk200, and carried out all offline HHsearches. SEM assayed CPY sorting, and carried out cloning and imaging. KC created and analyzed match lists, and created display items. PA, RE‐T and JI created and analyzed match lists. TPL conceived the study, created match lists, and created display items. All authors contributed to drafting of the manuscript, and read and approved the final manuscript.scop.berkeley.edu/, and Pfam 30.0. RED indicates PH‐like families that were missing from the PH‐like clan. “X” indicates that the family was missing completely. The penultimate column shows the number of PH‐like domains for each family in PDB (using a version non‐redundant at 70% identity), both for grouped families  or the full list (n = 39). The final column shows the 1 structure we chose to represent the family for searches in PSI‐BLAST and HHsearch. Where the structure includes more than 1 PH‐like domain, the segment used is indicated. The bottom lines show the total number of PH‐like families in each classification, and information on 1 domain wrongly assigned as PH‐like in Pfam. Table S1 : compares previous and current categorizations of the PH‐like clan, and lists seeds used here.Table S1 Classifications of PH‐like domains. Information on our classification of 39 PH‐like families , starting with the major groups that contain overlapping families in some classifications. Our classification is compared to those in Conserved Domain Database (CDD) at NCBI, the Structural Classification of Protein (SCOP) database at yeastgenome.org), Smart, SuperFamily (methods 1‐3) and HHsearch (PDB‐to‐yeast and yeast‐to‐PDB = methods 4 and 5). For methods 1‐3, any family specified is indicated , while “+” indicates a generic PH‐like identification. § False positives in InterProScan were produced by Gene3D in Cbk1, Fpk1p and Kin82p. HHsearch identified Age1p as a false positive . For method 4, the prob[SS] and family  of the strongest hit to the yeast domain is indicated. Other notes: c = crystal structure solved, h = homologous to a solved structure, o = omitted by Yu et al. (2004)42; ° numbering of PH‐like domains within individual proteins takes account of the new domains we identify . B, Newly identified PH‐like domains in yeast. Details include discoverability by different tools: (1) PSI‐BLAST, showing E‐value (log10) and number of iterations (#) when a known PH‐domain (definitions 1 or 2 including yeast proteins in part A above) is found in the hit list; T indicates only temporarily in hit list, lost before convergence; (2) SMART domain prediction server, showing E‐values (log10) for any domains detected; (3) FFAS profile‐profile tool, 74; (4) PHYRE2 structural prediction tool .75 HHsearch: method 5 = PDB‐to‐yeast (prob[SS]and query); method 6 = yeast‐to‐PDB (prob[SS] and target); method 7 = HHalign result with target in method 6. Prob[SS] values outlined in red were used to make identifications: 4 in PDB‐to‐yeast, 11 in yeast‐to‐PDB; 1 further identification was made by indirect searches (outlined in black). Other notes: ¶ Bud2p‐1 is indicated by SMART as overlapping a false‐positive C2 domain; § new true positive in Pkh1p already in SGD (identified by Gene3D); “T” indicates that for Pkh2p and Vid27p‐2 the PSI‐BLAST hit was only temporary, and was missing at convergence. Grey shading = non‐significant hit in Rec114p found using ssw = 30%; yellow = false positive for Age1p‐N, where the top hit in yeast‐to‐PDB searches was a thioredoxin, and pairwise alignment of Age1p‐N and the PH domain from centaurin (human ARFGEF) had prob[SH] = 0.1%. Table S2 : A, compiles literature not previously available in 1 resource, and is background information for Figure 2C; B, shows detail for Figure 4.Table S2. Description of PH‐like domains in yeast. A, 73 known PH‐like domains in yeast identified by 5 different methods: InterProScan : A, C‐terminus of yeast Get5p (3vej_A) aligned at 14 of its 41 residues to the helix of 4chj_A, prob[SS] = 77%; B, mid‐section of human FANCL (3zqs_A) aligned at 40 of its 186 residues to strands 3‐5 of 2kig_A, prob[SS] = 83%. C, αβ subdomain of NS1 from Dengue virus type 2  aligned at 90 of its 114 residues to all 7 sheets in 4gou_A, prob[SS] = 76%. Aligned regions shown in colors . While some non‐PH‐like hits are very short and can be identified as non‐PH‐like by that criterion (A), others cover multiple structural elements and cannot be excluded on the basis of shortness (B and C). Figure S1 : shows worked examples from Figure 3B is a comparison with Figure 1.Y. lipolytica ArfGEF , and T. nigroviridis ArfGEF . Coloring by HHsuite AlignmentViewer. All residues where the HHsearch alignment in part A. reported a good or very good hit (+ or |) are scored for actual conservation between Age1p and the other sequence(s): +, ±, − for strength of hit. Residues 81‐97 of Age1p predicted to align with alpha helix of centaurin in A. contains multiple prolines in its second half (highlighted in both A and B). The N‐terminus of Age1 has homologs only in species very closely related to S. cerevisiae, so this part of the MSA should only have 1 sequence. However, the downstream GEF (Age1p residues 168‐307) has 163 homologs, many of which have a domain structure BAR‐PH‐GEF. Two of these align to part of Age1p 1‐130 (A). These give a PH‐like appearance to the MSA at its N‐terminus that is not present in the original seed (B). Figure S2 : shows detail on sole mechanism uncovered for false positives in HHsearch.Figure S2: Dissection of a false positive in Age1p. A, Alignment showing a strong hit obtained in HHsearch between the PH‐like domain of human ArfGEF Centaurin and the N‐terminus of Age1p. For interpretation of the alignment, see Figure 5B legend. Three unstructured loops in centaurin of 43, 7 and 8 aa are omitted. The single‐most conserved residue in PH‐like domains is the tryptophan in the helix (asterisk), which is reported as making a very good hit (|) with a glutamine in Age1p. B, All sequence from the first 102 columns of the Age1p MSA in HHsuite. This part of the MSA includes only 3 of 164 sequences: Age1p N‐terminus (1‐102/482aa), yeastgenome.org). Known domains in these proteins are shaded as in Figure 4 or in green. Naming: where a protein only has a systematic name, just the suffix is given . Red indicates the proteins (19 = 14%) without prior structural/functional predictions . Seven of these (37%) had newly predicted domains. By contrast, 9 of 113 (8%) previously characterized proteins had newly identified domains. Figure S3 (with Beyond PH domains section): shows the extent to which new domains can be found.Figure S3. New domains found in 132 consecutive yeast genes. 132 consecutive verified open‐reading frames on the long arm of chromosome IV (“YDR”) starting at the centromere (YDR001C‐134C) were analyzed by HHsearch. Names in bold indicate proteins (x16) where new domains were documented (x21). New domains are outlined in black and shaded by prob[SS] on a white‐red scale; scores and main hit in PDB or Pfam are also given. All new hits were confirmed by pairwise alignments of domains alone. Asterisks indicate that the domain was detected by SMART even though absent from InterProScan data displayed at Click here for additional data file.Movie S1. PH‐like domains share structure. Rotating models of structures in Figure 1. Accompany Figure 1.Click here for additional data file.Movie S2. PH‐like domains share structure. Rotating models of structures in Figure 1. Accompany Figure 1.Click here for additional data file.Movie S3. PH‐like domains share structure. Rotating models of structures in Figure 1. Accompany Figure 1.Click here for additional data file.


While a lot is known about the deformation of metallic surfaces from experiments, elasticity theory and simulations, this investigation represents the first molecular-dynamics-based simulation of uniaxial deformation for the vicinal surfaces in a comparison of copper and nickel. These vicinal surfaces are composed of terraces divided by equidistant, mono-atomic steps. The periodicity of vicinals makes them good candidates for the study of the surface steps’ influences on surface dynamics. The simulations of tensile and compressive uniaxial deformations were performed for the (1 1 19) vicinal surfaces. Since the steps on the surfaces serve as stress concentrators, the first defects were expected to nucleate here. In the case of copper, this was found to be the case. In the case of nickel, however, dislocations nucleated beneath the near-surface layer affected by the displacement field generated by the steps. Slip was hindered at the surface step by the vortex in the displacement field. The differences in the deformation mechanisms for the Ni(1 1 19) and Cu(1 1 19) surfaces can be linked to the differences in their displacement fields. This could lead to novel bottom-up approaches to the nanostructuring of surfaces using strain. In the past 20 years investigations of stress and strain effects in the field of surface physics have become increasingly important as the manufacture of nanoscale materials and devices has become more widespread, leading to studies based on a combination of theoretical, computational and experimental investigations23456Elasticity also provides pressure maps that can help to predict the stress release resulting from atomic rearrangements128910Experiments on the nanoscale can be very time consuming and costly, requiring expensive equipment, particularly sensors; however, they confirm an array of unusual mechanical properties of nanoscale materials13141516Nano-indentation studies focus on dislocation nucleation beneath the indenter. The stress that is applied via the frictionless rigid indenter is non-uniform, but it can lead to homogeneous defect nucleation in a perfect crystal. The substrates are thin films1819242526As nanowires have a large surface-to-bulk ratio, the most comprehensive studies of the influence of free surfaces on the mechanical properties of metallic materials using molecular dynamics were made with samples of nanowires28293031In this study molecular dynamics simulations of copper and nickel (1 1 19) vicinal surfaces under an externally applied uniaxial strain were performed and the beginning of plastic deformation was studied in order to determine the stability of the surface steps during deformation and their influence on the deformation mechanisms. The (1 1 19) surfaces were chosen because the steps on this surface, vicinal to the (1 0 0) nominal surface, are dense, and yet the distance between the steps is large enough to ensure that the interaction between the steps is weak: the relaxations of the step edge atoms are only slightly modified by the presence of the other stepsA two-dimensional schematic of a (1 1 19) surface is shown in The steps on the surface of a metallic material play a role in the atomic arrangement of the surface layers. Near-surface atoms are displaced from their bulk positions to accommodate the lack of neighbours at the surface. In the case of the vicinal surfaces this minimal energy arrangement of atoms leads to a complex displacement field, stretching several layers into the bulk specific for each surface orientation and material2Although the displacement fields have been studied for a range of metals and surface orientations, their influence on the deformation mechanisms of the surfaces has never been investigated before. We have compared the displacement fields of Ni(1 1 19) and Cu(1 1 19) surfaces with their deformation mechanisms to investigate whether any influence of the displacement fields on the deformation mechanisms could be discerned.The displacement fields for the Ni(1 1 19) and Cu(1 1 19) surfaces are shown in In the case of nickel , some ofIn the case of copper , all theIn the case of nickel, the vortices can be thought of as straddling the (111) plane intersecting with the step, whereas in the case of copper the vortices can be seen as contained between two (111) planes intersecting with adjacent steps. In the view presented in Copper and nickel both have a face-centered cubic (fcc) lattice. In fcc crystals the close-packed planes and directions are preferred for slip. However, which slip systems are the most favorable is additionally determined by the direction of the strain. In our case the strain direction was . The bulk nucleation sites in nickel are the same as in the case of tensile deformation. Two perpendicular slip systems are activated at once. A dense mesh of dislocations forms. Due to the lack of space available, the dislocations that have nucleated at the surface climb along the terraces instead of growing into the bulk. In the case of copper, only one slip system is activated (b). As expected, the slip plane is perpendicular to the one active in tensile deformation. After the dislocations reach the bottom of the sample, deformation twinning is observed in the bulk (d). The slip system perpendicular to the primary one is not activated. In comparison, the bulk nucleation sites are present in nickel but not in copper and two slip systems are active in nickel, whereas only one is active in copper. In addition, deformation twinning is observed in copper but not in nickel.In the case of nickel deformed in compression, In the case of copper deformed in compression, dislocations nucleate at the edges of the terraces, In comparison, the bulk nucleation sites are observed in nickel, but not in copper. Two perpendicular slip system are active in nickel, while only one is active in copper. Deformation twinning occurs in both materials, starting at strains of −7.1% for copper and −7.5% for nickel.−1. Although the metals are very similar, we have found very significant differences in their plastic deformation mechanisms.We have investigated the plastic deformation of the (1 1 19) vicinal surfaces of copper and nickel thin films deformed in tension and in compression with a uniaxial engineering strain at a rate of 2.5% psThe low temperature and the high strain rate of the simulations influence the deformation mechanisms. At low temperatures the diffusion-controlled processes are suppressed and the main deformation mechanism is slipIn the size range of our simulations, i.e., approximately 10 nm, partial dislocations are generally preferred over full dislocations as the deformation mechanisms for metallic materials12As both metals have low stacking-fault energies, the expected deformation mechanisms were by partial dislocation slip and by twinning. As the stacking fault energy and the predicted twinning stress of nickel are higher than that of copper, a preference of twinning over slip is expected to be more pronounced in copperMultiple criteria are met, for both materials, predicting partial dislocations and twinning as the main deformation mechanisms, and both are observed in all the cases, superseding full dislocation nucleation.The arrays of steps on the (1 1 19) vicinal surfaces influence the deformation mechanisms of both metals. The regularity of the steps is translated into the regularity of the stacking faults that form in all cases.In the case of copper, steps on the surface serve as nucleation points and both tensile and compressive strains lead to a flattening out of the surface steps. This is as expected from the theory of elasticity.In the case of nickel, the point of dislocation nucleation lies 8–10 layers underneath the surface instead of at the surface. The nucleation sites are the same in tensile and compressive deformation, although in compression the dislocations nucleate at the surface steps as well. The defect nucleation sites buried below the surface are unexpected, since the steps are known as the stress-concentration points. The defect nucleation sites lie beneath the terraces just outside the region affected by the displacement field. In addition, the primary slip system activated in nickel deformed in tension is perpendicular to the primary system activated in copper.In the case of copper deformed in tension, slip occurs in the (111) plane that delineates two vortices underneath adjacent terraces. The atoms involved slip in the direction of their displacements. In the case of nickel, this process is hindered by the presence of the vortices. Nucleation points are shifted into the bulk beneath the displacement field. Slip occurs in the direction in which crystal symmetry is disturbed the most by the displacement field.In the case of nickel deformed in compression, nucleation points in the bulk and at the steps are activated. The area of the vortex is again initially avoided, then cut through by the stacking fault originating in the bulk, as was the case in tensile deformation. The nucleation of stacking faults at the steps is in this case not restricted by the displacement field.et al.Zimmerman et al.Shan et al.26Lu To date no such investigations were performed for nickel vicinal surfaces.et al.et al.26As the surfaces were first to deform in our study, we are in agreement with Shan We have observed distinct deformation mechanisms depending on the sign of the strain. Both materials were similarly affected, as a switch to a different deformation mechanism occurred in tensile deformation at higher strains, while multiple deformation mechanisms were activated at once in compression. Experiments show there are cases of different deformation mechanisms depending on the sign of strainWe conclude that the displacement fields of vicinal surfaces play a role in their deformation mechanisms. As expected, the regularity of the steps on the surface translates into the regularity of the dislocations and stacking faults that form beneath the surface. While all the dislocations were expected to nucleate at the steps, this was the case for copper, but not for nickel. In tensile deformation, the displacement field in the vicinity of the step in nickel seems to prevent slip in the (111) plane, which is the first to activate in the case of copper. In compressive deformation, the nucleation points beneath the surface in nickel are activated in addition to the ones at the surface that follow the expected pattern, as evidenced in copper.As the displacement fields are orientation dependent, differences in the deformation mechanism might also arise for other vicinal surfaces.As was shown for nickel, a patterned surface can be achieved, which has repercussions for bottom-up approaches to the nano-structuring of surfaces using strain. A high density of steps can be achieved, which could be used for templates, in catalysis3456739−1. The strain direction was (19 19 Copper and nickel thin films of 10 nm thickness with (1 1 19) surface orientation were simulated. The simulations of the tensile and compressive uniaxial deformations were performed at 10 K, applying engineering strain at a strain rate of ±2.5% pset al.et al.Copper and nickel single-crystal substrates were used in the molecular dynamics simulations, which were carried out using the LAMMPS Molecular Dynamics Simulatorx = (1 y = (19 19 z = (1 1 19).The axes of the simulation boxes were x and y directions and fixed in the z direction.The boundaries of the simulation boxes were periodic in the y direction the size of the simulation box was subject to requirements for periodicity of the terraces and steps for vicinal surfaces. The number of steps and terraces included was 8.In the z direction the simulated films were bound by a free surface at the top and by a layer of fixed atoms at the bottom to prevent the loss of atoms at the border of the simulation box and to simulate defect-free bulk. The thickness of this frozen layer was 1.2 nm. These atoms were fixed at the positions they had when equilibrated to 10 K and were remapped at every deformation of the simulation box. All the forces acting on these atoms were otherwise reset to zero.In the Physical dimensions of the simulated samples were as follows. The lattice parameter of copper was 0.36149 nm and the size of the simulated sample was 20.4 nm × 19.5 nm × 11.2 nm. The lattice parameter of nickel was 0.35200 nm and the size of the simulated sample was 19.9 nm × 19.0 nm × 11.2 nm.y direction in increments of 0.5% with 200 fs periods of equilibration in-between, resulting in the overall strain rate of 2.5% ps−1. The stress in the x direction was kept to zero.Damped dynamicsOVITOThe centro-symmetry parameter is used to identify dislocations and stacking faults in the simulations. In solid-state systems the centro-symmetry parameter is a useful measure of the local lattice disorder around an atom and can be used to characterize whether the atom is part of a perfect lattice, a local defect , or at a surface. This parameter is computed using the following formula46N nearest neighbours of each atom are identified and Ri and Ri+N/2 are vectors from the central atom to a particular pair of nearest neighbors. For an fcc lattice N is 12. For an atom on a lattice site, surrounded by atoms on a perfect lattice, the centro-symmetry parameter will be 0. It will be near 0 for small thermal perturbations of a perfect lattice. If a point defect exists, the symmetry is broken, and the parameter will be a larger positive value. An atom at a surface will have a large positive parameter.where the m = (sP · y) (sD · y), where sP, sD and y denote the slip-plane normal, the slip direction and the strain direction.Primary slip systems are defined as having the largest Schmid factors for the given strain direction, which are calculated as How to cite this article: Pukšič, N. et al. A comparison of the uniaxial deformation of copper and nickel (1 1 19) surfaces: a molecular dynamics study. Sci. Rep.7, 42234; doi: 10.1038/srep42234 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Autosomal recessive juvenile Parkinsonism (ARJP) is an inherited neurodegenerative disease in which 50% of affected individuals harbor mutations in the gene encoding the E3 ligase parkin. Parkin regulates the mitochondrial recycling pathway, which is induced by oxidative stress. In its native state, parkin is auto-inhibited by its N-terminal ubiquitin-like (Ubl) domain, which blocks the binding site for an incoming E2∼ubiquitin conjugate, needed for parkin's ubiquitination activity. Parkin is activated via phosphorylation of Ser-65 in its Ubl domain by PTEN-induced putative kinase 1 (PINK1) and a ubiquitin molecule phosphorylated at a position equivalent to Ser-65 in parkin. Here we have examined the underlying molecular mechanism of phosphorylation of parkin's Ubl domain carrying ARJP-associated substitutions and how altered phosphorylation modulates parkin activation and ubiquitination. We found that three substitutions in the Ubl domain  significantly decrease PINK1's ability to phosphorylate the Ubl domain. We noted that two basic loss-of-function substitutions (R33Q and R42P) are close to acidic patches in the proposed PINK1–parkin interface, indicating that ionic interactions at this site may be important for efficient parkin phosphorylation. Increased auto-ubiquitination with unique ubiquitin chain patterns was observed for two other Ubl domain substitutions (G12R and T55I), suggesting that these substitutions, along with phosphorylation, increase parkin degradation. Moreover, Ubl domain phosphorylation decreased its affinity for the potential effector protein ataxin-3, which edits ubiquitin chain building by parkin. Overall, our work provides a framework for the mechanisms of parkin's loss-of-function, indicating an interplay between ARJP-associated substitutions and phosphorylation of its Ubl domain. Mutations in the gene encoding parkin, an RBR RING1–in-between RING–Rcat RING2) E3 ubiquitin ligase, are the most prevalent cause of autosomal recessive juvenile parkinsonism (ARJP) E3 ubiquThe E3 ligase parkin consists of five distinct domains. The C-terminal region, common to all RBR E3 ligases, consists of a RING1 domain, required for E2-conjugating enzyme recruitment, a required-for-catalysis  domain that houses a catalytic cysteine needed for ubiquitin transfer, and an in-between RING domain that is structurally similar to the Rcat domain but lacks the catalytic site . Parkin Parkin exists in an auto-inhibited state, primarily through association of the Ubl domain with the remainder of the protein, that must be relieved to activate its ubiquitination function . Three-d12–15–21–In addition to acting as an auto-inhibitory module, it is less clear what the downstream roles of the Ubl domain are, especially in its phosphorylated state. The Ubl domain in its phosphorylated state is required for full E3 ligase activation , 24. HowMultiple potential outcomes of parkin ARJP mutations may lead to loss of function , 31. Sub32–35–38–Here we examine how pathogenic mutations in the parkin Ubl domain alter its ability to be phosphorylated by PINK1. We show that phosphorylation of the Ubl domain results in decreased stability of all variants harboring early-onset Parkinson's disease substitutions. Notably, in some cases, these lead to an increase in intrinsic auto-ubiquitination of parkin, a potential signal for degradation. In others, phosphorylation of the Ubl domain is dampened. Together, this work provides important mechanistic insights into the interplay between pathogenic mutations and phosphorylation of the parkin Ubl domain.G12R), P37L (UblP37L), R42P (UblR42P), R33Q (UblR33Q), and T55I (UblT55I), was examined for efficiency of phosphorylation by PINK1, effects on protein stability, alterations in ubiquitination activity, and interaction strength with a proposed partner protein, ataxin-3.The Ubl domain in parkin adopts a classical β-grasp fold comprising four β-strands, a longer α-helix that runs across one side of the β-sheet and a shorter α-helix that precedes Ser-65, the site of PINK1 phosphorylation . In the Pediculus humanus PINK1 was examined. Although Phos-Tag SDS-PAGE can be used to monitor this conversion, we found that this resulted in poor resolution and “laddering” of bands that made quantifying the amounts of each protein difficult, especially for full-length parkin. Instead, we used a pSer-65 parkin-specific antibody and measured fluorescence at 680 nm from the DyLight fluorophore attached to a secondary antibody as a measure of phosphoprotein concentration. This approach was highly reproducible for both the pUbl domain and Ser-65–phosphorylated full-length parkin (pParkin) and produced only negligible background from unphosphorylated versions of these proteins, even at short reaction times (30 s). Time course phosphorylation reactions showed that both proteins could be phosphorylated, but with more than an entire order of magnitude difference in efficiency. Strikingly, the isolated Ubl domain was phosphorylated ∼16-fold faster than the full-length protein, even when 10-fold more PINK1 was used to phosphorylate the full-length parkin , consistent with previous observations for ubiquitin  . These ein vitro . In addibiquitin . These eFig. S1, G12R, UblR33Q, UblP37L, and UblT55I) resulted in small (0.4–1.1 kJ/mol) changes in the overall structural stability of the Ubl domain. These differences were much less detrimental than other Parkinson's substitutions  that cause misfolding of the isolated Ubl domain (I44A). This substitution is frequently used with Ubl proteins because of its central role in protein interactions .Some ARJP substitutions in parkin lead to misfolding of the protein, which can lead to intracellular aggregation and increased turnover –37. This–l domain . For comractions , 44. Unem urea lower than their unphosphorylated versions, translating into about 3 kJ/mol decreased stability upon phosphorylation. Similarly, thermal unfolding experiments showed that all substituted pUbl proteins were about 1.5–2 kJ/mol lower stability in their phosphorylated states . The structure of the pUbl domain  had unfolding midpoints that were ∼1.0 l domain  shows thG12R- and pUblT55I-substituted proteins. Even more striking were the differences in the patterns of auto-ubiquitination between the phosphorylated variants. For example, the pUblG12R and pUblT55I parkin proteins reproducibly formed the bulk of polyubiquitin chains at higher molecular weights (>125 kDa) compared with the WT protein. In contrast, the pUblR33Q and pUblP37L proteins had ubiquitination efficiencies and formed chains with a more finite length (<125 kDa), similar to WT pParkin. These results indicate that phosphorylation of parkin, in combination with some PD substitutions, alters the ubiquitination efficiency and ubiquitin chain pattern.Phosphorylation of the Ubl domain is required for parkin to reach its full E3 ligase activity. To determine how PD substitutions alter the ubiquitination efficiencies upon phosphorylation, we examined the ubiquitination profiles of phosphorylated parkin carrying PD substitutions . All ass15–194–361) as a surrogate Ubl-interacting protein to examine how phosphorylation of the parkin Ubl domain affects its interaction with ataxin-3 and how PD mutations might further modulate this interaction.The parkin Ubl domain may function as a recruitment module for accessory proteins, substrates, or a docking module for ubiquitinated proteins , 9. Furt194–361) was titrated into 15N-labeled Ubl or pUbl domain proteins, and the interactions were monitored by chemical shift changes in the resulting 1H-15N NMR spectra. Titration of ataxin194–361 into the WT Ubl domain showed the largest changes in signals, corresponding to Ile-44, Lys-48, and Glu-49 near the Ile-44 hydrophobic patch; Gln-63, Gln-64, and Ser-65 in the Ser-65 phosphorylation site; and Arg-75 at the C terminus . Fitting of these data resulted in an apparent dissociation constant (dK) between ataxin194–361 and the parkin Ubl domain of dUblK = 187 ± 19 μm, similar to that reported previously . Notably, this was accompanied by negligible chemical shift changes in Gln-63, Gln-64, and pSer-65 and smaller changes to residues such as Lys-48 . Interestingly, the phosphomimetic UblS65E protein  had an affinity (KdS65E = 227 ± 26 μm) and chemical shift changes akin to the WT protein, perhaps highlighting a weaker charge effect than phosphorylation at the Ser-65 site.An identical titration of ataxinP37L and pUblP37L domains were also examined to identify how a Parkinson's disease–substituted parkin combined with phosphorylation might further alter this interaction (B). The UblP37L domain variant was chosen because its stability change upon phosphorylation was similar to the WT protein and it could be phosphorylated in large enough quantities for NMR experiments. NMR titration experiments revealed that the UblP37L domain bound nearly 3-fold tighter to ataxin194–361 (KdP37L = 61 ± 2 μm) than the WT protein. However, upon phosphorylation, the affinity for ataxin194–361 decreased about 4-fold to a value more similar to that for the WT protein lacking phosphorylation (KdpP37L = 231 ± 72 μm). Similar to the pUbl domain, the pUblP37L domain experienced little change in the positions of Gln-63, Gln-64, and pSer-65 compared with the unphosphorylated form in the presence of ataxin194–361. Overall, these data indicate that phosphorylation dampens the Ubl domain interaction with the UIM-containing protein ataxin-3 through loss of interactions with residues near the Ser-65 site.The interactions of ataxin-3 with the Ubleraction B. The UbEarly-onset Parkinson's disease substitutions are found throughout the E3 ligase parkin but appear to be concentrated in two domains: the N-terminal Ubl domain and the C-terminal Rcat (RING2) domain , 10, 49.I44A domain results from its juxtaposition to Insert3 where it contacts Phe-196–Tyr-198 (G12R) might create steric hindrance with the ATP in the active site. Thus, the decreased phosphorylation efficiencies of the Ubl domain carrying ARJP substitutions appear to be a direct reflection of improper recognition by PINK1 that would limit the ATP phosphoryl transfer step and provides a unifying mechanism underlying decreased overall E3 ligase activity.The Ubl domain must be phosphorylated by PINK1, typically under cellular oxidative stress conditions, to reach its full E3 ligase activity. In this work, three ARJP substitutions  showed marked decreases in phosphorylation efficiency, indicating that these substitutions will lead to overall lower E3 ligase activity. To provide a rationale for the decreased phosphorylation efficiency, we modeled the Ubl domain in place of ubiquitin in the recent structure of the PINK1–Ub complex . This mo–Tyr-198 . The decR42P domain is completely unfolded  promotes their degradation via endoplasmic reticulum-associated protein degradation  cells in Luria broth or M9 minimal medium ) and lysed using an EmulsiFlex-C5 homogenizer (Avestin). All proteins were purified by Ni2+-NTA affinity chromatography using a HisTrap FF column on an AKTA FPLC  and cleaved with Ulp1 protease (∼1:50 ratio protease:protein). Following cleavage, proteins were repassed over the HisTrap FF column, collecting the flow-through and applying this to a HiLoad Superdex75 gel filtration column pre-equilibrated in 25 mm HEPES, 100 mm NaCl, and 0.5 mm TCEP (pH 7.0). Proteins for phosphorylation experiments were aliquoted, flash-frozen, and stored at −80 °C until use. Proteins for ubiquitination experiments were used immediately after purification or phosphorylation.All human parkin (1–465) and Ubl domain (1–76) constructs were encoded as His–small ubiquitin–like modifier fusion proteins as described previously . Diseasel medium . For purE. coli BL21(DE3) cells in Luria broth medium. Cells were grown at 37 °C and induced with 0.63 mm isopropyl 1-thio-β-d-galactopyranoside when an A600 of 0.8 was reached. The temperature was then reduced to 16 °C, and cells were allowed to grow overnight. Cells were harvested and resuspended in a lysis buffer ) and lysed using an EmulsiFlex-C5 homogenizer (Avestin). The protein was purified by Ni2+-NTA affinity as described above and eluted with 20 mm NaH2PO4, 20 mm Na2HPO4, 300 mm NaCl, and 250 mm imidazole (pH 8.0). The His tag was cleaved using tobacco etch virus protease during overnight dialysis, and the untagged ataxin-3 protein was purified through reapplication to a Ni2+-NTA affinity column.The C-terminal portion of ataxin-3 (residues 194–361) containing three UIM regions was expressed as a His-tagged protein in P. humanus PINK1 (residues 128–575) was expressed in E. coli BL21(DE3) cells in Luria broth medium. Cells were grown at 37 °C until an A600 of 0.8 was reached, at which point expression was induced with 0.5 mm isopropyl 1-thio-β-d-galactopyranoside, and the incubation temperature was lowered to 16 °C for 18 h. Expressed proteins were purified on a GSTrap FF column  in lysis buffer ) and eluted with freshly prepared elution buffer ). Following elution, GSH was removed from PINK1 by two 2L dialysis changes against 50 mm Tris, 50 mm NaCl, and 3 mm DTT (pH 10), followed by a final 2L dialysis against 50 mm Tris, 50 mm NaCl, and 3 mm DTT (pH 7.5).GST-tagged m Tris, 100 mm NaCl, and 0.5 mm EDTA (pH 7.4)) was expressed and purified as described previously. The purified protein was modified with 5 mm Dylite800 (dissolved in 100% isopropanol) for 1 h and quenched with 5 mm DTT. Excess Dylite800 label was removed using a HiLoad Superdex75 gel filtration column. Aliquots of Dylite800-labeled ubiquitin (Ub800) were flash-frozen and stored at −80 °C until needed.Ubiquitin with an N-terminal cysteine  were diluted in 50 mm Tris, 50 mm NaCl, and 3 mm DTT (pH 7.5) to obtain a PINK1:parkin ratio of 1:2 (parkin) or 1:20 (Ubl domain) in a total volume of 200 μl. Phosphorylation reactions were initiated by addition of 20 mm MgCl2 and 10 mm ATP (pH 7.5) and allowed to proceed at 25 °C. At specified time intervals, aliquots (10 μl) were quenched with 3× SDS loading buffer (containing 100 mm EDTA) and boiled at 95 °C for 5 min. Samples were then analyzed by SDS-PAGE, and unstained gels were processed using a shared nitrocellulose membrane (0.2-μm pore size) using a semidry iBlot2 apparatus (Invitrogen). Membranes were rinsed with water and blocked with 10× BSA (Pierce) in TBS for 1 h at room temperature. A final rinse with TBS + 10% aqueous Tween 20 (TBST) was used prior to incubation with primary antibody  overnight at 4 °C. Following this, membranes were rinsed with three to four washes of TBST, incubated with a fluorescent secondary antibody  for 45 min, and washed again three times with TBST. Membranes were scanned by an Odyssey Imaging system (LiCor), and fluorescence intensity was measured at 700 nm.For phosphorylation time course experiments, purified GST-PINK1 was used to phosphorylate all parkin and Ubl domain variants. Proteins . The formation of pParkin can be described chemically as a second-order rate equation. Because the concentration of ATP is present at a 10,000-fold excess and largely unchanged over the reaction, analysis of the data was simplified to a pseudo-first-order equation that yielded the rate of formation of pParkin as a function of time.m KH2PO4 (pH 7.0) and 4 °C to remove chloride ions. Protein concentrations were determined by measuring the absorbance at 280 nm using a nanodrop instrument (DeNovix). A series of samples containing 0–6.5 M urea was prepared by diluting equivalent amounts of the desired protein into buffer and adding the appropriate amount of 10 m urea. Samples were incubated overnight at 4 °C. Chemical denaturation experiments were performed in duplicate using a JASCO J-810 CD spectropolarimeter equipped with a Peltier temperature control. Data points were collected as an average of five replicate scans using a 1-mm path length cuvette at 5 °C. The resulting CD ellipticity at 218 nm (Yobs) was plotted as a function of urea concentration [D] and fit based on a two-state unfolding transition between folded (F) and unfolded (U) forms of the protein (GuH2O) between folded and unfolded proteins and the slope of the unfolding transition (m) were determined as described previously (fY) and following (uY) the unfolding transition were accounted for in all fittings.Purified protein samples were dialyzed against three changes of 20 m protein –3. The feviously , 38, 60 50%) of each curve were used, and the difference in stability (ΔΔGuD50%) was calculated from m̄ is the average slope for the two proteins.To compare the stabilities between nonphosphorylated and phosphorylated proteins, the midpoints (DuG) between nonphosphorylated and phosphorylated proteins based on H(non) and mT(non) are the enthalpy and unfolding midpoint for the nonphosphorylated protein, and ΔmT is the difference in unfolding temperature between nonphosphorylated and phosphorylated proteins ΔΔGu15N-labeled Ubl domain with the appropriate amount of ataxin-3 and NMR buffer , and 10% (v/v) D2O). An internal reference of 200 μm 2,2-dimethyl-2-silapentanesulfonic acid was used, and 300 μm of imidazole was used as an internal pH indicator. The NMR data were collected using a Varian Inova 600-MHz NMR spectrometer. Data were processed using NMRPipe and analyzed using NMRViewJ. Dissociation constants (dK) were calculated by manually recording the 1H or 15N chemical shift for each residue after ataxin194–361 titration and subtracting the original chemical shift. These Δδ values were plotted against the total added [ataxin194–361], and all curves were globally fit for a single dK using GraphPad Prism with tP is the Ubl domain concentration, L is the ataxin194–361 concentration, and Δδ is the calculated change in chemical shift.A series of NMR samples was prepared by diluting the m Ub, 0.5 μm pUb, 0.5 μm Ub800, 0.5 μm UbcH7, 0.1 μm Uba1, 5 mm MgATP, 50 mm HEPES (pH 7.5), and 1 μm WT or substituted parkin and pParkin. Reactions were quenched at 0, 15, and 30 min using 3× SDS sample buffer and 1 m TCEP. Gradient gels  were used with MES running buffer ). Gels were scanned by the Odyssey Imaging system (LiCor), and fluorescence intensity was measured at 700 nm and 800 nm.Reactions were completed using 4 μJ. D. A., K. M. D., and G. S. S. conceptualization; J. D. A., K. M. D., R. L., and M. R. data curation; J. D. A., K. M. D., R. L., and G. S. S. formal analysis; J. D. A. and K. M. D. investigation; J. D. A., K. M. D., and R. L. methodology; J. D. A., K. M. D., and R. L. writing-original draft; J. D. A., K. M. D., and G. S. S. writing-review and editing; G. S. S. supervision; G. S. S. funding acquisition; G. S. S. validation.


We show that the MAM domain of NRP1 is monomeric in solution and insufficient to drive receptor dimerization, which leads us to propose a different role for this domain in the context of NRP membrane assembly and signaling.Neuropilins (NRPs) are single-pass transmembrane receptors involved in several signaling pathways that regulate key physiological processes such as vascular morphogenesis and axon guidance. The MAM domain of NRP, which has previously been implicated in receptor multimerization, was the only portion of the ectopic domain of the NRPs for which the structure, until now, has been elusive. Using site-directed mutagenesis in the linker region preceding the MAM domain we generated a protein construct amenable to crystallization. Here we present the crystal structure of the MAM domain of human NRP1 at 2.24 Å resolution. The protein exhibits a jellyroll topology, with Ca  •Structural description of the MAM domain of neuropilin-1•2+-binding site stabilizing the jellyroll foldThe structure includes a Ca•The MAM domain of neuropilin-1 is monomeric•MAM domains engage context-specific surfaces for interaction with other proteins 2+ ion while forming a molecular surface that is distinct from its structural homologs.Yelland and Djordjevic complete the structural description of the neuropilin-1 ectopic region by reporting the crystal structure of its MAM domain. The domain adopts a jellyroll fold that is stabilized by a Ca Neuropilins (NRPs) are single-pass transmembrane receptor proteins with a pivotal role in key physiological processes such as vasculogenesis, angiogenesis, axonal guidance, and immunomodulation . In addia1, at the N terminus, then a2, b1, b2, and c, followed by a single transmembrane helix and a short cytoplasmic tail. Several research groups investigated the detailed atomic structure of the first four extracellular domains, as well as their interaction with biological or synthetic ligands   and sema ligands . It has aphorins . NRP dom1 domain .c domain of NRPs is also called the MAM domain (referred to as such in the rest of the text) based on its sequence homology to the equivalent domains in meprin, A5, and mu-phosphatase (RPTPmu)  . While t(RPTPmu) . Namely,(RPTPmu) .We were able to generate a protein variant amenable to crystallization and we now report the first crystal structure of the MAM domain from NRPs, thus completing the structural characterization of the ectodomain of this receptor family. The crystal structure confirms that the domain shares an overall topology with the homologous domain of RPTPmu; however, we see no evidence that the NRP1 MAM domain forms biologically relevant dimers. This observation is also corroborated by the solution studies of the protein. We propose that while the MAM domain on its own is not sufficient to support multimerization of NRP molecules it might contribute to the assembly and regulation of the signaling complexes either by positioning the other extracellular domains of NRPs away from the membrane, and in an orientation suitable for protein/protein interaction, or via glycan-mediated interaction of the MAM domain with other proteins of the extracellular matrix.We have previously determined that the specific serine and threonine residues upstream of the predicted MAM domain of NRP1 are glycosylated , produci2+ and Mg2+, increased protein thermal stability by ∼10°C , and an adjacent eight-stranded β barrel organized in a jellyroll topology, with the strands named B-I, followed by the short α-helical turn at the C terminus , which calculated the largest interface between MAM monomers to cover 564 Å2 and with a complexation significance score  of 0.0. Therefore the observed dimer in the asymmetric unit is possibly a crystallographic artifact of no physiological relevance. In contrast to the meprin MAM domain . This geometry is consistent with a calcium-binding site based on the surveys of deposited crystal structures   (Overlaying the MAM domain structure from RPTPmu (PDB: to NRP1)  and meprto NRP1)  to that to NRP1) B. The β to NRP1) .This conclusion is reinforced by the analysis of the MAM domain structures which revealed a highly hydrophobic core spanning the entire length of the fold. In NRP1 the aromatic residues F652, W673, F692, F724, Y726, W753, W763, and F781 are arranged in a coordinated manner to optimize π-stacking interactions between the aromatic side chains C. In the2+ ion. Despite the conserved central β structure, connecting loops are very different in both amino acid composition and the length. Even when the surface loops of equivalent lengths are considered, such as the loop connecting βE to βF, the 3D positions of the equivalent Cα residues are up to 7 Å apart, thus creating a distinct molecular surface for each of the proteins.Further analysis of sequence conservation between the three proteins reveals that, apart from the residues contributing to the hydrophobic core there is only one sequence stretch of significant homology, spanning NRP1 residues G791 to I800. Interestingly, this area includes the key residue (D796) contributing to the binding of the CaDifferences in the structures of the loop regions give rise to the significantly different molecular surfaces of the various MAM domains A. Compar2C9A) (2V5Y)  , and as ) (2V5Y) , indicat) (2V5Y) . Further) (2V5Y) . In NRPsEven though it had been postulated that the MAM domain of NRP1 would be engaged in homo- and hetero-dimerization, the evidence for this hypothesis is weak, relying mostly on cell-based experiments with NRP1 variants where individual domains have been deleted . Using sa1a2b1b2) for their interaction with partner co-receptors. Alternatively, it may serve to modulate signaling and multimerization events through interactions with other binding partners, such as galectins (GALs). It has been shown that GAL-1 , was purchased from Life Technologies. In this expression construct, the codons corresponding to residues T629, T633, S637, T638, S641, and T645 were replaced with the codons for aspartate. The mutated residues removed the O-linked glycosylation sites to produce a homogeneous protein sample suitable for crystallization. The protein was cloned in frame with the Ig K-chain leader so that the MAM domain was exported through the native secretory pathway. A non-cleavable (His)6 cells/mL was performed using 1.25 mg of DNA and 1.87 mg of polyethylenimine (Sigma) in 40 mL of OptiPro (Life Technologies) supplemented with 4 mM L-glutamine (Sigma). Cells were incubated at 37°C, shook at 125 rpm for 4 days before being harvested by centrifugation at 1,000 × g for 10 min. The supernatant was filtered and loaded onto a 1 mL Ni2+-ion affinity HisTrap column . The column was washed with 10 column volumes of a buffer containing 20 mM Tris (pH 8.0) and 100 mM NaCl before the elution step with 5 column volumes of the buffer containing an additional 300 mM imidazole. The protein was further purified by size-exclusion chromatography on a Superdex S200 10/300 GL column . All protein concentrations were estimated based on absorbance at 280 nm.All large-scale expression protocols were carried out as follows: transfection of the 1 L cultures of FreeStyle HEK293-F cells (Thermo Fisher Scientific) at a density of 1.0–1.4 × 102 to a final concentration of 10 mM. Crystallization screening was performed using a mosquito (TTP Labtech) and a sparse matrix kit from Hampton Research (Index), Molecular Dimensions , and QIAGEN (PEGS II). Rod-shaped crystals (∼100 μM in length) grew at 16°C, in a solution containing 0.06 M MgCl2, 0.06 M CaCl2, 0.1 M Tris (base), 0.1 M bicine (pH 8.0), 12.5% MPD, 12.5% PEG 1000 and 12.5% (w/v) PEG 3350. The crystals were flash frozen directly in liquid nitrogen prior to data collection.Purified ngMAM protein was concentrated to 15 mg/mL using centrifugal concentrators  before adding CaCl2C9A, residues 21–177) was used . We were unable to obtain the solution until the following loop and flexible regions were omitted: residues 21–36, 51–67, 89–95, 106–108, 121–125, 147–154; the side chains of the remaining residues were cut to Cβ using Chainsaw (http://www.pymol.org).Diffraction data were collected at Diamond Light Source, beamline I04. Data were processed using Xia2  and reinChainsaw . The strChainsaw  and a reChainsaw . All figMAM domain dissociation experiments were performed using a MicroCal iTC200  instrument. The sample cell was filled with buffer  and the syringe contained 900 μM of the MAM domain in an identical buffer solution. The MAM domain solution was then titrated into the buffer with one 0.4 μL injection that was followed by 19 injections of 2 μL. The experiments were performed at 15°C and 20°C with a stirring rate of 1,000 rpm.Each well in a 96-well plate contained SYPRO orange (Sigma-Aldrich) at a final 1× concentration, 5 μM of the ngMAM domain, a 2 μL solution from a single condition from the Hampton Research crystallographic additive screen and a buffer  up to a total volume of 20 μL. The plate was placed in a LightCycler 480 II (Roche) and the samples were heated from 10°C to 90°C at a rate of 5°C per min. Fluorescence was monitored at 570 nm.https://salilab.org/modeller/tutorial/).Generation of the NRP2 MAM domain model structure was performed using MODELLER v9.16  and usinT.Y. and S.D. designed the experimental approaches. T.Y. carried out the experiments. S.D. supervised the work and assisted with data analysis. T.Y. and S.D. wrote the manuscript.


Pediococcus pentosaceus, Saccharomyces cerevisiae, Pantoea agglomerans, and Escherichia hermannii) were inoculated in doughs prepared with irradiated flour (gamma rays at 10 kGy), so that eight different microbial assemblies were obtained. Two non-inoculated controls were prepared, one of which (C-IF) using irradiated flour and the other (C) using non-irradiated flour. As shown by plate counts, irradiation of flour caused total inactivation of yeasts and a decrease of all the other microbial populations. However, acidification occurred also in the dough C-IF, due to metabolic activity of P. pentosaceus that had survived irradiation. After six fermentations, P. pentosaceus was the dominant lactic acid bacterium species in all the sourdoughs produced with irradiated flour (IF). Yet, IF-based sourdoughs broadly differed from each other in terms of strains of P. pentosaceus, probably due to the different microorganisms initially inoculated. Quantitative and qualitative differences of free amino acids concentration were found among the sourdoughs, possibly because of different microbial communities. In addition, as shown by culture-independent analysis (16S metagenetics), irradiation of flour lowered and modified microbial diversity of sourdough ecosystem.This work aimed to investigate whether different microbial assemblies in flour may influence the microbiological and biochemical characteristics of traditional sourdough. To reach this purpose, members of lactic acid bacteria, enterobacteria, and yeasts were isolated from durum wheat flour. Secondly, the isolated microorganisms ( Sourdough positively influences the sensory, nutritional, textural, and shelf-life features of leavened baked goods  and lactic acid bacteria (LAB). After fermentation, the dough is used as inoculum for fermenting newly prepared dough, which, in turn, will be used as inoculum for a subsequent step of fermentation  and Firmicutes  phyla  specific technology parameters; (ii) house microbiota; and (iii) flour . The gross composition was as follows: Moisture, 14.9%; protein (N × 5.7), 12.2%; total carbohydrates, 71.1% ; fat, 1.7%. Flour (5 kg) in paper bags was placed in a cardboard box and exposed to 60Co γ-ray source at Gammatom s.r.l. . Samples were irradiated with a dose of 10 kGy. Non-irradiated flour was used as the control.The alpha-amylase activity of the flour, before and after irradiation, was estimated through determination of the falling number. Falling number was determined in triplicate according to AACCI method 56-81.03 AACC, .−1 and NaCl 8.5 g l−1) solution  plates containing the highest dilutions of flour, transferred into the corresponding broth media and re-streaked until pure cultures were obtained.Five colonies of presumptive yeasts were picked up from the Sabouraud Dextrose agar plate containing the highest dilutions of flour, sub-cultured in the corresponding broth medium and re-streaked onto the same agar medium. All the isolates could ferment galactose, sucrose, maltose, and raffinose and could grow at 37°C.Enterobacteriaceae were picked up from the VRBGA plate containing the highest dilutions of flour, sub-cultured in Tryptone Soy broth and re-streaked onto Tryptone Soy agar.Twenty colonies of presumptive 16S rRNA and 26S rRNA genes, respectively. In detail, genomic DNA was extracted from bacteria using DNeasy Blood and Tissue Kit , according to the manufacturer's instructions . Pair-wise sequence alignments were carried out using the BLAST search in the NCBI Nucleotide Collection Database  of the above strains were centrifuged (4528 × g for 5 min at 4°C). The harvested cells were washed twice with sterile saline (NaCl 9 g l−1) solution and singly re-suspended, to a final cell density in the range 2–3 log cfu g−1, in the tap water used for preparing the initial dough  blender. After incubation (at 25°C for 30 min under stirring), the water-soluble extract was obtained by centrifugation . Maltose, glucose, fructose, lactic acid, acetic acid, and ethanol were determined in the water-soluble extract of sourdoughs by High Performance Liquid Chromatography (HPLC) -PCR using primers P4, P7   merging together the forward and reverse reads using the PEAR Illumina paired-end read merger . Principal Component Analysis (PCA) was also performed using Statistica 7.0.Data (at least three replicates) of pH, lactic acid, acetic acid, ethanol, carbohydrates, FAA, and cell density of presumptive LAB and yeasts were subjected to one-way ANOVA, and pair-comparison of treatment means was achieved by Tukey's procedure at PRJNA318402.The sequence data were submitted to the sequence read archive of NCBI database and the corresponding accession no. is Enterobacteriaceae , Pseudomonas sp. and yeasts were found at lower cell density. Enterococci, staphylococci and acetic acid bacteria were not detected. Irradiation of flour resulted in a reduction (from two to four log cycles) of all the microbial populations. Overall, bacteria were found at cell density lower than 1 log cfu g−1, whereas yeasts were not detected in 10 g of flour. No colonies (presumptive spore-formers) were detected in PCA plates inoculated with irradiated flour (IF) serially diluted and subjected to heat treatment (data not shown). The alpha-amylase activity of IF was significantly higher than flour prior to irradiation (272 ± 10 vs. 367 ± 15 s).As shown by plate counts, durum wheat flour was contaminated especially by presumptive e Figure . LAB, “fIF was used to prepare and propagate doughs inoculated  or not (C-IF) with one or more microorganisms isolated from flour before irradiation. The different microbial combinations for inoculating doughs were chosen on the basis of the dominating microorganisms isolated from non-irradiated flour. A control sourdough (C) was prepared by using non-irradiated flour in both the first fermentation and the consecutive back-slopping steps. Compared to C-IF and C sourdoughs, dough acidification was faster in all the inoculated doughs already after the first back-slopping (Supplementary Table Slight volume increase (2–5 ml) was found after the first back-slopping only for doughs D6-IF, D7-IF, D8-IF, and C doughs  to ca. 9.3 (D7-IF and C sourdoughs) log cfu g−1 (P > 0.05)  were found when cell density of LAB was estimated on MRS. Cell density of yeasts was below 1.0 log cfu g−1 for the D1-IF, D3-IF, D5-IF, C-IF, and C sourdoughs. For the remaining sourdoughs, this parameter ranged from ca. 2.8 (D7-IF) to ca. 7.4 (D2-IF) log cfu g−1.During propagation of sourdoughs, cell densities of LAB increased in all the doughs  showed the largest variation  to ca. 4.50 (C-IF sourdough) Table . The conP. pentosaceus A1) was included in the dendrogram, showing that no P. pentosaceus isolated from sourdoughs showed the same profile as A1. At 40% of similarity, strains were grouped in six clusters (I–VI), with two unclustered. Clusters I and II exclusively grouped all the strains isolated from the sourdough produced by using non-irradiated flour (C). The largest cluster (IV) grouped strains isolated from different sourdoughs produced by using IF. The C sourdough was characterized by the highest number of strains (13), whereas the others harbored from one to five strains. P. pentosaceus was identified in all the mature sourdoughs. Lactobacillus curvatus was found as dominant and sub-dominant species in the C and D4-IF sourdoughs, respectively  shared the same profiles as thirteen, three, and fifteen isolates from the sourdoughs D3-IF, D7-IF, and D8-IF, respectively.Microbial cultures isolated from mature sourdoughs are listed in Supplementary Table y Figure . P. pentS. cerevisiae, were grouped in two clusters (I–II), with two strains unclustered. Overall, the clustering of the strains was not related to the sourdough of origin. D8-IF10 shared the same RAPD profiles with three, five, and four isolates from D4-IF, D6-IF, and D7-IF sourdoughs (Supplementary Table S. cerevisiae SDA1) (data not shown).As regards yeasts, the combined RAPD profiles were subjected to cluster analysis, which revealed that similarity among strains ranged from ca. 41 to 90% Figure . At 70% 16S rRNA gene amplicons were obtained. Except for the dough C-IF after the first fermentation, which was characterized by the lowest number of reads (ca. 7000), the number of sequences per sample was higher than 25,000. The average length of the sequences was 383 bp. The highest (P <0.05) number of OTU and values of α-diversity indexes were found for the doughs after the first fermentation (C-IF-1st and C-1st) . As expected, upon continuous back-slopping, Firmicutes became dominant (> 99.6%) in the C-IF and C sourdoughs, as well as in all the others (data not shown). The relative abundance at the highest possible taxonomic level (species/genus/family/class) is shown in Figure Oscillatoriales (class) was the OTU found at the highest relative abundance (50.4%), followed by Pseudomonas sp. (12.1%), and P. pentosaceus (8.2%). On the contrary, the bacterial community of the dough prepared with non-irradiated flour was dominated, after the first fermentation, by Enterobacter sp. (82.6%). Pantoea sp. was detected in this dough as subdominant OTU (11.3%). The bacterial community of mature sourdoughs was dominated (> 95.2%) by P. pentosaceus, regardless of the use of IF and microbial inoculation. Only the C sourdough harbored L. curvatus and Lactobacillus johnsonii as minor OTUs with relative abundance of 1.6 and 1.4%, respectively.Doughs C-IF-1st and C-1st analyzed after the first fermentation were dominated by L. curvatus or P. pentosaceus) and biochemical characteristics  of sourdoughs clearly differentiated the two control sourdoughs (C and C-IF) from each other and from the inoculated sourdoughs  sharing S. cerevisiae SDA1 among the inoculated microorganisms were grouped in the III quadrant, because of their highest leavening capacity and yeast cell density. D1-IF, D3-IF, D5-IF, and D7-IF sourdoughs, characterized by highest concentration of glucose, maltose, arg, and tyr, were grouped in the I quadrant. Among the highest positive variable correlations, concentrations of ala and lys were correlated with L. curvatus . Residual maltose was negatively correlated with ΔV (r = −0.95) and ethanol (r = −0.96).PCA based on the microbiota  irradiation treatments  had higher yeast cell density than all the others, which allowed dough leavening. These sourdoughs also showed the lowest concentrations of residual glucose and maltose. This could be due to the preference by S. cerevisiae toward glucose and maltose  in the total aerobic counts upon similar treatment was reported by other authors  showed that irradiation had massively inactivated contaminating bacteria, as indicated by the relatively low number of reads. Irradiation also modified bacterial diversity. Indeed, C-IF-1st and non-inoculated, non-irradiated flour-based dough after the first fermentation (C-1st) shared only two (Erwinia sp. and Pantoea sp.) out of 16 (C-IF-1st) and 7 (C-1st) most representative OTUs.Overall, the results of 16S metagenetic analysis were in agreement with those from the culture-dependent analysis, except for the C sourdough, whose bacterial microbiota seemed to be dominated by P. pentosaceus strains were able to recover from irradiation damage and to dominate sourdough. Future studies on microbial assembly of sourdough should take into account: (i) the need for minimizing the influence of bacteria resistant to irradiation; (ii) additional combinations of microorganisms ; and (iii) repeated low level inoculation at each fermentation step.In conclusion, this work showed that the initial inoculation of dough ecosystem with different combinations of flour autochthonous microorganisms affected the sourdough microbial community in terms of strains of LAB. This, in turn, influenced the profile and concentration of FAA in sourdough. In addition, irradiation of flour at 10 kGy lowered and modified microbial diversity of sourdough ecosystem, but flour autochthonous GC carried out the experiments, MD discussed the results and wrote the manuscript, FM directed the experimental phases and wrote the manuscript, MG ideated the study and made funds available for the research costs.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.