Pericentrin

After processing raw files with the in house–developed software MaxQuant (version 1.0.12.36 or 1.0.13.12; Cox and Mann, 2008 (link)), data were searched against the human database concatenated with reversed copies of all sequences (Peng et al., 2003 (link)) and supplemented with frequently observed contaminants (porcine trypsin, achromobacter lyticus lysyl endopeptidase, and human keratins) using MASCOT (version 2.2.0; Matrix Science). For the analysis of pericentrin experiments, the mouse pericentrin sequence was added to the database. Carbamidomethylated cysteins were set as fixed, oxidation of methionine, and N-terminal acetylation as variable modification. Mass deviation of 0.5 D was set as maximum allowed for MS/MS peaks, and a maximum of two missed cleavages were allowed. Maximum false discovery rates (FDRs) were set to 0.01 both on peptide and protein levels. Minimum required peptide length was six amino acids.
Quantification of proteins in SILAC experiments was performed using MaxQuant (Cox and Mann, 2008 (link)). Methionine oxidations and acetylation of protein N termini were specified as variable modifications and carbamidomethylation as fixed modification. Maximum peptide charge was set to 6. SILAC settings were adjusted to doublets, and Lys0 and Lys8 were selected as light and heavy label, respectively. Peptide and protein FDRs were set to 0.01. The maximum PEP was set to 1, and six amino acids were required as minimum peptide length. Only proteins with at least two peptides (thereof one uniquely assignable to the respective protein group) were considered as reliably identified. Unique and razor peptides were considered for quantification with a minimum ratio count of 2. Forward and reverse experiments were analyzed together and specified as QUBICH and QUBICL in the experimentalDesign.txt. Ratios of the reverse experiment QUBICL were inverted. Specific interaction partners in SILAC experiments were determined by a combination of ratio and ratio significance calculated by MaxQuant. The p-value for the significance of enrichment had to be <0.01 in both the forward and reverse experiment. The provided R script QUBIC-SILAC.R was used to plot all identified proteins according to their ratios in the forward and reverse experiment and mark specific interaction partners (http://www.r-project.org).
Label-free quantification was performed with MaxQuant (see Supplemental data). Methionine oxidations and acetylation of protein N termini were specified as variable modifications and carbamidomethylation as fixed modification. Maximum peptide charge was set to 6. SILAC settings were set to singlets. Peptide and protein FDRs were set to 0.01. The maximum PEP was set to 1, and six amino acids were required as minimum peptide length. Only proteins with at least two peptides (thereof one uniquely assignable to the respective protein group) were considered as reliably identified. Label-free protein quantification was switched on, and unique and razor peptides were considered for quantification with a minimum ratio count of 1. Retention times were recalibrated based on the built-in nonlinear time-rescaling algorithm. MS/MS identifications were transferred between LC-MS/MS runs with the “Match between runs” option in which the maximal retention time window was set to 2 min. The quantification is based on the extracted ion current and is taking the whole three-dimensional isotope pattern into account. At least two quantitation events were required for a quantifiable protein. Every single experiment/raw file was annotated as a separate experiment in experimentalDesign.txt. Control experiments were named Control1, Control2, and Control3. Pull-downs were named with the specific bait name and the replicate number. Identification of specific interaction partners was determined using the MaxQuant-based program QUBICvalidator. The proteinGroups.txt file was loaded (Load – Generic), and a group file template, Groups.txt, was generated (Processing – Groups – Write group file template). Replicates were grouped using one unique name in Groups.txt. The file was then loaded into QUBICvalidator (Processing – Groups – Load groups). Subsequently, results were cleaned for reverse hits and contaminants (Processing – Filter – Filter category – Reverse = + and Contaminant = +). Positive intensity values were logarithmized (Processing – Transformation – LOG – Log2). Signals that were originally zero were imputed with random numbers from a normal distribution, whose mean and standard deviation were chosen to best simulate low abundance values below the noise level (Processing – Imputation – Replace missing values by normal distribution – Width = 0.3; Shift = 1.8). Significant interactors were determined by a volcano plot-based strategy, combining t test p-values with ratio information. The standard equal group variance t test was applied (Processing – Testing – Two groups). Significance lines in the volcano plot corresponding to a given FDR were determined by a permutation-based method (Tusher et al., 2001 (link)). The pull-down was selected as Group1 and the control as Group2. Threshold values (= FDR) were selected between 0.1 and 0.001 and SO values (= curve bend) between 0.5 and 2.0. The resulting table was then exported (Export – Tab separated). The second tab (Table S1 and Table S2) was selected, and values saved with the same file name were supplemented with “_sup” (e.g., Exp.txt → Exp_sup.txt). Results were then plotted using the open source statistical software R and the provided script QUBIC-LABELFREE.R. In the beginning of the script, Exp.txt and Exp_sup.txt have to be replaced with the real file names. Dynamic experiments were plotted using the script QUBIC-LABELFREE_dynamic.R. Significant TREX and TACC3 interactors were clustered using Genesis (Sturn et al., 2002 (link)).
A detailed step by step protocol and the raw data and programs associated with this manuscript may be downloaded from https://proteomecommons.org/tranche, launching Tranche, choosing “Open By Hash”, and entering the following hash: iNYsECWFuN0KDV0Q8QoE3uXxRGuBiCo5+iwydOM7h29jlyPv+Xv4+1piRkFr+mcnsy+eErYIvmcRQf9ZU/l5lxQYNQYAAAAAAABFCA==

Conjugates between NK cells and target cells at a 2:1 ratio were formed in suspension for 15 min and adhered to poly–l-lysine–coated glass slides (Polyprep; Sigma-Aldrich) for 15 min, all at 37°C, as previously described (10 (link)). In experiments evaluating NK cell activation without target cells, poly–l-lysine–coated glass slides were coated with IgG MOPC21 as a control, or anti-CD28, or anti-NKp30 by overnight incubation with 5 μg/ml of antibody in PBS. Slides were washed, and NK cells were incubated on the slide in media for 30 min at 37°C, after which nonadherent cells were rinsed. In either case, cells adhering to the slide were fixed and permeabilized with 4% formaldehyde, 0.1% saponin, and 0.1% Triton X-100 in PBS for 15 min, rinsed, and incubated for 1 h with anti-CIP4 mAb or nonspecific IgG clone MOPC21 (as a control). Slides were rinsed, incubated for 1 h with Alexa Fluor 647–conjugated highly cross-adsorbed goat anti–mouse (Invitrogen), rinsed again, and incubated with 10% heat-inactivated mouse serum (Sigma-Aldrich) for 30 min to block nonspecific binding. Slides were rinsed and incubated with biotinylated anti–α-tubulin mAb (Invitrogen) or biotinylated mouse IgG control (BD Biosciences) for 1 h, followed by additional rinsing and incubation with streptavidin-conjugated Pacific blue 405 (Invitrogen) and Alexa Fluor 568–conjugated phalloidin (Invitrogen). Slides were rinsed and covered with 0.15-mm glass coverslips (VWR Scientific) using Prolong Antifade reagent (Invitrogen) or Vectashield with DAPI . Other antibodies used for microscopy, where specified in the figures, include pAb rabbit anti–α-tubulin (Abcam), pAb antipericentrin (Abcam), Alexa Fluor 568–conjugated anti–rabbit IgG (Invitrogen), FITC anti–rabbit IgG (Jackson ImmunoResearch Laboratories), FITC anti–mouse IgG (Jackson ImmunoResearch Laboratories), and mAb FITC antiperforin (Becton Dickenson). All antibodies were used in the range of 1–20 μg/ml and were diluted in saponin-containing buffer. For each experiment, cells stained with individual fluorophores and controls for individual fluorophores were included as controls to allow for proper spectral separation and/or adjustment of the microscope.
Cell conjugates were visualized by using either a laser scanning confocal microscope (DMIRE2; Leica) or a spinning-disc confocal microscope (IX81 DSU; Olympus) via scanning through the x-y plane. Detection settings were adjusted so that a control-stained sample was uniformly negative and experimentally stained samples were not saturating or bleeding into other channels. The effector and target cells in the conjugate were confirmed either by size (for ex vivo NK cells) or by the presence or absence of GFP expression. The area of accumulation of fluorescent molecules in the NK cell was examined using the threshold of ≥40% of unaccumulated fluorescence intensity for evaluations of CD2 or F-actin (a number based on previously applied assumptions) (10 (link), 28 (link)). Accumulation of CD2 or F-actin at the IS consisted of an increased area of accumulated CD2 or F-actin at the IS relative to other cell-surface or cortical regions. Accumulated areas of CIP4, α-tubulin, and pericentrin were identified using the same threshold approach but were often not found at the IS or in the cell cortex. To determine the area occupied by an accumulated fluorescence intensity and colocalization between areas of different fluorescence, images were analyzed using the Volocity software package classification module (Improvision). The area occupied by each accumulated fluorophore only in the effector cell was measured. Areas containing two accumulated fluorophores were also measured and compared with the area occupied by the single fluorophore to calculate the percentage colocalization. The MTOC was defined either as the accumulated area of α-tubulin using a pixel-size threshold, to eliminate measurement of isolated microtubules, or as the accumulated area of the centrosomal protein pericentrin. As an alternative approach to evaluating colocalization with the MTOC, fluorescence intensities of the individual pixels that were over background levels in a 5-μm² region enclosing the MTOC were measured in some experiments, as noted in the figures. In experiments evaluating NK cell activation by a coated glass surface, scanning was performed using the Leica microscope scanning in the x-z plane to completely visualize the interface with the glass, and analysis was performed as for the conjugates. Polarization of the MTOC to the IS was defined as either there being at least some degree of colocalization of the α-tubulin–defined fluorescent region with cell-surface CD2, or cortical F-actin at the contact site with the target cell, or having some contact with the glass surface in x-z experiments. The shortest distance from the centroid of the accumulated fluorescence and the cell membrane (identified via differential interference contrast [DIC] microscopy) or the edge of the nucleus (identified via DAPI staining) was also measured using Volocity in some experiments to further define and evaluate polarization. In experiments using siRNA-transfected YTS cells, perforin was visualized using FITC-conjugated mouse anti–human perforin clone 27–35 (BD Biosciences) to identify the effector cell in conjugates formed between YTS and KT86 cells.

Spindle angle in metaphase cells were stained for pericentrin and DAPI to visualize the spindle poles, the lumen outer limit and chromatin, was calculated using ImageJ software (http://rsb.info.nih.gov/ij/, NIH, USA). The images were captured with a Leica DMI6000 confocal optical microscope (TCS SPE) equipped with a 63x oil-immersion objective controlled by LAS X software. Z-stack steps were of 0.64μm. For hiPSCs, the angle between the pole-pole axis and the substratum plane was calculated. Using imageJ software, a line crossing both spindle poles was drawn on the Z projection pictures and repositioned along the Z-axis using the stack of Z-sections. For R-NSCs, one line crossing both spindle poles and the tangent of the lumen outer limit were drawn on the Z projection pictures to determine the angle. Lumen area was calculated using Z-projection images. The outer boundary of the lumen was manually traced using pericentrin staining, and the perimeter was measured using ImageJ software. For mitosis counting, Z-projection images were employed to count the number of round DAPI-positive nuclei and cells in M-phase, characterized by condensed DAPI + chromosomes within rosette structures.