The protocol to produce lipid–arrays was developed from Kanter et al (2006)
. Briefly, 1 mM solutions of lipids were prepared in adequate solvent mixtures. Using an argon flow, 0.1 μl of each lipid was sprayed on a nitrocellulose membrane (Hybond-C Extra, GE Healthcare) with an ATS4S spotter (CAMAG). We also spotted a nitrobenzoxadiazole-labeled phosphatidylglycerol (Sigma) at different positions on the array and monitored the quality of the spotting procedure by scanning at 432 nm excitation (GenePix 4000B, Molecular Devices). The three different solvent mixtures used (chloroform, chloroform:methanol 1:1 and chloroform:methanol:water–HCl 1:1:0.2) were also sprayed as blank controls. All the samples were spotted in duplicate. The arrays were stored at 4°C under argon atmosphere and protected from light.
Lipid overlay assay
The S. cerevisiae
strains expressing the desired TAP-tagged protein were grown at 30°C to an OD600
of 3.5–3.8. Pelleted cells were disrupted by glass beads beating. Cell extracts were obtained by a 30 min centrifugation at 22 000 r.p.m. at 4°C and filtration (HPF Millex®
—0.45 μm). The lipid overlay assay was adapted from Dowler et al (2000)
. The arrays were blocked for 1 h in 2 ml of blocking buffer (3% fatty-acid-free BSA, 150 mM NaCl, 10 mM Tris pH 7.4). The arrays were then incubated for 1 h in the presence of cell extracts, washed and the bound TAP-tagged proteins were immunodetected with PAP or with V5-specific antibodies (Invitrogen).
Molecular biology and recombinant protein expression
All primers used are listed in Supplementary Table S8
. TAP-tagged proteins selected for recombinant expression in E. coli
(Supplementary Tables S1B and S2A
) and the PH domain of Slm1 (Slm1-PH) were cloned in pET100-D/TOPO or pET101-D/TOPO vector (Invitrogen) following the manufacturer's instructions. Mutations in Slm1 were introduced using the QuikChange®
lightning Site-Directed Mutagenesis kit (Stratagene). For detailed information on the cloning, mutagenesis, expression and purification of the recombinant proteins, as well as strains used in this study, see Supplementary information
Perturbation of sphingolipid metabolism with myriocin
The localization of endogenously expressed proteins was examined using yeast strains expressing GFP fusions (Huh et al, 2003
). Cells attached on 35 mm glass bottom culture dishes coated with Concanavalin A were treated with 5 μM myriocin or 5 μM myriocin and 5 μM DHS(Sigma). The effect of myriocin was measured after 2 h treatment, which represents the minimal exposure time that induced, in our experimental setting, the delocalization of two proteins that bound sphingolipids in vitro
: Mss4 and Slm1. Under these conditions, cells remained perfectly viable (data not shown) and other membrane resident were unaffected (; Supplementary Figure S8A
). For a more detailed description of the procedure, see Supplementary information
Imaging was performed with an Olympus IX81 microscope equipped with 100 × /NA 1.45 objective lens and Hamamatsu Orca-ER camera.
For 49 GFP fusions that did not localize in punctate structures, the effect of myriocin was assessed qualitatively. Those proteins were considered sensitive to myriocin if the effect was restored by DHS. Yhr131c did not fulfill this requirement. We quantified the effects of myriocin using a standardized method for 32 proteins that showed similar punctate localization patterns (see Supplementary information
Perturbation of PtdIns(4,5)P2 metabolism
The mss4ts cells coding for the respective C-terminal GFP-tagged protein were grown and attached to dishes at 25°C, following the same protocol described above. Dishes were kept at the selected temperature (25 or 37°C) for 2 h and imaged immediately after. Same protocol was followed for PLCδ-PH-GFP. In this case, mss4ts strain was transformed with the plasmid coding for PLCδ-PH-GFP.
Perturbation of Pkh1/Pkh2 signaling pathway
cells coding for the respective C-terminal GFP-tagged proteins were grown and attached to dishes at 25°C, following the same protocol described above. Dishes were kept at the selected temperature (25 or 37°C) for 1 h and imaged immediately after. At 37°C, pkh1ts
cells are defective in actin polarization (Inagaki et al, 1999
). One hour represents the first time point, in our experimental condition, in which we observed the delocalization of the actin-binding protein Abp1. Under these conditions, cells remained viable (data not shown).
Cell based assays to assess Slm1-PH function
Actin polarization assay was performed as previously described (Fadri et al, 2005
; see Supplementary information
). Yeast wild-type strain and strains carrying point mutations in Slm1-PH domain were grown on SC plates containing 500 ng ml–1
myriocin or equivalent amounts of methanol at 30°C for 3 days. Strains carrying Slm2 deletion (Δslm2
) were grown in YPD plates at 25 or 37°C for 1 day.
A mixture of the lipids was prepared in chloroform:methanol:water, 1:1:0.07, containing 0.03% HCl. We added 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (Avanti Polar Lipids) to a final concentration of 3.8 mM. Where indicated, PtdIns, PtdIns(3)P, PtdIns(4)P, PtdIns(5)P, PtdIns(3,4)P2, PtdIns(3,5)P2, PtdIns(4,5)P2, PtdIns(3,4,5)P3, DHS-1P (Avanti Polar Lipids) and phosphatidylserine (Sigma) were also included. Lipid mixtures were dried under an argon stream followed by 30 min high vacuum. Dried mixtures were rehydrated in binding buffer (10 mM HEPES, 150 mM NaCl, pH 7.4) by mixing at 60°C for 2 h. Lipids were subjected to 5 min sonication and three snap-freeze/thaw cycles in liquid N2 and shaking at 60°C. Finally, small unilamellar vesicles were generated using a mini-extruder (Avanti Polar Lipids) and a membrane pore size of 0.1 μm.
Liposome-binding assays: flotation assay and size exclusion chromatography and western blot
Flotation assay was performed as previously described (Miller et al, 2002
) (see Supplementary information
). Size exclusion chromatography was performed on Pharmacia FPLC system by using Superdex 200 HR 10/30 column, equilibrated with binding buffer at the flow rate 0.25 ml × min−1
. After 30 min incubation at 22°C with 8 μM Slm1-PH or PLCδ-PH, 250 μl of the different liposome solutions were injected. We collected 0.5 ml fractions that were then analyzed by SDS–PAGE and western blot. A V5-specific antibody produced in mouse (Invitrogen) was used to detect Slm1-PH. Total band intensity was integrated with Photoshop software and normalized versus the total amount of protein loaded. Presented results are the sum of all detected fractions of Slm1-PH or PLCδ-PH co-eluted with liposomes.
Isothermal titration calorimetry
Isothermal titration calorimetry (ITC) was performed using a VP-ITC Microcal calorimeter (Microcal). Injectant (Slm1-PH or PLCδ-PH) was dialyzed extensively against binding buffer before all titrations. The experiments were performed at 25°C. A typical titration consisted of injecting 6–12 μl aliquots of 47 μM protein into the different solutions of liposomes, at intervals of 5 min to ensure that the titration peak returned to the baseline. The ITC data were corrected for the injectant dilution heat. To estimate Kd, we used the concentration of binding sites on liposome surface as a fitting parameter, assuming that the interactions occur in a stoichiometry of 1:1. The analysis was performed with the Origin 5.0 software.
Slm1-PH crystallization and structure determination
Crystals were grown at 20°C by vapor diffusion using the sitting-drop method. For crystallization, 0.5 μl of protein solution (9 mg ml–1
) were mixed with 0.5 μl of precipitant solution (2 M (NH4
, 2% PEG 400, 0.1 M Hepes pH 7.5). A single crystal was cryo-protected in mother liquor supplemented with 30% glycerol and flash frozen in liquid nitrogen at 100 K. Diffraction data were collected at beamline ID14-2 of the European Synchrotron Radiation Facility (ESRF, Grenoble France) using an ADSC Q4r CCD detector, and subsequently processed with XDS (Kabsch, 2010
). The structure was solved by molecular replacement with the program PHASER (McCoy et al, 2007
) using a search model obtained from the PDB entry 1btk (Hyvonen and Saraste, 1997
) after conversion to polyalanine and removal of poorly conserved regions among PH domains. The search model included the following residues in the PDB entry 1btk: 5–14, 25–42, 53–57, 63–65, 101–104, 111–134. The initial solution was completed by iterative cycles of manual building in COOT (Emsley and Cowtan, 2004
) and refinement using PHENIX (Adams et al, 2002
), yielding a final model with R
values of 22.1 and 27.1, respectively (Supplementary Table S7
). The stereochemistry of the final model was checked with PROCHECK (Laskowski et al, 1993
). The atomic coordinates and structure factors have been deposited in the Protein Data Bank under accession code 3nsu
In , the electrostatic potential calculated with APBS (Baker et al, 2001
) is represented on the solvent-accessible surface. Blue and red indicate positive (+4 kT/e) and negative (−4 kT/e) potential, respectively. Images were generated using Pymol (DeLano, 2002
Estimation of accuracy based on interactions with PtdInsPs pathway
We thought to use the genetic coverage of the literature-derived reference data set to extrapolate the fraction of true interactions (accuracy) in our data (see below). We reasoned that if the lipid–array and the literature-derived reference data set are comparable in terms of quality and biological relevance, they should be similarly covered
by genetic interactions. As the literature-derived reference data set mainly consists of PtdInsPs, we used accuracy measured for this lipid class as an approximation for the entire data set. For this analysis, intermediate cutoff was used for Costanzo et al (2010)
data set along with data from SGD and literature (Supplementary Tables S2C and S4
; see also Supplementary Data 1
For different sets of proteins, we measured the fraction that interacts genetically with enzymes involved in the synthesis of PtdInsPs (): (i) proteins that bound PtdInsPs in the literature-derived reference data set (10/16=62.5%=reference genetic coverage); (ii) proteins that bound PtdInsPs in the lipid–array (40/86=46.5%=experimental genetic coverage); (iii) a set of proteins defined as those proteins devoid of LBD and that did not bind PtdInsPs in the lipid–array (4/19=21.1%=background genetic coverage). We observed that the literature-derived reference data set has significantly more genetic interactions than the background genetic coverage (P=0.015). The same was true for proteins that bound PtdInsPs in the lipid–array versus the background genetic coverage (P=0.035). Interestingly, the lipid–array data did not show any significant difference when compared with the literature-derived reference data set (P=0.18). Fisher's exact test was used to measure significance.
We can now interpolate the fraction of true interactions (accuracy) expected in the PtdInsPs lipid–array data set. The coverage of genetic interactions in our data set results from two different components: interactions of ‘true positive' (x) and ‘false positive' (1−x) proteins. Assuming that the ‘false positive' will have a genetic coverage equal to the background genetic coverage and that ‘true positive' will have a genetic coverage equal to the reference genetic coverage, we predict that 61.4% of the proteins are ‘true positives' (see below). If all of the 86 proteins that bound PtdInsPs in the lipid–array are equally likely to be among the ‘true positives', the ‘true positive' rate among our protein–lipid interactions will also be 61.4% ().
χ=‘true positive' in the lipid–array data set (accuracy).
(1−χ)=‘false positive' in the lipid–array data set.
=experimental genetic coverage.
=reference genetic coverage.
=background genetic coverage.
Prediction of a CRAL/TRIO in Ecm25
The putative CRAL/TRIO domain of Ecm25 was detected by running HHsearch (Soding, 2005
) for all yeast proteins against the SCOP 1.69 database. For detailed information on the sequence-based alignment of the non-redundant set of structures annotated by Pfam as having a CRAL/TRIO domain, see Supplementary information
Clustering of proteins and lipids according to their binding profiles
For every protein, we calculated the fraction f1 of all the lipids with which it interacted and the fraction f0 of all the lipids with which it did not interact. Likewise, for every lipid, we calculated the fraction f1 of all the proteins with which it interacted and the fraction f0 of all the proteins with which it did not interact. Then at every position (i, j) in the interaction matrix, we have a score s1i,j for an interaction between protein i and lipid j=log(f1i)+log(f1j), and a score s0i,j for no interaction=log(f0i)+log(f0j). Thus, an interaction between a promiscuous protein and a promiscuous lipid has a lower score than an interaction between a highly selective protein and lipid. We then scored the similarity between the lipid-binding profiles of all pairs of proteins i1 and i2 by summing the scores for every lipid j in the profile, where the score for lipid j=
We then clustered the proteins by complete linkage using the program OC (Barton, 2002
), on the basis of these scores. We followed the same procedure to cluster the lipids on the basis of their protein-binding profiles. The calculation of the binomial probability for a significant deficiency or enrichment with a particular attribute and correction for testing for a particular feature in multiple places is described in Supplementary information
For detailed description on other bioinformatic procedures (e.g. multiple sequence alignment), see Supplementary information