Abstract Neuronal cells are competent in precisely sensing nanotopographical features of their microenvironment. The perceived microenvironmental information will be “interpreted” by mechanotransductive processes and impacts on neuronal functioning and differentiation. Attempts to influence neuronal differentiation by engineering substrates that mimic appropriate extracellular matrix (ECM) topographies are hampered by the fact that profound details of mechanosensing/-transduction complexity remain elusive. Introducing omics methods into these biomaterial approaches has the potential to provide a deeper insight into the molecular processes and signaling cascades underlying mechanosensing/-transduction but their exigence in cellular material is often opposed by technical limitations of major substrate top-down fabrication methods. Supersonic cluster beam deposition (SCBD) allows instead the bottom-up fabrication of nanostructured substrates over large areas characterized by a quantitatively controllable ECM-like nanoroughness that has been recently shown to foster neuron differentiation and maturation. Exploiting this capacity of SCBD, we challenged mechanosensing/-transduction and differentiative behavior of neuron-like PC12 cells with diverse nanotopographies and/or changes of their biomechanical status, and analyzed their phosphoproteomic profiles in these settings. Versatile proteins that can be associated to significant processes along the mechanotransductive signal sequence, i.e., cell/cell interaction, glycocalyx and ECM, membrane/f-actin linkage and integrin activation, cell/substrate interaction, integrin adhesion complex, actomyosin organization/cellular mechanics, nuclear organization, and transcriptional regulation, were affected. The phosphoproteomic data suggested furthermore an involvement of ILK, mTOR, Wnt, and calcium signaling in these nanotopography- and/or cell mechanics-related processes. Altogether, potential nanotopography-sensitive mechanotransductive signaling hubs participating in neuronal differentiation were dissected. Keywords: mechanotransduction, integrin signaling, quantitative shot gun proteomics, biophysics, biomaterial, neuronal differentiation, cell adhesion Introduction Cells can sense nanotopographical cues deriving from the extracellular matrix (ECM), predominantly through integrin adhesion complexes (IAC), and the microenvironmental information is converted into alterations of the cytoskeletal organization and mechanics. Mechanosensitive signaling cascades and nuclear rearrangements eventually translate these modulations into cellular responses; this entire sequence is defined as mechanotransduction. Mechanosensing of the substrate nanotopography and the subsequent mechanotransduction strongly impact many physiological cellular behaviors, in particular in the context of cell differentiation (Geiger et al., [39]2009; Wang et al., [40]2009; Chen et al., [41]2014; Dalby et al., [42]2014; Jansen et al., [43]2015), but they might also influence pathophysiological processes, such as metastatic cell migration (Park et al., [44]2016). Many aspects regarding the cellular capacity of sensing nanoscale topographical cues and how the information is integrated into complex mechanotransductive signals are still largely unknown (Chen et al., [45]2014; Dalby et al., [46]2014). Artificial nanostructured surfaces produced by diverse top-down microfabrication techniques (typical of the semiconductor industry) have been useful tools that helped to understand principal surface topography-related parameters controlling mechanotransductive processes (Chen et al., [47]2014; Dalby et al., [48]2014) which are hard to access in vivo. This approach has two major limitations. First of all, starting from simple surface motifs it is extremely difficult to reconstruct the morphological complexity of the ECM. Secondly, achieving an in-depth comprehension of the mechanotransductive processes and signaling requires systematic high-throughput and omic approaches (Cranford et al., [49]2013; Groen et al., [50]2016). Admittedly, many micro-/nanofabrication techniques have technical limitations hindering a feasible and cost-effective scale-up necessary to provide sufficiently large surface areas with a defined nanotopography (Chen et al., [51]2014). However, the yield of a reasonable amount of cellular material is mandatory for the implementation of omics approaches. In this framework, we use the bottom-up nanofabrication method supersonic cluster beam deposition (SCBD) to quantitatively address the influence of nanoscale surface topography on mechanotransduction. SCBD permits the engineering of nanostructured surfaces with a reproducible nanoscale roughness parameter by assembling transition metal oxide clusters (Schulte et al., [52]2017), thereby realizing topographies that mimic ECM nano-features (Gasiorowski et al., [53]2013). SCBD can be applied efficiently to produce biocompatible substrates (made by titania or zirconia clusters) on large macroscopic areas rendering it compatible with profound biological analyses, such as proteomic studies (Schulte et al., [54]2017). Recently, using PC12 cells as a broadly accepted model system for neuronal differentiation, we demonstrated that appropriate biophysical stimuli; provided by the cellular interaction with nanotopographical cues of titania or zirconia surfaces produced by SCBD, promote neuronal differentiation processes (Tamplenizza et al., [55]2013; Schulte et al., [56]2016a). This potential of the cluster-assembled surfaces was also confirmed in hippocampal neurons (Schulte et al., [57]2016b). In both cellular models we applied label-free shotgun proteomics as an essential technique to examine the impact of the nanotopography on cellular differentiation processes since this quantitative approach can achieve simultaneously: (a) the identification of thousands of proteins isolated from a cellular model and (b) the quantification of each protein/phosphosite. It is therefore well suited to study differences in global protein expression between different samples, providing substantial information to delineate and profoundly understand cell signaling pathways and modulations of the cellular program (Toffolo et al., [58]2014; Zanotti et al., [59]2016), in particular also in the context of integrin-mediated mechanotransduction (Humphries et al., [60]2015; Robertson et al., [61]2015). Neuronal differentiation is a specifically interesting biological process in this mechanobiological context. It is accompanied by drastic morphological and cytoskeletal rearrangements throughout the realization of neurites, dendrites and axons, strongly controlled by point contact-mediated neuron/ECM interaction (Myers et al., [62]2011; Flynn, [63]2013; Kerstein et al., [64]2015). In fact, in PC12 cells the extent of nanotopography-triggered differentiation (even in the absence of a biochemical stimulus) was comparable to the canonical differentiation mediated by NGF-induced TrkA activation. In each case, either NGF- or nanotopography-induced, the outcome was the outgrowth of neurites and a differentiated cell. Our previous study furthermore revealed that in the latter condition, complex mechanotransductive events were at the basis of cellular processes that lead to the onset of neuritogenesis and neuronal differentiation. However, at the proteome level we only compared the nanostructured surface with a roughness parameter R[q] of 15 nm root mean square (RMS) (which induced the strongest neuritogenesis, called ns-Zr15 hereafter) against a flat zirconia surface (which even after NGF stimulus impeded neuronal differentiation, named flat-Zr herafter). The cells on ns-Zr15 were found to have small IAC (predominantly focal contact (FC) size), few to none stress fibers and a low cell rigidity, contrary to the large IAC (focal adhesion (FA) size), stress fibers and an increased cellular rigidity on flat-Zr (Schulte et al., [65]2016a). Besides these two conditions (ns-Zr15 and flat-Zr), the proteomic analyses in this study comprise instead PC12 in more versatile experimental conditions including a surface nanotopography with higher roughness, the biochemically NGF-induced canonical neuronal differentiation and manipulations that affect the biomechanical status of the PC12 cell. The characteristics of these additional experimental conditions evaluated in this extended proteomic analyses are (summarized in Figure [66]1): Figure 1. [67]Figure 1 [68]Open in a new tab Representations of the cell morphology in the different conditions and a summary of the results presented in a previous publication (Schulte et al., [69]2016a). The figure summarizes the results of our previous publication (Schulte et al., [70]2016a) which provided the basis for the selection of the experimental conditions of the extended phosphoproteomic analyses of this work. In the upper row representations of the surface nanotopographies are displayed which were also used in this work (PLL-coated glass, flat-Zr, ns-Zr15, and ns-Zr25). Underneath example photos demonstrate the morphology of PC12 cells in the indicated conditions. In the table the impact of these different conditions on examined cellular parameter are recapitulated (FA, focal adhesions; FC, focal complexes; IAC, integrin adhesion complex; n.a., not analyzed). * (1) The surface with an increased roughness R[q] of 25 nm RMS (ns-Zr25) has asperities that display subtle differences in diameter and dimension compared to ns-Zr15. This roughness induced neuritogenesis to a lower extent with respect to ns-Zr15 (Schulte et al., [71]2016a). * (2 and 3)As canonical reference, representing the broadly studied biochemically triggered neuritogenesis and neuronal differentiation, PC12 cells on PLL-coated glass, in the absence (PLL) or presence of NGF (NGF), were introduced into the analysis. The cells exhibited large IAC (FA size), stress fibers and an intermediate cell rigidity without the NGF stimulus. The IAC size (to FC), stress fibers frequency and cellular rigidity decreased upon NGF-induced differentiation (Schulte et al., [72]2016a). Moreover, the role of cellular biomechanics in this mechanotransductive sequence was approached by adding two conditions affecting the cellular tension: * (4) Cells grown on ns-Zr15 in hypoosmotic medium to increase the cellular tension by osmotic swelling which counteracts the lower rigidity of the cells on ns-Zr15 and inhibits the nanotopography-triggered neuritogenesis (Schulte et al., [73]2016a). * (5) Cells on PLL exposed to a short hyperosmotic shock (decrease in cellular tension), a treatment that morphologically triggered the outgrowth of neurites (Figure [74]S1). A correlation of these alterations in cellular and topographical characteristics to changes in the PC12 neuronal proteome allowed us to obtain a deeper understanding of cellular nanotopography sensing and mechanotransductive signal integration. We were able to define potentially relevant surface nanotopography-sensitive mechanotransductive proteins and signaling networks/hubs that might play a key role in the signal integration driving, in this case, neuronal differentiation. For the sake of clarity (considering the many diverse conditions), in the main text we will talk more generally about signaling pathways and cellular processes affected or modulated in the different experimental settings, highlighting only a few particularly interesting proteins dissected from the global picture that introduce new aspects. Further examples of proteins and information on their to-date reported functions relevant in this context will be provided in the corresponding tables we refer to. The precise analysis of biomolecular events triggered by cell/nanotopography interaction, combined with the technical capacities of SCBD, constitutes the necessary foundation for efficient near-future exploitation of SCBD for versatile bio-applications. Experimental procedures Substrate preparations As a basis for all substrates standard microscope glass slides with the dimensions of 76 × 26 mm (surface area ~20 cm^2) were used. On this carrier, we produced the cluster-assembled nanostructured films by supersonic cluster beam deposition (SCBD) of zirconia clusters obtained through a pulsed microplasma cluster source. Specific details on this bottom-up nanofabrication approach can be found in Wegner et al. ([75]2006) and Schulte et al. ([76]2017). These cluster-assembled zirconia surfaces are given the abbreviation ns-Zr throughout the manuscript. The number after Zr indicates the roughness parameter R[q]. Two batches were fabricated for this work with roughness parameters of 15 nm RMS (ns-Zr15) and 25 nm RMS (ns-Zr25). The roughness and the morphological parameters have been systematically characterized by atomic force microscopy (AFM) (Podestà et al., [77]2015; Borghi et al., [78]2016). The capacity of SCBD to reliably cover large macroscopic areas with nanostructured films of a predefined roughness allowed us to perform the experiments on microscope glass slides with the dimensions of 76 × 26 mm (~20 cm^2 surface area). This rendered possible the yield of sufficient cellular material from the different experimental situations to obtain the analyzed information, e.g., also data on the phosphorylation status of the proteins. The flat zirconia surfaces (flat-Zr) with a roughness of ~0.4 nm RMS were obtained with electron beam evaporation. For the canonical reference, the microscope glass slides were coated with poly-L-lysine (PLL) (Sigma-Aldrich, St. Louis, USA, Missouri) for 30 min at room temperature (RT), after cleaning with 70% ethanol and washing twice with PBS. This coating was done directly before plating the cells. All substrates were sterilized with UV light for 10 min before seeding the cells. Cell culture and preparation of the cells for the experiments PC12 cells (PC-12 Adh ATCC Catalog no. CRL-1721.1™) were routinely kept in culture in RPMI-1640 medium (Sigma-Aldrich) which was supplemented with 10% horse serum (HS, Sigma-Aldrich), 5% fetal bovine serum (FBS, Sigma-Aldrich), 2 mM L-glutamine, 10 mM HEPES, 100 units/ml penicillin, 1 mM pyruvic acid, and 100 μg/ml streptomycin. The culture conditions were 37°C and 5% CO[2] (98% air-humified). Subculturing was performed every 2–3 days by detaching the cells with 1 mM EDTA in HBSS or a trypsin solution (Sigma-Aldrich), centrifugation at 1,000× g (5 min) and resuspension in the culture medium. For the experiments the PC12 cells were detached with 1 mM EDTA in HBSS and centrifuged at 1,000× g (5 min), washed with low serum medium (RPMI-1640 with all the supplements, but only 1% HS and without FBS), and centrifuged again at 1,000× g (5 min). Before plating the cells on the different substrate conditions, the cells were counted with an improved Neubauer chamber and then seeded with the concentration of ~4,000 cells/cm^2 (after resuspension in RPMI low serum medium) onto the microscope slides that were placed into non-treated 4 well dishes with the dimensions 127.8 × 85.5 mm (Thermo Fisher). For the NGF condition, the NGF stimulus (human NGF-β, Sigma-Aldrich) was added to the medium right after plating the cells making a final concentration of 50 ng/ml. For the ns-Zr15 hypo condition, the cells were re-suspended in RPMI low serum medium diluted 7.5/2.5 with deionised water (supplements were kept at the aforementioned concentrations) and pre-incubated in the hypoosmotic medium for 15 min before plating the cells eventually into the well, always in the hypoosmotic medium. For the PLL hyper condition, after the adhesion of the cells (1 h after plating) a hyperosmotic shock was applied to the cells (150 mM sucrose final concentration in the RPMI low serum medium) for 15 min, and washed once with RPMI low serum medium. The cells were left in RPMI low serum medium for the rest of the experiment. The cells were left in the incubator for 24 h in all conditions. After washing twice with PBS, the cellular material was yielded for the proteomic analysis by scratching the cells from the microscope slides with cell scrapers (TPP, Trasadingen, Switzerland) in the presence of icecold PBS supplemented with protease (Roche, Basel, Switzerland) and phosphatase inhibitors (phosphatase inhibitor cocktail (Cell Signaling Technology), calyculine A (serine/threonine phosphatase inhibitor) 10 nM (Cell Signaling Technology), microcystin-LR 10 nM (Enzo Life Sciences). For the inhibition experiments with [79]SKF96365 (Sigma-Aldrich) and GsMTx4 (Alomone Labs, Israel), the resuspended cells were preincubated with the inhibitors ([80]SKF96365 15 μM; GsMTx4 10 μM) in RPMI low serum medium (supplemented with 50 ng/ml NGF in the PLL +NGF condition) for 15 min in suspension before plating. The inhibitor treatment was maintained for 1 h, and then the medium was discarded and exchanged with new RPMI low serum medium (plus 50 ng/ml NGF in the PLL +NGF condition). For the rapamycin inhibition (Sigma-Aldrich), the cells were treated with the indicated rapamycin concentrations for the whole duration of the experiment. After 24 h, respectively 48 h for the rapamycin experiments, the morphology of the PC12 cells was recorded with an inverted Axiovert 40 CFL microscope (Zeiss, Oberkochen, Germany) equipped with LD A-Plan 20x/0.3 Ph1 or CP-ACHROMAT 10x/0.25 Ph1 objectives (both Zeiss) and the analysis was performed with ImageJ (NIH, New York, USA). Cells with neurites >10 μm were counted as differentiated and only neurites with a length >10 μm were considered for neurite length quantification. If cells have multiple neurites only the longest two were taken into the quantification, and in case of neurite branching the longest branch was measured. The neurite morphology was comparable between the canonical biochemically (NGF-)induced and the nanotopography-triggered neuritogenesis with 1.82 ± 0.42 neurites per cell for the first and 1.66 ± 0.21 for the latter (in total 160 differentiated cells for each condition were quantified from 8 independent experiments) (Figure [81]S2). In both cases the median was 2 neurites per cell and the vast majority of cells bore 1 or 2 neurites (together 82%, respectively 90%). All the inhibition experiments were performed on coverslips with a diameter of 13 mm. The substrate preparation itself was the same as in the precedent section. Shotgun mass spectrometry and label free quantification After reduction and derivatisation, the proteins were digested with trypsin sequence grade (Roche) for 16 h at 37°C using a trypsin:protein ratio of 1:20. LC-ESI-MS/MS analysis was performed on a Dionex UltiMate 3000 HPLC System with a PicoFrit ProteoPrep C18 column (200 mm, internal diameter of 75 μm) (New Objective, USA). Gradient: 1% ACN in 0.1% formic acid for 10 min, 1–4% ACN in 0.1% formic acid for 6 min, 4–30% ACN in 0.1% formic acid for 147 min and 30–50% ACN in 0.1% formic for 3 min at a flow rate of 0.3 μl/min. The eluate was electrosprayed into an LTQ Orbitrap Velos (Thermo Fisher Scientific, Bremen, Germany) through a Proxeon nanoelectrospray ion source (Thermo Fisher Scientific). The LTQ-Orbitrap was operated in positive mode in data-dependent acquisition mode to automatically alternate between a full scan (350–2,000 m/z) in the Orbitrap (at resolution 60000, AGC target 1000000) and subsequent CID MS/MS in the linear ion trap of the 20 most intense peaks from full scan (normalized collision energy of 35%, 10 ms activation). Isolation window: 3 Da, unassigned charge states: rejected, charge state 1: rejected, charge states 2+, 3+, 4+: not rejected; dynamic exclusion enabled (60 s, exclusion list size: 200). Four technical replicate analyses of each sample were performed. Data acquisition was controlled by Xcalibur 2.0 and Tune 2.4 software (Thermo Fisher Scientific). Mass spectra were analyzed using MaxQuant software (version 1.3.0.5). The initial maximum allowed mass deviation was set to 6 ppm for monoisotopic precursor ions and 0.5 Da for MS/MS peaks. Enzyme specificity was set to trypsin, defined as C-terminal to arginine and lysine excluding proline, and a maximum of two missed cleavages were allowed. Carbamidomethylcysteine was set as a fixed modification, while N-terminal acetylation, methionine oxidation and Ser/Thr/Tyr phosphorylation were set as variable modifications. The spectra were searched by the Andromeda search engine against the rat Uniprot sequence database (release 29.05.2013). Protein identification required at least one unique or razor peptide per protein group. Quantification in MaxQuant was performed using the built in XIC-based label free quantification (LFQ) algorithm using fast LFQ. The required false positive rate (FDR) was set to 1% at the peptide, 1% at the protein and 1% at the site-modification level, and the minimum required peptide length was set to 6 amino acids. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (Vizcaíno et al., [82]2016) partner repository with the dataset identifier PXD007644. Statistical and bioinformatics analyses Statistical analyses were performed using the Perseus software (version 1.4.0.6, [83]www.biochem.mpg.de/mann/tools/). Only proteins/phosphopeptides present and quantified in at least 3 out of 4 technical repeats were considered as positively identified in a sample and used for statistical analyses. An Anova test (Permutation based FDR 0.05) was carried out to identify proteins/phosphopeptides differentially expressed among the different conditions. To tackle specific biological issues we then compared subsets of three proteomic data related to specific conditions, namely: [ns-Zr15, NGF, PLL], [ns-Zr15, NGF, flat-Zr], [ns-Zr15, NGF, ns-Zr25]. Therefore, proteins/phosphopeptides were considered differentially expressed if they were present only in one condition or showed a Post-hoc Bonferroni test p < 0.0167. Regarding the proteomic data of ns-Zr15 hypo and PLL hyper which refer to peculiar cell conditions, the following comparisons were performed: [ns-Zr15, ns-Zr15 hypo], [PLL hyper and PLL], and [ns-Zr15 hypo, PLL hyper]. Proteins/phosphopeptides were considered differentially expressed if they were present only in one condition or showed a significant Welch t-test difference (cut-off at 5% permutation based FDR). Bioinformatic analyses were carried out by DAVID software (release 6.7) (Huang et al., [84]2009), Panther software (Mi et al., [85]2017), ClueGO application of Cytoskape software (release 3.2.0) ([86]http://www.cytoscape.org/), and Ingenuity Pathway Analysis (IPA®) (QIAGEN Redwood City, [87]www.qiagen.com/ingenuity) to cluster enriched annotation groups of Molecular Function, Biological Processes, Pathways, and Networks within the set of identified proteins/phosphopeptides. The compared data sets are indicated in the relative figures. Functional grouping was based on a Fisher Exact test p ≤ 0.05 and at least two counts. Results and discussion Similarities and differences between biochemically and mechanotransductively promoted neuronal differentiation at the protein level Focus on ns-Zr15, NGF, PLL, flat-Zr The versatile conditions included in the extended proteomic approach presented here are summarized in the introduction and in Figure [88]1. Altogether, they address different aspects of surface nanotopography of the substrate and/or biomechanics of the cell, integrating also information on the phosphorylation status of the proteins. To dissect similarities and differences between the biochemically and mechanotransductively promoted neuronal differentiation at the proteome level we compared the data sets of ns-Zr15 (neuritogenesis-triggering cluster-assembled zirconia surface), PLL and NGF [canonical condition on PLL-coated glass, in the presence (NGF) or absence (PLL) of NGF]. The Venn diagram (Figure [89]S3A), the work flow (Figure [90]S3B), the Volcano plots (Figure [91]S3C) and the corresponding lists of differently expressed proteins (Tables [92]S1–[93]S6) are reported in the indicated Supplementary Information. The proteomic analysis of NGF[vs]PLL (Table [94]S1) compared to ns-Zr15[vs]PLL (Table [95]S3) highlights the common outcome of neuronal differentiation, independent of whether initiated canonically by NGF stimulation (NGF) or instead by mechanotransductive processes (ns-Zr15). 11 out of 35 proteins found to be significantly altered in NGF[vs]PLL are differentially expressed in the same manner also in ns-Zr15[vs]PLL (the common proteins are marked in gray in Table [96]S3). Several of these proteins indeed have prominent and versatile known roles in the regulation of neuronal functioning and neurogenic processes [such as e.g., Htra1 (Launay et al., [97]2008; Tennstaedt et al., [98]2012); Vps35 (Wang et al., [99]2012; Tang et al., [100]2015); Fasn (Knobloch et al., [101]2013); Pdia3/ERp57 (Castillo et al., [102]2015; Bargsted et al., [103]2016); C3 (Stevens et al., [104]2007); RPL19 (Zhou et al., [105]2010); details in Table [106]1: Similarities]. Table 1. Similarities between biochemically and mechanotransductively promoted neuronal differentiation at the protein level by comparing the conditions ns-Zr15, NGF, and PLL. Similarities Associated to Similarities and differences between biochemically and mechanotransductively promoted neuronal differentiation at the protein level Examples of proteins differentially expressed in the same manner in NGF[vs]PLL (Table [107]S1) and ns-Zr15[vs]PLL (Table [108]S3) and their reported roles in a neuronal context Protein name NGF and ns-Zr15 Reported protein functions References