The effect of high vacuum on the mechanical properties and bioactivity of collagen fibril matrices

Cellular interactions with the extracellular matrix (ECM) initiate an array of biophysical and biochemical signals that drive biological processes ranging from embryonic development to cancer progression [1-4]. In addition to receptor-mediated interactions between cells and the ECM [5,6], the mechanical environment that cells experience can exert strong influences on inter- and intracellular signaling and cell responses, and is likely critical to migration, differentiation, and development [4,7-10]. Elucidating the structural, mechanical, and chemical environment that the ECM presents to cells can be challenging. There has been a growing effort to employ a variety of surface sensitive microscopy techniques to measure the physicochemical properties of ECMs [11-16].Recently, a number of reports have analyzed decellularized tissues and ECMs created by cells in vitro using electron, ion, and x-ray bombardment induced ionization microscopy methods, which are performed under high vacuum (HV) [13-15,17-22]. The use of scanning electron microscopy (SEM), for example, is commonplace for obtaining structural information of supramolecular ECM systems [13,17,18,20], but methods for accessing information about the chemical environment that the ECM provides to cells has been more elusive. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is one such technique that can provide chemical information about the surface of the material being analyzed. The ToF-SIMS sampling depth, when operated in a so-called static mode, is approximately 1 nm to 2 nm, rendering it ideal for determining the surface composition of complex protein samples [14,23-26]. ToF-SIMS data are conducive to a variety of multivariate analysis techniques, such as principal component analysis (PCA), to provide sensitive discrimination between parent molecules based on spectral differences [24,25]. For example, PCA with ToF-SIMS has been utilized for identifying and classifying a variety of biologically relevan