(β2c-tubulin) β5-tubulin (refer to β1-tubulin) 1.6. Systems Biology Systems Biology is an inter-disciplinary field that is rapidly is gaining attention in bioscience research as a technique for studying complex biological systems [, , ]. It is especially relevant in this post-genomic era where many areas of research are rich in data but hypothesis-poor []. Although Systems Biology is a relatively new field in oncology research, it is proving a valuable tool for understanding the biological mechanisms underlying tumour development and for identifying novel targets for cancer therapeutics [, ]. A key aspect of Systems Biology is that it can be both data-driven and []. The two approaches complement each other when attempting to understand the relationships between ‘causes’ and ‘effects’ []. A hypothesis-driven approach links a proposed ‘cause’ or ‘theory’ to observed ‘effects’ and ‘evidence’ and is often applied to prove or disprove a hypothesis. A data-driven approach evaluates multiple ‘effects’ to predict a ‘cause’ in order to formulate a new hypothesis; this can then be tested experimentally via a second hypothesis-driven approach, thereby forming a ‘cycle of knowledge’ []. This iterative cycle enables the wealth of information that can be generated through quantitative high-throughput technologies, and data from the rapidly expanding bioinformatic databases, to be maximised []. Computational mechanistic or dynamical modelling is becoming an integral part of Systems Biology, due in part to being able to manage the large number of molecular components and their complex interactions when conducting a system-wide study.
3.4.9. Multi-plex iTRAQ quality control by correlation plots and dendrograms Quality control of the multi-plex iTRAQ protocol was performed by constructing correlation (or scatter) plots, and dendrograms (cluster analysis) to determine how closely the biological replicates matched, and how the different treatments clustered relative to each other. The correlation plots gave pair-wise comparisons between the biological replicates by plotting log2 fold-changes for each dataset against another. Ideally these should follow a straight line with a gradient of 1 but in reality there is always an element of scatter. Pearson’s correlation coefficient is frequently used to measure the strength of linear correlation between two sets of data when data is parametric, i.e. both measurements are continuous and normally distributed, and this was the method adopted here. This gives a value between +1 and -1, where +1 is maximum positive correlation (dependence) and -1 is maximum independence. Correlations were performed between each pair of data (117:118 and 119:121), each having a total of 331 rows. A second correlation was performed between all four replicates in a two-dimensional array, calculated by comparing each replicate against the others, giving a total of 1986 rows, as follows: P117:P118 P117:P119 P117:P121 P118:P119 P118:P121 P119:P121 The dendrograms showed how the reporter ions, and therefore the peptides, from the treated and untreated biological replicates clustered. High correlation between replicates gives maximum overlap indicating high reproducibility. Ideally there should
cells were simultaneous treated by adding 40 μl SCFA per well (5 x SCFA stock solutions in PBS) using a multi-channel pipette (Labret Biopette) to give a final volume of 200 μl per well. Treatment concentrations were 0 mM, 1 mM, 5 mM, 10 mM, and mM SCFA; the cells were incubated at 37°C for 24 h before being fixed in 4 % formalin for 15 min at room temperature. Untreated samples were included as controls. a) HCT116 cytoskeletal (actin-tubulin) plate map b) Representative plate micrograph Figure 4.1. HCA 96-well plate plan and micrographs of HCT116 cells after treatment with SCFAs. a) Top panel: colour key showing SCFA treatment concentrations; Lower panel: the plate map rows represent triplicate treatments. b) The ICC micrograph shows green fluorescent anti-body staining of cytoskeletal structure and blue (Hoescht) nuclei. The inset represents a single well. [vp, valproic acid; P, propionate; B, butyrate; V, valerate]. 4.4.3. Immunocytochemistry of actin and tubulin cytoskeletal structures After fixing, the nuclei were stained with Hoechst (blue) at a ratio of 1:1250 in digitonin and incubated for 30 min at room temperature. After staining, the cells were washed three times with PBS. The plates were sealed with a sealing film and transported on ice at 4°C to Imagen Biotech, Manchester, where they were stained with Phalloidin for actin and an anti-β tubulin antibody prior to HCA analysis. 4.4.4. HCA quantification of cytoskeletal integrity HCA imaging and analysis was carried out at Imagen Biotech using x10 and x20 objectives and ArrayScan II software (v. 3.5.1.2). Hoechst nuclear staining enabled Regions of Interest (ROIs) per well to be identified and corrections to background fluorescence to be made. The total staining intensity