MicroRNAs are small ~22 nucleotide RNA sequences that are guided to the 3’ untranslated region (UTR) of protein-coding target mRNA sequences. One particular microRNA, miR155, plays a remarkable role in the immune system, where it is essential for mounting appropriate immune responses. However, its dysregulation has been identified in multiple inflammatory disorders such as Multiple Sclerosis (MS), arthritis, psoriasis and colitis. More specifically, miR-155 has been found to be elevated in the serum and brain lesions of MS patients. Importantly, therapeutic inhibition of miR-155 can inhibit progression of the MS disease model. One of us has identified that macrophages are major contributor to miR-155 elevation in the MS disease model, whilst its inhibition specifically in macrophages can limit the disease. Here macrophages were isolated from the femur and tibia of wild-type (WT) mice and mice with a knock-out (KO) of the gene regulating miR-155 production, and were cultured in-vitro and stimulated with lipopolysaccharide (LPS) to simulate an immune response. Cells were then prepared for spectral analysis by FTIR imaging with a Perkin-Elmer Spotlight 400 imaging microscope. After pre-processing the dimensionality of spectra were reduced using principal components analysis, kernel-PCA and universal manifold application and projection (UMAP) and classified using a support vector machine algorithm, delivering a classification performance approaching F1~0.89. Spectral features differentiating WT and KO classes were observed across the fingerprint region with no single spectral marker being the sole source of differentiation of the downstream molecular events. This study exemplifies the challenge in spectral discrimination of the complexity of molecular events in ex-vivo models of immune dysregulation.
Multi-modal spectroscopic analysis of biological systems may offer an improved overall non-invasive biophotonic metric of the status of the system, further enhancing the diagnostic and prognostic capabilities of these technologies. In the present study macrophages were extracted from wild-type mice and mice with a knock-out of the gene regulating miR-155, which has been observed to occur in patients with various autoimmune disorders, including multiple sclerosis (MS). Macrophages were stimulated in-vitro to produce an immune response and were then screened spectroscopically with FTIR and Raman spectroscopy (at 532nm and 660nm). Low, medium and high level data fusion strategies for classification of response to stimulation and miRNA regulation were piloted, using downstream principal components analysis-support vector machine classifiers to test the impact of these strategies on classification performance. These techniques allowed the development of a combined highlevel data-fusion, classification pipeline with a high level of classification accuracy (F1<0.9), with reduced variability in performance. Our proposed spectroscopic assay-data fusion strategy may provide an adjunct to clinical screening and diagnosis of various autoimmune disorders whose aetiology is associated with genetic dysregulation.
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