Changing bioengineering with unbiased groups and tools

It is important to emphasize that an unbiased instrument is not a solution to a biased hypothesis or study design. As described here, unbiased tools are high-throughput assays that measure multiple analytes in parallel (eg, genes, proteins, and metabolites). A large number of analytes leads to an increase in the amount of comparable data, thus reducing the bias towards a particular analyte or biological outcome. In general, unbiased tools can be divided into two categories: omics and multiplexed assays. High-throughput omics assays seek to detect all biomolecules (e.g. RNA) in a sample, then combine this analysis with a reference to determine the type, abundance, and biological significance (e.g. gene expression) of those biomolecules. Omics methods and specializations include – but are not limited to – genomic, transcriptional, epigenomic, proteomic, and metabolomic. Multiplexed assays are variations of traditional assays (eg, cytokine enzyme-linked immunosorbent assay (ELISA)) that measure specific analytes. These experiments use innovations in microfabrication, nanotechnology and chemistry to increase productivity.

The use of unbiased tools in bioengineering research is increasing, but it is rare. Transcriptomics is the study of RNA molecules in the cell; Gene expression can then be linked to genomic and functional phenotypes of cells by RNA sequencing (RNA-seq). This capture of interconnected and dynamic gene expression networks within a cell is a powerful tool for analysis and hypothesis generation.². In bioengineering, transcriptomics can link engineering strategies to biological outcomes. Fortunately, engineering platforms such as microfluidic cell isolation have enabled RNAi-sec single cells.⁶. Single-cell RNA-seq (scRNA-seq) further increases the breadth of data by adding unique barcodes to thousands of individual cells. scRNA-seq has thus revolutionized the discovery of cell differentiation and rare cell populations.

Similarly, inflammatory pathways around lesions and implants can be investigated using scRNA-seq.⁷. Here, sRNA-seq can predict up-regulated tumor regulators in response to biomaterials, generating a second hypothesis that can then be independently validated. scRNA-seq and multiplexed gene expression were also used to test the hypothesis that cancer metastasis alters the biomarker response.⁸. This study revealed that cancer proliferation induces specific gene expression and cellular changes in biomaterial implants. Moreover, this specific immune response predicts treatment outcomes in a preclinical cancer model. In addition, cell barcoding can be combined with therapeutic barcoding. This strategy has been applied to test different lipid nanoparticle formulations and their potential to deliver mRNA vaccines.⁹, using the modularity of omics to design a mechanism of action for multiple engineering therapies in parallel. As a starting point, investigators can invest in training opportunities, such as certificate courses in omics, which are available for a fee. Alternatively, free resources from National Human Genome Research Institutecommercial omics suppliers and channels viz Biology And StatQuest.