THE ROLE OF BIOTECHNOLOGY IN UNDERSTANDING DISEASE CAUSATION

One of the single most valuable roles for biotechnology in medicine is providing scientists with the tools they need to study disease at a molecular level. Knowledge gives rise to conceptual models, diagnostics, treatments, and preventatives.

A Systems Approach to Understanding Disease Causation

Disease is caused by significant perturbations in biological systems, otherwise called molecular mechanisms of disease. Symptoms manifest because critical components of the system are askew, and must be righted. Thus, the first step to understanding disease is cataloging all the differences between diseased and healthy states. The easiest way to do this is by measuring stocks in the respective biological systems—that is the DNA, transcripts, and proteins—in healthy versus diseased cells/tissues. Unbiased ‘omic studies create biological “parts” lists that can be compared. Discernible differences between healthy and diseased states are called biomarkers; direct or indirect indicators of disease.

Defining a molecular mechanism of disease requires a functional understanding of the parts. Function is often investigated using genetically modified cells/organisms in which a target gene/protein is removed (knockout) or inhibited (knockdown). Knockouts are made by deleting or disrupting the coding region of a target gene (see Figure 3.1). Replacement deletion or insertion alleles are created by rDNA technologies or gene synthesis, and then integrated at the genome site. A length of DNA on either side of the mutant allele is engineered to match the target site within the genome. Sequence similarity between the fragments facilitates two

Knockout construction by allelic replacement

Figure 3.1. Knockout construction by allelic replacement.

cross-over events that lead to homologous recombination-mediated allelic replacement. The large insertion within the target results in nonfunctional proteins.

In a knockdown, small interfering RNA (RNAi) molecules are transiently introduced to inhibit the expression of a target gene. While the molecular details of knockout/-down strategies vary, they are based on one simple principle—by altering gene expression, detectable phenotypic change(s) will emerge. These changes can be used to deduce protein function. Analysis involves comparing the behavior and characteristics of mutants to paired wildtype (i.e., unaltered) controls.

Functional studies of individual genes/proteins are used to build increasingly complex conceptual models of biological systems and test hypotheses about disease causation.8 A simple conceptual model may look like that which is shown in Figure 3.2. Components “A”, “B”, and “C” interact with one another. “A” positively influences “B”, which positively influences “C.” “C” negatively influences “A.” Models like this are used to describe systems and develop hypotheses.

When quantitative information about the rate and strength of interactions between individual components is known, mathematical models emerge. Increasingly complex models are developed and analyzed using computational tools.

Simple model of a hypothetical biological system

Figure 3.2. Simple model of a hypothetical biological system.

Mammalian tissue culture and whole animal models are used to further explore molecular mechanisms of disease. These in vivo systems are often enhanced via genetic modification to mimic conditions observed in humans. For example, the mdx knockout mouse is a model for the human genetic disorder, Duchenne’s muscular dystrophy (DMD). Like DMD patients, mdx-mice do not produce functional Dystrophin protein because of a single nucleotide change in their mdx gene. By analogy, this transgenic animal model is used to study DMD pathology, diagnostics, and treatments. Such models are invaluable. Advances in CRISPR-mediated genome editing are likely to bring more and better animal models of disease, thus streamlining R&D efforts (Park 2016).

Biotechnologies are essential to the study of molecular mechanisms of disease. DNA sequencing, cataloging, and database mining facilitate the identification of putative disease-associated genes. ‘omic technologies, such as DNA microarrays and RNA sequencing, help identify biomarkers that warrant follow-up study. rDNA, genome editing, and RNAi technologies are required for the development of knockout/-in/-down mutants. PCR and its derivatives, DNA sequencing, blots, DNA microarray, and ELISAs are used to confirm genetic modification of cells/tissues/ organisms as well as phenotypically assess them. GM cells and organisms are used for models of disease; powerful tools for drug discovery and diagnostic development. In short, molecular mechanisms of disease are understood through the careful application of biotechnological bioassays.

 
Source
< Prev   CONTENTS   Source   Next >