How to Use Next-Generation Sequencing to Develop New Drugs


We recently completed a study in which we used next-generation sequencing (NGS) to identify and measure messenger RNA’s (mRNA’s) in cervical (neck) spinal cords from ALS patients and age-matched controls (CTL) that did not have ALS or any other neurological disease. Using a variety of bioinformatics tools, we were able to identify mRNA’s (that are made from DNA genes) that statistically were elevated in the ALS samples (“differentially expressed genes”, DEG), and played a major role in controlling other genes (“hub genes”, HG). We found nine genes that were both DEG’s and HG’s, implying that they played special roles in ALS.

Using engineered circles of DNA, known as “expression plasmids”, we forced cells to acquire these DEG’s/HG’s at levels higher than normal. We did these experiments in human neural stem cells that we made from blood samples of CTL persons. Our reasoning was that if we forced these CTL cells to acquire DEG’s/HG’s from the expression plasmids, we could turn them into cells more like ALS.

We found that if we combined expression plasmids for 6 DEG’s/HG’s in CTL human neural stem cells, we could kill them within 24-48 hours. We showed that this cell death took place if we carefully controlled the conditions of the assay, even when we used equivalent amounts of a control plasmid (that “expressed” nothing).

We have created a cell-based assay that re-creates the molecular genetic conditions found in ALS spinal cords. This test can be used to screen drugs that reduce death in human neural stem cells brought about by expression of the six DEG’s/HG’s we identified in ALS spinal cords. If converted to a “high throughput” system, this kind of test could efficiently screen hundreds-thousands of molecules. Those that reduce cell death in this assay could then be considered for further development as disease-altering therapy in ALS.


Alzheimer’s Disease

We used next-generation sequencing to quantitate both genes that code for proteins (known as “messenger RNA’s”, or mRNA’s) and small RNA’s, known as “micro RNA’s” or miRNA’s, that can regulate the levels of mRNA’s. Together, they form one component of the epigenetic system that can regulate gene expression in brain cells. Because genes ultimately become proteins, miRNA’s can control many critical cell functions, including their survival.

We carried out these two kinds of high-density sequencing on the same RNA samples isolated from brains (frontal cortex) of 10 Alzheimer disease (AD) and 9 Control (CTL, disease-free) subjects that were reasonably well matched for age at death and quality of RNA. By using the same RNA samples for both kinds of sequencing, we could more accurately speculate about miRNA control of mRNA genes in AD brain.

The most important finding of our study is that most of the 145 miRNA’s we examined were lower in AD brain compared to CTL brain. We used software algorithms that predict the strength of interaction of miRNA’s (of which there are >1000 known in humans) with mRNA’s (of which there are ~25,000 in humans). We found 15 mRNA genes in our sample of 55 overexpressed AD genes that were predicted to be regulated by the 2-5 of the miRNA’s we identified as being low in AD brain samples. When one combines these 15 mRNA genes with the other 17 mRNA genes that could be regulated by a single underexpressed-in-AD miRNA, then the majority (58%) of the overexpressed-in-AD mRNA genes are potentially regulated by miRNA’s.

This is a very perplexing outcome. We understand very little about miRNA’s except that they can exert extensive control over levels of the traditional mRNA genes. This part of our “epigenome” can be modified by life experiences. Are there life experiences of people that increase their risk of developing AD? Are there other components of the epigenome that are affected in AD?

A potential “translational” outcome of this study is drug screening. Drugs that might be useful in AD, at least in a subpopulation of AD patients, could be predicted to lower expression of the mRNA genes that are elevated in AD brain, and to raise miRNA levels that are depressed in AD brain. We can use human neural stem cells (made from adult blood cells) of AD subjects to see if this occurs. If this happens, it would form an efficient test to predict drug effectiveness. In this manner, hundreds-thousands of different molecules can be screened by “high-throughput testing”.

Thus, our experiment has two major outcomes. First, we need to do additional studies to see how the epigenome is altered in AD. There are chemical changes (known as “methylation”) made to DNA that are also part of our epigenome, and we isolated DNA samples from the same AD and CTL frontal cortex samples we used to isolate RNA. So we are set up to make direct sample-sample comparisons. Second, we need to find out if our results can form the basis for a high-throughput drug screening test. If this happens, then it is only a matter of time before we acquire an arsenal of drugs that can normalize the underlying molecular biological abnormalities of AD.