Team:BGU Israel/Project/Intelligent Medication

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Background


The Problem:
The Goal:

Mechanism


Results


Background


As part of our body’s metabolism, insulin is secreted from the pancreas and is in charge of absorbing glucose from the blood into our liver cells. Insulin receptors bind insulin and a downstream cellular process leads to the opening of glucose transporters. Resistance of the liver cells to insulin could lead to hyperglycemia, an increase of sugar in the blood, which increases the risk of diabetes type 2, heart diseases and blood disorders. In addition, insulin resistance leads to an increase in insulin in the blood which could result in expansion of the fatty tissues in our body. According to recent studies, such insulin resistance could be increased due to gain of body weight (Abbasi, Brown Jr, Lamendola, McLaughlin, & Reaven, 2002).

A common treatment for insulin resistance up to this day is by injecting a high dose of insulin to patients in order to increase glucose absorption. However, since insulin is a growth factor, this treatment often leads to the development of cancer therefore an alternative treatment is highly needed (Bowker, Majumdar, Veugelers, & Johnson, 2006).

It is known that insulin resistance show significant decrease in the downstream reaction of insulin signal transduction which occurs due to attenuated or diminished signaling from the receptors. Based on many studies, it has been found that protein tyrosine phosphatase N1 (PTPN1) has a major role in insulin signaling by dephosphorylating the insulin receptor and inactivating it. Moreover, it has been discovered that insulin receptor activity can be enhanced by the inhibition of PTPN1, making it a novel target for reducing insulin resistance (Johnson, Ermolieff, & Jirousek, 2002).


With today’s advanced tools and technology, scientists are able to shut down, or silence, the expression of specific genes in a systemic manner using RNA interference (RNAi). However, while the expression of a protein could have a negative effect in one tissue, it might be essential for another tissue to function correctly. Shutting down the expression of a protein systemically could lead to dangerous side effects.

This is the case with PTPN1. While the liver and skeletal muscles are most sensitive to insulin, other tissues have different degrees of sensitivity. Since insulin is essentially a growth factor, as mentioned above, increasing the sensitivity to insulin in tissues other than liver and skeletal muscles could potentially lead to cancer and other side effects.

A common strategy employed in order to overcome this side effect is targeted delivery, which would ensure the arrival of siRNA only to a desired tissue. We chose a different approach, in which a “smart” siRNA molecule is given systemically, but can sense its location and activate silencing only in a specific pre-determined tissue. In other words, we wanted to design a construct which would identify its location, and if it would sense it is inside liver cells, it would shut down the expression of PTPN1.

Mechanism


We based our design on “Conditional Dicer Substrate Formation via Shape and Sequence Transduction with Small Conditional RNAs” (Hochrein, Schwarzkopf, Shahgholi, Yin, & Pierce, 2013).

To implement our idea we engineered a small conditional RNA (scRNA) that upon binding to ‘mRNA detection target’ or ‘trigger’, undergoes a secondary structure change to form a Dicer substrate. The Dicer product is an siRNA that targets the ‘target mRNA’ for destruction.

Starting with a duplex scRNA A•B, the detection target X mediates displacement of A (red strand) from B (green strand) to yield a hairpin B with a 2-nt 3′-overhang, which is a Dicer substrate.

we will silence PTP1B using RNA interference and unique hairpin structure that will open as response to apolipoprotein 3 trigger, this molecule present naturally in the liver cells . For this trial, we programmed a software that can plan the best- preferred sequence for building the hairpin, given the target and the trigger gene and using on-line relevant information. This new tool can be a great facilitation for different and variant research purposes.

Click on the picture to check out the machanism

Figure 2 – Need to put content.

References

Abbasi, F., Brown Jr, B. W., Lamendola, C., McLaughlin, T., & Reaven, G. M. (2002). Relationship between obesity, insulin resistance, and coronary heart disease risk. Journal of the American College of Cardiology, 40(5), 937–943.

Bowker, S., Majumdar, S., Veugelers, P., & Johnson, J. (2006). Increased Cancer-Related Mortality for Patients with Type 2 Diabetes who use Sulfonylureas or Insulin. Diabetes Care, 29(2), 254–258.

Hochrein, L. M., Schwarzkopf, M., Shahgholi, M., Yin, P., & Pierce, N. a. (2013). Conditional Dicer substrate formation via shape and sequence transduction with small conditional RNAs. Journal of the American Chemical Society, 135(46), 17322–30.

Johnson, T. O., Ermolieff, J., & Jirousek, M. R. (2002). Protein tyrosine phosphatase 1B inhibitors for diabetes. Nature Reviews. Drug Discovery, 1(9), 696–709.

http://medicalgenomics.org/details_view_limited?db=rna_seq_atlas&gene_id=345