Team:MIT/miRNA

From 2014.igem.org

(Difference between revisions)
Line 23: Line 23:
<li><a href="#1">Low Sensor </a></li>
<li><a href="#1">Low Sensor </a></li>
<li><a href="#2">High Sensor </a></li>
<li><a href="#2">High Sensor </a></li>
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<li><a href="#3">L7ae Repression</a></li>
+
<li><a href="#3">L7ae </a></li>
<li><a href="#4">Single-Input </a></li>
<li><a href="#4">Single-Input </a></li>
<li><a href="#5">Multi-Input </a></li>
<li><a href="#5">Multi-Input </a></li>

Revision as of 03:34, 17 October 2014

 


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miRNA Detector Module

sensing Alzheimer's through multi-input miRNA-based logic



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Description

miRNAs (microRNAs) are short, noncoding strands of RNA that facilitate gene silencing - a single miRNA degrades an mRNA through a process involving complementary base-pairing between the miRNA and part of the mRNA sequence. A cell’s miRNA profile comprises the relative levels of all the miRNAs produced by that cell. Because miRNAs play a key role in regulating gene expression, it ought to be expected that a liver cell’s miRNA profile would differ significantly from that of a neuron. But more surprisingly, miRNA profiles can discriminate between identical cells in different conditions.

Neurons afflicted with Alzheimer’s disease display an miRNA profile significantly different from that of healthy neurons (A blood based 12-miRNA signature of Alzheimer disease patients, Leidinger et al, 2013). The miRNA subgroup aimed to use this difference as an approach to detecting Alzheimer’s disease. Our goal was to build a set of genetic sensors to specifically detect the miRNA profile of a neuron with Alzheimer’s and initiate a specific biological response upon doing so.

Our strategy took its inspiration from a similar detection circuit demonstrated to respond to cancer onset (Multi-input RNAi-based logic circuit for identification of specific cancer cells, Xie et al, 2011) Through existing research, we identified six miRNAs that are critically up- or down-regulated in Alzheimer’s neurons. Using the inverting logic inherent to miRNAs, we designed detection circuits to release a response factor upon sensing either heightened or lowered levels of their target miRNA, and customized each circuit to use one of the six miRNAs as its input. Using the principles of combinational logic, we can integrate the inputs from all six of our miRNA sensors, and actuate our response only when all six miRNAs meet their critical threshold concentrations. This ensures excellent specificity for our circuit.

Outcome

The miRNA detection team built individual sensing constructs for each miRNA. We determined input-output relations for our sensors using flow cytometry and found that our sensors respond to miRNA levels by modulating the production of a fluorescent reporter, exactly as we had predicted.

Future work on our sensors will focus largely on implementation concerns - tuning as well as integration. Although we have shown that our sensors respond on a digital level, this does not accurately model the dynamic chemical conditions of the intracellular environment. We would thus like to refine our sensor control. In the ideal case, a small shift in a critical range of miRNA concentration will result in a large output signal, so that the treatment response is both specific and substantial.

We only tested binary combinatorial inputs for our sensors (one high and one low, or two of each). The ultimate goal is to use all six sensors in tandem with one another. When we use more sensors, we achieve greater precision, but as a tradeoff we gain more variables that require keeping track. There is also the complication that the various miRNAs are not biologically present at the same concentrations, meaning that each of our sensors must be individually tuned for optimal response to its own miRNA. Because all six of our sensors actuate the same response, we must also ensure that one sensor does not become overstimulated, activating our treatment even in the absence of input from the other sensors. These are all issues that can only be answered through extensive iterative testing.

The miRNA sensing team has established a conceptual grounding for a detection mechanism that responds to cellular conditions in the fashion of a true biological system. It is worthwhile to note that our strategy is not Alzheimer’s-specific, and can be implemented with any disease with a characteristic miRNA profile. This can be a novel approach for diseases with poorly understood etiologies, such as Parkinson’s (MicroRNA profiling of Parkinson's disease brains identifies early downregulation of miR-34b/c which modulate mitochondrial function, Minones-Moyano, 2011)

Experiments


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Parts

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