Biomolecules circulating within an organism can be likened to a data stream, providing valuable information that can be accessed to identify disease states and processes such as inflammation. Recent studies have focused on developing autonomous devices for this purpose, incorporating biologically derived molecules such as DNA into computing structures capable of analyzing biomolecular input and carrying out logic-gated functions such as cellular analysis and molecule delivery. Magnetic nanoparticles possess inherent properties that make them well suited for such applications.
In a recent publication, M. P. Nikitin et al. demonstrated the capability of nano- and microparticles to be incorporated into autonomous programmable biocomputers to create structures capable of implementing Boolean logic.
Basic design of biocomputing structures
Logic gating was achieved through an interface on the surface of a core particle. The interface was composed of a corona with distinct signal transduction capacities. A specific output action, mediated by an output receptor, was dependent on logic gates. All of the computation and output action implementation capabilities were contained within the structure and dependent solely on received input and the presence of a corresponding output target.
Single-input YES gating systems consisted of input and output receptors co-localized on the core particle’s surface. The receptors assembled such that output receptors were sterically blocked by shielding particles coordinated by the input receptor-input ligand bond. The input action (YES) interrupted said bond, rendering the output receptor accessible to output ligand.
Core particles designed for single-input NOT gated structures contained input receptors, which assembled with input ligand-output receptor conjugate. In the absence of input (NOT), output ligand bound to the core particle via the assembled output receptor, while input (YES) resulted in disassembly of the bond between input ligand and output receptor, preventing output ligand binding to the structure.
Double-input gates were implemented through a combination of the aforementioned operands. The AND logic gates were constructed by mixing the YES/NOT operands, while OR logic gates were achieved through a mixture of YES/NOT/AND structures.
Programming biocomputers to target a cell population
By adjusting the composition of the interface corona, biocomputing structures can be “programmed” to target cells as a result of logic calculations based on biomolecular input. To demonstrate the programmability of their structures, Nikitin et. al. utilized core particles consisting of commercially obtained magnetic nanoparticles coated with glucuronic acid. Wheat germ agglutinin (WGA) served as the output receptor, and cells expressing WGA-specific carbohydrates – namely, human leukemic Jurkat T-cells – served as the target for binding.
Anti-fluorescein (Anti-FLUO) antibody was utilized as the input receptor, and fluorescein (FLUO) label as the corresponding input.
Investigators demonstrated proof-of-concept for both single-input YES(FLUO) and single-input NOT(FLUO) gates. By incorporating chloramphenicol and anti-chloramphenicol as respective input receptor and input ligand, double-input gate functionality was demonstrated as well. Output was measured by quantification of cell-bound structures. Specificity was assessed by assaying binding in the presence of WGA-inhibiting monosaccharide, as well as with hybridoma cells with a different glycosylation profile. Both cases yielded an output of false.
These results have a number of notable implications. Autonomous biocomputing structures have the potential to be utilized for important medical applications, such as logic-gated drug delivery to diseased cells. One of the most significant advantages of the approach is its versatility. The sensory interface can be modified to assess a wide range of inputs. While the present study focused on protein-based interfaces, incorporating other types of molecules is theoretically possible.
A full report of the findings published by Nikitin et. al. can be found online in “Nature Nanotechnology”.