| 1. |
- Meinecke, Christoph R., et al.
(författare)
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Nanolithographic Fabrication Technologies for Network-Based Biocomputation Devices
- 2023
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Ingår i: Materials. - : MDPI. - 1996-1944. ; 16:3
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Tidskriftsartikel (refereegranskat)abstract
- Network-based biocomputation (NBC) relies on accurate guiding of biological agents through nanofabricated channels produced by lithographic patterning techniques. Here, we report on the large-scale, wafer-level fabrication of optimized microfluidic channel networks (NBC networks) using electron-beam lithography as the central method. To confirm the functionality of these NBC networks, we solve an instance of a classical non-deterministic-polynomial-time complete ("NP-complete") problem, the subset-sum problem. The propagation of cytoskeletal filaments, e.g., molecular motor-propelled microtubules or actin filaments, relies on a combination of physical and chemical guiding along the channels of an NBC network. Therefore, the nanofabricated channels have to fulfill specific requirements with respect to the biochemical treatment as well as the geometrical confienement, with walls surrounding the floors where functional molecular motors attach. We show how the material stack used for the NBC network can be optimized so that the motor-proteins attach themselves in functional form only to the floor of the channels. Further optimizations in the nanolithographic fabrication processes greatly improve the smoothness of the channel walls and floors, while optimizations in motor-protein expression and purification improve the activity of the motor proteins, and therefore, the motility of the filaments. Together, these optimizations provide us with the opportunity to increase the reliability of our NBC devices. In the future, we expect that these nanolithographic fabrication technologies will enable production of large-scale NBC networks intended to solve substantially larger combinatorial problems that are currently outside the capabilities of conventional software-based solvers.
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| 2. |
- Rahman, Mohammad A., et al.
(författare)
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Regeneration of Assembled, Molecular-Motor-Based Bionanodevices
- 2019
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Ingår i: Nano Letters. - : American Chemical Society (ACS). - 1530-6984 .- 1530-6992. ; 19:10, s. 7155-7163
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Tidskriftsartikel (refereegranskat)abstract
- The guided gliding of cytoskeletal filaments, driven by biomolecular motors on nano/microstructured chips, enables novel applications in biosensing and biocomputation. However, expensive and time-consuming chip production hampers the developments. It is therefore important to establish protocols to regenerate the chips, preferably without the need to dismantle the assembled microfluidic devices which contain the structured chips. We here describe a novel method toward this end. Specifically, we use the small, nonselective proteolytic enzyme, proteinase K to cleave all surface-adsorbed proteins, including myosin and kinesin motors. Subsequently, we apply a detergent (5% SDS or 0.05% Triton X100) to remove the protein remnants. After this procedure, fresh motor proteins and filaments can be added for new experiments. Both, silanized glass surfaces for actin-myosin motility and pure glass surfaces for microtubule-kinesin motility were repeatedly regenerated using this approach. Moreover, we demonstrate the applicability of the method for the regeneration of nano/microstructured silicon-based chips with selectively functionalized areas for supporting or suppressing gliding motility for both motor systems. The results substantiate the versatility and a promising broad use of the method for regenerating a wide range of protein-based nano/microdevices.
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| 3. |
- Surendiran, Pradheebha, et al.
(författare)
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Solving Exact Cover Instances with Molecular-Motor-Powered Network-Based Biocomputation
- 2022
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Ingår i: ACS Nanoscience Au. - : American Chemical Society (ACS). - 2694-2496 .- 2694-2496.
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Tidskriftsartikel (refereegranskat)abstract
- Information processing by traditional, serial electronic processors consumes an ever-increasing part of the global electricity supply. An alternative, highly energy efficient, parallel computing paradigm is network-based biocomputation (NBC). In NBC a given combinatorial problem is encoded into a nanofabricated, modular network. Parallel exploration of the network by a very large number of independent molecular-motor-propelled protein filaments solves the encoded problem. Here we demonstrate a significant scale-up of this technology by solving four instances of Exact Cover, a nondeterministic polynomial time (NP) complete problem with applications in resource scheduling. The difficulty of the largest instances solved here is 128 times greater in comparison to the current state of the art for NBC.
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