We describe a technique for the rapid ab-initio discovery of target-tailored tumoricidal DNA oligonucleotides inside an Illumina sequencing chip. By sequencing oligonucleotide pools we generate a physical microfluidic map of hundreds of millions of potential oligo clusters, in which every cluster is mapped to a specific set of spatial coordinates. Tumor cells, pre-loaded with a fluorogenic reporter of apoptosis, are then injected into the chip and monitored over time. Apoptotic tumor cells are identified and analyzed across the entire map, automatically revealing the coordinates of oligos that induced this effect. We demonstrate this method by identifying, within just a few hours, new oligos capable of directly and selectively inducing apoptosis in primary human tumor cells. Such a major capability could lead to a new paradigm of personalized cancer therapy.

New types of robots inspired by biological principles of assembly, locomotion, and behavior have been recently described. In this work we explored the concept of robots that are based on more fundamental physical phenomena, such as fluid dynamics, and their potential capabilities. We report a robot made entirely of non-Newtonian fluid, driven by shear strains created by spatial patterns of audio waves. We demonstrate various robotic primitives such as locomotion and transport of metallic loads-up to 6-fold heavier than the robot itself-between points on a surface, splitting and merging, shapeshifting, percolation through gratings, and counting to 3. We also utilized interactions between multiple robots carrying chemical loads to drive a bulk chemical synthesis reaction. Free of constraints such as skin or obligatory structural integrity, fluid robots represent a radically different design that could adapt more easily to unfamiliar, hostile, or chaotic environments and carry out tasks that neither living organisms nor conventional machines are capable of.

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The Monty Hall problem is a decision problem with an answer that is surprisingly counter-intuitive yet provably correct. Here we simulate and prove this decision in a highthroughput DNA sequencing machine, using a simple encoding. All possible scenarios are represented by DNA oligonucleotides, and gameplay decisions are implemented by sequencing these oligonucleotides from specific positions, with a single run simulating more than 12,000,000 independent games. This work highlights high-throughput DNA sequencing as a new tool that could extend existing capabilities and enable new encoding schemes for problems in DNA computing.

Our current model of drug discovery is challenged by the relative ineffectiveness of drugs against highly variable and rapidly evolving diseases and their relatively high incidence of adverse effects due to poor selectivity. Here we describe a robust and reproducible platform which could potentially address these limitations. The platform enables rapid, de-novo discovery of DNA aptamers evolved in-vitro to exert specific biological effects on target cells. Unlike conventional aptamers, which are selected by their ligand binding capacity, this platform is driven directly by therapeutic effect and selectivity towards target vs negative target cells. The process could, therefore, operate without any a-priori knowledge (e.g. mutations, biomarker expression, or known drug resistance) of the target. We report the discovery of DNA aptamers with direct and selective cytotoxicity towards several tumor cell lines as well as primary, patient-derived solid and hematological tumors, some with chemotherapy resistance. Aptamers discovered by this platform exhibited favorable biodistribution in animals, persistence in target tumors up to 48 hours after injection, and safety in human blood. These aptamers showed remarkable efficacy in-vivo as well as ex-vivo in freshly obtained, 3D cultured human tumors resistant to multiple chemotherapies. With further improvement, these findings could lead to a drug discovery model which is target-tailored, mechanism-flexible, and nearly on-demand.