Detection of biomolecules at low abundances is crucial to the rapid diagnosis of disease. Impressive sensitivities, typically measured with small model analytes, have been obtained with a variety of nano- and microscale sensors. A remaining challenge, however, is the rapid detection of large native biomolecules in real biological samples. Here we develop and investigate a sensor system that directly addresses the source of this challenge: the slow diffusion of large biomolecules traveling through solution to fixed sensors, and inefficient complexation of target molecules with immobilized probes. We engineer arrayed sensors on two distinct length scales: a ∼100 μm length scale commensurable with the distance bacterial mRNA can travel in the 30 min sample-to-answer duration urgently required in point-of-need diagnostic applications; and the nanometer length scale we prove necessary for efficient target capture. We challenge the specificity of our hierarchical nanotextured microsensors using crude bacterial lysates and document the first electronic chip to sense trace levels of bacteria in under 30 min.

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BackgroundWith the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence.FindingsUsing the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput.ConclusionsBarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net