Prairie Queen

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Simulate_PCR for amplicon prediction and annotation from multiplex, degenerate primers and probes

BACKGROUND: Pairing up primers to amplify desired targets and avoid undesired cross reactions can be a combinatorial challenge. Effective prediction of specificity and inclusivity from multiplexed primers and TaqMan®/Luminex® probes is a critical step in PCR design. RESULTS: Code is described to identify all primer and probe combinations from a list of unpaired, unordered candidates that should produce a product. It predicts and extracts all amplicon sequences in a large sequence database from a list of primers and probes, allowing degenerate bases and user-specified levels of primer-target mismatch tolerance. Amplicons hit by TaqMan®/Luminex® probes are indicated, and products may be annotated with gene information from NCBI. Fragment length distributions are calculated to predict electrophoretic gel banding patterns. CONCLUSIONS: Simulate_PCR is the only freely available software that can be run from the command line for high throughput applications which can calculate all products from large lists of primers and probes compared to a large sequence database such as nt. It requires no prior knowledge of how primers should be paired. Degenerate bases are allowed and entire amplicon sequences are extracted and annotated with gene information. Examples are provided for sets of TaqMan®/Luminex® PCR signatures predicted to amplify all HIV-1 genomes, all Coronaviridae genomes, and a group of antibiotic resistance genes. The software is a command line perl script freely available as open source

Shape Memory Polymer Resonators as Highly Sensitive Uncooled Infrared Detectors

Uncooled InfraRed (IR) detectors have enabled the rapid growth of thermal imaging applications. These detectors are predominantly bolometers, where the heating of pixel from incoming IR radiation is read out as a resistance change. Another uncooled sensing method is to transduce the IR radiation into the frequency shift of a mechanical resonator. We present here a highly sensitive, simple to fabricate resonant IR sensor, based on thermo-responsive Shape Memory Polymers (SMPs). By exploiting the phase-change polymer as the transduction mechanism, our approach provides 2 orders of magnitude improvement of the temperature coefficient of frequency (TCF). The SMP has very good absorption in IR wavelengths, obviating the need for an absorber layer. A Noise Equivalent Temperature Difference (NETD) of 22 mK in vacuum and 112 mK in air are obtained using f/2 optics. Such high performance in air eliminates the need for vacuum packaging, paving a path towards flexible IR sensors

A microbial detection array (MDA) for viral and bacterial detection

BACKGROUND: Identifying the bacteria and viruses present in a complex sample is useful in disease diagnostics, product safety, environmental characterization, and research. Array-based methods have proven utility to detect in a single assay at a reasonable cost any microbe from the thousands that have been sequenced. METHODS: We designed a pan-Microbial Detection Array (MDA) to detect all known viruses (including phages), bacteria and plasmids and developed a novel statistical analysis method to identify mixtures of organisms from complex samples hybridized to the array. The array has broader coverage of bacterial and viral targets and is based on more recent sequence data and more probes per target than other microbial detection/discovery arrays in the literature. Family-specific probes were selected for all sequenced viral and bacterial complete genomes, segments, and plasmids. Probes were designed to tolerate some sequence variation to enable detection of divergent species with homology to sequenced organisms, and to have no significant matches to the human genome sequence. RESULTS: In blinded testing on spiked samples with single or multiple viruses, the MDA was able to correctly identify species or strains. In clinical fecal, serum, and respiratory samples, the MDA was able to detect and characterize multiple viruses, phage, and bacteria in a sample to the family and species level, as confirmed by PCR. CONCLUSIONS: The MDA can be used to identify the suite of viruses and bacteria present in complex samples

Draft versus finished sequence data for DNA and protein diagnostic signature development

Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop high-quality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors or NNs) to sequence. We use SAP to assess whether draft data are sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high-quality draft with error rates of 10(−3)–10(−5) (∼8× coverage) of target organisms is suitable for DNA signature prediction. Low-quality draft with error rates of ∼1% (3× to 6× coverage) of target isolates is inadequate for DNA signature prediction, although low-quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high-quality draft of target and low-quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures

DNA signatures for detecting genetic engineering in bacteria

Using newly designed computational tools we show that, despite substantial shared sequences between natural plasmids and artificial vector sequences, a robust set of DNA oligomers can be identified that can differentiate artificial vector sequences from all available background viral and bacterial genomes and natural plasmids. We predict that these tools can achieve very high sensitivity and specificity rates for detecting new unsequenced vectors in microarray-based bioassays. Such DNA signatures could be important in detecting genetically engineered bacteria in environmental samples

SSIVP: Spacecraft Supercomputing Experiment for STP-H6

The Department of Defense Space Test Program (STP) provides spaceflight opportunities for conducting on-orbit research and technology demonstrations to advance the future of spacecraft. STP-H6, the next mission of the program to the International Space Station (ISS), will include a prototype spacecraft supercomputing experiment and framework, called Spacecraft Supercomputing for Image and Video Processing (SSIVP), developed at the National Science Foundation (NSF) Center for High-Performance Reconfigurable Computing (CHREC) at the University of Pittsburgh. SSIVP introduces scalable, high-performance computing (HPC) principles to a CubeSat form-factor to advance the state of the art in space computing. SSIVP adopts the CHREC Space Processor (CSP) concept, a multifaceted design philosophy for a hybrid system of commercial and radiation-hardened (rad-hard) components supplemented with fault-tolerant computing, and a hybrid processor combining fixed-logic CPU and reconfigurable-logic FPGA. SSIVP features five flight-qualified CSPv1 computers as compute nodes, to facilitate this supercomputing concept, and one μCSP smart module, for running a Gallium Nitride (GaN)-based power converter sub-experiment. SSIVP is a versatile, heterogenous platform capable of processing application workloads in the processor or on runtime-reconfigurable FPGA accelerators. In this paper, we present the flight hardware and software, frameworks for parallel and dependable computing, and mission objectives for SSIVP

Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions

The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ∼24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation