New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence.

MOTIVATION: It has long been hypothesized that incorporating models of network noise as well as edge directions and known pathway information into the representation of protein-protein interaction (PPI) networks might improve their utility for functional inference. However, a simple way to do this has not been obvious. We find that diffusion state distance (DSD), our recent diffusion-based metric for measuring dissimilarity in PPI networks, has natural extensions that incorporate confidence, directions and can even express coherent pathways by calculating DSD on an augmented graph. RESULTS: We define three incremental versions of DSD which we term cDSD, caDSD and capDSD, where the capDSD matrix incorporates confidence, known directed edges, and pathways into the measure of how similar each pair of nodes is according to the structure of the PPI network. We test four popular function prediction methods (majority vote, weighted majority vote, multi-way cut and functional flow) using these different matrices on the Baker's yeast PPI network in cross-validation. The best performing method is weighted majority vote using capDSD. We then test the performance of our augmented DSD methods on an integrated heterogeneous set of protein association edges from the STRING database. The superior performance of capDSD in this context confirms that treating the pathways as probabilistic units is more powerful than simply incorporating pathway edges independently into the network. AVAILABILITY: All source code for calculating the confidences, for extracting pathway information from KEGG XML files, and for calculating the cDSD, caDSD and capDSD matrices are available from http://dsd.cs.tufts.edu/capdsd

Multiplexed direct detection of barcoded protein reporters on a nanopore array.

Detection of specific proteins using nanopores is currently challenging. To address this challenge, we developed a collection of over twenty nanopore-addressable protein tags engineered as reporters (NanoporeTERs, or NTERs). NTERs are constructed with a secretion tag, folded domain and a nanopore-targeting C-terminal tail in which arbitrary peptide barcodes can be encoded. We demonstrate simultaneous detection of up to nine NTERs expressed in bacterial or human cells using MinION nanopore sensor arrays.

A nanopore interface for higher bandwidth DNA computing.

DNA has emerged as a powerful substrate for programming information processing machines at the nanoscale. Among the DNA computing primitives used today, DNA strand displacement (DSD) is arguably the most popular, with DSD-based circuit applications ranging from disease diagnostics to molecular artificial neural networks. The outputs of DSD circuits are generally read using fluorescence spectroscopy. However, due to the spectral overlap of typical small-molecule fluorescent reporters, the number of unique outputs that can be detected in parallel is limited, requiring complex optical setups or spatial isolation of reactions to make output bandwidths scalable. Here, we present a multiplexable sequencing-free readout method that enables real-time, kinetic measurement of DSD circuit activity through highly parallel, direct detection of barcoded output strands using nanopore sensor array technology (Oxford Nanopore Technologies' MinION device). These results increase DSD output bandwidth by an order of magnitude over what is currently feasible with fluorescence spectroscopy.

Rapid and robust assembly and decoding of molecular tags with DNA-based nanopore signatures.

Molecular tagging is an approach to labeling physical objects using DNA or other molecules that can be used when methods such as RFID tags and QR codes are unsuitable. No molecular tagging method exists that is inexpensive, fast and reliable to decode, and usable in minimal resource environments to create or read tags. To address this, we present Porcupine, an end-user molecular tagging system featuring DNA-based tags readable within seconds using a portable nanopore device. Porcupine's digital bits are represented by the presence or absence of distinct DNA strands, called molecular bits (molbits). We classify molbits directly from raw nanopore signal, avoiding basecalling. To extend shelf life, decrease readout time, and make tags robust to environmental contamination, molbits are prepared for readout during tag assembly and can be stabilized by dehydration. The result is an extensible, real-time, high accuracy tagging system that includes an approach to developing highly separable barcodes.

Histoimmunogenetics Markup Language 1.0: Reporting next generation sequencing-based HLA and KIR genotyping.

We present an electronic format for exchanging data for HLA and KIR genotyping with extensions for next-generation sequencing (NGS). This format addresses NGS data exchange by refining the Histoimmunogenetics Markup Language (HML) to conform to the proposed Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines (miring.immunogenomics.org). Our refinements of HML include two major additions. First, NGS is supported by new XML structures to capture additional NGS data and metadata required to produce a genotyping result, including analysis-dependent (dynamic) and method-dependent (static) components. A full genotype, consensus sequence, and the surrounding metadata are included directly, while the raw sequence reads and platform documentation are externally referenced. Second, genotype ambiguity is fully represented by integrating Genotype List Strings, which use a hierarchical set of delimiters to represent allele and genotype ambiguity in a complete and accurate fashion. HML also continues to enable the transmission of legacy methods (e.g. site-specific oligonucleotide, sequence-specific priming, and Sequence Based Typing (SBT)), adding features such as allowing multiple group-specific sequencing primers, and fully leveraging techniques that combine multiple methods to obtain a single result, such as SBT integrated with NGS.