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Discovering new long non-coding RNAs (lncRNAs) has been a fundamental step in lncRNA-related research. Nowadays, many machine learning-based tools have been developed for lncRNA identification. However, many methods predict lncRNAs using sequence-derived features alone, which tend to display unstable performances on different species. Moreover, the majority of tools cannot be re-trained or tailored by users and neither can the features be customized or integrated to meet researchers’ requirements. In this study, features extracted from sequence-intrinsic composition, secondary structure and physicochemical property are comprehensively reviewed and evaluated. An integrated platform named LncFinder is also developed to enhance the performance and promote the research of lncRNA identification. LncFinder includes a novel lncRNA predictor using the heterologous features we designed. Experimental results show that our method outperforms several state-of-the-art tools on multiple species with more robust and satisfactory results. Researchers can additionally employ LncFinder to extract various classic features, build classifier with numerous machine learning algorithms and evaluate classifier performance effectively and efficiently. LncFinder can reveal the properties of lncRNA and mRNA from various perspectives and further inspire lncRNA–protein interaction prediction and lncRNA evolution analysis. It is anticipated that LncFinder can significantly facilitate lncRNA-related research, especially for the poorly explored species. LncFinder is released as R package (https://CRAN.R-project.org/package=LncFinder). A web server (http://bmbl.sdstate.edu/lncfinder/) is also developed to maximize its availability.

In one more years, we will ‘celebrate’ an exact centenary of the Spanish flu pandemic. With the rapid evolution of the influenza virus, the possibility of novel pandemic remains ever a concern. This review covers our current knowledge of the influenza A virus: on the role of RNA in translation, replication, what is known of the expressed proteins and the protein products generated from alternative splicing, and on the role of base pairing in RNA structure. We highlight the main events associated with viral entry into the cell, the transcription and replication process, an export of the viral genetic material from the nucleus and the final release of the virus. We discuss the observed potential roles of RNA secondary structure (the RNA base-pairing arrangement) and RNA/RNA interactions in this scheme.

Colorimetric detection with smartphones is ideal for point-of-care measurements because the signal reader is easily available. Densitometric detection schemes enable semiquantitative measurements but require a lightproof box to control photographic conditions and/or extensive data treatment to extract information. Approaches based on pattern recognition are not so sensitive to light artifacts but can only yield a yes/no type of answer when the signal is above or below a certain threshold. Here, we introduce a new method for detecting different concentrations of proteins as well as light artifacts with origami immunosensors and digital logic. The origami design consists of a folded piece of paper with three identical biorecognition sites so that one drop of sample generates three colorimetric signals simultaneously. The three colorimetric signals are then evaluated with an augmented reality app that generates a virtual semaphore that sequentially turns on its green, yellow, and red lights depending on the concentration of analyte. These three Boolean variables pass through "and" and "not" logic gates in a 3-to-8 decoder that enables the semiquantitative detection of proteins and adds a failsafe against erroneous results. The proposed method can detect the model analyte mouse IgG with a limit of detection and sensitivity comparable to densitometry performed under light-controlled conditions. It can also detect the sepsis biomarker procalcitonin at clinically relevant concentrations. With our approach, the detection is performed in real time, and signal processing is not required, which makes it suitable for rapid analyses by nonspecialists at the point of need.

Under many in vitro conditions, some small viruses spontaneously encapsidate a single stranded (ss) RNA into a protein shell called the capsid. While viral RNAs are found to be compact and highly branched because of long distance base-pairing between nucleotides, recent experiments reveal that in a head-to-head competition between an ssRNA with no secondary or higher order structure and a viral RNA, the capsid proteins preferentially encapsulate the linear polymer! In this paper, we study the impact of genome stiffness on the encapsidation free energy of the complex of RNA and capsid proteins. We show that an increase in effective chain stiffness because of base-pairing could be the reason why under certain conditions linear chains have an advantage over branched chains when it comes to encapsidation efficiency. While branching makes the genome more compact, RNA base-pairing increases the effective Kuhn length of the RNA molecule, which could result in an increase of the free energy of RNA confinement, that is, the work required to encapsidate RNA, and thus less efficient packaging.

Genomes of single-stranded RNA viruses have evolved to optimize several concurrent properties. One of them is the architecture of their genomic folds, which must not only feature precise structural elements at specific positions, but also allow for overall spatial compactness. The latter was shown to be disrupted by random synonymous mutations, a disruption which can consequently negatively affect genome encapsidation. In this study, we use three mutation schemes with different degrees of locality to mutate the genomes of phage MS2 and Brome Mosaic virus in order to understand the observed sensitivity of the global compactness of their folds. We find that mutating local stretches of their genomes’ sequence or structure is less disruptive to their compactness compared to inducing randomly-distributed mutations. Our findings are indicative of a mechanism for the conservation of compactness acting on a global scale of the genomes, and have several implications for understanding the interplay between local and global architecture of viral RNA genomes.

The excessive use of antibiotics in food-producing animals causes a steady rise of multiple antibiotic resistance in foodborne bacteria. Next to sulfonamides, the most common antibiotics groups are fluoroquinolones, aminoglycosides, and &szlig, lactams. Therefore, there is a need for a quick, efficient, and low-cost detection procedure for antibiotics. In this study, we propose an inkjet-printed aptamer-based biosensor developed for the detection of the fluoroquinolone ciprofloxacin. Due to their extraordinary high affinity and specificity, aptamers are already widely used in various applications. Here we present a ciprofloxacin-binding RNA aptamer developed by systematic evolution of ligands by exponential enrichment (SELEX). We characterized the secondary structure of the aptamer and determined the KD to 36 nM that allow detection of antibiotic contamination in a relevant range. We demonstrate that RNA aptamers can be inkjet-printed, dried, and resolved while keeping their functionality consistently intact. With this proof of concept, we are paving the way for a potential range of additional aptamer-based, printable biosensors.

A multiplexed solid-phase nucleic acid hybridization assay on a paper-based platform is presented using multicolor immobilized quantum dots (QDs) as donors in fluorescence resonance energy transfer (FRET). The surface of paper was modified with imidazole groups to immobilize two types of QD-probe oligonucleotide conjugates that were assembled in solution. Green-emitting QDs (gQDs) and red-emitting QDs (rQDs) served as donors with Cy3 and Alexa Fluor 647 (A647) acceptors. The gQD/Cy3 FRET pair served as an internal standard, while the rQD/A647 FRET pair served as a detection channel, combining the control and analytical test zones in one physical location. Hybridization of dye-labeled oligonucleotide targets provided the proximity for FRET sensitized emission from the acceptor dyes, which served as an analytical signal. Hybridization assays in the multicolor format provided a limit of detection of 90 fmol and an upper limit of dynamic range of 3.5 pmol. The use of an array of detection zones was designed to provide improved analytical figures of merit compared to that which could be achieved on one type of array design in terms of relative concentration of multicolor QDs. The hybridization assays showed excellent resistance to nonspecific adsorption of oligonucleotides. Selectivity of the two-plex hybridization assay was demonstrated by single nucleotide polymorphism (SNP) detection at a contrast ratio of 50:1. Additionally, it is shown that the use of preformed QD-probe oligonucleotide conjugates and consideration of the relative number density of the two types of QD-probe conjugates in the two-color assay format is advantageous to maximize assay sensitivity and the upper limit of dynamic range.

SummarySynthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides an alternate, versatile venue for synthetic biologists to operate and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze dried onto paper, enabling the inexpensive, sterile, and abiotic distribution of synthetic-biology-based technologies for the clinic, global health, industry, research, and education. For field use, we create circuits with colorimetric outputs for detection by eye and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small-molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors.