Stabilities of HIV-1 DIS type RNA loop–loop interactions in vitro and in vivo

RNA loop–loop interactions are a prevalent motif in the formation of tertiary structure and are well suited to trigger molecular recognition between RNA molecules. We determined the stabilities of several loop–loop interactions with a constant 6 bp core sequence and varying unpaired flanking nucleotides and found that the flanking bases have a strong influence on the stability and ion dependence of the kissing complex. In general, the stabilities determined in 1 M Na(+) are equivalent to those in the presence of near physiological Mg(2+) concentrations. Therefore we further tested whether the stabilities determined in vitro and within yeast cells correlate, using a recently developed yeast RNA-hybrid system. For the majority of the loop types analyzed here, the melting temperatures determined in vitro are in good agreement with the relative β-galactosidase activity in yeast cells, showing that data derived from in vitro measurements reflect in vivo properties. The most stable interactions are the naturally occurring HIV-1 DIS MAL and LAI derived loops with the motif (5′ A(A)/(G)N(6)A 3′), emphasizing the crucial role of stable kissing complexes in HIV genome dimerization

Fully flexible analysis of behavioural sequences based on parametric survival models with frailties—A tutorial

Recent automated systems allow collecting continuous data on individual animals with high accuracy over a long time. During this time, animals can be traced across different (discrete) types of behavioural states, with the duration in each state being known. Nevertheless, analyses of such sequences of states or behaviours may prove difficult. Classic Markov-chain methods have limitations in respect to incorporating “memory” (effects of past states), the duration in the states and accounting for dependencies. Dependencies occur in many data sets, where, for example a variety of individuals from different groups are observed and/or when an experiment is divided in different crossover treatment phases. So-called parametric survival analysis with frailties can incorporate aforementioned aspects in one coherent model. The time spent in a specific state (performing a specific behaviour) can be modelled in dependence of the subsequent state (transition probabilities) while incorporating how these transitions are influenced by experimental treatments. In addition, prior states can be used as predictor variables (accounting for past behaviour). Finally, random effects can be included to account for dependencies according to, for example individual identity, group/farm/laboratory or experimental period. Using interactions between random and fixed effects, the within- and between-subject variability of the transition probabilities can be estimated to indicate variation between and consistency within individual subjects (individuality and personality). Moreover, relative hazards describing transitions from one state to several potential follow-up states can be estimated. Behavioural sequences and their modulation by experimental situations can be studied accordingly. Using two exemplary data sets, the data type and structure adequate for parametric survival analysis are introduced and advice is given on how to specify and run such models. Overall, parametric survival analysis with frailties presents a modern and versatile approach that can revive sequential analysis. This will facilitate more detailed use of behavioural data and accordingly detect more subtle aspects of behaviour.Ministerie van Economische Zaken en Klimaat http://dx.doi.org/10.13039/501100016238Bundesamt für Lebensmittelsicherheit und Veterinärwesen http://dx.doi.org/10.13039/501100006454Peer Reviewe

RNA chaperone activity and RNA-binding properties of the E. coli protein StpA

The E. coli protein StpA has RNA annealing and strand displacement activities and it promotes folding of RNAs by loosening their structures. To understand the mode of action of StpA, we analysed the relationship of its RNA chaperone activity to its RNA-binding properties. For acceleration of annealing of two short RNAs, StpA binds both molecules simultaneously, showing that annealing is promoted by crowding. StpA binds weakly to RNA with a preference for unstructured molecules. Binding of StpA to RNA is strongly dependent on the ionic strength, suggesting that the interactions are mainly electrostatic. A mutant variant of the protein, with a glycine to valine change in the nucleic-acid-binding domain, displays weaker RNA binding but higher RNA chaperone activity. This suggests that the RNA chaperone activity of StpA results from weak and transient interactions rather than from tight binding to RNA. We further discuss the role that structural disorder in proteins may play in chaperoning RNA folding, using bioinformatic sequence analysis tools, and provide evidence for the importance of conformational disorder and local structural preformation of chaperone nucleic-acid-binding sites

Antifungal defense of probiotic Lactobacillus rhamnosus GG is mediated by blocking adhesion and nutrient depletion

Data Availability: All relevant data are available from the Gene Expression Omnibus at the following accession number: GSE97755. Funding: This work was funded by the German Research Council (DFG) Graduation College 685, Dr. Jekyll and Mr. Hyde: A systems approach to the therapy of nosocomial infections caused by Candida albicans: a commensal organism switches to a deadly pathogen/ PTJ (FKZ: 0315409BBMBF), the Dr. Manfred Plempel-foundation, the Dr. Siegried Stettendorf-Foundation, the InfectERA Program (FunComPath; BMBF FKZ 031L0001A), the Integrated Research and Treatment Center for Sepsis Control and Care (CSCC) project CanBac (BMBF, FKZ: 01EO1002), and the German Research Council (DFG) GZ:HE7565/1-1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Monitoring Genomic Sequences during SELEX Using High-Throughput Sequencing: Neutral SELEX

Background: SELEX is a well established in vitro selection tool to analyze the structure of ligand-binding nucleic acid sequences called aptamers. Genomic SELEX transforms SELEX into a tool to discover novel, genomically encoded RNA or DNA sequences binding a ligand of interest, called genomic aptamers. Concerns have been raised regarding requirements imposed on RNA sequences undergoing SELEX selection. Methodology/Principal Findings: To evaluate SELEX and assess the extent of these effects, we designed and performed a Neutral SELEX experiment omitting the selection step, such that the sequences are under the sole selective pressure of SELEX’s amplification steps. Using high-throughput sequencing, we obtained thousands of full-length sequences from the initial genomic library and the pools after each of the 10 rounds of Neutral SELEX. We compared these to sequences obtained from a Genomic SELEX experiment deriving from the same initial library, but screening for RNAs binding with high affinity to the E. coli regulator protein Hfq. With each round of Neutral SELEX, sequences became less stable and changed in nucleotide content, but no sequences were enriched. In contrast, we detected substantial enrichment in the Hfq-selected set with enriched sequences having structural stability similar to the neutral sequences but with significantly different nucleotide selection. Conclusions/Significance: Our data indicate that positive selection in SELEX acts independently of the neutral selectiv

Fully flexible analysis of behavioural sequences based on parametric survival models with frailties: A tutorial

Recent automated systems allow collecting continuous data on individual animals with high accuracy over a long time. During this time, animals can be traced across different (discrete) types of behavioural states, with the duration in each state being known. Nevertheless, analyses of such sequences of states or behaviours may prove difficult. Classic Markov-chain methods have limitations in respect to incorporating “memory” (effects of past states), the duration in the states and accounting for dependencies. Dependencies occur in many data sets, where, for example a variety of individuals from different groups are observed and/or when an experiment is divided in different crossover treatment phases. So-called parametric survival analysis with frailties can incorporate aforementioned aspects in one coherent model. The time spent in a specific state (performing a specific behaviour) can be modelled in dependence of the subsequent state (transition probabilities) while incorporating how these transitions are influenced by experimental treatments. In addition, prior states can be used as predictor variables (accounting for past behaviour). Finally, random effects can be included to account for dependencies according to, for example individual identity, group/farm/laboratory or experimental period. Using interactions between random and fixed effects, the within- and between-subject variability of the transition probabilities can be estimated to indicate variation between and consistency within individual subjects (individuality and personality). Moreover, relative hazards describing transitions from one state to several potential follow-up states can be estimated. Behavioural sequences and their modulation by experimental situations can be studied accordingly. Using two exemplary data sets, the data type and structure adequate for parametric survival analysis are introduced and advice is given on how to specify and run such models. Overall, parametric survival analysis with frailties presents a modern and versatile approach that can revive sequential analysis. This will facilitate more detailed use of behavioural data and accordingly detect more subtle aspects of behaviour