Yeast mutations in multiple complementation groups inhibit brome mosaic virus RNA replication and transcription and perturb regulated expression of the viral polymerase-like gene

Brome mosaic virus (BMV), a member of the alphavirus-like superfamily of positive-strand RNA viruses, encodes two proteins, 1a and 2a, that interact with each other, with unidentified host proteins, and with host membranes to form the viral RNA replication complex. Yeast expressing 1a and 2a support replication and subgenomic mRNA synthesis by BMV RNA3 derivatives. Using a multistep selection and screening process, we have isolated yeast mutants in multiple complementation groups that inhibit BMV-directed gene expression. Three complementation groups, represented by mutants mab1–1, mab2–1, and mab3–1 (for maintenance of BMV functions), were selected for initial study. Each of these mutants has a single, recessive, chromosomal mutation that inhibits accumulation of positive- and negative-strand RNA3 and subgenomic mRNA. BMV-directed gene expression was inhibited when the RNA replication template was introduced by in vivo transcription from DNA or by transfection of yeast with in vitro transcripts, confirming that cytoplasmic RNA replication steps were defective. mab1–1, mab2–1, and mab3–1 slowed yeast growth to varying degrees and were temperature-sensitive, showing that the affected genes contribute to normal cell growth. In wild-type yeast, expression of the helicase-like 1a protein increased the accumulation of 2a mRNA and the polymerase-like 2a protein, revealing a new level of viral regulation. In association with their other effects, mab1–1 and mab2–1 blocked the ability of 1a to stimulate 2a mRNA and protein accumulation, whereas mab3–1 had elevated 2a protein accumulation. Together, these results show that BMV RNA replication in yeast depends on multiple host genes, some of which directly or indirectly affect the regulated expression and accumulation of 2a.

αβ T cell receptor interactions with syngeneic and allogeneic ligands: Affinity measurements and crystallization

Cellular immunity is mediated by the interaction of an αβ T cell receptor (TCR) with a peptide presented within the context of a major histocompatibility complex (MHC) molecule. Alloreactive T cells have αβ TCRs that can recognize both self- and foreign peptide–MHC (pMHC) complexes, implying that the TCR has significant complementarity with different pMHC. To characterize the molecular basis for alloreactive TCR recognition of pMHC, we have produced a soluble, recombinant form of an alloreactive αβ T cell receptor in Drosophila melanogaster cells. This recombinant TCR, 2C, is expressed as a correctly paired αβ heterodimer, with the chains covalently connected via a disulfide bond in the C-terminal region. The native conformation of the 2C TCR was probed by surface plasmon resonance (SPR) analysis by using conformation-specific monoclonal antibodies, as well as syngeneic and allogeneic pMHC ligands. The 2C interaction with H-2Kb-dEV8, H-2Kbm3-dEV8, H-2Kb-SIYR, and H-2Ld-p2Ca spans a range of affinities from Kd = 10−4 to 10−6M for the syngeneic (H-2Kb) and allogeneic (H-2Kbm3, H-2Ld) ligands. In general, the syngeneic ligands bind with weaker affinities than the allogeneic ligands, consistent with current threshold models of thymic selection and T cell activation. Crystallization of the 2C TCR required proteolytic trimming of the C-terminal residues of the α and β chains. X-ray quality crystals of complexes of 2C with H-2Kb-dEV8, H-2Kbm3-dEV8 and H-2Kb-SIYR have been grown.

ICB database: the gyrB database for identification and classification of bacteria

The Identification and Classification of Bacteria (ICB) database (http:/www.mbio.co.jp/icb) contains currently available information about the DNA gyrase subunit B (gyrB) gene in bacteria. The database is designed to provide the scientific community with a reference point for using gyrB as an evolutionary and taxonomic marker. Nucleic and amino acid sequence data are currently available for over 850 strains, along with alignments at several different taxonomic levels and an exhaustive review of primer selection and background information.

Induced fit DNA recognition by a minor groove binding analogue of Hoechst 33258: fluctuations in DNA A tract structure investigated by NMR and molecular dynamics simulations

NMR analysis and molecular dynamics simulations of d(GGTAATTACC)2 and its complex with a tetrahydropyrimidinium analogue of Hoechst 33258 suggest that DNA minor groove recognition in solution involves a combination of conformational selection and induced fit, rather than binding to a preorganised site. Analysis of structural fluctuations in the bound and unbound states suggests that the degree of induced fit observed is primarily a consequence of optimising van der Waals contacts with the walls of the minor groove resulting in groove narrowing through: (i) changes in base step parameters, including increased helical twist and propeller twist; (ii) changes to the sugar–phosphate backbone conformation to engulf the bound ligand; (iii) suppression of bending modes at the TpA steps. In contrast, the geometrical arrangement of hydrogen bond acceptors on the groove floor appears to be relatively insensitive to DNA conformation (helical twist and propeller twist). We suggest that effective recognition of DNA sequences (in this case an A tract structure) appears to depend to a significant extent on the sequence being flexible enough to be able to adopt the geometrically optimal conformation compatible with the various binding interactions, rather than involving ‘lock and key’ recognition.

Pseudoknots in prion protein mRNAs confirmed by comparative sequence analysis and pattern searching

The human prion gene contains five copies of a 24 nt repeat that is highly conserved among species. An analysis of folding free energies of the human prion mRNA, in particular in the repeat region, suggested biased codon selection and the presence of RNA patterns. In particular, pseudoknots, similar to the one predicted by Wills in the human prion mRNA, were identified in the repeat region of all available prion mRNAs available in GenBank, but not those of birds and the red slider turtle. An alignment of these mRNAs, which share low sequence homology, shows several co-variations that maintain the pseudoknot pattern. The presence of pseudoknots in yeast Sup35p and Rnq1 suggests acquisition in the prokaryotic era. Computer generated three-dimensional structures of the human prion pseudoknot highlight protein and RNA interaction domains, which suggest a possible effect in prion protein translation. The role of pseudoknots in prion diseases is discussed as individuals with extra copies of the 24 nt repeat develop the familial form of Creutzfeldt–Jakob disease.

DNA sequence insertion and evolutionary variation in gene regulation.

Current evidence on the long-term evolutionary effect of insertion of sequence elements into gene regions is reviewed, restricted to cases where a sequence derived from a past insertion participates in the regulation of expression of a useful gene. Ten such examples in eukaryotes demonstrate that segments of repetitive DNA or mobile elements have been inserted in the past in gene regions, have been preserved, sometimes modified by selection, and now affect control of transcription of the adjacent gene. Included are only examples in which transcription control was modified by the insert. Several cases in which merely transcription initiation occurred in the insert were set aside. Two of the examples involved the long terminal repeats of mammalian endogenous retroviruses. Another two examples were control of transcription by repeated sequence inserts in sea urchin genomes. There are now six published examples in which Alu sequences were inserted long ago into human gene regions, were modified, and now are central in control/enhancement of transcription. The number of published examples of Alu sequences affecting gene control has grown threefold in the last year and is likely to continue growing. Taken together, all of these examples show that the insertion of sequence elements in the genome has been a significant source of regulatory variation in evolution.

Isolation and characterization of mutant cell lines defective in transforming growth factor beta signaling.

To isolate and characterize effector molecules of the transforming growth factor beta (TGFbeta) signaling pathway we have used a genetic approach involving the generation of stable recessive mutants, defective in their TGFbeta signaling, which can subsequently be functionally complemented to clone the affected genes. We have generated a cell line derived from a hypoxanthine-guanine phosphoribosyltransferase negative (HPRT-) HT1080 clone that contains the selectable marker Escherichia coli guanine phosphoribosyltransferase (gpt) linked to a TGFbeta-responsive promoter. This cell line proliferates or dies in the appropriate selection medium in response to TGFbeta. We have isolated three distinct TGFbeta-unresponsive mutants following chemical mutagenesis. Somatic cell hybrids between pairs of individual TGFbeta-unresponsive clones reveal that each is in a distinct complementation group. Each mutant clone retains all three TGFbeta receptors yet fails to induce a TGFbeta-inducible luciferase reporter construct or TGFbeta-mediated plasminogen activator inhibitor-1 (PAI-1) expression. Two of the three have an attenuated TGFbeta-induced fibronectin response, whereas in the other mutant the fibronectin response is intact. These TGFbeta-unresponsive cells should allow selection and identification of signaling molecules through functional complementation.

Transfection and continuous expression of heterologous genes in the protozoan parasite Entamoeba histolytica.

To provide tools for functional molecular genetics of the protozoan parasite Entamoeba histolytica, we investigated the use of the prokaryotic neomycin phosphotransferase (NEO) gene as a selectable marker for the transfection of the parasite. An Escherichia coli-derived plasmid vector was constructed (pA5'A3'NEO) containing the NEO coding region flanked by untranslated 5' and 3' sequences of an Ent. histolytica actin gene. Preceding experiments had revealed that amoebae are highly sensitive to the neomycin analogue G418 and do not survive in the presence of as little as 2 micrograms/ml. Transfection of circular pA5'A3'NEO via electroporation resulted in Ent. histolytica trophozoites resistant to G418 up to 100 micrograms/ml. DNA and RNA analyses of resistant cells indicated that (i) the transfected DNA was not integrated into the amoeba genome but was segregated episomally, (ii) in the amoebae, the plasmid replicated autonomously, (iii) the copy number of the plasmid and the expression of NEO-specific RNA were proportional to the amount of G418 used for selection, and (iv) under continuous selection, the plasmid was propagated over an observation period of 6 months. Moreover, the plasmid could be recloned into E. coli and was found to be unrearranged. To investigate the use of pA5'A3'NEO to coexpress other genes in Ent. histolytica, a second marker, the prokaryotic chloramphenicol acetyltransferase (CAT) gene under control of an Ent. histolytica lectin gene promoter was introduced into the plasmid. Transfection of the amoebae with this construct also conferred G418 resistance and, in addition, allowed continuous expression of CAT activity in quantities corresponding to the amount of G418 used for selection. When selection was discontinued, transfected plasmids were lost as indicated by an exponential decline of CAT activity in trophozoite extracts.

Enhancer-dependent interaction between 5' and 3' splice sites in trans.

Splice-site selection and alternative splicing of nuclear pre-mRNAs can be controlled by splicing enhancers that act by promoting the activity of upstream splice sites. Here we show that RNA molecules containing a 3' splice site and enhancer sequence are efficiently spliced in trans to RNA molecules containing normally cis-spliced 5' splice sites or to normally trans-spliced spliced leader RNAs from lower eukaryotes. In addition, we show that this reaction is stimulated by (Ser + Arg)-rich splicing factors that are known to promote protein-protein interactions in the cis-splicing reaction. Thus, splicing enhancers facilitate the assembly of protein complexes on RNAs containing a 3' splice site, and this complex is sufficiently stable to functionally interact with 5' splice sites located on separate RNAs. This trans-splicing is mediated by interactions between (Ser + Arg)-rich splicing factors bound to the enhancer and general splicing factors bound to the 5' and 3' splice sites. These same interactions are likely to play a crucial role in alternative splicing and splice-site selection in cis.

Complete congruence between gene diversity estimates derived from genotypic data at enzyme and random amplified polymorphic DNA loci in black spruce.

Controversy still exists over the adaptive nature of variation of enzyme loci. In conifers, random amplified polymorphic DNAs (RAPDs) represent a class of marker loci that is unlikely to fall within or be strongly linked to coding DNA. We have compared the genetic diversity in natural populations of black spruce [Picea mariana (Mill.) B.S.P.] using genotypic data at allozyme loci and RAPD loci as well as phenotypic data from inferred RAPD fingerprints. The genotypic data for both allozymes and RAPDs were obtained from at least six haploid megagametophytes for each of 75 sexually mature individuals distributed in five populations. Heterozygosities and population fixation indices were in complete agreement between allozyme loci and RAPD loci. In black spruce, it is more likely that the similar levels of variation detected at both enzyme and RAPD loci are due to such evolutionary forces as migration and the mating system, rather than to balancing selection and overdominance. Furthermore, we show that biased estimates of expected heterozygosity and among-population differentiation are obtained when using allele frequencies derived from dominant RAPD phenotypes.

Proactive and reactive inhibition during overt and covert actions. An electrical neuroimaging study.

Response inhibition is the ability to suppress inadequate but automatically activated, prepotent or ongoing response tendencies. In the framework of motor inhibition, two distinct operating strategies have been described: “proactive” and “reactive” control modes. In the proactive modality, inhibition is recruited in advance by predictive signals, and actively maintained before its enactment. Conversely, in the reactive control mode, inhibition is phasically enacted after the detection of the inhibitory signal. To date, ample evidence points to a core cerebral network for reactive inhibition comprising the right inferior frontal gyrus (rIFG), the presupplementary motor area (pre-SMA) and the basal ganglia (BG). Moreover, fMRI studies showed that cerebral activations during proactive and reactive inhibition largely overlap. These findings suggest that at least part of the neural network for reactive inhibition is recruited in advance, priming cortical regions in preparation for the upcoming inhibition. So far, proactive and reactive inhibitory mechanisms have been investigated during tasks in which the requested response to be stopped or withheld was an “overt” action execution (AE) (i.e., a movement effectively performed). Nevertheless, inhibitory mechanisms are also relevant for motor control during “covert actions” (i.e., potential motor acts not overtly performed), such as motor imagery (MI). MI is the conscious, voluntary mental rehearsal of action representations without any overt movement. Previous studies revealed a substantial overlap of activated motor-related brain networks in premotor, parietal and subcortical regions during overtly executed and imagined movements. Notwithstanding this evidence for a shared set of cerebral regions involved in encoding actions, whether or not those actions are effectively executed, the neural bases of motor inhibition during MI, preventing covert action from being overtly performed, in spite of the activation of the motor system, remain to be fully clarified. Taking into account this background, we performed a high density EEG study evaluating cerebral mechanisms and their related sources elicited during two types of cued Go/NoGo task, requiring the execution or withholding of an overt (Go) or a covert (MI) action, respectively. The EEG analyses were performed in two steps, with different aims: 1) Analysis of the “response phase” of the cued overt and covert Go/NoGo tasks, for the evaluation of reactive inhibitory control of overt and covert actions. 2) Analysis of the “preparatory phase” of the cued overt and covert Go/NoGo EEG datasets, focusing on cerebral activities time-locked to the preparatory signals, for the evaluation of proactive inhibitory mechanisms and their related neural sources. For these purposes, a spatiotemporal analysis of the scalp electric fields was applied on the EEG data recorded during the overt and covert Go/NoGo tasks. The spatiotemporal approach provide an objective definition of time windows for source analysis, relying on the statistical proof that the electric fields are different and thus generated by different neural sources. The analysis of the “response phase” revealed that key nodes of the inhibitory circuit, underpinning inhibition of the overt movement during the NoGo response, were also activated during the MI enactment. In both cases, inhibition relied on the activation of pre-SMA and rIFG, but with different temporal patterns of activation in accord with the intended “covert” or “overt” modality of motor performance. During the NoGo condition, the pre-SMA and rIFG were sequentially activated, pointing to an early decisional role of pre-SMA and to a later role of rIFG in the enactment of inhibitory control of the overt action. Conversely, a concomitant activation of pre-SMA and rIFG emerged during the imagined motor response. This latter finding suggested that an inhibitory mechanism (likely underpinned by the rIFG), could be prewired into a prepared “covert modality” of motor response, as an intrinsic component of the MI enactment. This mechanism would allow the rehearsal of the imagined motor representations, without any overt movement. The analyses of the “preparatory phase”, confirmed in both overt and covert Go/NoGo tasks the priming of cerebral regions pertaining to putative inhibitory network, reactively triggered in the following response phase. Nonetheless, differences in the preparatory strategies between the two tasks emerged, depending on the intended “overt” or “covert” modality of the possible incoming motor response. During the preparation of the overt Go/NoGo task, the cue primed the possible overt response programs in motor and premotor cortex. At the same time, through preactivation of a pre-SMA-related decisional mechanism, it triggered a parallel preparation for the successful response selection and/or inhibition during the subsequent response phase. Conversely, the preparatory strategy for the covert Go/NoGo task was centred on the goal-oriented priming of an inhibitory mechanism related to the rIFG that, being tuned to the instructed covert modality of the motor performance and instantiated during the subsequent MI enactment, allowed the imagined response to remain a potential motor act. Taken together, the results of the present study demonstrate a substantial overlap of cerebral networks activated during proactive recruitment and subsequent reactive enactment of motor inhibition in both overt and covert actions. At the same time, our data show that preparatory cues predisposed ab initio a different organization of the cerebral areas (in particular of the pre-SMA and rIFG) involved with sensorimotor transformations and motor inhibitory control for executed and imagined actions. During the preparatory phases of our cued overt and covert Go/NoGo tasks, the different adopted strategies were tuned to the “how” of the motor performance, reflecting the intended overt and covert modality of the possible incoming action.

Magnetic activity and differential rotation in the young Sun-like stars KIC 7985370 and KIC 7765135

Aims. We present a detailed study of the two Sun-like stars KIC 7985370 and KIC 7765135, to determine their activity level, spot distribution, and differential rotation. Both stars were previously discovered by us to be young stars and were observed by the NASA Kepler mission. Methods. The fundamental stellar parameters (vsini, spectral type, T_eff, log g, and [Fe/H]) were derived from optical spectroscopy by comparison with both standard-star and synthetic spectra. The spectra of the targets allowed us to study the chromospheric activity based on the emission in the core of hydrogen Hα and Ca ii infrared triplet (IRT) lines, which was revealed by the subtraction of inactive templates. The high-precision Kepler photometric data spanning over 229 days were then fitted with a robust spot model. Model selection and parameter estimation were performed in a Bayesian manner, using a Markov chain Monte Carlo method. Results. We find that both stars are Sun-like (of G1.5 V spectral type) and have an age of about 100–200 Myr, based on their lithium content and kinematics. Their youth is confirmed by their high level of chromospheric activity, which is comparable to that displayed by the early G-type stars in the Pleiades cluster. The Balmer decrement and flux ratio of their Ca ii-IRT lines suggest that the formation of the core of these lines occurs mainly in optically thick regions that are analogous to solar plages. The spot model applied to the Kepler photometry requires at least seven persistent spots in the case of KIC 7985370 and nine spots in the case of KIC 7765135 to provide a satisfactory fit to the data. The assumption of the longevity of the star spots, whose area is allowed to evolve with time, is at the heart of our spot-modelling approach. On both stars, the surface differential rotation is Sun-like, with the high-latitude spots rotating slower than the low-latitude ones. We found, for both stars, a rather high value of the equator-to-pole differential rotation (dΩ ≈ 0.18 rad d^-1), which disagrees with the predictions of some mean-field models of differential rotation for rapidly rotating stars. Our results agree instead with previous works on solar-type stars and other models that predict a higher latitudinal shear, increasing with equatorial angular velocity, that can vary during the magnetic cycle.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.