520 research outputs found
Data analysis program collection for Westermann et al.
No full text<p>Program collection the data analysis of the study "Dual RNA-seq unveils noncoding RNA functions in host–pathogen interactions" by Westermann et al., Nature, 2016</p>
Allinder, Lamsa A. (Death, 1889-02-07)
No full textAddress: 1013 Central AvenueAge at death: 26111/Pg 15/1889/F W M/City/Dr. Wm. J. Murray/Westermann/Carthage RoadOriginal record filed in drawer labeled'ALEXANDER-ALMS'
Self-production facilitates and adult input interferes in a neural network model of infant vowel imitation.
No full textIt is well known that greater amounts of adult input facilitate a child\u27s language development. Thus, one might expect that increased amounts of adult input would help an infant learn to accurately imitate the vowels of his/her native language. In addition, an infant\u27s own production of sounds during cooing, babbling, etc. is known to be important to the development of speech abilities. We simulate infant vowel development using a neural network that contains a layer of auditory neurons, a layer of motor neurons, and bidirectional connections linking these perceptual and motor layers. During an initial babbling phase, the system produces random motor activations, hears the acoustic consequences of these motor activations, and adjusts the weights between its auditory and motor layers in a Hebbian fashion. In simulations, passive auditory input from an external caregiver is also included during the babbling phase, and is used to update existing auditory-motor connections. In a testing phase, the model is given adult vowels as auditory input and asked to imitate them. Results indicate that self-productions do promote the development of the ability to imitate, but, somewhat counterintuitively, the more adult input this model receives during babbling, the less accurate its imitations are during test. Explanations and implications of this finding are discussed.12
Post-transcriptional regulation in Klebsiella pneumoniae
No full textthe aim of this study was to decipher the transcriptome of the major human pathogen K. pneumoniae and to identify post-transcriptional mechanisms by which this bacterium adapts to changing environmental conditions. The results presented in this thesis substantially expand the understanding of this understudied microorganism and shed light on sRNA-based regulatory mechanisms, many of which are likely conserved in other bacteria. The application of different HTS approaches generated comprehensive datasets that will serve as a valuable resource for future studies on K. pneumoniae. The transcriptome annotation was refined by identifying TSSs, 5' UTRs and sRNAs using dRNA-seq (2.2.1), RIP-seq (2.2.2) and comparative bioinformatics (2.2.3). In addition, the RNA ligands of the two major RBPs, Hfq (2.2.2) and ProQ (2.5.4), and the RNA-RNA interactomes associated with these proteins (2.2.4 and 2.6) were identified. Furthermore, LexA-bound DNA regions were mapped (2.5.1) and the global transcriptomic response to SOS stress was characterized (2.5.2). Beyond these global analyses, this study also highlights the functional importance of specific sRNAs in bacterial adaptation, particularly with regard to the regulation of cell division. Six Klebsiella-specific sRNAs were identified that directly base-pair with ftsZ mRNA, thereby inhibiting cell division and adding an additional layer of regulation to this essential cellular process (2.3). Of particular note was the discovery of DinR, an sRNA derived from the 3' UTR of dinI mRNA that is processed by RNase E in response to DNA damage (2.4). This finding underscores the role of sRNAs in coordinating essential stress responses and highlights how even well-characterized pathways, such as the SOS response, can be further refined through studies in non-model organisms like K. pneumoniae
A Globally Conforming Lattice Structure for 2D Stress Tensor Visualization
No full textWe present a visualization technique for 2D stress tensor fields based on the construction of a globally conforming lattice. Conformity ensures that the lattice edges follow the principal stress directions and the aspect ratio of lattice elements represents the stress anisotropy. Since such a lattice structure cannot be space-filling in general, it is constructed from multiple intersecting lattice beams. Conformity at beam intersections is ensured via a constrained optimization problem, by computing the aspect ratio of elements at intersections so that their edges meet when continued along the principal stress lines. In combination with a coloring scheme that encodes relative stress magnitudes, a global visualization is achieved. By introducing additional constraints on the positional variation of the beam intersections, coherent visualizations are achieved when external loads or material parameters are changed. In a number of experiments using non-trivial scenarios, we demonstrate the capability of the proposed visualization technique to show the global and local structure of a given stress field.Accepted Author ManuscriptMaterials and Manufacturin
Resolving host-pathogen interactions by dual RNA-seq.
No full textThe transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables "dual RNA-seq" studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique
Group B Streptococcus transcriptome when interacting with brain endothelial cells
No full textUnlabelled: Bacterial meningitis is a life-threatening infection of the central nervous system (CNS) that occurs when bacteria are able to cross the blood-brain barrier (BBB) or the meningeal-cerebrospinal fluid barrier (mBCSFB). The BBB and mBCSFB comprise highly specialized brain endothelial cells (BECs) that typically restrict pathogen entry. Group B Streptococcus (GBS or Streptococcus agalactiae) is the leading cause of neonatal meningitis. Until recently, identification of GBS virulence factors has relied on genetic screening approaches. Instead, we here conducted RNA-seq analysis on GBS when interacting with induced pluripotent stem cell-derived BECs (iBECs) to pinpoint virulence-associated genes. Of the 2,068 annotated protein-coding genes of GBS, 430 transcripts displayed significant changes in expression after interacting with BECs. Notably, we found that the majority of differentially expressed GBS transcripts were downregulated (360 genes) during infection of iBECs. Interestingly, codY, encoding a pleiotropic transcriptional repressor in low-G + C Gram-positive bacteria, was identified as being highly downregulated. We conducted qPCR to confirm the codY downregulation observed via RNA-seq during the GBS-iBEC interaction and obtained codY mutants in three different GBS background parental strains. As anticipated from the RNA-seq results, the [Formula: see text]codY strains were more adherent and invasive in two in vitro BEC models. Together, this demonstrates the utility of RNA-seq during the BEC interaction to identify GBS virulence modulators. Importance: Group B Streptococcus (GBS) meningitis remains the leading cause of neonatal meningitis. Research work has identified surface factors and two-component systems that contribute to GBS disruption of the blood-brain barrier (BBB). These discoveries often relied on genetic screening approaches. Here, we provide transcriptomic data describing how GBS changes its transcriptome when interacting with brain endothelial cells. Additionally, we have phenotypically validated these data by obtaining mutants of a select regulator that is highly down-regulated during infection and testing on our BBB model. This work provides the research field with a validated data set that can provide an insight into potential pathways that GBS requires to interact with the BBB and open the door to new discoveries
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