RNA interference-mediated knockdown of CD49e (alpha 5 integrin chain) in human thymic epithelial cells modulates the expression of multiple genes and decreases thymocyte adhesion

Background: The thymus is a central lymphoid organ, in which bone marrow-derived T cell precursors undergo a complex process of maturation. Developing thymocytes interact with thymic microenvironment in a defined spatial order. A component of thymic microenvironment, the thymic epithelial cells, is crucial for the maturation of T-lymphocytes through cell-cell contact, cell matrix interactions and secretory of cytokines/chemokines. There is evidence that extracellular matrix molecules play a fundamental role in guiding differentiating thymocytes in both cortical and medullary regions of the thymic lobules. The interaction between the integrin alpha 5 beta 1 (CD49e/CD29; VLA-5) and fibronectin is relevant for thymocyte adhesion and migration within the thymic tissue. Our previous results have shown that adhesion of thymocytes to cultured TEC line is enhanced in the presence of fibronectin, and can be blocked with anti-VLA-5 antibody. Results: Herein, we studied the role of CD49e expressed by the human thymic epithelium. For this purpose we knocked down the CD49e by means of RNA interference. This procedure resulted in the modulation of more than 100 genes, some of them coding for other proteins also involved in adhesion of thymocytes; others related to signaling pathways triggered after integrin activation, or even involved in the control of F-actin stress fiber formation. Functionally, we demonstrated that disruption of VLA-5 in human TEC by CD49e-siRNA-induced gene knockdown decreased the ability of TEC to promote thymocyte adhesion. Such a decrease comprised all CD4/CD8-defined thymocyte subsets. Conclusion: Conceptually, our findings unravel the complexity of gene regulation, as regards key genes involved in the heterocellular cell adhesion between developing thymocytes and the major component of the thymic microenvironment, an interaction that is a mandatory event for proper intrathymic T cell differentiation.

PAMM: A Redox Regulatory Protein That Modulates Osteoclast Differentiation

The central role of reactive oxygen species (ROS) in osteoclast differentiation and in bone homeostasis prompted us to characterize the redox regulatory system of osteoclasts. In this report, we describe the expression and functional characterization of PAMM, a CXXC motif-containing peroxiredoxin 2-like protein expressed in bone marrow monocytes on stimulation with M-CSF and RANKL. Expression of wild-type (but not C to G mutants of the CXXC domain) PAMM in HEK293 cells results in an increased GSH/GSSG ratio, indicating a shift toward a more reduced environment. Expression of PAMM in RAW264.7 monocytes protected cells from hydrogen peroxide-induced oxidative stress, indicating that PAMM regulates cellular redox status. RANKL stimulation of RAW 264.7 cells caused a decrease in the GSH/GSSG ratio (reflecting a complementary increase in ROS). In addition, RANKL-induced osteoclast formation requires phosphorylation and translocation of NF-kappa B and c-Jun. In stably transfected RAW 264.7 cells, PAMM overexpression prevented the reduction of GSH/GSSG induced by RANKL. Concurrently, PAMM expression completely abolished RANKL-induced p100 NF-kappa B and c-Jun activation, as well as osteoclast formation. We conclude that PAMM is a redox regulatory protein that modulates osteoclast differentiation in vitro. PAMM expression may affect bone resorption in vivo and help to maintain bone mass. Antioxid. Redox Signal. 13, 27-37.

The gene transformer-2 of Anastrepha fruit flies (Diptera, Tephritidae) and its evolution in insects

Background: In the tephritids Ceratitis, Bactrocera and Anastrepha, the gene transformer provides the memory device for sex determination via its auto-regulation; only in females is functional Tra protein produced. To date, the isolation and characterisation of the gene transformer-2 in the tephritids has only been undertaken in Ceratitis, and it has been shown that its function is required for the female-specific splicing of doublesex and transformer pre-mRNA. It therefore participates in transformer auto-regulatory function. In this work, the characterisation of this gene in eleven tephritid species belonging to the less extensively analysed genus Anastrepha was undertaken in order to throw light on the evolution of transformer-2. Results: The gene transformer-2 produces a protein of 249 amino acids in both sexes, which shows the features of the SR protein family. No significant partially spliced mRNA isoform specific to the male germ line was detected, unlike in Drosophila. It is transcribed in both sexes during development and in adult life, in both the soma and germ line. The injection of Anastrepha transformer-2 dsRNA into Anastrepha embryos caused a change in the splicing pattern of the endogenous transformer and doublesex pre-mRNA of XX females from the female to the male mode. Consequently, these XX females were transformed into pseudomales. The comparison of the eleven Anastrepha Transformer-2 proteins among themselves, and with the Transformer-2 proteins of other insects, suggests the existence of negative selection acting at the protein level to maintain Transformer-2 structural features. Conclusions: These results indicate that transformer-2 is required for sex determination in Anastrepha through its participation in the female-specific splicing of transformer and doublesex pre-mRNAs. It is therefore needed for the auto-regulation of the gene transformer. Thus, the transformer/transfomer-2 > doublesex elements at the bottom of the cascade, and their relationships, probably represent the ancestral state ( which still exists in the Tephritidae, Calliphoridae and Muscidae lineages) of the extant cascade found in the Drosophilidae lineage ( in which tra is just another component of the sex determination gene cascade regulated by Sex-lethal). In the phylogenetic lineage that gave rise to the drosophilids, evolution co-opted for Sex-lethal, modified it, and converted it into the key gene controlling sex determination.

Complete Genome Viral Phylogenies Suggests the Concerted Evolution of Regulatory Cores and Accessory Satellites

We consider the concerted evolution of viral genomes in four families of DNA viruses. Given the high rate of horizontal gene transfer among viruses and their hosts, it is an open question as to how representative particular genes are of the evolutionary history of the complete genome. To address the concerted evolution of viral genes, we compared genomic evolution across four distinct, extant viral families. For all four viral families we constructed DNA-dependent DNA polymerase-based (DdDp) phylogenies and in addition, whole genome sequence, as quantitative descriptions of inter-genome relationships. We found that the history of the polymerase gene was highly predictive of the history of the genome as a whole, which we explain in terms of repeated, co-divergence events of the core DdDp gene accompanied by a number of satellite, accessory genetic loci. We also found that the rate of gene gain in baculovirus and poxviruses proceeds significantly more quickly than the rate of gene loss and that there is convergent acquisition of satellite functions promoting contextual adaptation when distinct viral families infect related hosts. The congruence of the genome and polymerase trees suggests that a large set of viral genes, including polymerase, derive from a phylogenetically conserved core of genes of host origin, secondarily reinforced by gene acquisition from common hosts or co-infecting viruses within the host. A single viral genome can be thought of as a mutualistic network, with the core genes acting as an effective host and the satellite genes as effective symbionts. Larger virus genomes show a greater departure from linkage equilibrium between core and satellites functions.

The constancy of global regulation across a species: the concentrations of ppGpp and RpoS are strain-specific in Escherichia coli

Background: Sigma factors and the alarmone ppGpp control the allocation of RNA polymerase to promoters under stressful conditions. Both ppGpp and the sigma factor sigma(S) (RpoS) are potentially subject to variability across the species Escherichia coli. To find out the extent of strain variation we measured the level of RpoS and ppGpp using 31 E. coli strains from the ECOR collection and one reference K-12 strain. Results: Nine ECORs had highly deleterious mutations in rpoS, 12 had RpoS protein up to 7-fold above that of the reference strain MG1655 and the remainder had comparable or lower levels. Strain variation was also evident in ppGpp accumulation under carbon starvation and spoT mutations were present in several low-ppGpp strains. Three relationships between RpoS and ppGpp levels were found: isolates with zero RpoS but various ppGpp levels, strains where RpoS levels were proportional to ppGpp and a third unexpected class in which RpoS was present but not proportional to ppGpp concentration. High-RpoS and high-ppGpp strains accumulated rpoS mutations under nutrient limitation, providing a source of polymorphisms. Conclusions: The ppGpp and sigma(S) variance means that the expression of genes involved in translation, stress and other traits affected by ppGpp and/or RpoS are likely to be strain-specific and suggest that influential components of regulatory networks are frequently reset by microevolution. Different strains of E. coli have different relationships between ppGpp and RpoS levels and only some exhibit a proportionality between increasing ppGpp and RpoS levels as demonstrated for E. coli K-12.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Identification of protein-coding and non-coding RNA expression profiles in CD34(+) and in stromal cells in refractory anemia with ringed sideroblasts

Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

Identification of archaeal proteins that affect the exosome function in vitro

Background: The archaeal exosome is formed by a hexameric RNase PH ring and three RNA binding subunits and has been shown to bind and degrade RNA in vitro. Despite extensive studies on the eukaryotic exosome and on the proteins interacting with this complex, little information is yet available on the identification and function of archaeal exosome regulatory factors. Results: Here, we show that the proteins PaSBDS and PaNip7, which bind preferentially to poly-A and AU-rich RNAs, respectively, affect the Pyrococcus abyssi exosome activity in vitro. PaSBDS inhibits slightly degradation of a poly-rA substrate, while PaNip7 strongly inhibits the degradation of poly-A and poly-AU by the exosome. The exosome inhibition by PaNip7 appears to depend at least partially on its interaction with RNA, since mutants of PaNip7 that no longer bind RNA, inhibit the exosome less strongly. We also show that FITC-labeled PaNip7 associates with the exosome in the absence of substrate RNA. Conclusions: Given the high structural homology between the archaeal and eukaryotic proteins, the effect of archaeal Nip7 and SBDS on the exosome provides a model for an evolutionarily conserved exosome control mechanism.

Identification of Novel Immunoregulatory Molecules in Human Thymic Regulatory CD4(+)CD25(+) T Cells by Phage Display

Thymic CD4(+)CD25(+) cells play an important role in immune regulation and are continuously developed in the thymus as an independent lineage. How these cells are generated, what are their multiple pathways of suppressive activity and which are their specific markers are questions that remain unanswered. To identify molecules involved in the function and development of human CD4(+)CD25(+) T regulatory cells we targeted thymic CD4(+)CD25(+) cells by peptide phage display. A phage library containing random peptides was screened ex vivo for binding to human thymic CD4(+)CD25(+) T cells. After four rounds of selection on CD4(+)CD25(+) enriched populations of thymocytes, we sequenced several phage displayed peptides and selected one with identity to the Vitamin D Receptor (VDR). We confirmed the binding of the VDR phage to active Vitamin D in vitro, as well as the higher expression of VDR in CD4(+)CD25(+) cells. We suggest that differential expression of VDR on natural Tregs may be related to the relevance of Vitamin D in function and ontogeny of these cells.

Expression of genes related to muscle plasticity after strength and power training regimens

The purpose of our study was to compare the effects of 8-week progressive strength and power training regimens on strength gains and muscle plasticity [muscle fiber hypertrophy and phenotype shift, mammalian target of rapamycin (mTOR), regulatory-associated protein of mTOR (RAPTOR), rapamycin-insensitive companion of m-TOR (RICTOR), calcineurin and calcipressin gene expression]. Twenty-nine physically active subjects were divided into three groups: strength training (ST), power training (PT) and control (C). Squat 1 RM and muscle biopsies were obtained before and after the training period. Strength increased similarly for both ST and PT groups (P < 0.001). Fiber types I, IIa and IIb presented hypertrophy main time effect (P < 0.05). Only type IIb percentage decreased from pre- to post-test (main time effect, P < 0.05). mTOR and RICTOR mRNA expression increased similarly from pre- to post-test (P < 0.01). RAPTOR increased after training for both groups (P < 0.0001), but to a greater extent in the ST (P < 0.001) than in the PT group. 4EBP-1 decreased after training when the ST and PT groups were pooled (P < 0.05). Calcineurin levels did not change after training, while calcipressin increased similarly from pre- to post-test (P < 0.01). In conclusion, our data indicate that these training regimens produce similar performance improvements; however, there was a trend toward greater hypertrophy-related gene expression and muscle fiber hypertrophy in the ST group.

Tick saliva induces regulatory dendritic cells: MAP-kinases and Toll-like receptor-2 expression as potential targets

Ticks (Acari: Ixodidae) are bloodsucking ectoparasitic arthropods of human and veterinary medical importance. Tick saliva has been shown to contain a wide range of bioactive molecules with vasodilatory, antihemostatic, and immunomodulatory activities. We have previously demonstrated that saliva from Rhipicephalus sanguineus ticks inhibits the maturation of dendritic cells (DCs) stimulated with LPS. Here we examined the mechanism of this immune subversion, evaluating the effect of tick saliva on Toll-like receptor (TLR)-4 signalling pathway in bone marrow-derived DCs. We demonstrated that R. sanguineus tick saliva impairs maturation of DCs stimulated with LIPS, a TLR-4 ligand, leading to increased production of interleukin (IL)-10 and reduced synthesis of IL-12p70 and TNF-alpha. The immunomodulatory effect of the tick saliva on the production of pro-inflammatory cytokines by DCs stimulated with LPS was associated with the observation that tick saliva inhibits the activation of the ERK 1/2 and p38 MAP kinases. These effects were independent of the expression of TLR-4 on the surface of DCs. Additionally, saliva-treated DCs also presented a similar pattern of cytokine modulation in response to other TLR ligands. Since the recent literature reports that several parasites evade immune responses through TLR-2-mediated production of IL-10, we evaluated the effect of tick saliva on the percentage of TLR-2(+) DCs stimulated with the TLR-2 ligand lipoteicoic acid (LTA). The data showed that the population of DCs expressing TLR-2 was significantly increased in DCs treated with LTA plus saliva. In addition, tick saliva alone increased the expression of TLR-2 in a dose- and time-dependent manner. Our data suggest that tick saliva induces regulatory DCs, which secrete IL-10 and low levels of IL-12 and TNF-alpha when stimulated by TLR ligands. Such regulatory DCs are associated with expression of TLR-2 and inhibition of ERK and p38, which promotes the production of IL-10 and thus down-modulates the host`s immune response, possibly favouring susceptibility to tick infestations. (C) 2009 Elsevier B.V. All rights reserved.

Regulatory effects of an inhibitor from Plathymenia foliolosa seeds on the larval development of Anagasta kuehniella (Lepidoptera)

The Mediterranean flour moth, Anagasta kuehniella, is one of the most important insect pests of grains, reported worldwide, feeding on stored grains and products of rice, rye, corn and wheat. Plants synthesize a variety of molecules, including trypsin inhibitors, to defend themselves against attack by insects. In this study, a trypsin inhibitor (PFTI) was purified from Plathymenia foliolosa (Benth.) seeds and was tested for insect growth regulatory effect. The survival and mass of A. kuehniella larvae feeding on control seeds were about 82.7% and 5 ring, respectively, whereas survival on seeds containing 0.7% PFTI was about 56%, while a 66.1% reduction in the average mass of the larvae was observed. The results from dietary utilization experiments with A. kuehniella larvae showed a reduction in efficiency of conversion of ingested food and digested food, and an increase in approximate digestibility and metabolic cost. The level of trypsin was significantly decreased in larval midgut and increased in the feces of larvae reared on a diet containing 0.7% PFTI. Results indicate that PFTI possesses a toxic effect against A. kuehniella larvae. (C) 2008 Elsevier Inc. All rights reserved.