Tunable reporter signal production in feedback-uncoupled arsenic bioreporters.

Escherichia coli-based bioreporters for arsenic detection are typically based on the natural feedback loop that controls ars operon transcription. Feedback loops are known to show a wide range linear response to the detriment of the overall amplification of the incoming signal. While being a favourable feature in controlling arsenic detoxification for the cell, a feedback loop is not necessarily the most optimal for obtaining highest sensitivity and response in a designed cellular reporter for arsenic detection. Here we systematically explore the effects of uncoupling the topology of arsenic sensing circuitry on the developed reporter signal as a function of arsenite concentration input. A model was developed to describe relative ArsR and GFP levels in feedback and uncoupled circuitry, which was used to explore new ArsR-based synthetic circuits. The expression of arsR was then placed under the control of a series of constitutive promoters, which differed in promoter strength, and which could be further modulated by TetR repression. Expression of the reporter gene was maintained under the ArsR-controlled Pars promoter. ArsR expression in the systems was measured by using ArsR-mCherry fusion proteins. We find that stronger constitutive ArsR production decreases arsenite-dependent EGFP output from Pars and vice versa. This leads to a tunable series of arsenite-dependent EGFP outputs in a variety of systematically characterized circuitries. The higher expression levels and sensitivities of the response curves in the uncoupled circuits may be useful for improving field-test assays using arsenic bioreporters.

Generic approach for the sensitive absolute quantification of large undigested peptides in plasma using a particular liquid chromatography-mass spectrometry setup.

A generic LC-MS approach for the absolute quantification of undigested peptides in plasma at mid-picomolar levels is described. Nine human peptides namely, brain natriuretic peptide (BNP), substance P (SubP), parathyroid hormone 1-34 (PTH), C-peptide, orexines A and B (Orex-A and -B), oxytocin (Oxy), gonadoliberin-1 (gonadothropin releasing-hormone or luteinizing hormone-releasing hormone, LHRH) and α-melanotropin (α-MSH) were targeted. Plasma samples were extracted via a 2-step procedure: protein precipitation using 1vol of acetonitrile followed by ultrafiltration of supernatants on membranes with a MW cut-off of 30 kDa. By applying a specific LC-MS setup, large volumes of filtrates (e.g., 2×750 μL) were injected and the peptides were trapped on a 1mm i.d.×10 mm length C8 column using a 10× on-line dilution. Then, the peptides were back-flushed and a second on-line dilution (2×) was applied during the transfer step. The refocalized peptides were resolved on a 0.3mm i.d. C18 analytical column. Extraction recovery, matrix effect and limits of detection were evaluated. Our comprehensive protocol demonstrates a simple and efficient sample preparation procedure followed by the analysis of peptides with limits of detection in the mid-picomolar range. This generic approach can be applied for the determination of most therapeutic peptides and possibly for endogenous peptides with latest state-of-the-art instruments.

Digestion of Streptococcus pneumoniae cell walls with its major peptidoglycan hydrolase releases branched stem peptides carrying proinflammatory activity.

The peptidoglycan of Gram-positive bacteria is known to trigger cytokine release from peripheral blood mononuclear cells (PBMCs). However, it requires 100-1000 times more Gram-positive peptidoglycan than Gram-negative lipopolysaccharide to release the same amounts of cytokines from target cells. Thus, either peptidoglycan is poorly active or only part of it is required for PBMC activation. To test this hypothesis, purified Streptococcus pneumoniae walls were digested with their major autolysin N-acetylmuramoyl-L-alanine amidase, and/or muramidase. Solubilized walls were separated by reverse phase high pressure chromatography. Individual fractions were tested for their PBMC-stimulating activity, and their composition was determined. Soluble components had a Mr between 600 and 1500. These primarily comprised stem peptides cross-linked to various extents. Simple stem peptides (Mr <750) were 10-fold less active than undigested peptidoglycan. In contrast, tripeptides (Mr >1000) were >/=100-fold more potent than the native material. One dipeptide (inactive) and two tripeptides (active) were confirmed by post-source decay analysis. Complex branched peptides represented </=2% of the total material, but their activity (w/w) was almost equal to that of LPS. This is the first observation suggesting that peptidoglycan stem peptides carry high tumor necrosis factor-stimulating activity. These types of structures are conserved among Gram-positive bacteria and will provide new material to help elucidate the mechanism of peptidoglycan-induced inflammation.

Functional dynamics of PDZ binding domains: a normal-mode analysis.

Postsynaptic density-95/disks large/zonula occludens-1 (PDZ) domains are relatively small (80-120 residues) protein binding modules central in the organization of receptor clusters and in the association of cellular proteins. Their main function is to bind C-terminals of selected proteins that are recognized through specific amino acids in their carboxyl end. Binding is associated with a deformation of the PDZ native structure and is responsible for dynamical changes in regions not in direct contact with the target. We investigate how this deformation is related to the harmonic dynamics of the PDZ structure and show that one low-frequency collective normal mode, characterized by the concerted movements of different secondary structures, is involved in the binding process. Our results suggest that even minimal structural changes are responsible for communication between distant regions of the protein, in agreement with recent NMR experiments. Thus, PDZ domains are a very clear example of how collective normal modes are able to characterize the relation between function and dynamics of proteins, and to provide indications on the precursors of binding/unbinding events.

Strength of family history in predicting levels of blood pressure, plasma glucose and cholesterol

Rapport de synthèse : L'histoire familiale reflète non seulement la susceptibilité génétique d'un individu à certaines maladies mais également ses comportements et habitudes, notamment partagées au sein d'une famille. L'hypertension artérielle, le diabète et l'hypercholestérolémie sont des facteurs de risque cardio-vasculaire modifiables hautement prévalent. L'association entre l'histoire familiale d'hypertension artérielle ou de diabète et le risque accru de développer de l'hypertension artérielle ou du diabète, respectivement, a été préalablement établie. Par contre, le lien entre l'histoire familiale de facteurs de risque cardio-vasculaire et les traits continus correspondants n'avaient jamais été mis clairement en évidence. De même, la signification d'une histoire familiale inconnue n'avait jusqu'alors pas été décrite. Ce travail, effectué dans le cadre de l'étude Colaus (Cohorte Lausannoise), une cohorte regroupant un échantillon composé de 6102 participants âgés de 35 à 75 ans sélectionnés au hasard dans la population lausannoise, a permis de décrire en détail la relation entre l'histoire familiale des facteurs de risque cardio-vasculaires et les trait correspondants dans la population étudiée. Les différentes analyses statistiques ont permis de mettre en évidence une relation forte entre l'histoire familiale d'hypertension artérielle, de diabète ainsi que de l'hypercholestérolémie et leurs traits dichotomique et continu correspondants. Les anamnèses des frères et soeurs avaient des valeurs prédictives positives plus élevées que les anamnèses parentales. Ceci signifie que les programmes de dépistage ne prenant en compte que l'histoire familiale des frères et soeurs seraient probablement plus efficaces que ceux qui comportent l'évaluation des anamnèses paternelle et maternelle. Plus de 40% des participants ignoraient l'histoire familiale d'hypertension d'au moins un des membres de leur famille. Ceux-ci avaient des valeurs de tension artérielle systolique plus élevées que ceux dont l'histoire familiale était négative, permettant de souligner la valeur prédictive du fait de ne pas connaître l'histoire familiale d'hypertension artérielle. Ces résultats montrent également que, lors d'analyses de la relation entre l'anamnèse familiale de facteurs de risque cardiovasculaires et leurs traits correspondants, les participants donnant des réponses négatives doivent être distingués de ceux qui ne connaissent pas leur anamnèse familiale. Les résultats de cette étude confirment la place centrale qu'occupe l'anamnèse familiale dans l'évaluation du risque cardio-vasculaire auprès de la population générale. L'importance de cet outil prédictif simple et bon marché ne va cesser d'augmenter avec la disponibilité croissante d'information génétique détaillée pour les maladies cardiovasculaires communes.

Predicting current and future biological invasions: both native and invaded ranges matter.

The classical approach to predicting the geographical extent of species invasions consists of training models in the native range and projecting them in distinct, potentially invasible areas. However, recent studies have demonstrated that this approach could be hampered by a change of the realized climatic niche, allowing invasive species to spread into habitats in the invaded ranges that are climatically distinct from those occupied in the native range. We propose an alternative approach that involves fitting models with pooled data from all ranges. We show that this pooled approach improves prediction of the extent of invasion of spotted knapweed (Centaurea maculosa) in North America on models based solely on the European native range. Furthermore, it performs equally well on models based on the invaded range, while ensuring the inclusion of areas with similar climate to the European niche, where the species is likely to spread further. We then compare projections from these models for 2080 under a severe climate warming scenario. Projections from the pooled models show fewer areas of intermediate climatic suitability than projections from the native or invaded range models, suggesting a better consensus among modelling techniques and reduced uncertainty.

Predicting global change impacts on plant species' distributions: Future challenges

Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species' range shifts, changes in phenology and species' extinctions, accurate projections of species' responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species' responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species' distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the "trailing edge" of shifting populations, species' interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes A occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species' migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species' distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world. (c) 2007 Rubel Foundation, ETH Zurich. Published by Elsevier GrnbH. All rights reserved.

Involvement of the extracellular signal-regulated kinase cascade for cocaine-rewarding properties

A central feature of drugs of abuse is to induce gene expression in discrete brain structures that are critically involved in behavioral responses related to addictive processes. Although extracellular signal-regulated kinase (ERK) has been implicated in several neurobiological processes, including neuronal plasticity, its role in drug addiction remains poorly understood. This study was designed to analyze the activation of ERK by cocaine, its involvement in cocaine-induced early and long-term behavioral effects, as well as in gene expression. We show, by immunocytochemistry, that acute cocaine administration activates ERK throughout the striatum, rapidly but transiently. This activation was blocked when SCH 23390 [a specific dopamine (DA)-D1 antagonist] but not raclopride (a DA-D2 antagonist) was injected before cocaine. Glutamate receptors of NMDA subtypes also participated in ERK activation, as shown after injection of the NMDA receptor antagonist MK 801. The systemic injection of SL327, a selective inhibitor of the ERK kinase MEK, before cocaine, abolished the cocaine-induced ERK activation and decreased cocaine-induced hyperlocomotion, indicating a role of this pathway in events underlying early behavioral responses. Moreover, the rewarding effects of cocaine were abolished by SL327 in the place-conditioning paradigm. Because SL327 antagonized cocaine-induced c-fos expression and Elk-1 hyperphosphorylation, we suggest that the ERK intracellular signaling cascade is also involved in the prime burst of gene expression underlying long-term behavioral changes induced by cocaine. Altogether, these results reveal a new mechanism to explain behavioral responses of cocaine related to its addictive properties.

Topological comparison of methods for predicting transcriptional cooperativity in yeast

Background: The cooperative interaction between transcription factors has a decisive role in the control of the fate of the eukaryotic cell. Computational approaches for characterizing cooperative transcription factors in yeast, however, are based on different rationales and provide a low overlap between their results. Because the wealth of information contained in protein interaction networks and regulatory networks has proven highly effective in elucidating functional relationships between proteins, we compared different sets of cooperative transcription factor pairs (predicted by four different computational methods) within the frame of those networks. Results: Our results show that the overlap between the sets of cooperative transcription factors predicted by the different methods is low yet significant. Cooperative transcription factors predicted by all methods are closer and more clustered in the protein interaction network than expected by chance. On the other hand, members of a cooperative transcription factor pair neither seemed to regulate each other nor shared similar regulatory inputs, although they do regulate similar groups of target genes. Conclusion: Despite the different definitions of transcriptional cooperativity and the different computational approaches used to characterize cooperativity between transcription factors, the analysis of their roles in the framework of the protein interaction network and the regulatory network indicates a common denominator for the predictions under study. The knowledge of the shared topological properties of cooperative transcription factor pairs in both networks can be useful not only for designing better prediction methods but also for better understanding the complexities of transcriptional control in eukaryotes.

Predicting cancer involvement of genes from heterogeneous data

Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data. Results: We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature. Conclusion: Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks.

Interplay of spectral efficiency, power and doppler spectrum for reference-signal-assisted wireless communication

Expressions relating spectral efficiency, power, and Doppler spectrum, are derived for Rayleigh-faded wireless channels with Gaussian signal transmission. No side information on the state of the channel is assumed at the receiver. Rather, periodic reference signals are postulated in accordance with the functioning of most wireless systems. The analysis relies on a well-established lower bound, generally tight and asymptotically exact at low SNR. In contrast with most previous studies, which relied on block-fading channel models, a continuous-fading model is adopted. This embeds the Doppler spectrum directly in the derived expressions, imbuing them with practical significance. Closed-form relationships are obtained for the popular Clarke-Jakes spectrum and informative expansions, valid for arbitrary spectra, are found for the low- and high-power regimes. While the paper focuses on scalar channels, the extension to multiantenna settings is also discussed.

Optimum power allocation for multiuser OFDM with arbitrary signal constellations

This paper formulates power allocation policies that maximize the region of mutual informationsachievable in multiuser downlink OFDM channels. Arbitrary partitioning ofthe available tones among users and arbitrary modulation formats, possibly different forevery user, are considered. Two distinct policies are derived, respectively for slow fadingchannels tracked instantaneously by the transmitter and for fast fading channels knownonly statistically thereby. With instantaneous channel tracking, the solution adopts theform of a multiuser mercury/waterfilling procedure that generalizes the single-user mercury/waterfilling introduced in [1, 2]. With only statistical channel information, in contrast,the mercury/waterfilling interpretation is lost. For both policies, a number of limitingregimes are explored and illustrative examples are provided.

Predicting species distributions for conservation decisions.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

Autosis is a Na+,K+-ATPase-regulated form of cell death triggered by autophagy-inducing peptides, starvation, and hypoxia-ischemia.

A long-standing controversy is whether autophagy is a bona fide cause of mammalian cell death. We used a cell-penetrating autophagy-inducing peptide, Tat-Beclin 1, derived from the autophagy protein Beclin 1, to investigate whether high levels of autophagy result in cell death by autophagy. Here we show that Tat-Beclin 1 induces dose-dependent death that is blocked by pharmacological or genetic inhibition of autophagy, but not of apoptosis or necroptosis. This death, termed "autosis," has unique morphological features, including increased autophagosomes/autolysosomes and nuclear convolution at early stages, and focal swelling of the perinuclear space at late stages. We also observed autotic death in cells during stress conditions, including in a subpopulation of nutrient-starved cells in vitro and in hippocampal neurons of neonatal rats subjected to cerebral hypoxia-ischemia in vivo. A chemical screen of ~5,000 known bioactive compounds revealed that cardiac glycosides, antagonists of Na(+),K(+)-ATPase, inhibit autotic cell death in vitro and in vivo. Furthermore, genetic knockdown of the Na(+),K(+)-ATPase α1 subunit blocks peptide and starvation-induced autosis in vitro. Thus, we have identified a unique form of autophagy-dependent cell death, a Food and Drug Administration-approved class of compounds that inhibit such death, and a crucial role for Na(+),K(+)-ATPase in its regulation. These findings have implications for understanding how cells die during certain stress conditions and how such cell death might be prevented.

Spectral efficiency in reference-signal-assisted low-power wireless communication

Expressions relating spectral efficiency, power and Doppler spectrum are derived for low-power Rayleighfaded wireless channels with proper complex signaling. Noside information on the state of the channel is assumed at the receiver. Rather, periodic reference signals are postulated inaccordance with the functioning of most wireless systems. In contrast with most previous studies, which relied on block-fading channel models, a continuous-fading model is adopted. This embeds the Doppler spectrum directly in thederived expressions thereby imbuing them with practical significance.