Linear Pathway Research Articles

BMI1–UBR5 axis regulates transcriptional repression at damaged chromatin

BMI1 is a component of the Polycomb Repressive Complex 1 (PRC1), which plays a key role in maintaining epigenetic silencing during development. BMI1 also participates in gene silencing during DNA damage response, but the precise downstream function of BMI1 in gene silencing is unclear. Here we identified the UBR5 E3 ligase as a downstream factor of BMI1. We found that UBR5 forms damage-inducible nuclear foci in a manner dependent on the PRC1 components BMI1, RNF1 (RING1a), and RNF2 (RING1b). Whereas transcription is repressed at UV-induced lesions on chromatin, depletion of the PRC1 members or UBR5 alone derepressed transcription elongation at these sites, suggesting that UBR5 functions in a linear pathway with PRC1 in inducing gene silencing at lesions. Mass spectrometry (MS) analysis revealed that UBR5 associates with BMI1 as well as FACT components SPT16 and SSRP1. We found that UBR5 localizes to the UV-induced lesions along with SPT16. We show that UBR5 ubiquitinates SPT16, and depletion of UBR5 or BMI1 leads to an enlargement of SPT16 foci size at UV lesions, suggesting that UBR5 and BMI1 repress SPT16 enrichment at the damaged sites. Consistently, depletion of the FACT components effectively reversed the transcriptional derepression incurred in the UBR5 and BMI1 KO cells. Finally, UBR5 and BMI1 KO cells are hypersensitive to UV, which supports the notion that faulty RNA synthesis at damaged sites is harmful to the cell fitness. Altogether, these results suggest that BMI1 and UBR5 repress the polymerase II (Pol II)-mediated transcription at damaged sites, by negatively regulating the FACT-dependent Pol II elongation.

Where Next for Social Protection?

The rapid ascendancy of social protection up the development policy agenda raises questions about whether its current prominence will be sustained, or whether it will turn out to be just another development fad. What trajectory will social protection follow, which actors will drive it forward and what will be the main issues and challenges? This article reports on a small foresight study designed to address the question: ‘Where next for social protection?’ A scenario-building exercise revealed that there is no single linear pathway for social protection, but multiple highly context-specific trajectories subject to change as political ideologies and institutional capacities shift. A ‘wind-tunnelling’ exercise highlighted the importance of a country’s political regime as a fundamental determinant of which social protection policies will be adopted. Better understanding of political processes is needed to protect gains made in social protection against possible reversals when the political climate shifts against pro-poor redistributive policies.

Dynamic optimization of biological networks under parametric uncertainty.

BackgroundMicro-organisms play an important role in various industrial sectors (including biochemical, food and pharmaceutical industries). A profound insight in the biochemical reactions inside micro-organisms enables an improved biochemical process control. Biological networks are an important tool in systems biology for incorporating microscopic level knowledge. Biochemical processes are typically dynamic and the cells have often more than one objective which are typically conflicting, e.g., minimizing the energy consumption while maximizing the production of a specific metabolite. Therefore multi-objective optimization is needed to compute trade-offs between those conflicting objectives. In model-based optimization, one of the inherent problems is the presence of uncertainty. In biological processes, this uncertainty can be present due to, e.g., inherent biological variability. Not taking this uncertainty into account, possibly leads to the violation of constraints and erroneous estimates of the actual objective function(s). To account for the variance in model predictions and compute a prediction interval, this uncertainty should be taken into account during process optimization. This leads to a challenging optimization problem under uncertainty, which requires a robustified solution.ResultsThree techniques for uncertainty propagation: linearization, sigma points and polynomial chaos expansion, are compared for the dynamic optimization of biological networks under parametric uncertainty. These approaches are compared in two case studies: (i) a three-step linear pathway model in which the accumulation of intermediate metabolites has to be minimized and (ii) a glycolysis inspired network model in which a multi-objective optimization problem is considered, being the minimization of the enzymatic cost and the minimization of the end time before reaching a minimum extracellular metabolite concentration. A Monte Carlo simulation procedure has been applied for the assessment of the constraint violations. For the multi-objective case study one Pareto point has been considered for the assessment of the constraint violations. However, this analysis can be performed for any Pareto point.ConclusionsThe different uncertainty propagation strategies each offer a robustified solution under parametric uncertainty. When making the trade-off between computation time and the robustness of the obtained profiles, the sigma points and polynomial chaos expansion strategies score better in reducing the percentage of constraint violations. This has been investigated for a normal and a uniform parametric uncertainty distribution. The polynomial chaos expansion approach allows to directly take prior knowledge of the parametric uncertainty distribution into account.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0328-6) contains supplementary material, which is available to authorized users.

Gene-gene interactions in gastrointestinal cancer susceptibility.

Cancer arises from complex, multi-layer interactions between diverse genetic and environmental factors. Genetic studies have identified multiple loci associated with tumor susceptibility. However, little is known about how germline polymorphisms interact with one another and with somatic mutations within a tumor to mediate acquisition of cancer traits. Here, we survey recent studies showing gene-gene interactions, also known as epistases, affecting genetic susceptibility in colorectal, gastric and esophageal cancers. We also catalog epistasis types and cancer hallmarks with respect to the interacting genes. A total of 22 gene variation pairs displayed all levels of statistical epistasis, including synergistic, redundant, suppressive and co-suppressive interactions. Five genes primarily involved in base excision repair formed a linear topology in the interaction network, MUTYH-OGG1-XRCC1-PARP1-MMP2, and three genes in mTOR cell-proliferation pathway formed another linear network, PRKAG2-RPS6KB1-PIK3CA. Discrete pairwise epistasis was also found in nucleotide excision repair, detoxification, proliferation, TP53, TGF-β and other pathways. We propose that three modes of biological interaction underlie the molecular mechanisms for statistical epistasis. The direct binding, linear pathway and convergence modes can exhibit any level of statistical epistasis in susceptibility to gastrointestinal cancers, and this is likely true for other complex diseases as well. This review highlights the link between cancer hallmarks and susceptibility genes.

Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene signaling. Analysis of each network topology results in predictions about changes that occur in network components that can be experimentally tested to give insights into which, if either, network underlies ethylene responses.

A Toll receptor-FoxO pathway represses Pavarotti/MKLP1 to promote microtubule dynamics in motoneurons.

FoxO proteins are evolutionarily conserved regulators of neuronal structure and function, yet the neuron-specific pathways within which they act are poorly understood. To elucidate neuronal FoxO function in Drosophila melanogaster, we first screened for FoxO's upstream regulators and downstream effectors. On the upstream side, we present genetic and molecular pathway analyses indicating that the Toll-6 receptor, the Toll/interleukin-1 receptor domain adaptor dSARM, and FoxO function in a linear pathway. On the downstream side, we find that Toll-6-FoxO signaling represses the mitotic kinesin Pavarotti/MKLP1 (Pav-KLP), which itself attenuates microtubule (MT) dynamics. We next probed in vivo functions for this novel pathway and found that it is essential for axon transport and structural plasticity in motoneurons. We demonstrate that elevated expression of Pav-KLP underlies transport and plasticity phenotypes in pathway mutants, indicating that Toll-6-FoxO signaling promotes MT dynamics by limiting Pav-KLP expression. In addition to uncovering a novel molecular pathway, our work reveals an unexpected function for dynamic MTs in enabling rapid activity-dependent structural plasticity.

Folding analysis of the most complex Stevedore's protein knot.

DehI is a homodimeric haloacid dehalogenase from Pseudomonas putida that contains the most complex 61 Stevedore’s protein knot within its folding topology. To examine how DehI attains such an intricate knotted topology we combined far-UV circular dichroism (CD), intrinsic fluorescence spectroscopy and small angle X-ray scattering (SAXS) to investigate its folding mechanism. Equilibrium unfolding of DehI by chemical denaturation indicated the presence of two highly populated folding intermediates, I and I’. While the two intermediates vary in secondary structure contents and tertiary packing according to CD and intrinsic fluorescence, respectively, their overall dimension and compactness are similar according to SAXS. Three single-tryptophan variants (W34, W53, and W196) were generated to probe non-cooperative unfolding events localized around the three fluorophores. Kinetic fluorescence measurements indicated that the transition from the intermediate I’ to the unfolded state is rate limiting. Our multiparametric folding analyses suggest that DehI unfolds through a linear folding pathway with two distinct folding intermediates by initial hydrophobic collapse followed by nucleation condensation, and that knotting precedes the formation of secondary structures.

Effects of a Cardiotonic Medicine, Danshen Pills, on Cognitive Ability and Expression of PSD-95 in a Vascular Dementia Rat Model

A widely used Chinese cardiotonic proprietary medicine, compound Danshen dripping pills (CDDP, Fufang Danshen Diwan) has also begun to be used for treatment of vascular dementia (VaD). We tried to explore the mechanism of CDDP action in this case. A VaD experimental model was built in rats by bilateral ligation of the common carotid arteries. The cognitive ability of experimental animals was evaluated in the Morris water maze test. Synaptic ultrastructural changes in the hippocampus were detected by transmission electron microscopy; expression of PSD-95 mRNA in the hippocampus was examined using hybridization in situ. The latter index (mRNA expression) in the VaD group was significantly lower than those in the CDDP and sham-operated groups (P < 0.05). CDDP treatment considerably improved disturbed ultrastructural synaptic characteristics in the hippocampus of VaD rats. The mean escape latency in the Morris water maze test was significantly shorter in CDDP-treated VaD rats, compared with that those of the VaD group (P < 0.05). In the CDDP group compared to the VaD one, escape strategies improved from edge and random searches to more linear swim pathway (P < 0.05). Thus, decreasing expression of PSD-95 plays an important role in the pathogenesis of VaD. CDDP treatment improves the learning and memory ability of VaD rats by improving neural synaptic ultrastructural characteristics and increasing expression of PSD-95 mRNA in the hippocampus.

Ambiguity: A new way of thinking about responses to climate change

Diversity, interdisciplinarity and transdisciplinarity are now recognized as vital to tackling wicked problems such as those presented by a changing climate (Nature editorial 2015, Ledford 2015; Dick et al., 2016). Including diverse disciplines in science projects enables a range of different views which often facilitate the creation of innovative solutions. Supporting multiple views and options requires a different way of working beyond traditional reductionist approaches to science, communication and decision-making. To embrace diversity in scientific project teams in order to tackle complex, integrated and urgent issues but to expect singular and linear pathways forward is paradoxical. Much has been written about the need for the scientific community to embrace uncertainty (e.g. Popper, Lempert & Bankes 2005; Lempert et al., 2004; Nelson, Howden & Hayman 2013; Bammer & Smithson 2008). We argue that this in itself will not suffice, and that there is also a need to embrace ambiguity in certain situations. Thus, in this article we explore: (1) what ambiguity is, including the benefits it can offer to climate adaptation in particular, using existing approaches to ambiguity in the arts and humanities as examples (2), we discuss practical meanings of ambiguity in relation to climate change, (3) we propose possible next steps for bringing ambiguity into interdisciplinary practice, and (4) we identify some challenges and necessary preconditions to successfully and appropriately embracing ambiguity.

Coordination of the recruitment of the FANCD2 and PALB2 Fanconi anemia proteins by an ubiquitin signaling network

Fanconi anemia (FA) is a chromosome instability syndrome and the 20 identified FA proteins are organized into two main arms which are thought to function at distinct steps in the repair of DNA interstrand crosslinks (ICLs). These two arms include the upstream FA pathway, which culminates in the monoubiquitination of FANCD2 and FANCI, and downstream breast cancer (BRCA)-associated proteins that interact in protein complexes. How, and whether, these two groups of FA proteins are integrated is unclear. Here, we show that FANCD2 and PALB2, as indicators of the upstream and downstream arms, respectively, colocalize independently of each other in response to DNA damage induced by mitomycin C (MMC). We also show that ubiquitin chains are induced by MMC and colocalize with both FANCD2 and PALB2. Our finding that the RNF8 E3 ligase has a role in recruiting FANCD2 and PALB2 also provides support for the hypothesis that the two branches of the FA-BRCA pathway are coordinated by ubiquitin signaling. Interestingly, we find that the RNF8 partner, MDC1, as well as the ubiquitin-binding protein, RAP80, specifically recruit PALB2, while a different ubiquitin-binding protein, FAAP20, functions only in the recruitment of FANCD2. Thus, FANCD2 and PALB2 are not recruited in a single linear pathway, rather we define how their localization is coordinated and integrated by a network of ubiquitin-related proteins. We propose that such regulation may enable upstream and downstream FA proteins to act at distinct steps in the repair of ICLs.

Suicide surveillance and health systems in Nepal: a qualitative and social network analysis.

BackgroundDespite increasing recognition of the high burden of suicide deaths in low- and middle-income countries, there is wide variability in the type and quality of data collected and reported for suspected suicide deaths. Suicide data are filtered through reporting systems shaped by social, cultural, legal, and medical institutions. Lack of systematic reporting may underestimate public health needs or contribute to misallocation of resources to groups most at risk.MethodsThe goal of this study was to explore how institutional structures, cultural perspectives on suicide, and perceived criminality of self-harm influence the type and quality of suicide statistics, using Nepal as an example because of its purported high rate of suicide in the public health literature. Official documentation and reporting networks drawn by police, policy makers, and health officials were analyzed. Thirty-six stakeholders involved in various levels of the death reporting systems in Nepal participated in in-depth interviews and an innovative drawn surveillance system elicitation task.ResultsContent analysis and social network analysis revealed large variation across the participants perceived networks, where some networks were linear pathways dominated by a single institution (police or community) with few nodes involved in data transmission, while others were complex and communicative. Network analysis demonstrated that police institutions controlled the majority of suicide information collection and reporting, whereas health and community institutions were only peripherally involved. Both health workers and policy makers reported that legal codes criminalizing suicide impaired documentation, reporting, and care provision. However, legal professionals and law review revealed that attempting suicide is not a crime punishable by incarceration. Another limitation of current reporting was the lack of attention to male suicide.ConclusionsEstablishment and implementation of national suicide prevention strategies will not be possible without reliable statistics and comprehensive standardized reporting practices. The case of Nepal points to the need for collaborative reporting and accountability shared between law enforcement, administrative, and health sectors. Awareness of legal codes among health workers, in particular dispelling myths of suicide’s illegality, is crucial to improve mental health services and reporting practices.

Systems pharmacology – Towards the modeling of network interactions

Mechanism-based pharmacokinetic and pharmacodynamics (PKPD) and disease system (DS) models have been introduced in drug discovery and development research, to predict in a quantitative manner the effect of drug treatment in vivo in health and disease. This requires consideration of several fundamental properties of biological systems behavior including: hysteresis, non-linearity, variability, interdependency, convergence, resilience, and multi-stationarity.Classical physiology-based PKPD models consider linear transduction pathways, connecting processes on the causal path between drug administration and effect, as the basis of drug action. Depending on the drug and its biological target, such models may contain expressions to characterize i) the disposition and the target site distribution kinetics of the drug under investigation, ii) the kinetics of target binding and activation and iii) the kinetics of transduction. When connected to physiology-based DS models, PKPD models can characterize the effect on disease progression in a mechanistic manner. These models have been found useful to characterize hysteresis and non-linearity, yet they fail to explain the effects of the other fundamental properties of biological systems behavior.Recently systems pharmacology has been introduced as novel approach to predict in vivo drug effects, in which biological networks rather than single transduction pathways are considered as the basis of drug action and disease progression. These models contain expressions to characterize the functional interactions within a biological network. Such interactions are relevant when drugs act at multiple targets in the network or when homeostatic feedback mechanisms are operative. As a result systems pharmacology models are particularly useful to describe complex patterns of drug action (i.e. synergy, oscillatory behavior) and disease progression (i.e. episodic disorders).In this contribution it is shown how physiology-based PKPD and disease models can be extended to account for internal systems interactions. It is demonstrated how SP models can be used to predict the effects of multi-target interactions and of homeostatic feedback on the pharmacological response. In addition it is shown how DS models may be used to distinguish symptomatic from disease modifying effects and to predict the long term effects on disease progression, from short term biomarker responses. It is concluded that incorporation of expressions to describe the interactions in biological network analysis opens new avenues to the understanding of the effects of drug treatment on the fundamental aspects of biological systems behavior.

The Oxygen quantum yield in diverse algae and cyanobacteria is controlled by partitioning of flux between linear and cyclic electron flow within photosystem II

We have measured flash-induced oxygen quantum yields (O2-QYs) and primary charge separation (Chl variable fluorescence yield, Fv/Fm) in vivo among phylogenetically diverse microalgae and cyanobacteria. Higher O2-QYs can be attained in cells by releasing constraints on charge transfer at the Photosystem II (PSII) acceptor side by adding membrane-permeable benzoquinone (BQ) derivatives that oxidize plastosemiquinone QB− and QBH2. This method allows uncoupling PSII turnover from its natural regulation in living cells, without artifacts of isolating PSII complexes. This approach reveals different extents of regulation across species, controlled at the QB− acceptor site. Arthrospira maxima is confirmed as the most efficient PSII-WOC (water oxidizing complex) and exhibits the least regulation of flux. Thermosynechococcus elongatus exhibits an O2-QY of 30%, suggesting strong downregulation. WOC cycle simulations with the most accurate model (VZAD) show that a light-driven backward transition (net addition of an electron to the WOC, distinct from recombination) occurs in up to 25% of native PSIIs in the S2 and S3 states, while adding BQ prevents backward transitions and increases the lifetime of S2 and S3 by 10-fold. Backward transitions occur in PSIIs that have plastosemiquinone radicals in the QB site and are postulated to be physiologically regulated pathways for storing light energy as proton gradient through direct PSII-cyclic electron flow (PSII-CEF). PSII-CEF is independent of classical PSI/cyt-b6f-CEF and provides an alternative proton translocation pathway for energy conversion. PSII-CEF enables variable fluxes between linear and cyclic electron pathways, thus accommodating species-dependent needs for redox and ion-gradient energy sources powered by a single photosystem.

Principles of geomorphic disturbance and recovery in response to storms

AbstractThe most important geomorphic responses to storms are qualitative changes in system state. Minor storms produce no state change or very rapid recovery to pre‐storm state, and extinction events wipe out the system. In other cases disturbance results in a state change, which may be transitional (change to a previously existing state), state space expansion (change to a new state), and clock‐resetting events that return the system to its initial state. Recovery pathways are much more varied than the monotonic progressions represented in classic vegetation succession and linear channel evolution models. Those linear sequential pathways are only one of several archetypal recovery pathways, which also include binary, convergent, divergent, and more complex networks. Filter‐dominated systems are more likely to follow linear sequential or convergent patterns, whereas amplifier‐dominance is characteristic of divergent and more complex mesh or fully‐connected patterns. Amplifier domination is also more likely to lead to evolutionary or state space expansion responses. Amplification and filtering in geomorphic response and recovery can be assessed using the 'Four R's' framework of response, resistance, relaxation, and recursion. High resistance and resilience, rapid relaxation times, and stable recursive feedback networks reduce or offset effects of disturbances, thus filtering their impacts. Conversely, low resistance and resilience, slow relaxation, and dynamically unstable feedbacks can exaggerate disturbances, creating disproportionately large and long‐lived impacts, thereby amplifying disturbances.Unless new filter mechanisms evolve (either autogenically or anthropically), or the number of extinction or clock‐resetting events increases, intensified storminess will result in more geomorphic variability. These ideas are applied to a case study of a flood on the Clark Fork River, Montana, USA. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Population pharmacokinetics and exposure-response relationship of amatuximab, an anti-mesothelin monoclonal antibody, in patients with malignant pleural mesothelioma and its application in dose selection.

To characterize amatuximab pharmacokinetics (PK) and the relationship of amatuximab exposure with response in patients with unresectable malignant pleural mesothelioma (MPM) receiving amatuximab with pemetrexed and cisplatin. A nonlinear mixed effects PK model was built using data from all of the amatuximab studies conducted to date. Patients received amatuximab alone or in combination with chemotherapy. The influence of demographic, laboratory and disease characteristics on PK parameters was assessed. Exposure-response analyses explored relationships between amatuximab exposure and overall survival (OS), progression-free survival (PFS) and safety. Alternative amatuximab dosing regimens were explored with simulations using population PK and parametric survival models. Amatuximab PK was best described by a two-compartment model with parallel linear and nonlinear elimination pathways. Body weight and an antidrug antibodies reaction with the titer >64 affected volume of distribution and clearance, respectively. Exposure-response analyses demonstrated that the amatuximab exposure (C min) showed a significant effect on OS (log-rank test, P=0.0202). For patients with amatuximab C min above the median (38.2μg/mL), the median OS was 583days (90% CI 418 -NE). For patients with C min≤38.2μg/mL, the median OS was 375days (90% CI 325-486). The amatuximab exposure showed similar significant effect on PFS. Exposure-response analysis for adverse events did not reveal any relationship. In patients with MPM, higher amatuximab exposure in combination with chemotherapy was shown to be associated with longer OS, supporting evaluation of more frequent dosing in future trials to achieve higher exposure and subsequently longer OS.

GED: a manually curated comprehensive resource for epigenetic modification of gametogenesis

Reproductive infertility affects seventh of couples, which is most attributed to the obstacle of gametogenesis. Characterizing the epigenetic modification factors involved in gametogenesis is fundamental to understand the molecular mechanisms and to develop treatments for human infertility. Although the genetic factors have been implicated in gametogenesis, no dedicated bioinformatics resource for gametogenesis is available. To elucidate the relationship of epigenetic modification and mammalian gametogenesis, we developed a new database, gametogenesis epigenetic modification database (GED), a manually curated database, which aims at providing a comprehensive resource of epigenetic modification of gametogenesis. The database integrates three kinds information of epigenetic modifications during gametogenesis (DNA methylation, histone modification and RNA regulation), and the gametogenesis has been detailed as 16 stages in seven mammal species (Homo sapiens, Mus musculus, Rattus norvegicus, Sus scrofa, Bos taurus, Capra hircus and Ovis aries). Besides, we have predicted the linear pathways of epigenetic modification which were composed of 211 genes/proteins and microRNAs that were involved in gametogenesis. GED is a user-friendly Web site, through which users can obtain the comprehensive epigenetic factor information and molecular pathways by visiting our database freely. GED is free available at http://gametsepi.nwsuaflmz.com.

NMR-based metabonomic analysis of normal rat urine and faeces in response to (±)-venlafaxine treatment

(±)-Venlafaxine, a bicyclic antidepressant of the serotonin-norepinephrine reuptake inhibitor (SNRI) class, is prescribed for the treatment of depression and anxiety disorders. As is the case with other antidepressants, its precise mechanisms of action are still unknown. Pharmacometabonomic approaches allow for the detection of diverse metabolites, unlike classic methods for analysing drug interaction based on single metabolites and linear pathways. This provides a global view of the state of homeostasis during treatment and an insight into the mechanisms of action of a drug. Accordingly, the final outcome of treatment is characterised by the network of reactome pathways derived from the on-target and off-target effects of the drug. Regarding antidepressants, the drug network may be located in the gut–microbiome–brain–liver–kidney–immune–cardiovascular system axis (GMBLKICA), implying that neurotransmitters participate as signalling molecules in bidirectional communication. If their bioavailability is increased, this communication and the state of homeostasis may be disrupted. With a pharmacometabonomic approach using NMR in combination with different chemometric methods, a determination was made of subtle changes in the metabolic profile (metabotype) of urine and faeces in normal Wistar rats following a single administration of pharmacological doses of (±)-venlafaxine hydrochloride. Based on the drug-response metabotypes observed, (±)-venlafaxine had effects on gut microbial co-metabolites and osmolytes. Hence, it can be hypothesized that bidirectional communication in the multiorgan axis was perturbed by this drug, and very likely by its active metabolite, (±)-desvenlafaxine. This disrupted signalling could be related not only to therapeutic and adverse effects, but also to the lag period in treatment response.

Glycosylation of a Fasciclin-Like Arabinogalactan-Protein (SOS5) Mediates Root Growth and Seed Mucilage Adherence via a Cell Wall Receptor-Like Kinase (FEI1/FEI2) Pathway in Arabidopsis.

Fundamental processes that underpin plant growth and development depend crucially on the action and assembly of the cell wall, a dynamic structure that changes in response to both developmental and environmental cues. While much is known about cell wall structure and biosynthesis, much less is known about the functions of the individual wall components, particularly with respect to their potential roles in cellular signaling. Loss-of-function mutants of two arabinogalactan-protein (AGP)-specific galactosyltransferases namely, GALT2 and GALT5, confer pleiotropic growth and development phenotypes indicating the important contributions of carbohydrate moieties towards AGP function. Notably, galt2galt5 double mutants displayed impaired root growth and root tip swelling in response to salt, likely as a result of decreased cellulose synthesis. These mutants phenocopy a salt-overly sensitive mutant called sos5, which lacks a fasciclin-like AGP (SOS5/FLA4) as well as a fei1fei2 double mutant, which lacks two cell wall-associated leucine-rich repeat receptor-like kinases. Additionally, galt2gal5 as well as sos5 and fei2 showed reduced seed mucilage adherence. Quintuple galt2galt5sos5fei1fei2 mutants were produced and provided evidence that these genes act in a single, linear genetic pathway. Further genetic and biochemical analysis of the quintuple mutant demonstrated involvement of these genes with the interplay between cellulose biosynthesis and two plant growth regulators, ethylene and ABA, in modulating root cell wall integrity.

ESCRT-III on endosomes: new functions, new activation pathway.

The multivesicular body (MVB) pathway sorts ubiquitinated membrane cargo to intraluminal vesicles (ILVs) within the endosome, en route to the lysosomal lumen. The pathway involves the sequential action of conserved protein complexes [endosomal sorting complexes required for transport (ESCRTs)], culminating in the activation by ESCRT-II of ESCRT-III, a membrane-sculpting complex. Although this linear pathway of ESCRT activation is widely accepted, a study by Luzio and colleagues in a recent issue of the Biochemical Journal suggests that there is greater complexity in ESCRT-III activation, at least for some MVB cargoes. They show that ubiquitin-dependent sorting of major histocompatibility complex (MHC) class I to the MVB requires the central ESCRT-III complex but does not involve either ESCRT-II or functional links between ESCRT-II and ESCRT-III. Instead, they propose that MHC class I utilizes histidine-domain protein tyrosine phosphatase (HD-PTP), a non-canonical ESCRT interactor, to promote ESCRT-III activation.

Studying Cancer Evolution in Barrett's Esophagus and Esophageal Adenocarcinoma.

Technological advances in genome sequencing and copy number analysis have allowed researchers to catalog the wide variety of genomic alterations that occur across diverse cancer types. For most cancer types, the lack of high-frequency alterations and the heterogeneity observed both within and between tumors suggest neoplastic progression proceeds through a branched evolutionary pathway as proposed by Nowell in 1976, as opposed to the linear pathway that has dominated medical science for the last century. To understand how cancer evolves over time and space in the body, new study designs are needed that can distinguish between alterations that develop in patients who progress to cancer from to those who don't. Here we present approaches developed in the study of Barrett's esophagus, a premalignant precursor of esophageal adenocarcinoma, and discuss strategies for applying the results from these analyses to address the critical clinical problems of overdiagnosis of benign disease, early detection of life-threatening cancer, and effective risk stratification.