In silico Prioritization of Transporter–Drug Relationships From Drug Sensitivity Screens

The interplay between drugs and cell metabolism is a key factor in determining both compound potency and toxicity. In particular, how and to what extent transmembrane transporters affect drug uptake and disposition is currently only partially understood. Most transporter proteins belong to two protein families: the ATP-Binding Cassette (ABC) transporter family, whose members are often involved in xenobiotic efflux and drug resistance, and the large and heterogeneous family of solute carriers (SLCs). We recently argued that SLCs are collectively a rather neglected gene group, with most of its members still poorly characterized, and thus likely to include many yet-to-be-discovered associations with drugs. We searched publicly available resources and literature to define the currently known set of drugs transported by ABCs or SLCs, which involved ∼500 drugs and more than 100 transporters. In order to extend this set, we then mined the largest publicly available pharmacogenomics dataset, which involves approximately 1,000 molecularly annotated cancer cell lines and their response to 265 anti-cancer compounds, and used regularized linear regression models (Elastic Net, LASSO) to predict drug responses based on SLC and ABC data (expression levels, SNVs, CNVs). The most predictive models included both known and previously unidentified associations between drugs and transporters. To our knowledge, this represents the first application of regularized linear regression to this set of genes, providing an extensive prioritization of potentially pharmacologically interesting interactions

Temperature Responses of Heterotrophic Bacteria in Co-culture With a Red Sea Synechococcus Strain

Interactions between autotrophic and heterotrophic bacteria are fundamental for marine biogeochemical cycling. How global warming will affect the dynamics of these essential microbial players is not fully understood. The aims of this study were to identify the major groups of heterotrophic bacteria present in a Synechococcus culture originally isolated from the Red Sea and assess their joint responses to experimental warming within the metabolic ecology framework. A co-culture of Synechococcus sp. RS9907 and their associated heterotrophic bacteria, after determining their taxonomic affiliation by 16S rRNA gene sequencing, was acclimated and maintained in the lab at different temperatures (24–34°C). The abundance and cellular properties of Synechococcus and the three dominant heterotrophic bacterial groups (pertaining to the genera Paracoccus, Marinobacter, and Muricauda) were monitored by flow cytometry. The activation energy of Synechococcus, which grew at 0.94–1.38 d–1, was very similar (0.34 ± 0.02 eV) to the value hypothesized by the metabolic theory of ecology (MTE) for autotrophs (0.32 eV), while the values of the three heterotrophic bacteria ranged from 0.16 to 1.15 eV and were negatively correlated with their corresponding specific growth rates (2.38–24.4 d–1). The corresponding carrying capacities did not always follow the inverse relationship with temperature predicted by MTE, nor did we observe a consistent response of bacterial cell size and temperature. Our results show that the responses to future ocean warming of autotrophic and heterotrophic bacteria in microbial consortia might not be well described by theoretical universal rules

Caspase-8 binding to cardiolipin in giant unilamellar vesicles provides a functional docking platform for bid

Caspase-8 is involved in death receptor-mediated apoptosis in type II cells, the proapoptotic programme of which is triggered by truncated Bid. Indeed, caspase-8 and Bid are the known intermediates of this signalling pathway. Cardiolipin has been shown to provide an anchor and an essential activating platform for caspase-8 at the mitochondrial membrane surface. Destabilisation of this platform alters receptor-mediated apoptosis in diseases such as Barth Syndrome, which is characterised by the presence of immature cardiolipin which does not allow caspase-8 binding. We used a simplified in vitro system that mimics contact sites and/or cardiolipin-enriched microdomains at the outer mitochondrial surface in which the platform consisting of caspase-8, Bid and cardiolipin was reconstituted in giant unilamellar vesicles. We analysed these vesicles by flow cytometry and confirm previous results that demonstrate the requirement for intact mature cardiolipin for caspase-8 activation and Bid binding and cleavage. We also used confocal microscopy to visualise the rupture of the vesicles and their revesiculation at smaller sizes due to alteration of the curvature following caspase-8 and Bid binding. Biophysical approaches, including Laurdan fluorescence and rupture/tension measurements, were used to determine the ability of these three components (cardiolipin, caspase-8 and Bid) to fulfil the minimal requirements for the formation and function of the platform at the mitochondrial membrane. Our results shed light on the active functional role of cardiolipin, bridging the gap between death receptors and mitochondria

Early Post-treatment Prostate-specific Antigen at 4 Weeks and Abiraterone and Enzalutamide Treatment for Advanced Prostate Cancer: An International Collaborative Analysis.

Background Declines in prostate-specific antigen (PSA) levels at 12wk are used to evaluate treatment response in metastatic castration-resistant prostate cancer (mCRPC). PSA fall by ≥30% at 4wk (PSA4w30) has been reported to be associated with better outcome in a single-centre cohort study.Objective To evaluate clinical relevance of early PSA decline in mCRPC patients treated with next-generation hormonal treatments (NGHTs) such as abiraterone and enzalutamide.Design, setting, and participants This was a retrospective multicentre analysis. Eligible patients received NGHT for mCRPC between 6 January 2006 and 31 December 2017 in 13 cancer centres worldwide, and had PSA levels assessed at baseline and at 4 and/or 12wk after treatment. PSA response was defined as a ≥30% decline (progression as a ≥25% increase) from baseline.Outcome measurements and statistical analysis Association with overall survival (OS) was analysed using landmark multivariable Cox regression adjusting for previous chemotherapy, including cancer centre as a shared frailty term.Results and limitations We identified 1358 mCRPC patients treated with first-line NGHT (1133 had PSA available at 4wk, and 948 at both 4 and 12wk). Overall, 583 (52%) had a PSA4w30; it was associated with longer OS (median: 23; 95% confidence interval [CI]: 21-25) compared with no change (median: 17; 95% CI: 15-18) and progression (median: 13; 95% CI: 10-15). A PSA12w30 was associated with lower mortality (median OS 22 vs 14; hazard ratio=0.57; 95% CI=0.48-0.67; p<0.001). PSA4w30 strongly correlated with PSA12w30 (ρ=0.91; 95% CI=0.90-0.92; p<0.001). In total, 432/494 (87%) with a PSA4w30 achieved a PSA12w30. Overall, 11/152 (7%) patients progressing at 4wk had a PSA12w30 (1% of the overall population).Conclusions PSA changes in the first 4wk of NGHT therapies are strongly associated with clinical outcome from mCRPC and can help guide early treatment switch decisions.Patient summary Prostate-specific antigen changes at 4wk after abiraterone/enzalutamide treatment are important to determine patients' outcome and should be taken into consideration in clinical practice

Central role for MCP-1/CCL2 in injury-induced inflammation revealed by in vitro, in silico, and clinical studies

The translation of in vitro findings to clinical outcomes is often elusive. Trauma/hemorrhagic shock (T/HS) results in hepatic hypoxia that drives inflammation. We hypothesize that in silico methods would help bridge in vitro hepatocyte data and clinical T/HS, in which the liver is a primary site of inflammation. Primary mouse hepatocytes were cultured under hypoxia (1% O 2) or normoxia (21% O2) for 1-72 h, and both the cell supernatants and protein lysates were assayed for 18 inflammatory mediators by Luminex™ technology. Statistical analysis and data-driven modeling were employed to characterize the main components of the cellular response. Statistical analyses, hierarchical and k-means clustering, Principal Component Analysis, and Dynamic Network Analysis suggested MCP-1/CCL2 and IL-1α as central coordinators of hepatocyte-mediated inflammation in C57BL/6 mouse hepatocytes. Hepatocytes from MCP-1-null mice had altered dynamic inflammatory networks. Circulating MCP-1 levels segregated human T/HS survivors from non-survivors. Furthermore, T/HS survivors with elevated early levels of plasma MCP-1 post-injury had longer total lengths of stay, longer intensive care unit lengths of stay, and prolonged requirement for mechanical ventilation vs. those with low plasma MCP-1. This study identifies MCP-1 as a main driver of the response of hepatocytes in vitro and as a biomarker for clinical outcomes in T/HS, and suggests an experimental and computational framework for discovery of novel clinical biomarkers in inflammatory diseases. © 2013 Ziraldo et al

Identification of a Topological Characteristic Responsible for the Biological Robustness of Regulatory Networks

Attribution of biological robustness to the specific structural properties of a regulatory network is an important yet unsolved problem in systems biology. It is widely believed that the topological characteristics of a biological control network largely determine its dynamic behavior, yet the actual mechanism is still poorly understood. Here, we define a novel structural feature of biological networks, termed ‘regulation entropy’, to quantitatively assess the influence of network topology on the robustness of the systems. Using the cell-cycle control networks of the budding yeast (Saccharomyces cerevisiae) and the fission yeast (Schizosaccharomyces pombe) as examples, we first demonstrate the correlation of this quantity with the dynamic stability of biological control networks, and then we establish a significant association between this quantity and the structural stability of the networks. And we further substantiate the generality of this approach with a broad spectrum of biological and random networks. We conclude that the regulation entropy is an effective order parameter in evaluating the robustness of biological control networks. Our work suggests a novel connection between the topological feature and the dynamic property of biological regulatory networks

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

Information Routing Driven by Background Chatter in a Signaling Network

Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity –or chatter– that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios

Unassisted solar lignin valorisation using a compartmented photo-electro-biochemical cell

Lignin is a major component of lignocellulosic biomass. Although it is highly recalcitrant to break down, it is a very abundant natural source of valuable aromatic carbons. Thus, the effective valorisation of lignin is crucial for realising a sustainable biorefinery chain. Here, we report a compartmented photo-electro-biochemical system for unassisted, selective, and stable lignin valorisation, in which a TiO2 photocatalyst, an atomically dispersed Co-based electrocatalyst, and a biocatalyst (lignin peroxidase isozyme H8, horseradish peroxidase) are integrated, such that each system is separated using Nafion and cellulose membranes. This cell design enables lignin valorisation upon irradiation with sunlight without the need for any additional bias or sacrificial agent and allows the protection of the biocatalyst from enzymedamaging elements, such as reactive radicals, gas bubbles, and light. The photo-electrobiochemical system is able to catalyse lignin depolymerisation with a 98.7% selectivity and polymerisation with a 73.3% yield using coniferyl alcohol, a lignin monomer