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Bacteriophage (phage) therapy is a promising approach to combat the rise of multidrug-resistant bacteria. Currently, the preferred clinical modality is to pair phage with an antibiotic, a practice thought to improve efficacy. However, antagonism between phage and antibiotics has been reported, the choice of phage and antibiotic is not often empirically determined, and the effect of the host factors on the effectiveness is unknown. Here, we interrogate phage-antibiotic interactions across antibiotics with different mechanisms of action. Our results suggest that phage can lower the working MIC for bacterial strains already resistant to the antibiotic, is dependent on the antibiotic class and stoichiometry of the pairing, and is dramatically influenced by the host microenvironment. The continued rise in antibiotic resistance is precipitating a medical crisis. Bacteriophage (phage) has been hailed as one possible therapeutic option to augment the efficacy of antibiotics. However, only a few studies have addressed the synergistic relationship between phage and antibiotics. Here, we report a comprehensive analysis of phage-antibiotic interaction that evaluates synergism, additivism, and antagonism for all classes of antibiotics across clinically achievable stoichiometries. We combined an optically based real-time microtiter plate readout with a matrix-like heat map of treatment potencies to measure phage and antibiotic synergy (PAS), a process we term synography. Phage-antibiotic synography was performed against a pandemic drug-resistant clonal group of extraintestinal pathogenic Escherichia coli (ExPEC) with antibiotic levels blanketing the MIC across seven orders of viral titers. Our results suggest that, under certain conditions, phages provide an adjuvating effect by lowering the MIC for drug-resistant strains. Furthermore, synergistic and antagonistic interactions are highly dependent on the mechanism of bacterial inhibition by the class of antibiotic paired to the phage, and when synergism is observed, it suppresses the emergence of resistant cells. Host conditions that simulate the infection environment, including serum and urine, suppress PAS in a bacterial growth-dependent manner. Lastly, two different related phages that differed in their burst sizes produced drastically different synograms. Collectively, these data suggest lytic phages can resuscitate an ineffective antibiotic for previously resistant bacteria while also synergizing with antibiotics in a class-dependent manner, processes that may be dampened by lower bacterial growth rates found in host environments. IMPORTANCE Bacteriophage (phage) therapy is a promising approach to combat the rise of multidrug-resistant bacteria. Currently, the preferred clinical modality is to pair phage with an antibiotic, a practice thought to improve efficacy. However, antagonism between phage and antibiotics has been reported, the choice of phage and antibiotic is not often empirically determined, and the effect of the host factors on the effectiveness is unknown. Here, we interrogate phage-antibiotic interactions across antibiotics with different mechanisms of action. Our results suggest that phage can lower the working MIC for bacterial strains already resistant to the antibiotic, is dependent on the antibiotic class and stoichiometry of the pairing, and is dramatically influenced by the host microenvironment.

Aim: The impact of multiple stressors on biodiversity is one of the most pressing questions in ecology and biodiversity conservation. Here we critically assess how often and efficiently two main drivers of global change have been simultaneously integrated into research, with the aim of providing practical solutions for better integration in the future. We focus on the integration of climate change (CC) and land‐use change (LUC) when studying changes in species distributions. Location: Global. Methods: We analysed the peer‐reviewed literature on the effects of CC and LUC on observed changes in species distributions, i.e. including species range and abundance, between 2000 and 2014. Results: Studies integrating CC and LUC remain extremely scarce, which hampers our ability to develop appropriate conservation strategies. The lack of CC–LUC integration is likely to be a result of insufficient recognition of the co‐occurrence of CC and LUC at all scales, covariation and interactions between CC and LUC, as well as correlations between species thermal and habitat requirements. Practical guidelines for the study of these interactive effects include considering multiple drivers and processes when designing studies, using available long‐term datasets on multiple drivers, revisiting single‐driver studies with additional drivers or conducting comparative studies and meta‐analyses. Combining various methodological approaches, including time lags and adaptation processes, represent further avenues to improve global change science. Main conclusions: Despite repeated claims for a better integration of multiple drivers, the effects of CC and LUC on species distributions and abundances have been mostly studied in isolation, which calls for a shift of standards towards more integrative global change science. The guidelines proposed here will encourage study designs that account for multiple drivers and improve our understanding of synergies or antagonisms among drivers.

We evaluated the potential of an investigational histone methylation reversal agent, 3-deazaneplanocin A (DZNep), in improving the chemosensitivity of pancreatic cancer to nucleoside analogs (i.e., gemcitabine). DZNep brought delayed but selective cytotoxicity to pancreatic cancer cells without affecting normal human pancreatic ductal epithelial (HPDE) cells. Co-exposure of DZNep and gemcitabine induced cytotoxic additivity or synergism in both well- and poorly-differentiated pancreatic cell lines by increased apoptosis. In contrast, DZNep exerted antagonism with gemcitabine against HPDE cells with significant reduction in cytotoxicity compared with the gemcitabine-alone regimen. DZNep marginally depended on purine nucleoside transporters for its cytotoxicity, but the transport dependence was circumvented by acyl derivatization. Drug exposure studies revealed that a short priming with DZNep followed by gemcitabine treatment rather than co-treatment of both agents to produce a maximal chemosensitization response in both gemcitabine-sensitive and gemcitabine-resistant pancreatic cancer cells. DZNep rapidly and reversibly decreased trimethylation of histone H3 lysine 27 but increased trimethylation of lysine 9 in an EZH2- and JMJD1A/2C-dependent manner, respectively. However, DZNep potentiation of nucleoside analog chemosensitization was found to be temporally coupled to trimethylation changes in lysine 27 and not lysine 9. Polymeric nanoparticles engineered to chronologically release DZNep followed by gemcitabine produced pronounced chemosensitization and dose-lowering effects. Together, our results identify that an optimized DZNep exposure can presensitize pancreatic cancer cells to anticancer nucleoside analogs through the reversal of histone methylation, emphasizing the promising clinical utilities of epigenetic reversal agents in future pancreatic cancer combination therapies.

Peroxisome‐localized oxo‐phytodienoic acid (OPDA) reductases (OPR) are enzymes converting 12‐OPDA into jasmonic acid (JA). However, the biochemical and physiological functions of the cytoplasmic non‐JA producing OPRs remain largely unknown. Here, we generated Mutator‐insertional mutants of the maize OPR2 gene and tested its role in resistance to pathogens with distinct lifestyles. Functional analyses showed that the opr2 mutants were more susceptible to the (hemi)biotrophic pathogens Colletotrichum graminicola and Ustilago maydis, but were more resistant to the necrotrophic fungus Cochliobolus heterostrophus. Hormone profiling revealed that increased susceptibility to C. graminicola was associated with decreased salicylic acid (SA) but increased JA levels. Mutation of the JA‐producing lipoxygenase 10 (LOX10) reversed this phenotype in the opr2 mutant background, corroborating the notion that JA promotes susceptibility to this pathogen. Exogenous SA did not rescue normal resistance levels in opr2 mutants, suggesting that this SA‐inducible gene is the key downstream component of the SA‐mediated defences against C. graminicola. Disease assays of the single and double opr2 and lox10 mutants and the JA‐deficient opr7opr8 mutants showed that OPR2 negatively regulates JA biosynthesis, and that JA is required for resistance against C. heterostrophus. Overall, this study uncovers a novel function of a non‐JA producing OPR as a major negative regulator of JA biosynthesis during pathogen infection, a function that leads to its contrasting contribution to either resistance or susceptibility depending on pathogen lifestyle. ZmOPR2 functions as a key component of salicylic acid‐mediated defences via suppressing jasmonic acid biosynthesis during pathogen infection, leading to its contrasting contribution to either resistance or susceptibility depending on pathogen lifestyle.

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells. Resistance to first line treatment is a major hurdle in cancer treatment, that can be overcome with drug combinations. Here, the authors provide a large drug combination screen across cancer cell lines to benchmark crowdsourced methods and to computationally predict drug synergies.

In systems with several effectors, the results of dose-response (DR) experiments are usually assessed by checking them against two hypotheses: independent action (IA) and concentration addition (CA). Both are useful simplifications, but do not represent the only possible responses, and avoid to a large extent the analysis of the interactions that are possible in the system. In addition, these are often applied in such a way that they produce insufficient descriptions of the problem that raises them, frequent inconclusive cases and doubtful decisions. In this work a generative approach is attempted, starting from some simple mechanisms necessarily underlying the response of an elementary biological entity to an effector agent. A set of simulations is formulated next through an equally simple system of logical rules, and several families of virtual responses are thus generated. These families include typical responses of IA and CA modes of action, other ones not less probable from a physiological point of view, and even other derived from common and expectable forms of interactions. The analysis of these responses enabled, firstly, to relate some phenomenological regularities with some general mechanistic principles, and to detect several causes by which the IA-CA dualism is necessarily ambiguous. Secondly, it allowed identifying different forms of synergy and antagonism that contribute to explain some controversial aspects of these notions. Finally, it led to propose two sets of explicit algebraic equations that describe accurately a wide diversity of possible and realistic responses.

Background Incidental adrenal masses are commonly detected during imaging for other pathologies. 10% of the elderly population has an 'adrenal incidentaloma', up to 20% of these show low-grade autonomous cortisol secretion and 60% of patients with autonomous cortisol secretion have insulin resistance. Cortisol excess is known to cause insulin resistance, an independent cardiovascular risk marker, however in patients with adrenal incidentalomas it is unknown whether their insulin resistance is secondary to the excess cortisol and therefore potentially reversible. In a proof of concept study we examined the short-term effects of glucocorticoid receptor (GR) antagonism in patients with an adrenal incidentaloma to determine whether their insulin resistance was reversible. Methodology/Principal Findings In a prospective open-label pilot study, six individuals with adrenal incidentalomas and autonomous cortisol secretion were treated with mifepristone (a GR antagonist) 200 mg twice daily and studied for 4 weeks on a Clinical Research Facility. Insulin resistance at four weeks was assessed by insulin resistance indices, lnHOMA-IR and lnMatsuda, and AUC insulin during a 2-hour glucose tolerance test. Biochemical evidence of GR blockade was shown in all individuals and across the group there was a significant reduction in insulin resistance: lnHOMA-IR (1.0vs0.6; p = 0.03), lnHOMA-%beta (4.8vs4.3; p = 0.03) and lnMatsuda (1.2vs1.6; p = 0.03). Five out of six individuals showed a reduction in insulin AUC >7237 pmol/l.min, and in two patients this showed a clinically significant cardiovascular benefit (as defined by the Helsinki heart study). Conclusions Short-term GR antagonism is sufficient to reduce insulin resistance in some individuals with adrenal incidentalomas and mild cortisol excess. Further assessment is required to assess if the responses may be used to stratify therapy as adrenal incidentalomas may be a common remediable cause of increased cardiovascular risk. Trial Registration ClinicalTrials.gov NCT00721201

Although synergy is a pillar of modern pharmacology, toxicology, and medicine, there is no consensus on its definition despite its nearly one hundred-year history. Moreover, methods for statistical determination of synergy that account for variation of response to treatment are underdeveloped and if exist are reduced to the traditional t-test, but do not comply with the normal distribution assumption. We offer statistical models for estimation of synergy using an established definition of Bliss drugs' independence. Although Bliss definition is well-known, it remains a theoretical concept and has never been applied for statistical determination of synergy with various forms of treatment outcome. We rigorously and consistently extend the Bliss definition to detect statistically significant synergy under various designs: (1) in vitro, when the outcome of a cell culture experiment with replicates is the proportion of surviving cells for a single dose or multiple doses, (2) dose-response methodology, (3) in vivo studies in organisms, when the outcome is a longitudinal measurement such as tumor volume, and (4) clinical studies, when the outcome of treatment is measured by survival. For each design, we developed a specific statistical model and demonstrated how to test for independence, synergy, and antagonism, and compute the associated p-value.

Anthropogenic environmental changes, or ‘stressors’, increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.

In this interview, academics Mauro Salazar and Alejandro Osorio talk with Argentine political theorist Ernesto Laclau, whose work has been of special relevance in understanding a wave of national-popular governments in Latin America in recent decades. In this respect, the scope of this interview deals with general and specific aspects of the (post-)Marxist tradition, but with an accent on the uses and abuses of the notion of hegemony, given the discursive nature of the approach in question. Thus, along with reviewing a diversity of political matters, Laclau’s notion of hegemony creates a space from which to think about the mixtures of populism