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Viral replication relies on host metabolic machinery and precursors to produce large numbers of progeny - often very rapidly. A fundamental example is the infection of Escherichia coli by bacteriophage T7. The resource draw imposed by viral replication represents a significant and complex perturbation to the extensive and interconnected network of host metabolic pathways. To better understand this system, we have integrated a set of structured ordinary differential equations quantifying T7 replication and an E. coli flux balance analysis metabolic model. Further, we present here an integrated simulation algorithm enforcing mutual constraint by the models across the entire duration of phage replication. This method enables quantitative dynamic prediction of virion production given only specification of host nutritional environment, and predictions compare favorably to experimental measurements of phage replication in multiple environments. The level of detail of our computational predictions facilitates exploration of the dynamic changes in host metabolic fluxes that result from viral resource consumption, as well as analysis of the limiting processes dictating maximum viral progeny production. For example, although it is commonly assumed that viral infection dynamics are predominantly limited by the amount of protein synthesis machinery in the host, our results suggest that in many cases metabolic limitation is at least as strict. Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism.

Can a bacterial cell model vet large datasets from disparate sources? Macklin et al. explored whether a comprehensive mathematical model can be used to verify or find conflicts in massive amounts of data that have been reported for the bacterium Escherichia coli , produced in thousands of papers from hundreds of labs. Although most data were consistent, there were data that could not accommodate known biological results, such as insufficient output of RNA polymerases and ribosomes to produce measured cell-doubling times. Other analyses showed that for some essential proteins, no RNA may be transcribed or translated in a cell's lifetime, but viability can be maintained without certain enzymes through a pool of stable metabolites produced earlier. Science , this issue p. eaav3751 Construction of a large-scale mechanistic model of Escherichia coli brings models and large datasets together to enhance knowledge in biology. The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle—and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

Lipopolysaccharide (LPS), found in the outer membrane of gram-negative bacteria, elicits a strong response from the transcription factor family Nuclear factor (NF)-κB via Toll-like receptor (TLR) 4. The cellular response to lipopolysaccharide varies depending on the source and preparation of the ligand, however. Our goal was to compare single-cell NF-κB dynamics across multiple sources and concentrations of LPS. Using live-cell fluorescence microscopy, we determined the NF-κB activation dynamics of hundreds of single cells expressing a p65-dsRed fusion protein. We used computational image analysis to measure the nuclear localization of the fusion protein in the cells over time. The concentration range spanned up to nine orders of magnitude for three E. coli LPS preparations. We find that the LPS preparations induce markedly different responses, even accounting for potency differences. We also find that the ability of soluble TNF receptor to affect NF-κB dynamics varies strikingly across the three preparations. Our work strongly suggests that the cellular response to LPS is highly sensitive to the source and preparation of the ligand. We therefore caution that conclusions drawn from experiments using one preparation may not be applicable to LPS in general.

Lipopolysaccharide (LPS), found in the outer membrane of gram-negative bacteria, elicits a strong response from the transcription factor family Nuclear factor (NF)-[kappa]B via Toll-like receptor (TLR) 4. The cellular response to lipopolysaccharide varies depending on the source and preparation of the ligand, however. Our goal was to compare single-cell NF-[kappa]B dynamics across multiple sources and concentrations of LPS. Using live-cell fluorescence microscopy, we determined the NF-[kappa]B activation dynamics of hundreds of single cells expressing a p65-dsRed fusion protein. We used computational image analysis to measure the nuclear localization of the fusion protein in the cells over time. The concentration range spanned up to nine orders of magnitude for three E. coli LPS preparations. We find that the LPS preparations induce markedly different responses, even accounting for potency differences. We also find that the ability of soluble TNF receptor to affect NF-[kappa]B dynamics varies strikingly across the three preparations. Our work strongly suggests that the cellular response to LPS is highly sensitive to the source and preparation of the ligand. We therefore caution that conclusions drawn from experiments using one preparation may not be applicable to LPS in general.

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model ofEscherichia colienabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle—and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

Mycoplasma ovipneumoniae, a well-established respiratory pathogen of sheep and goats, has gained increased importance recently because of its detection in wild ruminants including members of the Cervidae family. Despite its frequent isolation from apparently healthy animals, it is responsible for outbreaks of severe respiratory disease which are often linked to infections with multiple heterologous strains. Furthermore, M. ovipneumoniae is characterized by an unusually wide host range, a high degree of phenotypic, biochemical, and genomic heterogeneity, and variable and limited growth in mycoplasma media. A number of mechanisms have been proposed for its pathogenicity, including the production of hydrogen peroxide, reactive oxygen species production, and toxins. It shows wide metabolic activity in vitro, being able to utilize substrates such as glucose, pyruvate, and isopropanol; these patterns can be used to differentiate strains. Treatment of infections in the field is complicated by large variations in the susceptibility of strains to antimicrobials, with many showing high minimum inhibitory concentrations. The lack of commercially available vaccines is probably due to the high cost of developing vaccines for diseases in small ruminants not presently seen as high priority. Multiple strains found in affected sheep and goats may also hamper the development of effective vaccines. This review summarizes the current knowledge and identifies gaps in research on M. ovipneumoniae, including its epidemiology in sheep and goats, pathology and clinical presentation, infection in wild ruminants, virulence factors, metabolism, comparative genomics, genotypic variability, phenotypic variability, evolutionary mechanisms, isolation and culture, detection and identification, antimicrobial susceptibility, variations in antimicrobial susceptibility profiles, vaccines, and control.

The mammalian target of rapamycin (mTOR) kinase is a master regulator of protein synthesis that couples nutrient sensing to cell growth and cancer. However, the downstream translationally regulated nodes of gene expression that may direct cancer development are poorly characterized. Using ribosome profiling, we uncover specialized translation of the prostate cancer genome by oncogenic mTOR signalling, revealing a remarkably specific repertoire of genes involved in cell proliferation, metabolism and invasion. We extend these findings by functionally characterizing a class of translationally controlled pro-invasion messenger RNAs that we show direct prostate cancer invasion and metastasis downstream of oncogenic mTOR signalling. Furthermore, we develop a clinically relevant ATP site inhibitor of mTOR, INK128, which reprograms this gene expression signature with therapeutic benefit for prostate cancer metastasis, for which there is presently no cure. Together, these findings extend our understanding of how the ‘cancerous’ translation machinery steers specific cancer cell behaviours, including metastasis, and may be therapeutically targeted. Ribosome profiling reveals specialized translation of the prostate cancer genome by oncogenic mTOR signalling; stringent inhibition of mTOR signalling reduces prostate cancer invasion and metastasis in a mouse model. Mechanism of mTOR signalling The mTOR pathway is important in the regulation of protein synthesis and is activated in many human cancers. Two papers in this issue of Nature use ribosome profiling to study the control of messenger RNA translation by mTOR signalling. Hsieh et al . find that in prostate cancer cells and mouse prostate tumours, the translation of several genes involved in cancer invasion is regulated by mTOR by means of the 4EBP1 translational repressor. The experimental drug INK128, currently in clinical trials in people with prostate cancer, inhibits mTOR signalling and reduces the progression of prostate cancers to invasive carcinomas in a mouse model. Thoreen et al . show that through the 4E-BP protein family, the mTORC1 kinase recognizes and regulates a subset of mRNAs with an oligopyrimidine motif at the 5′ end.

Rationale Orexin-1 receptor antagonists have been shown to block the reinforcing effects of drugs of abuse and food. However, whether blockade of orexin-2 receptor has similar effects has not been determined. We have recently described the in vitro and in vivo effects of JNJ-10397049, a selective and brain penetrant orexin-2 receptor antagonist. Objective The goal of these studies was to evaluate whether systemic administration of JNJ-10397049 blocks the rewarding effects of ethanol and reverses ethanol withdrawal in rodents. As a comparison, SB-408124, a selective orexin-1 receptor antagonist, was also evaluated. Methods Rats were trained to orally self-administer ethanol (8% v / v ) or saccharin (0.1% v / v ) under a fixed-ratio 3 schedule of reinforcement. A separate group of rats received a liquid diet of ethanol (8% v / v ) and withdrawal signs were evaluated 4 h after ethanol discontinuation. In addition, ethanol-induced increases in extracellular dopamine levels in the nucleus accumbens were tested. In separate experiments, the acquisition, expression, and reinstatement of conditioned place preference (CPP) were evaluated in mice. Results Our results indicate that JNJ-10397049 (1, 3, and 10 mg/kg, sc) dose-dependently reduced ethanol self-administration without changing saccharin self-administration, dopamine levels, or withdrawal signs in rats. Treatment with JNJ-10397049 (10 mg/kg, sc) attenuated the acquisition, expression, and reinstatement of ethanol CPP and ethanol-induced hyperactivity in mice. Surprisingly, SB-408124 (3, 10 and 30 mg/kg, sc) did not have any effect in these procedures. Conclusions Collectively, these results indicate, for the first time, that blockade of orexin-2 receptors is effective in reducing the reinforcing effects of ethanol.

Contagious agalactia (CA), an infectious disease of small ruminants, caused by Mycoplasma agalactiae, is responsible for severe losses to dairy sheep production with substantial socioeconomic impacts on small-scale farmers. The diagnosis of CA is still problematic, time-consuming and requires well-equipped labs for confirmation of outbreaks. Therefore, rapid, accurate and cost-effective diagnostic tests are urgently needed. This work aims to validate a novel Loop-Mediated Isothermal Amplification (LAMP) test, based on the p40 target gene, for the detection of M. agalactiae in dairy sheep in order to confirm its potential practical use as a rapid and cheap field test. The LAMP system proposed in this study consists of a portable device composed of real-time fluorometer with the automatic interpretation of results displayed in a tablet. A total of 110 milk samples (90 positives and 20 negatives) were analysed to optimise the analysis procedure and to investigate the efficacy and robustness of the LAMP method. All samples were analysed using LAMP and conventional real-time PCR to compare the diagnostic sensitivity of the methods. The sensitivity of the LAMP was 10-fold higher than that of real-time PCR, with a detection limit up to 103 CFU/ml. The LAMP assay was able to detect M. agalactiae in 81 of 90 (90%, 95%CI 0.84–0.96) positive milk samples compared to 69 (77%, 95%CI 0.59–0.95) positive samples detected by real-time PCR; no positive signal occurred for any of the negative milk samples in either test. Therefore, the LAMP assay was found to be more sensitive than real-time PCR, low-cost, easy to perform, fast and not affected by contamination, indicating its potential as an effective diagnostic tool in the field level for the diagnosis of CA.