The United States of America and Scientific Research

To gauge the current commitment to scientific research in the United States of America (US), we compared federal research funding (FRF) with the US gross domestic product (GDP) and industry research spending during the past six decades. In order to address the recent globalization of scientific research, we also focused on four key indicators of research activities: research and development (R&D) funding, total science and engineering doctoral degrees, patents, and scientific publications. We compared these indicators across three major population and economic regions: the US, the European Union (EU) and the People's Republic of China (China) over the past decade. We discovered a number of interesting trends with direct relevance for science policy. The level of US FRF has varied between 0.2% and 0.6% of the GDP during the last six decades. Since the 1960s, the US FRF contribution has fallen from twice that of industrial research funding to roughly equal. Also, in the last two decades, the portion of the US government R&D spending devoted to research has increased. Although well below the US and the EU in overall funding, the current growth rate for R&D funding in China greatly exceeds that of both. Finally, the EU currently produces more science and engineering doctoral graduates and scientific publications than the US in absolute terms, but not per capita. This study's aim is to facilitate a serious discussion of key questions by the research community and federal policy makers. In particular, our results raise two questions with respect to: a) the increasing globalization of science: “What role is the US playing now, and what role will it play in the future of international science?”; and b) the ability to produce beneficial innovations for society: “How will the US continue to foster its strengths?

Neonatal Astrocyte Damage Is Sufficient to Trigger Progressive Striatal Degeneration in a Rat Model of Glutaric Acidemia-I

BACKGROUND: We have investigated whether an acute metabolic damage to astrocytes during the neonatal period may critically disrupt subsequent brain development, leading to neurodevelopmental disorders. Astrocytes are vulnerable to glutaric acid (GA), a dicarboxylic acid that accumulates in millimolar concentrations in Glutaric Acidemia I (GA-I), an inherited neurometabolic childhood disease characterized by degeneration of striatal neurons. While GA induces astrocyte mitochondrial dysfunction, oxidative stress and subsequent increased proliferation, it is presently unknown whether such astrocytic dysfunction is sufficient to trigger striatal neuronal loss. METHODOLOGY/PRINCIPAL FINDINGS: A single intracerebroventricular dose of GA was administered to rat pups at postnatal day 0 (P0) to induce an acute, transient rise of GA levels in the central nervous system (CNS). GA administration potently elicited proliferation of astrocytes expressing S100β followed by GFAP astrocytosis and nitrotyrosine staining lasting until P45. Remarkably, GA did not induce acute neuronal loss assessed by FluoroJade C and NeuN cell count. Instead, neuronal death appeared several days after GA treatment and progressively increased until P45, suggesting a delayed onset of striatal degeneration. The axonal bundles perforating the striatum were disorganized following GA administration. In cell cultures, GA did not affect survival of either striatal astrocytes or neurons, even at high concentrations. However, astrocytes activated by a short exposure to GA caused neuronal death through the production of soluble factors. Iron porphyrin antioxidants prevented GA-induced astrocyte proliferation and striatal degeneration in vivo, as well as astrocyte-mediated neuronal loss in vitro. CONCLUSIONS/SIGNIFICANCE: Taken together, these results indicate that a transient metabolic insult with GA induces long lasting phenotypic changes in astrocytes that cause them to promote striatal neuronal death. Pharmacological protection of astrocytes with antioxidants during encephalopatic crisis may prevent astrocyte dysfunction and the ineluctable progression of disease in children with GA-I

The potential of urinary metabolites for diagnosing multiple sclerosis

A definitive diagnostic test for multiple sclerosis (MS) does not exist; instead physicians use a combination of medical history, magnetic resonance imaging, and cerebrospinal fluid analysis (CSF). Significant effort has been employed to identify biomarkers from CSF to facilitate MS diagnosis; however none of the proposed biomarkers have been successful to date. Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, non-invasive, inexpensive, and efficient diagnostic tool for various human diseases. Nevertheless, urinary metabolites have not been extensively explored as a source of biomarkers for MS. Instead, we demonstrate that urinary metabolites have significant promise for monitoring disease-progression, and response to treatment in MS patients. NMR analysis of urine permitted the identification of metabolites that differentiate experimental autoimmune encephalomyelitis (EAE)-mice (prototypic disease model for MS) from healthy and MS drug-treated EAE mice

An appeal to the global health community for a tripartite innovation: an ‘‘Essential Diagnostics List,’’ ‘‘Health in All Policies,’’ and ‘‘See-Through 21st Century Science and Ethics"

Diagnostics spanning a wide range of new biotechnologies, including proteomics, metabolomics, and nanotechnology, are emerging as companion tests to innovative medicines. In this Opinion, we present the rationale for promulgating an ‘‘Essential Diagnostics List.’’ Additionally, we explain the ways in which adopting a vision for ‘‘Health in All Policies’’ could link essential diagnostics with robust and timely societal outcomes such as sustainable development, human rights, gender parity, and alleviation of poverty. We do so in three ways. First, we propose the need for a new, ‘‘see through’’ taxonomy for knowledge-based innovation as we transition from the material industries (e.g., textiles, plastic, cement, glass) dominant in the 20th century to the anticipated knowledge industry of the 21st century. If knowledge is the currency of the present century, then it is sensible to adopt an approach that thoroughly examines scientific knowledge, starting with the production aims, methods, quality, distribution, access, and the ends it purports to serve. Second, we explain that this knowledge trajectory focus on innovation is crucial and applicable across all sectors, including public, private, or public–private partnerships, as it underscores the fact that scientific knowledge is a co-product of technology, human values, and social systems. By making the value systems embedded in scientific design and knowledge co-production transparent, we all stand to benefit from sustainable and transparent science. Third, we appeal to the global health community to consider the necessary qualities of good governance for 21st century organizations that will embark on developing essential diagnostics. These have importance not only for science and knowledge based innovation, but also for the ways in which we can build open, healthy, and peaceful civil societies today and for future generations

Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment

<p>Abstract</p> <p>Background</p> <p>A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution.</p> <p>Results</p> <p>Our experimentation with <it>E. coli </it>and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms; this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives.</p> <p>Conclusion</p> <p>Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influences the prediction accuracy of the PPC approach. We note that the predictive power of the PPC approach, especially in eukaryotes, is heavily influenced by the primary endosymbiosis and subsequent bacterial contributions. The over-representation of parasitic unicellular eukaryotes and vertebrates additionally make eukaryotes less useful in the reference sets. Reference sets composed of highly non-redundant set of genomes from all three super-kingdoms fare better with pathways showing considerable vertical inheritance and strong conservation (e.g. translation apparatus), while reference sets solely composed of prokaryotic genomes fare better for more variable pathways like carbohydrate metabolism. Differential performance of the PPC approach on various pathways, and a weak positive correlation between functional and profile similarities suggest that caution should be exercised while interpreting functional linkages inferred from genome-wide large-scale profile comparisons using a single reference set.</p

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation

Research activity and capability in the European reference network MetabERN

BACKGROUND: MetabERN is one of the 24 European Reference Networks created according to the European Union directive 2011/24/EU on patient's rights in cross border healthcare. MetabERN associates 69 centres in 18 countries, which provide care for patients with Hereditary Metabolic Diseases, and have the mission to reinforce research and provide training for health professionals in this field. MetabERN performed a survey in December 2017 with the aim to produce an overview documenting research activities and potentials within the network. As the centres are multidisciplinary, separated questionnaires were sent to the clinical, university and laboratory teams. Answers were received from 52 out of the 69 centres of the network, covering 16 countries. A descriptive analysis of the information collected is presented. RESULTS: The answers indicate a marked interest of the respondents for research, who expressed high motivation and commitment, and estimated that the conditions to do research in their institution were mostly satisfactory. They are active in research, which according to several indicators, is competitive and satisfies standards of excellence, as well as the education programs offered in the respondent's universities. Research in the centres is primarily performed in genetics, pathophysiology, and epidemiology, and focuses on issues related to diagnosis. Few respondents declared having activity in human and social sciences, including research on patient's quality of life, patient's awareness, or methods for social support. Infrastructures offering services for medical research were rarely known and used by respondents, including national and international biobanking platforms. In contrast, respondents often participate to patient registries, even beyond their specific field of interest. CONCLUSIONS: Taken as a whole, these results provide an encouraging picture of the research capacities and activities in the MetabERN network, which, with respect to the number and representativeness of the investigated centres, gives a comprehensive picture of research on Hereditary Metabolic Diseases in Europe, as well as the priorities for future actions. Marginal activity in human and social sciences points out the limited multidisciplinary constitution of the responding teams with possible consequences on their current capability to participate to patient's empowerment programs and efficiently collaborate with patient's advocacy groups

Generation and Validation of a Shewanella oneidensis MR-1 Clone Set for Protein Expression and Phage Display

A comprehensive gene collection for S. oneidensis was constructed using the lambda recombinase (Gateway) cloning system. A total of 3584 individual ORFs (85%) have been successfully cloned into the entry plasmids. To validate the use of the clone set, three sets of ORFs were examined within three different destination vectors constructed in this study. Success rates for heterologous protein expression of S. oneidensis His- or His/GST- tagged proteins in E. coli were approximately 70%. The ArcA and NarP transcription factor proteins were tested in an in vitro binding assay to demonstrate that functional proteins can be successfully produced using the clone set. Further functional validation of the clone set was obtained from phage display experiments in which a phage encoding thioredoxin was successfully isolated from a pool of 80 different clones after three rounds of biopanning using immobilized anti-thioredoxin antibody as a target. This clone set complements existing genomic (e.g., whole-genome microarray) and other proteomic tools (e.g., mass spectrometry-based proteomic analysis), and facilitates a wide variety of integrated studies, including protein expression, purification, and functional analyses of proteins both in vivo and in vitro