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

Comparative Omics-Driven Genome Annotation Refinement: Application across Yersiniae

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing errors inherent to automated computational annotations is to apply data from omics measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis Pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation

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

Reciprocal interactions between circadian clocks and aging

Virtually, all biological processes in the body are modulated by an internal circadian clock which optimizes physiological and behavioral performance according to the changing demands of the external 24-h world. This circadian clock undergoes a number of age-related changes, at both the physiological and molecular levels. While these changes have been considered to be part of the normal aging process, there is increasing evidence that disruptions to the circadian system can substantially impact upon aging and these impacts will have clear health implications. Here we review the current data of how both the physiological and core molecular clocks change with age and how feedback from external cues may modulate the aging of the circadian system

Sources of Terrestrial Organic Carbon in the Mississippi Plume Region: Evidence for the Importance of Coastal Marsh Inputs

High sedimentation rates along river-dominated margins make these systems important repositories for organic carbon derived from both allochthonous and autochthonous sources. Using elemental carbon/nitrogen ratios, molecular biomarker (lignin phenol), and stable carbon isotopic (bulk and compound-specific) analyses, this study examined the sources of organic carbon to the Louisiana shelf within one of the primary dispersive pathways of the Mississippi River. Surface sediment samples were collected from stations across the inner, mid, and outer Louisiana shelf, within the Mississippi River plume region, during two cruises in the spring and fall of 2000. Lignin biomarker data showed spatial patterns in terrestrial source plant materials within the river plume, such that sediments near the mouth of the Mississippi River were comparatively less degraded and richer in C 4 plant carbon than those found at mid-depth regions of the shelf. A molecular and stable isotope-based mixing model defining riverine, marsh, and marine organic carbon suggested that the highest organic carbon inputs to the shelf in spring were from marine sources (55–61% marine organic carbon), while riverine organic carbon was the highest (63%) in fall, likely due to lower inputs of marine organic carbon at this time compared with the spring season. This model also indicated that marsh inputs, ranging from 19 to 34% and 3–15% of the organic carbon in spring and fall, respectively, were significantly more important sources of organic carbon on the inner Louisiana shelf than previously suggested. Finally, we propose that the decomposition of terrestrial-derived organic carbon (from the river and local wetlands sources) in mobile muds may serve as a largely unexplored additional source of oxygen-consuming organic carbon in hypoxic bottom waters of the Louisiana shelf