Steps towards a consumer-driven ‘concept innovation machine’ for food and drink

Innovation is often left to insight and serendipity. A lot of what researchers call innovation is actually a process by which one can make the individual consumer or practitioner more ‘creative’. Although it is important to work with the creative individual in hopes of coming up with the better ‘idea’ and new product/service opportunity, an equally valid albeit novel and counterintuitive approach systematizes creativity in a ‘research-driven machine’. This paper presents an approach to the systematization, based upon the point of view that creativity and innovation comprise the recombination of components into new blends. Given this point of view, to then spur innovation requires a systematic database that the user can access, with tools to help manipulate that database. The paper shows how such a database can be constructed and then used to create a novel product. The approach provides a general framework for the sensory professional to become more involved in the early stages of product development, where the focus is on the conceptual aspects of food features rather than on their physical manifestations in actual products.     

Issues in the Reconstruction of Gene Order Evolution

As genomes evolve over hundreds of millions years, the chromosomes become rearranged, with segments of some chromosomes inverted, while other chromosomes reciprocally exchange chunks from their ends. These rearrangements lead to the scrambling of the elements of one genome with respect to another descended from a common ancestor. Multidisciplinary work undertakes to mathematically model these processes and to develop statistical analyses and mathematical algorithms to understand the scrambling in the chromo...     

A statistical approach to high-throughput screening of predicted orthologs

Orthologs are genes in different species that have diverged from a common ancestral gene after speciation. In contrast, paralogs are genes that have diverged after a gene duplication event. For many comparative analyses, it is of interest to identify orthologs with similar functions. Such orthologs tend to support species divergence (ssd-orthologs) in the sense that they have diverged only due to speciation, to the same relative degree as their species. However, due to incomplete sequencing or gene loss in a species, predicted orthologs can sometimes be paralogs or other non-ssd-orthologs. To increase the specificity of ssd-ortholog prediction, Fulton et al. [Fulton, D., Li, Y., Laird, M., Horsman, B., Roche, F., Brinkman, F., 2006. Improving the specificity of high-throughput ortholog prediction. BMC Bioinformatics 7 (1), 270] developed Ortholuge, a bioinformatics tool that identifies predicted orthologs with atypical genetic divergence. However, when the initial list of putative orthologs contains a non-negligible number of non-ssd-orthologs, the cut-off values that Ortholuge generates for orthology classification are difficult to interpret and can be too high, leading to decreased specificity of ssd-ortholog prediction. Therefore, we propose a complementary statistical approach to determining cut-off values. A benefit of the proposed approach is that it gives the user an estimated conditional probability that a predicted ortholog pair is unusually diverged. This enables the interpretation and selection of cut-off values based on a direct measure of the relative composition of ssd-orthologs versus non-ssd-orthologs. In a simulation comparison of the two approaches, we find that the statistical approach provides more stable cut-off values and improves the specificity of ssd-ortholog prediction for low-quality data sets of predicted orthologs.     

The LabMatrix system

The LabMatrix^™ is a prototyping system designed to give the user a practical and versatile platform for testing microfluidic applications in the fields of health care and life sciences. The LabMatrix^™ system consists of a microfluidic breadboard and cover that align and secure a series of specially designed LabMatrix^™ microfluidic chips. Chips are easily arranged and rearranged into a user-defined fluidic network. The LabMatrix^™ system is designed with maximum flexibility in mind, providing the user with a means to prototype a wide range of microfluidic applications in a short period.     

Intelligence: Genetics, Genes, and Genomics.

More is known about the genetics of intelligence than about any other trait, behavioral or biological, which is selectively reviewed in this article. Two of the most interesting genetic findings are that heritability of intelligence increases throughout the life span and that the same genes affect diverse cognitive abilities. The most exciting direction for genetic research on intelligence is to harness the power of the Human Genome Project to identify some of the specific genes responsible for the heritability of intelligence. The next research direction will be functional genomics--for example, understanding the brain pathways between genes and intelligence. Deoxyribonucleic acid (DNA) will integrate life sciences research on intelligence; bottom-up molecular biological research will meet top-down psychological research in the brain. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Discovery of the Tiancilactone Antibiotics by Genome Mining of Atypical Bacterial Type II Diterpene Synthases

Although genome mining has advanced the identification, discovery, and study of microbial natural products, the discovery of bacterial diterpenoids continues to lag behind. Herein, we report the identification of 66 putative producers of novel bacterial diterpenoids, and the discovery of the tiancilactone (TNL) family of antibiotics, by genome mining of type II diterpene synthases that do not possess the canonical DXDD motif. The TNLs, which are broad‐spectrum antibiotics with moderate activities, are produced by both Streptomyces sp. CB03234 and Streptomyces sp. CB03238 and feature a highly functionalized diterpenoid skeleton that is further decorated with chloroanthranilate and γ‐butyrolactone moieties. Genetic manipulation of the tnl gene cluster resulted in TNL congeners, which provided insights into their biosynthesis and structure–activity relationships. This work highlights the biosynthetic potential that bacteria possess to produce diterpenoids and should inspire continued efforts to discover terpenoid natural products from bacteria.     

Phylogenetic-Derived Insights into the Evolution of Sialylation in Eukaryotes: Comprehensive Analysis of Vertebrate β-Galactoside α2,3/6-Sialyltransferases (ST3Gal and ST6Gal)

Cell surface of eukaryotic cells is covered with a wide variety of sialylated molecules involved in diverse biological processes and taking part in cell–cell interactions. Although the physiological relevance of these sialylated glycoconjugates in vertebrates begins to be deciphered, the origin and evolution of the genetic machinery implicated in their biosynthetic pathway are poorly understood. Among the variety of actors involved in the sialylation machinery, sialyltransferases are key enzymes for the biosynthesis of sialylated molecules. This review focus on β-galactoside α2,3/6-sialyltransferases belonging to the ST3Gal and ST6Gal families. We propose here an outline of the evolutionary history of these two major ST families. Comparative genomics, molecular phylogeny and structural bioinformatics provided insights into the functional innovations in sialic acid metabolism and enabled to explore how ST-gene function evolved in vertebrates.     

Metabolites and Genes behind Cardiac Metabolic Remodeling in Mice with Type 1 Diabetes Mellitus

Metabolic remodeling is at the heart of diabetic cardiomyopathy. High glycemic fluctuations increase metabolic stress in the type 1 diabetes mellitus (T1DM) heart. There is a lack of understanding on how metabolites and genes affect metabolic remodeling in the T1DM heart. We hypothesize that differential expression of metabolic genes and metabolites synergistically influence metabolic remodeling preceding T1DM cardiomyopathy. To test our hypothesis, we conducted high throughput analysis of hearts from adult male hyperglycemic Ins2^+/− (Akita) and littermate normoglycemic Ins2^+/+ (WT) mice. The Akita mouse is a spontaneous, genetic model of T1DM that develops increased levels of consistent glycemic variability without the off-target cardiotoxic effects present in chemically- induced models of T1DM. After validating the presence of a T1DM phenotype, we conducted metabolomics via LC-MS analysis and genomics via next-generation sequencing in left ventricle tissue from the Akita heart. Ingenuity Pathway Analyses revealed that 108 and 30 metabolic pathways were disrupted within the metabolomics and genomics datasets, respectively. Notably, a comparison between the two analyses showed 15 commonly disrupted pathways, including ketogenesis, ketolysis, cholesterol biosynthesis, acetyl CoA hydrolysis, and fatty acid biosynthesis and beta-oxidation. These identified metabolic pathways predicted by the differential expression of metabolites and genes provide the foundation for understanding metabolic remodeling in the T1DM heart. By limited experiment, we revealed a predicted disruption in the metabolites and genes behind T1DM cardiac metabolic derangement. Future studies targeting these genes and metabolites will unravel novel therapies to prevent/improve metabolic remodeling in the T1DM heart.