We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

Over the past ten years, scientific and technological advances have established biocatalysis as a practical and environmentally friendly alternative to traditional metallo- and organocatalysis in chemical synthesis, both in the laboratory and on an industrial scale. Key advances in DNA sequencing and gene synthesis are at the base of tremendous progress in tailoring biocatalysts by protein engineering and design, and the ability to reorganize enzymes into new biosynthetic pathways. To highlight these achievements, here we discuss applications of protein-engineered biocatalysts ranging from commodity chemicals to advanced pharmaceutical intermediates that use enzyme catalysis as a key step.

Engineering the third wave of biocatalysis

Microbial engineering often requires fine control over protein expression--for example, to connect genetic circuits or control flux through a metabolic pathway. To circumvent the need for trial and error optimization, we developed a predictive method for designing synthetic ribosome binding sites, enabling a rational control over the protein expression level. Experimental validation of >100 predictions in Escherichia coli showed that the method is accurate to within a factor of 2.3 over a range of 100,000-fold. The design method also correctly predicted that reusing identical ribosome binding site sequences in different genetic contexts can result in different protein expression levels. We demonstrate the method's utility by rationally optimizing protein expression to connect a genetic sensor to a synthetic circuit. The proposed forward engineering approach should accelerate the construction and systematic optimization of large genetic systems.

Automated design of synthetic ribosome binding sites to control protein expression

There are a number of ways in which a clinical diagnosis of dementia of the Alzheimer type can be made – the application of clinical criteria is the commonest but ancillary techniques such as neuroima

Clinical Diagnosis of Alzheimer's Disease

Increasing energy costs and environmental concerns have emphasized the need to produce sustainable renewable fuels and chemicals. Major efforts to this end are focused on the microbial production of high-energy fuels by cost-effective 'consolidated bioprocesses'. Fatty acids are composed of long alkyl chains and represent nature's 'petroleum', being a primary metabolite used by cells for both chemical and energy storage functions. These energy-rich molecules are today isolated from plant and animal oils for a diverse set of products ranging from fuels to oleochemicals. A more scalable, controllable and economic route to this important class of chemicals would be through the microbial conversion of renewable feedstocks, such as biomass-derived carbohydrates. Here we demonstrate the engineering of Escherichia coli to produce structurally tailored fatty esters (biodiesel), fatty alcohols, and waxes directly from simple sugars. Furthermore, we show engineering of the biodiesel-producing cells to express hemicellulases, a step towards producing these compounds directly from hemicellulose, a major component of plant-derived biomass.

Microbial production of fatty-acid-derived fuels and chemicals from plant biomass

Global energy and environmental problems have stimulated increased efforts towards synthesizing biofuels from renewable resources. Compared to the traditional biofuel, ethanol, higher alcohols offer advantages as gasoline substitutes because of their higher energy density and lower hygroscopicity. In addition, branched-chain alcohols have higher octane numbers compared with their straight-chain counterparts. However, these alcohols cannot be synthesized economically using native organisms. Here we present a metabolic engineering approach using Escherichia coli to produce higher alcohols including isobutanol, 1-butanol, 2-methyl-1-butanol, 3-methyl-1-butanol and 2-phenylethanol from glucose, a renewable carbon source. This strategy uses the host's highly active amino acid biosynthetic pathway and diverts its 2-keto acid intermediates for alcohol synthesis. In particular, we have achieved high-yield, high-specificity production of isobutanol from glucose. The strategy enables the exploration of biofuels beyond those naturally accumulated to high quantities in microbial fermentation.

Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels

http://2010.igem.org/wiki/images/e/e4/Butanol.pdf

Metabolic engineering of Escherichia coli for 1-butanol production.

A synthetic pathway was engineered in Escherichia coli to produce isopropanol by expressing various combinations of genes from Clostridium acetobutylicum ATCC 824, E. coli K-12 MG1655, Clostridium beijerinckii NRRL B593, and Thermoanaerobacter brockii HTD4. The strain with the combination of C. acetobutylicum thl (acetyl-coenzyme A [CoA] acetyltransferase), E. coli atoAD (acetoacetyl-CoA transferase), C. acetobutylicum adc (acetoacetate decarboxylase), and C. beijerinckii adh (secondary alcohol dehydrogenase) achieved the highest titer. This strain produced 81.6 mM isopropanol in shake flasks with a yield of 43.5% (mol/mol) in the production phase. To our knowledge, this work is the first to produce isopropanol in E. coli, and the titer exceeded that from the native producers.

Taizo Hanai

Papers

Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels

Metabolic engineering of Escherichia coli for 1-butanol production.

Engineered synthetic pathway for isopropanol production in Escherichia coli.

Metabolic flux redirection from a central metabolic pathway toward a synthetic pathway using a metabolic toggle switch

Improvement of isopropanol production by metabolically engineered Escherichia coli using gas stripping.