Complete genome sequence of Polynucleobacter necessarius subsp. asymbioticus type strain (QLW-P1DMWA-1T)

Polynucleobacter necessarius subsp. asymbioticus strain QLW-P1DMWA-1T is a planktonic freshwater bacterium affiliated with the family Burkholderiaceae (class Betaproteobacteria). This strain is of interest because it represents a subspecies with cosmopolitan and ubiquitous distribution in standing freshwater systems. The 16S-23S ITS genotype represented by the sequenced strain comprised on average more than 10% of bacterioplankton in its home habitat. While all strains of the subspecies P. necessarius asymbioticus are free-living freshwater bacteria, strains belonging to the only other subspecies, P. necessarius subsp. necessarius are obligate endosymbionts of the ciliate Euplotes aediculatus. The two subspecies of P. necessarius are the instances of two closely related subspecies that differ in their lifestyle (free-living vs. obligate endosymbiont), and they are the only members of the genus Polynucleobacter with completely sequenced genomes. Here we describe the features of P. necessarius subsp. asymbioticus, together with the complete genome sequence and annotation. The 2,159,490 bp long chromosome with a total of 2,088 protein-coding and 48 RNA genes is the first completed genome sequence of the genus Polynucleobacter to be published and was sequenced as part of the DOE Joint Genome Institute Community Sequencing Program 2006

Combined Metabolic Targeting With Metformin and the NSAIDs Diflunisal and Diclofenac Induces Apoptosis in Acute Myeloid Leukemia Cells

The accelerated metabolism of tumor cells, inevitable for maintaining high proliferation rates, is an emerging target for tumor therapy. Increased glucose and lipid metabolism as well as mitochondrial activity have been shown in solid tumors but also in leukemic cells. As tumor cells are able to escape the blockade of one metabolic pathway by a compensatory increase in other pathways, treatment strategies simultaneously targeting metabolism at different sites are currently developed. However, the number of clinically applicable anti-metabolic drugs is still limited. Here, we analyzed the impact of the anti-diabetic drug metformin alone or in combination with two non-steroidal anti-inflammatory drugs (NSAIDs) diclofenac and diflunisal on acute myeloid leukemia (AML) cell lines and primary patient blasts. Diclofenac but not diflunisal reduced lactate secretion in different AML cell lines (THP-1, U937, and KG-1) and both drugs increased respiration at low concentrations. Despite these metabolic effects, both NSAIDs showed a limited effect on tumor cell proliferation and viability up to a concentration of 0.2 mM. In higher concentrations of 0.4–0.8 mM diflunisal alone exerted a clear effect on proliferation of AML cell lines and blocked respiration. Single treatment with the anti-diabetic drug metformin blocked mitochondrial respiration, but proliferation and viability were not affected. However, combining all three drugs exerted a strong cytostatic and cytotoxic effect on THP-1 cells. Comparable to the results obtained with THP-1 cells, the combination of all three drugs significantly reduced proliferation of primary leukemic blasts and induced apoptosis. Furthermore, NSAIDs supported the effect of low dose chemotherapy with cytarabine and reduced proliferation of primary AML blasts. Taken together we show that low concentrations of metformin and the two NSAIDs diclofenac and diflunisal exert a synergistic inhibitory effect on AML proliferation and induce apoptosis most likely by blocking tumor cell metabolism. Our results underline the feasibility of applying anti-metabolic drugs for AML therapy

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Improved Visualization of Prostate Cancer Using Multichannel Computed Diffusion Images: Combining ADC and DWI

(1) Background: For the peripheral zone of the prostate, diffusion weighted imaging (DWI) is the most important MRI technique; however, a high b-value image (hbDWI) must always be evaluated in conjunction with an apparent diffusion coefficient (ADC) map. We aimed to unify the important contrast features of both a hbDWI and ADC in one single image, termed multichannel computed diffusion images (mcDI), and evaluate the values of these images in a retrospective clinical study; (2) Methods: Based on the 2D histograms of hbDWI and ADC images of 70 patients with histologically proven prostate cancer (PCa) in the peripheral zone, an algorithm was designed to generate the mcDI. Then, three radiologists evaluated the data of 56 other patients twice in three settings (T2w images +): (1) hbDWI and ADC; (2) mcDI; and (3) mcDI, hbDWI, and ADC. The sensitivity, specificity, and inter-reader variability were evaluated; (3) Results: The overall sensitivity/specificity were 0.91/0.78 (hbDWI + ADC), 0.85/0.88 (mcDI), and 0.97/0.88 (mcDI + hbDWI + ADC). The kappa-values for the inter-reader variability were 0.732 (hbDWI + ADC), 0.800 (mcDI), and 0.853 (mcDI + hbDWI + ADC). (4) Conclusions: By using mcDI, the specificity of the MRI detection of PCa was increased at the expense of the sensitivity. By combining the conventional diffusion data with the mcDI data, both the sensitivity and specificity were improved