Synthesis and Evaluation of Novologues as C-Terminal Hsp90 Inhibitors with Cytoprotective Activity against Sensory Neuron Glucotoxicity

Compound 2 (KU-32) is a first-generation novologue (a novobiocin-based, C-terminal, heat shock protein 90 (Hsp90) inhibitor), that decreases glucose-induced death of primary sensory neurons and reverses numerous clinical indices of diabetic peripheral neuropathy in mice. The current study sought to exploit the C-terminal binding site of Hsp90 to determine whether the optimization of hydrogen bonding and hydrophobic interactions of second generation novologues could enhance neuroprotective activity. Using a series of substituted phenylboronic acids to replace the coumarin lactone of 2, we identified electronegative atoms placed at the meta-position of the B-ring exhibit improved cytoprotective activity, which is believed to result from favorable interactions with Lys539 in the Hsp90 C-terminal binding pocket. Consistent with these results, a meta-3-fluorophenyl substituted novologue (13b) exhibited a 14-fold lower ED50 compared to 2 for protection against glucose-induced toxicity of primary sensory neurons

Production of ent-kaurene from lignocellulosic hydrolysate in Rhodosporidium toruloides.

BACKGROUND:Rhodosporidium toruloides has emerged as a promising host for the production of bioproducts from lignocellulose, in part due to its ability to grow on lignocellulosic feedstocks, tolerate growth inhibitors, and co-utilize sugars and lignin-derived monomers. Ent-kaurene derivatives have a diverse range of potential applications from therapeutics to novel resin-based materials. RESULTS:The Design, Build, Test, and Learn (DBTL) approach was employed to engineer production of the non-native diterpene ent-kaurene in R. toruloides. Following expression of kaurene synthase (KS) in R. toruloides in the first DBTL cycle, a key limitation appeared to be the availability of the diterpene precursor, geranylgeranyl diphosphate (GGPP). Further DBTL cycles were carried out to select an optimal GGPP synthase and to balance its expression with KS, requiring two of the strongest promoters in R. toruloides, ANT (adenine nucleotide translocase) and TEF1 (translational elongation factor 1) to drive expression of the KS from Gibberella fujikuroi and a mutant version of an FPP synthase from Gallus gallus that produces GGPP. Scale-up of cultivation in a 2 L bioreactor using a corn stover hydrolysate resulted in an ent-kaurene titer of 1.4 g/L. CONCLUSION:This study builds upon previous work demonstrating the potential of R. toruloides as a robust and versatile host for the production of both mono- and sesquiterpenes, and is the first demonstration of the production of a non-native diterpene in this organism

Quantifying two-dimensional filamentous and invasive growth spatial patterns in yeast colonies

The top-view, two-dimensional spatial patterning of non-uniform growth in a Saccharomyces cerevisiae yeast colony is considered. Experimental images are processed to obtain data sets that provide spatial information on the cell-area that is occupied by the colony. A method is developed that allows for the analysis of the spatial distribution with three metrics. The growth of the colony is quantified in both the radial direction from the centre of the colony and in the angular direction in a prescribed outer region of the colony. It is shown that during the period of 100-200 hours from the start of the growth of the colony there is an increasing amount of non-uniform growth. The statistical framework outlined in this work provides a platform for comparative quantitative assays of strain-specific mechanisms, with potential implementation in inferencing algorithms used for parameter-rate estimation.Benjamin J. Binder, Joanna F. Sundstrom, Jennifer M. Gardner, Vladimir Jiranek, Stephen G. Olive

The Effects of Pre-Race Apnoeas on 400-m Freestyle Swimming Performance

This study aimed to establish whether a series of three apnoeas prior to a 400-m freestyle time-trial affected swimming performance when compared to, and combined with a warm-up. Nine (6 males, 3 females) regional to national standard swimmers completed four 400-m freestyle time-trials in 4 randomized conditions: without warm-up or apnoeas (CON), warm-up only (WU), apnoeas only (AP) and warm-up and apnoeas (WUAP). Time-trial performance was significantly improved after WUAP (275.79 ±12.88 s) compared to CON (278.66 ±13.31 s, P = 0.035) and AP (278.64 ±4.10 s, P =0.015). However, there were no significant differences between the WU (276.01 ±13.52 s, P >0.05), and other interventions. Spleen volume compared to baseline was significantly reduced following the apnoeas by a maximum of ~45% in the WUAP and by ~20% in WU. This study showed that the combination of a warm-up with apnoeas could significantly improve 400-m freestyle swim performance compared to a control and apnoea intervention. Further investigation into whether long-term apnoea training can enhance this response is justified

FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis

Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci) to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ

Nutrient-limited growth with non-linear cell diffusion as a mechanism for floral pattern formation in yeast biofilms

Available online 7 April 2018Abstract not availableAlexander Tam, J. Edward F. Green, Sanjeeva Balasuriya, Ee Lin Tek, Jennifer M. Gardner, Joanna F. Sundstrom, Vladimir Jiranek, Benjamin J. Binde

Gut microbiota-derived propionate reduces cancer cell proliferation in the liver

Peer reviewedPublisher PD

The state, civil society and social rights in contemporary Russia

peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=fjcs21peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=fjcs2