p140trk mRNA marks NGF-responsive forebrain neurons: evidence that trk gene expression is induced by NGF.

Nerve growth factor (NGF) appears to act as a neurotrophic factor for basal forebrain and caudate-putamen cholinergic neurons. The mechanism by which NGF transduces its signal in these neurons is yet to be defined. Recent data indicate that the product of the trk gene, p140trk, is a critical component of the NGF receptor. Herein, we show that p140trk mRNA is highly restricted in its distribution in the adult rat forebrain, that it is present in cholinergic neurons, and that most if not all cholinergic neurons contain p140trk mRNA. Furthermore, induction of trk expression by NGF suggests that neurotrophin-mediated up-regulation of their receptor tyrosine kinases is an important feature of their actions and that neurotrophins may regulate the activity of responsive neurons through increasing the level of their receptors.     

The binding epitopes of neurotrophin-3 to its receptors trkC and gp75 and the design of a multifunctional human neurotrophin.

Survival and maintenance of vertebrate neurons are influenced by neurotrophic factors which mediate their signal by binding to specific cell surface receptors. We determined the binding sites of human neurotrophin-3 (NT-3) to its receptors trkC and gp75 by mutational analysis and compared them to the analogous interactions of nerve growth factor (NGF) with trkA and gp75. The trkC binding site extends around the central beta-strand bundle and in contrast to NGF does not make use of non-conserved loops and the six N-terminal residues. The gp75 epitope is dominated by loop residues and the C-terminus of NT-3. A novel rapid biological screening procedure allowed the identification of NT-3 mutants that are able to signal efficiently through the non-preferred receptors trkA and trkB, which are specific for NGF and BDNF respectively. Mutation of only seven residues in NT-3 resulted in a human neurotrophin variant which bound to all receptors of the trk family with high affinity and efficiently supported the survival of NGF-, BDNF- and NT-3-dependent neurons. Our results suggest that the specificity among neurotrophic factors is not solely encoded in sequence diversity, but rather in the way each neurotrophin interacts with its preferred receptor.     

Microbiological and technological aspects of cassava-starch fermentation

The major genera found in the microflora of fermented, sour, cassava-starch were Streptococcus, Bacillus, Lactobacillus and Saccharomyces with amylase activity. Lactic acid bacteria predominated whereas the presence of moulds was not significant. No coliforms were detected. Electron microscopy showed bacteria and yeasts in contact with the starch granules and signs of erosion on the granule surface. Lactic acid was the main metabolite; no oligosaccharides, maltose or glucose were detected, indicating their rapid utilization. The degree of acidification, which correlated with the decrease in viscosity and the final quality of the product, was influenced by the variable microbial ecology.     

Concentration by ultrafiltration and stabilization of phytase produced by solid-state fermentation

Ultrafiltration is an attractive downstream processing technique for concentrating enzymes and could be considered the primary step of purification. However, the efficiency of this process is often limited by protein fouling and shear-induced enzyme inactivation, which decreases permeate flux and results in the loss of enzyme activity. Although the rejection of phytase was higher than 99%, the loss of the enzyme activity was 14% during operation, indicating that the shear forces generated in the filter have significant influences on the enzyme activity. Two preparations using glycerol (25% and 35%, v/v) as a cryo-protecting agent at different temperatures were studied. The preparation containing 35% glycerol retained 70% of the initial enzyme activity at 70 °C after 1 h and had more than 3 and 6 months storage half-life at 29 °C and 4 °C, respectively.     

The tumor suppressor CDKN3 controls mitosis

Mitosis is controlled by a network of kinases and phosphatases. We screened a library of small interfering RNAs against a genome-wide set of phosphatases to comprehensively evaluate the role of human phosphatases in mitosis. We found four candidate spindle checkpoint phosphatases, including the tumor suppressor CDKN3. We show that CDKN3 is essential for normal mitosis and G1/S transition. We demonstrate that subcellular localization of CDKN3 changes throughout the cell cycle. We show that CDKN3 dephosphorylates threonine-161 of CDC2 during mitotic exit and we visualize CDC2^pThr-161 at kinetochores and centrosomes in early mitosis. We performed a phosphokinome-wide mass spectrometry screen to find effectors of the CDKN3-CDC2 signaling axis. We found that one of the identified downstream phosphotargets, CKβ phosphorylated at serine 209, localizes to mitotic centrosomes and controls the spindle checkpoint. Finally, we show that CDKN3 protein is down-regulated in brain tumors. Our findings indicate that CDKN3 controls mitosis through the CDC2 signaling axis. These results have implications for targeted anticancer therapeutics.     

Stoichiometric modeling of oxidation of reduced inorganic sulfur compounds (Riscs) in Acidithiobacillus thiooxidans

The prokaryotic oxidation of reduced inorganic sulfur compounds (RISCs) is a topic of utmost importance from a biogeochemical and industrial perspective. Despite sulfur oxidizing bacterial activity is largely known, no quantitative approaches to biological RISCs oxidation have been made, gathering all the complex abiotic and enzymatic stoichiometry involved. Even though in the case of neutrophilic bacteria such as Paracoccus and Beggiatoa species the RISCs oxidation systems are well described, there is a lack of knowledge for acidophilic microorganisms. Here, we present the first experimentally validated stoichiometric model able to assess RISCs oxidation quantitatively in Acidithiobacillus thiooxidans (strain DSM 17318), the archetype of the sulfur oxidizing acidophilic chemolithoautotrophs. This model was built based on literature and genomic analysis, considering a widespread mix of formerly proposed RISCs oxidation models combined and evaluated experimentally. Thiosulfate partial oxidation by the Sox system (SoxABXYZ) was placed as central step of sulfur oxidation model, along with abiotic reactions. This model was coupled with a detailed stoichiometry of biomass production, providing accurate bacterial growth predictions. In silico deletion/inactivation highlights the role of sulfur dioxygenase as the main catalyzer and a moderate function of tetrathionate hydrolase in elemental sulfur catabolism, demonstrating that this model constitutes an advanced instrument for the optimization of At. thiooxidans biomass production with potential use in biohydrometallurgical and environmental applications. Biotechnol. Bioeng. 2013; 110: 2242–2251. © 2013 Wiley Periodicals, Inc.     

Short-term observations of marine bacterial and viral communities: patterns,connections and resilience

Observation of short-term temporal variation in bacterial and viral communities is important for understanding patterns of aquatic microbial diversity. We collected surface seawater once daily for 38 consecutive days with seven more samples interspersed over 40 more days at one location ∼2 km from Santa Catalina Island, California. Bacterial communities were analyzed by automated ribosomal intergenic spacer analysis (ARISA) and viral communities were analyzed by terminal restriction fragment length polymorphism (TRFLP) of the conserved T4-like myoviral gene encoding the major capsid protein (g23). Common bacterial and viral taxa were consistently dominant, and relatively few displayed dramatic increases/decreases or ‘boom/bust'' patterns that might be expected from dynamic predator-prey interactions. Association network analysis showed most significant covariations (associations) occurred among bacterial taxa or among viral taxa and there were several modular (highly-interconnected) associations (P⩽0.005). Associations observed between bacteria and viruses (P⩽0.005) occurred with a median time lag of 2 days. Regression of all pairwise Bray-Curtis similarities between samples indicated a rate of bacterial community change that slows from 2.1%–0.18% per day over a week to 2 months; the rate stays around 0.4% per day for viruses. Our interpretation is that, over the scale of days, individual bacterial and viral OTUs can be dynamic and patterned; resulting in statistical associations regarded as potential ecological interactions. However, over the scale of weeks, average bacterial community variation is slower, suggesting that there is strong community-level ecological resilience, that is, a tendency to converge towards a ‘mean'' microbial community set by longer-term controlling factors.     

Automatically Generated Algorithms for the Vertex Coloring Problem

The vertex coloring problem is a classical problem in combinatorial optimization that consists of assigning a color to each vertex of a graph such that no adjacent vertices share the same color, minimizing the number of colors used. Despite the various practical applications that exist for this problem, its NP-hardness still represents a computational challenge. Some of the best computational results obtained for this problem are consequences of hybridizing the various known heuristics. Automatically revising the space constituted by combining these techniques to find the most adequate combination has received less attention. In this paper, we propose exploring the heuristics space for the vertex coloring problem using evolutionary algorithms. We automatically generate three new algorithms by combining elementary heuristics. To evaluate the new algorithms, a computational experiment was performed that allowed comparing them numerically with existing heuristics. The obtained algorithms present an average 29.97% relative error, while four other heuristics selected from the literature present a 59.73% error, considering 29 of the more difficult instances in the DIMACS benchmark.