Nitrogen fertilization increases diversity and productivity of prairie communities used for bioenergy

Using prairie biomass as a renewable source of energy may constitute an important opportunity to improve the environmental sustainability of managed land. To date, assessments of the feasibility of using prairies for bioenergy production have focused on marginal areas with low yield potential. Growing prairies on more fertile soil or with moderate levels of fertilization may be an effective means of increasing yields, but increased fertility often reduces plant community diversity. At a fertile site in central Iowa with high production potential, we tested the hypothesis that nitrogen fertilization would increase aboveground biomass production but would decrease diversity of prairies sown and managed for bioenergy production. Over a 3 year period (years 2–4 after seeding), we measured aboveground biomass after plant senescence and species and functional‐group diversity in June and August for multispecies mixtures of prairie plants that received no fertilizer or 84 kg N ha^?1 year^?1. We found that nitrogen fertilization increased aboveground biomass production, but with or without fertilization, the prairies produced a substantial amount of biomass: averaging (±SE) 12.2 ± 1.3 and 9.1 ± 1.0 Mg ha^?1 in fertilized and unfertilized prairies, respectively. Unfertilized prairies had higher species diversity in June, whereas fertilized prairies had higher species diversity in August at the end of the study period. Functional‐group diversity was almost always higher in fertilized prairies. Composition of unfertilized prairies was characterized by native C₄ grasses and legumes, whereas fertilized prairies were characterized by native C₃ grasses and forbs. Although most research has found that nitrogen fertilization reduces prairie diversity, our results indicate that early‐spring nitrogen fertilization, when used with a postsenescence annual harvest, may increase prairie diversity. Managing prairies for bioenergy production, including the judicious use of fertilization, may be an effective means of increasing the amount of saleable products from managed lands while potentially increasing plant diversity.     

24(S)‐hydroxycholesterol is actively eliminated from neuronal cells by ABCA1

High cholesterol turnover catalyzed by cholesterol 24‐hydroxylase is essential for neural functions, especially learning. Because 24(S)‐hydroxycholesterol (24‐OHC), produced by 24‐hydroxylase, induces apoptosis of neuronal cells, it is vital to eliminate it rapidly from cells. Here, using differentiated SH‐SY5Y neuron‐like cells as a model, we examined whether 24‐OHC is actively eliminated via transporters induced by its accumulation. The expression of ABCA1 and ABCG1 was induced by 24‐OHC, as well as TO901317 and retinoic acid, which are ligands of the nuclear receptors liver X receptor/retinoid X receptor (LXR/RXR). When the expression of ABCA1 and ABCG1 was induced, 24‐OHC efflux was stimulated in the presence of high‐density lipoprotein (HDL), whereas apolipoprotein A‐I was not an efficient acceptor. The efflux was suppressed by the addition of siRNA against ABCA1, but not by ABCG1 siRNA. To confirm the role of each transporter, we analyzed human embryonic kidney 293 cells stably expressing human ABCA1 or ABCG1; we clearly observed 24‐OHC efflux in the presence of HDL, whereas efflux in the presence of apolipoprotein A‐I was marginal. Furthermore, the treatment of primary cerebral neurons with LXR/RXR ligands suppressed the toxicity of 24‐OHC. These results suggest that ABCA1 actively eliminates 24‐OHC in the presence of HDL as a lipid acceptor and protects neuronal cells.     

The conformational quality of insoluble recombinant proteins is enhanced at low growth temperatures

Protein aggregation is a major bottleneck during the bacterial production of recombinant proteins. In general, the induction of gene expression at sub-optimal growth temperatures improves the solubility of aggregation-prone polypeptides and minimizes inclusion body (IB) formation. However, the effect of low temperatures on the quality of the recombinant protein, especially within the insoluble cell fraction, has been hardly ever explored. In this work, we have examined the conformational status of a recombinant GFP protein when produced in Escherichia coli below 37 degrees C. As expected, the fraction of aggregated protein largely decreased at lower temperatures, while the conformational quality of both soluble and aggregated GFP, as reflected by its specific fluorescence emission, progressively improved. This observation indicates that physicochemical conditions governing protein folding affect concurrently the quality of the soluble and the aggregated forms of a misfolding-prone protein, and that protein misfolding and aggregation are clearly not coincident events.     

Long non‐coding RNA expressed in macrophage co‐varies with the inflammatory phenotype during macrophage development and polarization

Advances in microarray, RNA‐seq and omics techniques, thousands of long non‐coding RNAs (lncRNAs) with unknown functions have been discovered. LncRNAs have presented a diverse perspective on gene regulation in diverse biological processes, especially in human immune response. Macrophages participate in the whole phase of immune inflammatory response. They are able to shape their phenotype and arouse extensive functional activation after receiving physiological and pathological stimuli. Emerging studies indicated that lncRNAs participated in the gene regulatory network during complex biological processes of macrophage, including macrophage‐induced inflammatory responses. Here, we reviewed the existing knowledges of lncRNAs in the processes of macrophage development and polarization, and their roles in several different inflammatory diseases. Specifically, we focused on how lncRNAs function in macrophage, which might help to discover some potential therapeutic targets and diagnostic biomarkers.     

Prostaglandin E2 is a Potential Mediator of Extracellular ATP Action in Osteoblast-Like Cells

Extracellular ATP dose dependently stimulated ⁴⁵Ca²⁺ influx even in the presence of nifedipine, a Ca²⁺ antagonist that inhibits voltage-dependent Ca²⁺ channel, in osteoblast-like MC3T3-E1 cells. ATP stimulated arachidonic acid release and the synthesis of prostaglandin E₂ (PGE₂). However, the ATP-induced arachidonic acid release was significantly reduced by chelating extracellular Ca²⁺ with EGTA. On the other hand, ATP induced DNA synthesis of these cells in a dose-dependent manner in the range between 1μM and 1 mM. The pretreatment with indomethacin, a cyclooxygenase inhibitor, suppressed both ATP-induced PGE₂ synthesis and DNA synthesis in these cells. The inhibitory effect by 50μM indomethacin on the DNA synthesis was reversed by adding 10μM PGE₂. These results strongly suggest that extracellular ATP stimulates Ca²⁺ influx resulting in the release of arachidonic acid in osteoblast-like cells and that extracellular ATP-induced proliferative effect is mediated, at least in part, by ATP-stimulated PGE₂ synthesis.     

Dynamics of the protein structure of T169S pyranose 2‐oxidase in solution: Molecular dynamics simulation

Pyranose 2‐oxidase (P2O) from Trametes multicolor contains FAD as cofactor, and forms a tetramer. The protein structure of a mutated P2O, T169S (Thr169 is replaced by Ser), in solution was studied by means of molecular dynamics simulation and analyses of photoinduced electron transfer (ET) from Trp168 to excited isoalloxazine (Iso*), and was compared with wild type (WT) P2O. Hydrogen bonding between Iso and nearby amino acids was very similar as between T169S and WT protein. Distances between Iso and Tyr456 were extremely heterogeneous among the subunits, 1.7 (1.5 in WT) in subunit A (Sub A), 0.97 (2.2 in WT) in Sub B, 1.3 (2.1 in WT) in Sub C, 1.3 nm (2.0 in WT) in Sub D. Mean values of root of mean square fluctuation over all residues were greater by four times than those in WT. This suggests that the protein structure of T169S is much more flexible than that of WT. Electrostatic (ES) energies between Iso anion in one subunit and ionic groups in the entire protein were evaluated. It was found that more than 50% of the total ES energy in each subunit is contributed from other subunits. Reported fluorescence decays were analyzed by a method as WT, previously reported. Electron affinities of Iso* in T169S were appreciably higher than those in WT. Static dielectric constants near Iso and Trp168 were also quite higher in T169S than those in WT.     

Systematic Evaluation of Protein Sequence Filtering Algorithms for Proteoform Identification Using Top‐Down Mass Spectrometry

Complex proteoforms contain various primary structural alterations resulting from variations in genes, RNA, and proteins. Top‐down mass spectrometry is commonly used for analyzing complex proteoforms because it provides whole sequence information of the proteoforms. Proteoform identification by top‐down mass spectral database search is a challenging computational problem because the types and/or locations of some alterations in target proteoforms are in general unknown. Although spectral alignment and mass graph alignment algorithms have been proposed for identifying proteoforms with unknown alterations, they are extremely slow to align millions of spectra against tens of thousands of protein sequences in high throughput proteome level analyses. Many software tools in this area combine efficient protein sequence filtering algorithms and spectral alignment algorithms to speed up database search. As a result, the performance of these tools heavily relies on the sensitivity and efficiency of their filtering algorithms. Here, we propose two efficient approximate spectrum‐based filtering algorithms for proteoform identification. We evaluated the performances of the proposed algorithms and four existing ones on simulated and real top‐down mass spectrometry data sets. Experiments showed that the proposed algorithms outperformed the existing ones for complex proteoform identification. In addition, combining the proposed filtering algorithms and mass graph alignment algorithms identified many proteoforms missed by ProSightPC in proteome‐level proteoform analyses.