Improvement in fermentation characteristics of degermed ground corn by lipid supplementation

With rapid growth of fuel ethanol industry, and concomitant increase in distillers dried grains with solubles (DDGS), new corn fractionation technologies that reduce DDGS volume and produce higher value coproducts in dry grind ethanol process have been developed. One of the technologies, a dry degerm, defiber (3D) process (similar to conventional corn dry milling) was used to separate germ and pericarp fiber prior to the endosperm fraction fermentation. Recovery of germ and pericarp fiber in the 3D process results in removal of lipids from the fermentation medium. Biosynthesis of lipids, which is important for cell growth and viability, cannot proceed in strictly anaerobic fermentations. The effects of ten different lipid supplements on improving fermentation rates and ethanol yields were studied and compared to the conventional dry grind process. Endosperm fraction (from the 3D process) was mixed with water and liquefied by enzymatic hydrolysis and was fermented using simultaneous saccharification and fermentation. The highest ethanol concentration (13.7% v/v) was achieved with conventional dry grind process. Control treatment (endosperm fraction from 3D process without lipid supplementation) produced the lowest ethanol concentration (11.2% v/v). Three lipid treatments (fatty acid ester, alkylphenol, and ethoxylated sorbitan ester 1836) were most effective in improving final ethanol concentrations. Fatty acid ester treatment produced the highest final ethanol concentration (12.3% v/v) among all lipid supplementation treatments. Mean final ethanol concentrations of alkylphenol and ethoxylated sorbitan ester 1836 supplemented samples were 12.3 and 12.0% v/v, respectively.Mention of brand or firm names does not constitute an endorsement by University of Illinois or USDA above others of similar nature not mentioned     

TspMI, a thermostable isoschizomer of XmaI (5′C/CCGGG3′): characterization and single molecule imaging with DNA

TspMI, a thermostable isoschizomer of XmaI from a Thermus sp., has been characterized. The enzyme was purified to homogeneity using Cibacron-Blue 3GA agarose, Heparin agarose, SP sephadex C50, and Mono-Q fast protein liquid chromatography and was found to be a homodimer of 40 kDa. Restriction mapping and run-off sequencing of TspMI-cleaved DNA ends depicted that it cleaved at 5′C/CCGGG3′ to generate a four-base, 5′-CCGG overhang. The enzyme was sensitive to methylation of second and third cytosines in its recognition sequence. TspMI worked optimally at 60°C with 6 mM Mg²⁺, no Na⁺/K⁺, and showed no star activity in the presence of 25% glycerol. The enzyme could efficiently digest the DNA labeled with a higher concentration of YOYO-I (one dye molecule to one nucleotide), making it a useful candidate for real-time imaging experiments. Single molecule interaction between TspMI and λ DNA was studied using total internal reflection fluorescence microscopy. The enzyme survived 30 polymerase chain reaction (PCR) cycles in the presence of 10% glycerol and 0.5 M trehalose without any activity loss and, hence, is suitable for incorporation in restriction-endonuclease-mediated selective-PCR for various applications.Electronic Supplementary Material Supplementary material for this article is available at     

Genetic affinities among the lower castes and tribal groups of India: inference from Y chromosome and mitochondrial DNA

Background

Past work on asthmatic African American families revealed a strong linkage peak with modest evidence of association on chromosome 11q. Here, we perform tests of association for asthma and a panel of 609 SNPs in African American subjects using a sliding window approach. While efficient in screening a region of dense genotyping, this approach does create some problems: high numbers of tests, assimilating thousands of results, and questions about setting priorities on regions with association signals.

Results

We present a newly developed tool, Graphical Assessment of Sliding P-values or GrASP, which uses color display to indicate the width of the sliding windows, significance of individual tests, density of SNP coverage and location of known genes that simplifies some of these issues, and use it to identify regions of interest in these data.

Conclusion

We demonstrate that GrASP makes it easier to visualize, summarize and prioritize regions of interest from sliding window haplotype analysis, based jointly on the p-value from all the tests from these windows and the building of haplotypes of significance in the region. Using this approach, five regions yielded strong evidence for linkage and association with asthma, including the prior peak linkage region.     

Selection for early and late adult emergence alters the rate of pre-adult development in Drosophila melanogaster

Background  

Circadian clocks have been implicated in the regulation of pre-adult development of fruit flies Drosophila melanogaster. It is believed that faster clocks speed up development and slower clocks slow it down. We established three sets of D. melanogaster populations (early, control and late). The early and late populations were raised by selecting for flies that emerged either in the morning or in the evening under 12:12 hr light/dark (LD) cycles. After 75 generations of selection, the time course and waveform of the adult emergence and activity rhythms of the early and the late populations diverged from each other as well as from the controls. In this paper, we report the consequence of this selection on the rate of pre-adult development.     

Calculation of rate spectra from noisy time series data

As the resolution of experiments to measure folding kinetics continues to improve, it has become imperative to avoid bias that may come with fitting data to a predetermined mechanistic model. Toward this end, we present a rate spectrum approach to analyze timescales present in kinetic data. Computing rate spectra of noisy time series data via numerical discrete inverse Laplace transform is an ill‐conditioned inverse problem, so a regularization procedure must be used to perform the calculation. Here, we show the results of different regularization procedures applied to noisy multiexponential and stretched exponential time series, as well as data from time‐resolved folding kinetics experiments. In each case, the rate spectrum method recapitulates the relevant distribution of timescales present in the data, with different priors on the rate amplitudes naturally corresponding to common biases toward simple phenomenological models. These results suggest an attractive alternative to the “Occam's razor” philosophy of simply choosing models with the fewest number of relaxation rates. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Effects of Familial Mutations on the Monomer Structure of Aβ42

Amyloid beta (Aβ) peptide plays an important role in Alzheimer’s disease. A number of mutations in the Aβ sequence lead to familial Alzheimer’s disease, congophilic amyloid angiopathy, or hereditary cerebral hemorrhage with amyloid. Using molecular dynamics simulations of ∼200 μs for each system, we characterize and contrast the consequences of four pathogenic mutations (Italian, Dutch, Arctic, and Iowa) for the structural ensemble of the Aβ monomer. The four familial mutations are found to have distinct consequences for the monomer structure.Amyloid beta (Aβ) peptides have long been thought to play a central role in Alzheimer’s disease (AD). Usually 40 or 42 residues in length, Aβ peptides are proteolytic products of the Aβ precursor protein and they aggregate to form the fibrillar plaques in AD patients’ brains. Besides fibrillar plaques, Aβ oligomers are also neurotoxic. The significance and nature of Aβ oligomerization has recently become a focus of intensive research studies and debates (1,2). Notably, numerous pathogenic mutations have been identified in the Aβ precursor protein sequence and in the enzymes involved in Aβ processing (3). These mutations generally lead to early onset of AD or cerebral amyloid angiopathy. Understanding how the pathogenic mutations alter Aβ oligomerization/aggregation is essential to our understanding of the disease mechanism.Four of these pathogenic mutations (Italian E22K, Dutch E22Q, Arctic E22G, and Iowa D23N) cluster in the region of E22 and D23 in the Aβ sequence (distal from proteolytic cleavage sites) and they have higher neurotoxicity compared to wild-type (WT) Aβ (4). These mutations are thought to modify the physicochemistry of the peptide. For example, kinetic studies (4) show that the E22K and E22Q mutations lead to faster peptide aggregation, whereas the E22G and D23N mutations result in slightly slower aggregation than WT Aβ₄₂ (although the E22G mutation shows increased protofibril formation (5)). Recent solid-state NMR studies also suggest that rather than the in-register β-sheet conformation adopted by WT Aβ, the Iowa D23N mutant forms amyloid fibrils with antiparallel β-sheet structure (6).To understand how the mutations modify the peptide oligomerization/aggregation it is critical to characterize the starting point of the process, the monomers. Unfortunately, investigating the early phase of the oligomerization process experimentally is a challenging task due to the high aggregation propensity of Aβ and its intrinsic disorder. Therefore, a number of computational approaches have been adopted to investigate the consequences of mutations for the monomer structure (7–16). However, due to the high computational demands of explicit-solvent molecular dynamics (MD) simulations to simulate full-length Aβ peptides, most of these computational studies are either on Aβ fragments (to decrease the system size) using explicit-solvent simulations (8–12) or on full-length Aβ using implicit-solvent simulations (which are less computationally demanding and enable longer simulation times, but lack explicit water molecules in the simulations to fully describe water-peptide interactions) (13–15). In a very recent report, explicit-solvent simulations were used to study the effects of the E22Q mutation on full-length Aβ; however, rather limited data (<10 μs) were collected (16). Thus, characterizing full-length Aβ monomers remains quite a daunting task even with simulations.To characterize the effects of mutations on full-length Aβ monomer using explicit-solvent MD simulations, we employed distributed computing (17) to simulate the WT Aβ₄₂, Aβ₄₂-E22K, Aβ₄₂-E22Q, Aβ₄₂-E22G, and Aβ₄₂-D23N monomers. MD simulations of >200 μs were performed for each system and AMBER ff99sb (18) and the tip3p water model (19) were used for force field parameters. Peptide configurations in the MD trajectories were clustered with the root mean-square deviation metric to identify representative conformations (i.e., states) and transitions between these states were counted. Markov state model analysis was then performed where the master equations were solved and the equilibrium population of each state deduced (20). Details of the MD simulation procedures and Markov state model analysis can be found in the Supporting Material.Each of the five Aβ monomer systems exhibits great structural diversity and can only be characterized in an ensemble fashion (rather than described by a handful of representative configurations). This is in accord with the notion that full-length Aβ peptides are intrinsically disordered (21,22). Using the Dictionary of Secondary Structure of Proteins program (23) to assign secondary structure, it is clear that the five Aβ monomer systems are found overall not well structured, although small β-hairpins and α-helices are observed. In Fig. 1 we plot the residue-dependent extended β propensity and α-helix propensity, in the top and bottom panels, respectively, for each Aβ monomer system. Although we are reasonably confident of the convergence behavior of the α-helix propensity, we note that the convergence of the extended β-propensity might be more challenging and demand a much longer sampling time than the current aggregate simulation time of ∼200 μs (24).Open in a separate windowFigure 1Ensemble-averaged %population of β-strand (top) and α-helix (bottom) propensity for all five monomer systems. The sequence of the WT Aβ₄₂ is given on the x axis.We observe in Fig. 1 that all five Aβ monomer systems share a rather similar residue-dependent tendency to form an extended β-structure, although minor differences are present. On the other hand, these pathogenic mutations alter the α-helix propensity quite significantly. The E22K and E22Q mutations increase the α-helix propensity in the region of residues 20–23. All four mutations (E22K, E22Q, E22G, and D23N) decrease the α-helix propensity in the region of residues 33–36.Notably, we find that in all five systems only short stretches of α-helices are formed. That is, when a residue is involved in α-helix formation, it participates in forming mostly short helical segments (consisting of only four helical residues). To provide more insight into the changes of α-helix propensity due to the mutations, in Fig. S1 we plot the tendency of forming short α-helices along the sequence for all five systems. Each data point in Fig. S1 represents the propensity to form an α-helix of four residues in length, ending at the specific residue. For example, in the structural ensemble adopted by the WT peptide, ∼5.5% of the conformations have a short α-helix of size four, involving residues 15–18. We see from Fig. S1 that the E22K and E22Q mutations induce the formation of two short helices in residues 19–22 and 20–23. The higher α-helix propensity in this region for the E22K mutant compared to the WT was previously attributed to the elimination of the electrostatic repulsion between E22 and D23 in the WT by the mutation and the longer aliphatic chain of K22 in the mutant compared to E22 in the WT (9,22). This is consistent with the observation that the E22Q mutation also induces helix formation in this region (by eliminating the electrostatic repulsion between E22 and D23 in the WT) but to a lesser extent, possibly due to the shorter aliphatic chain of Q22 compared to K22.In the E22G mutant, although the mutation eliminates the electrostatic repulsion between E22 and D23 in the WT peptide, glycine is known to be a helix breaker (25), leading to diminished α-helix propensity in the region around residue G22 seen in Fig. S1.In the D23N mutant, although the mutation eliminates the electrostatic repulsion between E22 and D23 in the WT peptide, it does not induce (or rather even slightly decreases) helix formation around residue 23. This may be due to the short aliphatic chain of N23 but it is possible that the mutation induces some nonlocal effects on the peptide structure, disfavoring helix formation in this region.It is worth noting that all four mutations (E22K, E22Q, E22G, and D23N) virtually eliminate the α-helix propensity in the region of residues 33–36. This region is rather far away from the mutation sites in sequence but its α-helix propensity is nonetheless affected. The origin of such a nonlocal effect is less straightforward to explain and further analysis will aid untangling this behavior. Nonetheless, the diminished α-helix propensity in the region of residues 33–36 appears to be a consistent feature across all four mutants.The four mutations studied here (E22K, E22Q, E22G, and D23N) have been thought to modify the physicochemistry of the peptide and alter the oligomerization/aggregation process, leading to higher neurotoxicity. In predicting intrinsic aggregation propensities using peptide sequences, all four mutants are suggested to be more aggregation prone (26). On the other hand, kinetic studies show that only the E22K and E22Q mutants aggregate more quickly, whereas the E22G and D23N mutations result in slightly slower aggregation than WT Aβ₄₂ (4). Our simulation results suggest these pathogenic mutations have complicated effects on the monomer structure—all four mutations decrease helix propensity in residues 33–36, whereas only the E22K and E22Q mutations increase helix propensity in residues 20–23. It is interesting to note that α-helix propensity is generally thought to anticorrelate with aggregation propensity; however, recent studies have suggested an important role of α-helical intermediates in amyloid oligomerization (27–29). Our studies suggest that it would be of great value to investigate how the distinct patterns of α-helix propensity in these five systems may propagate to give rise to different oligomerization kinetics or even mechanisms. The pathogenic mutations studied here have complex effects on the oligomerization of the peptide. The characterization of the monomer structural ensembles reported here should aid understanding of such an important and complicated process.     

Transforming growth factor-β protein inversely regulates in vivo differentiation of interleukin-17 (IL-17)-producing CD4+ and CD8+ T cells

TGF-β is a pleiotropic cytokine that predominantly exerts inhibitory functions in the immune system. Unexpectedly, the in vitro differentiation of both Th17 and Tc17 cells requires TGF-β. However, animals that are impaired in TGF-β signaling (TGF-βRIIDN mice) display multiorgan autoimmune disorders. Here we show that CD4(+) T cells from TGF-βRIIDN mice are resistant to Th17 cell differentiation and, paradoxically, that CD8(+) T cells from these animals spontaneously acquire an IL-17-producing phenotype. Neutralization of IL-17 or depletion of CD8(+) T cells dramatically inhibited inflammation in TGF-βRIIDN mice. Therefore, the absence of TGF-β triggers spontaneous differentiation of IL-17-producing CD8(+) T cells, suggesting that the in vivo and in vitro conditions that promote the differentiation of IL-17-producing CD8(+) T cells are distinct.     

Uncoupling of eNOS causes superoxide anion production and impairs NO signaling in the cerebral microvessels of hph-1 mice

J. Neurochem. (2012) 122, 1211-1218. ABSTRACT: In this study, we used the GTP cyclohydrolase I-deficient mice, i.e., hyperphenylalaninemic (hph-1) mice, to test the hypothesis that the loss of tetrahydrobiopterin (BH(4) ) in cerebral microvessels causes endothelial nitric oxide synthase (eNOS) uncoupling, resulting in increased superoxide anion production and inhibition of endothelial nitric oxide signaling. Both homozygous mutant (hph-1(-/-) ) and heterozygous mutant (hph-1(+/-) mice) demonstrated reduction in GTP cyclohydrolase I activity and reduced bioavailability of BH(4) . In the cerebral microvessels of hph-1(+/-) and hph-1(-/-) mice, increased superoxide anion production was inhibited by supplementation of BH(4) or NOS inhibitor- L- N(G) -nitro arginine-methyl ester, indicative of eNOS uncoupling. Expression of 3-nitrotyrosine was significantly increased, whereas NO production and cGMP levels were significantly reduced. Expressions of antioxidant enzymes namely copper and zinc superoxide dismutase, manganese superoxide dismutase, and catalase were not affected by uncoupling of eNOS. Reduced levels of BH(4) , increased superoxide anion production, as well as inhibition of NO signaling were not different between the microvessels of male and female mice. The results of our study are the first to demonstrate that, regardless of gender, reduced BH(4) bioavailability causes eNOS uncoupling, increases superoxide anion production, inhibits eNOS/cGMP signaling, and imposes significant oxidative stress in the cerebral microvasculature.     

Bcl-2/adenovirus E1B 19 kDa-interacting protein 3 (BNIP3) expression is epigenetically regulated by one-carbon metabolism in invasive duct cell carcinoma of breast

In view of recent studies highlighting the prognostic relevance of expression and CpG island methylator phenotype (CIMP) of Bcl-2/adenovirus E1B 19 kDa-interacting protein 3 (BNIP3) in invasive duct cell carcinoma (IDC), we hypothesized in this article that impaired one-carbon metabolism might influence CIMP phenotype of BNIP3. In order to substantiate the prognostic relevance of BNIP3, we explored its association with 8-oxo-2'deoxyguanosine (8-oxodG), a marker of oxidative stress with prognostic relevance. BNIP3 expression and CIMP phenotype were studied using semi-quantitative RT-PCR and combined bisulfite restriction analysis (COBRA), respectively, in 56 IDC tumors. Eight polymorphisms in one-carbon metabolism were studied using PCR-RFLP and PCR-AFLP approaches. 8-oxodG was measured using competitive ELISA kit. BNIP3 was found to be upregulated in IDC (cases vs. controls: 0.94 ± 0.05 vs. 0.18 ± 0.08, P < 0.0001). COBRA analysis confirmed hypomethylation of BNIP3 promoter CpG island in these cases. CIMP phenotype of BNIP3 showed positive association with tubule formation (P = 0.034) and methionine synthase reductase (MTRR) A66G (P = 0.002); inverse association with cytosolic serine hydroxyl methyltransferase (cSHMT) C1420T (P < 0.005) and 8-oxodG (<10% vs. >10% methylation: 7.24 ± 2.77 ng/ml vs. 4.42 ± 2.93 ng/ml, P < 0.0005); and no association with nuclear pleomorphism or mitotic index or ER, PR, and HER statuses. Synergistic effect of MTR A2756G and MTRR A66G variants on BNIP3 hypermethylator phenotype was clearly evident (P < 0.0007). MTRR A66G and cSHMT C1420T polymorphisms influence CIMP phenotype of BNIP3, thus epigenetically regulating BNIP3 in breast cancer. The linear association between BNIP3 and 8-oxodG substantiates the role of BNIP3 as redox sensor as well as prognostic marker in breast cancer.