Responses of Soil,Heterotrophic, and Autotrophic Respiration to Experimental Open-Field Soil Warming in a Cool-Temperate Deciduous Forest

How global warming will affect soil respiration (R _S) and its source components is poorly understood despite its importance for accurate prediction of global carbon (C) cycles. We examined the responses of R _S, heterotrophic respiration (R _H), autotrophic respiration (R _A), nitrogen (N) availability, and fine-root biomass to increased temperature in an open-field soil warming experiment. The experiment was conducted in a cool-temperate deciduous forest ecosystem in northern Japan. As this forest is subjected to strong temporal variation in temperature, on scales ranging from daily to seasonal, we also investigated the temporal variation in the effects of soil warming on R _S, R _H, and R _A. Soil temperature was continuously elevated by about 4.0°C from 2007 to 2014 using heating wires buried in the soil, and we measured soil respiratory processes in all four seasons from 2012 to 2014. Soil warming increased annual R _S by 32–45%, but the magnitude of the increase was different between the components: R _H and R _A were also stimulated, and increased by 39–41 and 17–18%, respectively. Soil N availability during the growing season and fine-root biomass were not remarkably affected by the warming treatment. We found that the warming effects varied seasonally. R _H increased significantly throughout the year, but the warming effect showed remarkable seasonal differences, with the maximum stimulation in the spring. This suggests that warmer spring temperature will produce a greater increase in CO₂ release than warmer summer temperatures. In addition, we found that soil warming reduced the temperature sensitivity (Q ₁₀) of R _S. Although the Q ₁₀ of both R _H and R _A tended to be reduced, the decrease in the Q ₁₀ of R _S was caused mainly by a decrease in the response of R _A to warming. These long-term results indicate that a balance between the rapid and large response of soil microbes and the acclimation of plant roots both play important roles in determining the response of R _S to soil warming, and must be carefully considered to predict the responses of soil C dynamics under future temperature conditions.     

Identification of 21 novel <Emphasis Type="Italic">S-RNase</Emphasis> alleles and determination of <Emphasis Type="Italic">S</Emphasis>-genotypes in 66 loquat (<Emphasis Type="Italic">Eriobotrya</Emphasis>) accessions

As observed in other self-incompatible species in the Pyrinae subtribe, loquat (Eriobotrya japonica) demonstrates gametophytic self-incompatibility that is controlled by the S-locus, which encodes a polymorphic stylar ribonuclease (S-RNase). This allows the female reproductive organ (style) to recognize and reject the pollen from individuals with the same S-alleles, but allows the pollen from individuals with different S-alleles to effect fertilization. The S-genotype is therefore an important consideration in breeding strategies and orchard management. In an attempt to optimize the selection of parental lines in loquat production, the S-RNase alleles of 35 loquat cultivars and their 26 progeny, as well as five wild loquat species, were identified and characterized in this study. The best pollinizer cultivar combinations were also explored. A total of 28 S-alleles were detected, 21 of which constituted novel S-RNase alleles. The S-haplotypes S₂ and S₆ were the most frequent, followed by S ₂₉ , S ₃₁ , S ₅ , S ₂₄ , S ₂₈ , S ₃₃ , S ₃₄ , S ₃₂ , and S ₁₅ , while the rare alleles S ₁ , S ₉ , S ₁₄ , S ₁₆ , S ₁₇ , S ₁₈ , S ₁₉ , S ₂₀ , S ₂₁ , S ₂₂ , S ₂₃ , S ₂₇ , and S ₃₅ were only observed in one of the accessions tested. Moreover, the S-genotypes of five wild loquat species (E. prinoides, E. bengalensis, E. prinoides var. dadunensis, E. deflexa, and E. japonica) are reported here for the first time. The results will not only facilitate the selection of suitable pollinators for optimal orchard management, but could also encourage the crossbreeding of wild loquat species to enhance the genetic diversity of loquat cultivars.     

The R* rule and energy flux in a plant-nutrient ecosystem

The R* rule predicts that the species that can survive in steady state at the lowest level of limiting resource, R*, excludes all other species. Simple models indicate that this concept is not necessarily consistent with Lotka's conjecture that an ecological system should evolve towards a state of maximum power, Max(G), where G is the power, or rate of biomass production of the system. To explore the relationship in detail, we used a published model of a plant-nutrient system in which a plant can use various strategies, S, of allocation of energy between foliage, roots, and wood. We found that the allocation strategy, S_MinR*, that leads to , where is a limiting nutrient in soil pore water in our model (and equivalent to R* in Tilman's notation), is the same as the strategy, S_{MaxG_root}, for which energy flux to roots is maximized. However, that allocation strategy is different from the strategy, S_MaxG, that produces maximum power, or maximum photosynthetic rate, for the plant system, Max(G). Hence, we conclude that and Max(G) should not necessarily co-occur in an ecological system. We also examined which strategy, S_fit, was fittest; that is, eliminated any other strategies, when allowed to compete. The strategy S_fit differed from S_MinR*, S_MaxG, and S_{MaxG_root}, which we demonstrated mathematically. We also considered the feasible situation in which a plant is able to positively influence external nutrient input to the system. Under such conditions, the strategy, S_{MaxG_root}, that maximizes energy flux to roots was the same as the strategy, S_MaxR*, that leads to maximum concentration of available nutrient in soil pore water, , and not same as S_MinR*, for .     

The effect of sulfur on CVD performance of Pd(II) β-diketonate precursors and the completion of a structural trans-influence series: synthesis and structural characterization of Pd(S,S-tmhd)2

The three complexes, Pd(tmhd)₂ (1), Pd(S-tmhd)₂ (2), and Pd(S,S-tmhd)₂ (3) (where tmhd, S-tmhd, and S,S-tmhd are the anions of 2,2,6,6-tetramethyl-3,5-heptanedione, 2,2,6,6-tetramethyl-5-thioxo-3-heptanone, and 2,2,6,6-tetramethyl-3,5-heptanedithione, respectively) were prepared and characterized by thermogravimetric analysis in order to assess their relative volatilities as a function of sulfur substitution. Complexes 1 and 2 volatilized with little residue, while 3 experienced significant decomposition during volatilization. The solid-state structure of 3 was determined in order to complete a structural trans-influence series with 1 and 2 and to assess possible reasons for its lower thermal stability. A large trans-influence was observed for the bond lengths in the coordination sphere across the series of complexes 1, 2, and 3. The longer Pd-S bond distances found in 3 may be a contributing factor to its unsuitability as a CVD precursor.     

Multilevel Selection 4: Modeling the Relationship of Indirect Genetic Effects and Group Size

Indirect genetic effects (IGE) occur when individual trait values depend on genes in others. With IGEs, heritable variance and response to selection depend on the relationship of IGEs and group size. Here I propose a model for this relationship, which can be implemented in standard restricted maximum likelihood software.SOCIAL interactions among individuals are abundant in life (Frank 2007). Trait values of individuals may, therefore, depend on genes in other individuals, a phenomenon known as indirect genetic effects (IGE; Wolf et al. 1998) or associative effects (Griffing 1967; Muir 2005). IGEs may have drastic effects on the rate and direction of response to selection. Moreover, with IGEs, heritable variance and response to selection depend on the size of the interaction group, hereafter denoted group size (Griffing 1967; Bijma et al. 2007; McGlothlin et al. 2010). The magnitude of the IGEs themselves, however, may also depend on group size, because interactions between a specific pair of individuals are probably less intense in larger groups (Arango et al. 2005). The relationship between the magnitude of IGEs and group size is relevant because it affects the dynamics of response to selection, heritable variation, and group size, determining, e.g., whether or not selection is more effective with larger groups. Moreover, a model for this relationship is required to estimate IGEs from data containing varying group sizes. Hadfield and Wilson (2007) proposed a model for the relationship between IGEs and group size. Here I present an alternative.With IGEs, the trait value of focal individual i is the sum of a direct effect rooted in the focal individual itself, P_D,i, and the sum of the indirect effects, P_S,j, of each of its n − 1 group mates j,(1)where A and E represent the heritable and nonheritable component of the full direct and indirect effect, respectively, and n denotes group size (Griffing 1967). When IGEs are independent of group size, total heritable variance in the trait equals (Bijma et al. 2007)(2)For a fixed becomes very large with large groups. This is unrealistic because an individual''s IGE on a single recipient probably becomes smaller in larger groups. The decrease of IGEs with group size, referred to as dilution here, will depend on the trait of interest. With competition for a finite amount of feed per group, for example, an individual consuming 1 kg has an average indirect effect of P_S,i = −1/(n − 1) on feed intake of each of its group mates. Hence, the indirect effect is inversely proportional to the number of group mates, indicating full dilution. The other extreme of no dilution may be illustrated by alarm-calling behavior, where an individual may warn all its group mates when a predator appears, irrespective of group size. Here the indirect effect each group mate receives is independent of group size, indicating no dilution. The degree of dilution is an empirical issue, which may be trait and population specific, and needs to be estimated.Here I propose to model dilution of indirect effects as(3)where P_S,i,n is the indirect effect of individual i in a group of n members, P_S,i,2 the indirect effect of i in a group of two members, and d the degree of dilution. With no dilution, d = 0, indirect effects do not depend on group size, P_S,i,n = P_S,i,2, as with alarm-calling behavior. With full dilution, d = 1, indirect effects are inversely proportional to the number of group mates, P_S,i,n = P_S,i,2/(n − 1), as with competition for a finite amount of feed. Equation 3 is an extension of the model of Arango et al. (2005), who used d = 1.Assuming that IGEs are diluted in the same manner as the full indirect effect, the indirect genetic variance for groups of n members equals(4)and total heritable variance equals(5)Hence, for σ_ADS = 0, total heritable variance increases with group size as long as dilution is incomplete (d < 1). Total heritable variance is independent of group size with full dilution (d = 1). Phenotypic variance also depends on group size. With unrelated group members,(6)which increases with group size for d < 0.5, is independent of group size for d = 0.5, and decreases with group size for d > 0.5.The degree of dilution can be estimated from data containing variation in group size, by using a mixed model with restricted maximum likelihood and evaluating the likelihood for different fixed values of d (Arango et al. 2005; Canario et al. 2010). With Equation 3, however, the estimated genetic (co)variances and breeding values for indirect effect refer to a group size of two individuals, which is inconvenient when actual group size differs considerably. Estimates of A_S, , and σ_ADS referring to the average group size may be obtained from the following mixed model,(7)where z is a vector of observations, Xb are the usual fixed effects, Z_Da_D are the direct genetic effects, Z_gg are random group effects, and e is a vector of residuals. The is a vector of IGEs referring to the average group size, and Z_S(d) is the incidence matrix for IGEs, which depends on the degree of dilution; dilution being specified relative to the average group size. Elements of Z_S(d) are(8)where denotes average group size. This model is equivalent to Equation 3, but yields estimates of genetic parameters and breeding values referring to the average group size because for . When the magnitude of IGEs depends on group size, the group and residual variance in Equation 7 will depend on group size:(9a)(9b)Hence, to obtain unbiased estimates of the genetic parameters and d, it may be required to fit a separate group and residual variance for each group size.To account for the relationship between IGEs and group size, Hadfield and Wilson (2007; HW07) proposed including an additional IGE. In their model, an individual''s full IGE is the sum of an effect independent of group size, and an effect regressed by the reciprocal of the number of group mates,(10)There are a number of differences between both models. First, Equation 3 specifies the relationship between the magnitude of IGEs and group size on the population level, which is sufficient to remedy the problem of increasing variance with group size. The HW07 model, in contrast, specifies the relationship between the magnitude of IGEs and group size on the individual level. In the HW07 model, the absolute value of (1/(n − 1))A_SR,_i decreases with group size, while A_S,i is constant. Consequently, the relationship between an individual''s full IGE and group size depends on the relative magnitudes of its A_S,i and A_SR,_i; the IGEs of individuals with greater |A_SR| show greater change when group size varies. This alters the IGE ranking of individuals when group size varies. The HW07 model, therefore, not only scales IGEs with group size, but also allows for IGE-by-group-size interaction, whereas Equation 3 scales IGEs of all individuals in the same way. Second, the interpretation of the genetic parameters differs between both models. In the HW07 model, lim_n→∞ A_S,i,HW07 = A_S,i, meaning that Var(A_S) represents the variance in IGEs when group size is infinite. With Equation 3 or 7, in contrast, refers to groups of two individuals or to the average group size. Third, in the HW07 model, the dilution of IGEs with group size is implicitly incorporated in the magnitudes of Var(A_S) and Var(A_SR), greater Var(A_SR) implying greater dilution. Equation 3, in contrast, has a single parameter for the degree of dilution, expressed on a 0–1 scale. Finally, implementing the HW07 model involves estimating three additional covariance parameters, Var(A_SR), Cov(A_D, A_SR), and Cov(A_S, A_SR), whereas implementing the model proposed here involves estimating a single additional fixed effect, which is simpler. In conclusion, the HW07 model has greater flexibility than the model proposed here, but is also more difficult to implement and interpret.     

How Common Are Intragene Windows with <Emphasis Type="Italic">K</Emphasis><Subscript>A</Subscript> > <Emphasis Type="Italic">K</Emphasis><Subscript>S</Subscript> Owing to Purifying Selection on Synonymous Mutations?

One method for diagnosing the mode of sequence evolution considers the ratio of nonsynonymous substitutions per nonsynonymous site (K _A) to the corresponding figure for synonymous substitutions (K _S). A ratio (K _A/K _S) greater than unity is taken as evidence for positive selection. This, however, need not necessarily be the case. Notably, there is one instance of a high intragenic K _A/K _S peak, revealed by sliding window analysis and observed in two pairwise comparisons, better accounted for by localised purifying selection on synonymous mutations that affect splicing. Is this example exceptional? To address this we isolate intragenic domains with K _A/K _S > 1 from more than 1000 long mouse-rat orthologues. Approximately one K _A/K _S > 1 peak is found per 12–15 kb of coding sequence. Surprisingly, low synonymous substitution rates underpin more incidences than do high nonsynonymous rates. Several reasons, however, prevent us from supposing that the low synonymous rates reflect purifying selection on synonymous mutations. First, for many peaks, the null that the peak is no higher than expected given the underlying rates of evolution, cannot be rejected. Second, of 18 statistically significant incidences with unusually low K _S values, only 3 are repeatable across independent comparisons. At least two of these are within alternatively spliced exons. We conclude that repeatable statistically significant intragenic domains of low intragenic K _S are rare. As so few K _A/K _S peaks reflect increased rates of protein evolution and so few hold statistical support, we additionally conclude that sliding window analysis to infer domains of positive selection is highly error-prone.     

The complexation between holothurian triterpene glycosides and Chl as the basis for lipid-saponin carriers of subunit protein antigens

The ability of holothurian triterpene glycosides (cucumarioside A₂-2 from Cucumaria japonica, cucumarioside G₁ from C. fraudatrix, frondoside A from C. frondosa, and holotoxin A₁ from Apostichopus japonicus) to form supramolecular lipid-saponin complexes was studied. TEM demonstrated that all the studied compounds form supramolecular cholesterol-saponin complexes (nanoparticles) in aqueous medium. The complexes formed by cucumarioside A₂-2, holotoxin A₁, and frondoside A had a tubular structure and fundamentally differed in the structure from the particles produced by cucumarioside G₁. The morphology of the nanoparticles formed by cucumarioside A₂-2, holotoxin A₁, and cucumarioside G₁ changed depending on the fraction of cholesterol in the lipid-saponin system; however, this pattern was not observed for frondoside A. At the same molar fraction of cholesterol in the lipid-saponin system, cucumarioside A₂-2 formed the particles with the most pronounced tubular structure; the cholesterol-saponin complexes of holotoxin A₁ had a less pronounced tubular structure, whereas the structure of frondoside A particles was extremely heterogeneous. Comparative analysis of the morphology of the described supramolecular complexes and specific structural features of the glycosides demonstrated that the structure of the corresponding nanoparticles depended on the degree of branching of the carbohydrate moiety in the glycoside molecule and the complexation with cholesterol was determined by the specific features of aglycone structure. Thus, the feasibility of producing new generation antigen carriers using the complexes in question was proved.     

Effect of outer sphere anions on the structure and color of nitrosylpentaamminechromium complex

Three kinds of crystalline compounds containing the nitrosylpentaamminechromium complexes [Cr(NO)(NH₃)₅]²⁺(A) were obtained: chloride ACl₂ (red-orange), chloride perchlorate ACl(ClO₄) (brown), and perchlorate A(ClO₄)₂ (green). The cause of the color change of the complex A with the change of outer sphere anions was sought using X-ray structural data of ACl₂, ACl(ClO₄), and A(ClO₄)₂. Crystal data: ACl₂, orthorhombic, space group Cmcm, a=10.0236 (9) Å, b=9.098 (3) Å, c=10.357(1) Å, V=944.5 (5) ų, Z=4; ACl(ClO₄), tetragonal, space group P4/nmm, a=7.6986 (8) Å, c=9.9566(8) Å, V=590.1 (1) Å^3,Z=2; A(ClO₄)₂, orthorhombic, space group Pnma, a=15.760 (2) Å, b=11.480(2) Å, c=7.920 (2) Å, V=1432.9 (4) ų, Z=4. The complex cation in ACl₂ has a distorted octahedral structure with a linear CrNO moiety. The short CrN (nitrosyl) distance of 1.692 (7) Å indicates the presence of multiple bonding between the chromium atom and the nitrogen atom in the nitrosyl group. The interatomic distances and angles within the complex cations hardly change with the change of the counter anions, while the distances between the complex cations in each crystal increase in the order ACl₂<ACl(ClO₄)<A(ClO₄)₂. The bulky perchlorate anions seems to separate the complex cations, while smaller chloride anions are not large enough to separate them. The distance (3.213(5) Å) between O(NO) and N(NH₃ in the adjacent complex cation) is rather short in the crystal of ACl₂, and there are six hydrogen bonds, where the NO group is surrounded by four NH₃ ligands. The distance (4.002(5) Å) between O(NO) and N(NH₃) is much longer in the crystal of A(ClO₄)₂, indicating the presence of no hydrogen bonding. In the crystal of ACl(ClO₄) the distance (3.452(4) Å) between O(NO) and N(NH₃) is in between those of ACl₂ and A(ClO₄)₂. The presence of hydrogen bonding between O(NO) and N(NH₃ in the adjacent complex cation) seems to cause the color change with the change of outer sphere anions.     

Photo- and thermal-induced linkage isomerizations in a peroxydithiocarbamate-Ru complex

Previous work has shown that mono-oxygenation of Ru(bpy)₂(N,N′-dimethyldithiocarbamate)⁺, 1, yields two different linkage isomers: S,S-bound 2a and O,S-bound 2b, as well as a stable dioxygenate, Ru(bpy)₂(N,N-dimethylthiocarbamate-sulfinate-S,S)⁺, 3. In this report, the interconversion of the two peroxydithiocarbamate isomers was investigated using photolysis and thermal activations. The O,S-bound 2b undergoes phototriggered linkage isomerization to form the less stable S,S-bound 2a at low temperatures in non-coordinating solvents. The more reactive S,S-bound 2a then converts to O,S-bound 2b by a thermal isomerization at moderate temperatures in polar solvents. The different solvent and temperature dependences suggest distinct pathways for the two isomerizations.     

Synthesis, structure, and catalytic activity of chiral Cu(II) and Ag(I) complexes with (S,S)-1,2-diaminocyclohexane-based N4-donor ligands

Condensation of (S,S)-1,2-cyclohexanediamine with 2 equiv. of 2-pyridine carboxaldehyde in toluene in the presence of molecular sieves at 70 °C gives N,N′-bis(pyridin-2-ylmethylene)-(S,S)-1,2-cyclohexanediamine (S,S-1) in 95% yield. Reduction of 1 with an excess of NaBH₄ in MeOH at 50 °C gives N,N′-bis(pyridin-2-ylmethyl)-(S,S)-1,2-cyclohexanediamine (S,S-2) in 90% yield. Reaction of 1 or 2 with 1 equiv. of CuCl₂ · 2H₂O in methanol gives complexes [N-(pyridin-2-ylmethylene)-(S,S)-1,2-cyclohexanediamine]CuCl₂ (3) and [Cu(S,S-2)(H₂O)]Cl₂ · H₂O (4), respectively, in good yields. Complex 4 can further react with 1 equiv. of CuCl₂ · 2H₂O in methanol to give [Cu(S,S-2)][CuCl₄] (5) in 75% yield. The rigidity of the ligand coupled with the steric effect of the free anion plays an important role in the formation of the helicates. Treatment of ligand S,S-1 with AgNO₃ induces a polymer helicate {[Ag(S,S-1)][NO₃]}_n (6), while reaction of ligand 2 with AgPF₆ or AgNO₃ in methanol affords a mononuclear single helicate [Ag(S,S-2)][PF₆] (7) or a dinuclear double helicate [Ag₂(S,S-2)₂][NO₃]₂ · 2CH₃OH (8) in good yields, respectively. All compounds have been characterized by various spectroscopic data and elemental analyses. Compounds 1, 3-5, 7 and 8 have been further subjected to single-crystal X-ray diffraction analyses. The Cu(II) complexes do not show catalytic activity for allylation reaction, in contrast to Ag(I) complexes, but they do show catalytic activity for Henry reaction (nitroaldol reaction) that Ag(I) complexes do not.     

Roots affect the response of heterotrophic soil respiration to temperature in tussock grass microcosms

Aims and Background

While the temperature response of soil respiration (R_S) has been well studied, the partitioning of heterotrophic respiration (R_H) by soil microbes from autotrophic respiration (R_A) by roots, known to have distinct temperature sensitivities, has been problematic. Further complexity stems from the presence of roots affecting R_H, the rhizosphere priming effect. In this study the short-term temperature responses of R_A and R_H in relation to rhizosphere priming are investigated.

Methods

Temperature responses of R_A, R_H and rhizosphere priming were assessed in microcosms of Poa cita using a natural abundance δ¹³C discrimination approach.

Results

The temperature response of R_S was found to be regulated primarily by R_A, which accounted for 70 % of total soil respiration. Heterotrophic respiration was less sensitive to temperature in the presence of plant roots, resulting in negative priming effects with increasing temperature.

Conclusions

The results emphasize the importance of roots in regulating the temperature response of R_S, and a framework is presented for further investigation into temperature effects on heterotrophic respiration and rhizosphere priming, which could be applied to other soil and vegetation types to improve models of soil carbon turnover.     

Kinetic modeling of electron transfer reactions in photosystem I complexes of various structures with substituted quinone acceptors

The reduction kinetics of the photo-oxidized primary electron donor P₇₀₀ in photosystem I (PS I) complexes from cyanobacteria Synechocystis sp. PCC 6803 were analyzed within the kinetic model, which considers electron transfer (ET) reactions between P₇₀₀, secondary quinone acceptor A₁, iron-sulfur clusters and external electron donor and acceptors – methylviologen (MV), 2,3-dichloro-naphthoquinone (Cl₂NQ) and oxygen. PS I complexes containing various quinones in the A₁-binding site (phylloquinone PhQ, plastoquinone-9 PQ and Cl₂NQ) as well as F _X-core complexes, depleted of terminal iron–sulfur F _A/F _B clusters, were studied. The acceleration of charge recombination in F _X-core complexes by PhQ/PQ substitution indicates that backward ET from the iron–sulfur clusters involves quinone in the A₁-binding site. The kinetic parameters of ET reactions were obtained by global fitting of the P₇₀₀ ⁺ reduction with the kinetic model. The free energy gap ΔG ₀ between F _X and F _A/F _B clusters was estimated as ?130 meV. The driving force of ET from A₁ to F _X was determined as ?50 and ?220 meV for PhQ in the A and B cofactor branches, respectively. For PQ in A_1A-site, this reaction was found to be endergonic (ΔG ₀?=?+75 meV). The interaction of PS I with external acceptors was quantitatively described in terms of Michaelis–Menten kinetics. The second-order rate constants of ET from F _A/F _B, F _X and Cl₂NQ in the A₁-site of PS I to external acceptors were estimated. The side production of superoxide radical in the A₁-site by oxygen reduction via the Mehler reaction might comprise ≥0.3% of the total electron flow in PS I.     

Phenotypic Plasticity in Photosynthetic Temperature Acclimation among Crop Species with Different Cold Tolerances

While interspecific variation in the temperature response of photosynthesis is well documented, the underlying physiological mechanisms remain unknown. Moreover, mechanisms related to species-dependent differences in photosynthetic temperature acclimation are unclear. We compared photosynthetic temperature acclimation in 11 crop species differing in their cold tolerance, which were grown at 15°C or 30°C. Cold-tolerant species exhibited a large decrease in optimum temperature for the photosynthetic rate at 360 μL L⁻¹ CO₂ concentration [Opt (A₃₆₀)] when growth temperature decreased from 30°C to 15°C, whereas cold-sensitive species were less plastic in Opt (A₃₆₀). Analysis using the C₃ photosynthesis model shows that the limiting step of A₃₆₀ at the optimum temperature differed between cold-tolerant and cold-sensitive species; ribulose 1,5-bisphosphate carboxylation rate was limiting in cold-tolerant species, while ribulose 1,5-bisphosphate regeneration rate was limiting in cold-sensitive species. Alterations in parameters related to photosynthetic temperature acclimation, including the limiting step of A₃₆₀, leaf nitrogen, and Rubisco contents, were more plastic to growth temperature in cold-tolerant species than in cold-sensitive species. These plastic alterations contributed to the noted growth temperature-dependent changes in Opt (A₃₆₀) in cold-tolerant species. Consequently, cold-tolerant species were able to maintain high A₃₆₀ at 15°C or 30°C, whereas cold-sensitive species were not. We conclude that differences in the plasticity of photosynthetic parameters with respect to growth temperature were responsible for the noted interspecific differences in photosynthetic temperature acclimation between cold-tolerant and cold-sensitive species.The temperature dependence of leaf photosynthetic rate shows considerable variation between plant species and with growth temperature (Berry and Björkman, 1980; Cunningham and Read, 2002; Hikosaka et al., 2006). Plants native to low-temperature environments and those grown at low temperatures generally exhibit higher photosynthetic rates at low temperatures and lower optimum temperatures, compared with plants native to high-temperature environments and those grown at high temperatures (Mooney and Billings, 1961; Slatyer, 1977; Berry and Björkman, 1980; Sage, 2002; Salvucci and Crafts-Brandner, 2004b). For example, the optimum temperature for photosynthesis differs between temperate evergreen species and tropical evergreen species (Hill et al., 1988; Read, 1990; Cunningham and Read, 2002). Such differences have been observed even among ecotypes of the same species (Björkman et al., 1975; Pearcy, 1977; Slatyer, 1977).Temperature dependence of the photosynthetic rate has been analyzed using the biochemical model proposed by Farquhar et al. (1980). This model assumes that the photosynthetic rate (A) is limited by either ribulose 1,5-bisphosphate (RuBP) carboxylation (A_c) or RuBP regeneration (A_r). The optimum temperature for photosynthetic rate in C₃ plants is thus potentially determined by (1) the temperature dependence of A_c, (2) the temperature dependence of A_r, or (3) both, at the colimitation point of A_c and A_r (Fig. 1; Farquhar and von Caemmerer, 1982; Hikosaka et al., 2006).Open in a separate windowFigure 1.A scheme illustrating the shift in the optimum temperature for photosynthesis depending on growth temperature. Based on the C₃ photosynthesis model, the A₃₆₀ (white and black circles) is limited by A_c (solid line) or A_r (broken line). The optimum temperature for the photosynthetic rate is potentially determined by temperature dependence of A_c (A), temperature dependence of A_r (B), or the intersection of the temperature dependences of A_c and A_r (C). When the optimum temperature for the photosynthetic rate shifts to a higher temperature, there are also three possibilities determining the optimum temperature: temperature dependence of A_c (D), temperature dependence of A_r (E), or the intersection of the temperature dependences of A_c and A_r (F). Especially in the case that the optimum temperature is determined by the intersection of the temperature dependences of A_c and A_r, the optimum temperature can shift by changes in the balance between A_c and A_r even when the optimum temperatures for these two partial reactions do not change.In many cases, the photosynthetic rate around the optimum temperature is limited by A_c, and thus the temperature dependence of A_c determines the optimum temperature for the photosynthetic rate (Hikosaka et al., 1999, 2006; Yamori et al., 2005, 2006a, 2006b, 2008; Sage and Kubien, 2007; Sage et al., 2008). As the temperature increases above the optimum, A_c is decreased by increases in photorespiration (Berry and Björkman, 1980; Jordan and Ogren, 1984; von Caemmerer, 2000). Furthermore, it has been suggested that the heat-induced deactivation of Rubisco is involved in the decrease in A_c at high temperature (Law and Crafts-Brandner, 1999; Crafts-Brandner and Salvucci, 2000; Salvucci and Crafts-Brandner, 2004a; Yamori et al., 2006b). Numerous previous studies have shown changes in the temperature dependence of A_c with growth temperature (Hikosaka et al., 1999; Bunce, 2000; Yamori et al., 2005). Also, the temperature sensitivity of Rubisco deactivation may differ between plant species (Salvucci and Crafts-Brandner, 2004b) and with growth temperature (Yamori et al., 2006b), which may explain variation in the optimum temperature for photosynthesis (Fig. 1, A and D).A_r is more responsive to temperature than A_c and often limits photosynthesis at low temperatures (Hikosaka et al., 1999, 2006; Sage and Kubien, 2007; Sage et al., 2008). Recently, several researchers indicated that A_r limits the photosynthetic rate at high temperature (Schrader et al., 2004; Wise et al., 2004; Cen and Sage, 2005; Makino and Sage, 2007). They suggested that the deactivation of Rubisco at high temperatures is not the cause of decreased A_c but a result of limitation by A_r. However, it remains unclear whether limitation by A_r is involved in the variation in the optimum temperature for the photosynthetic rate (Fig. 1, B and E).A shift in the optimum temperature for photosynthesis can result from changes in the balance between A_r and A_c, even when the optimum temperatures for these two partial reactions do not change (Fig. 1, C and F; Farquhar and von Caemmerer, 1982). The balance between A_r and A_c has been shown to change depending on growth temperature (Hikosaka et al., 1999; Hikosaka, 2005; Onoda et al., 2005a; Yamori et al., 2005) and often brings about a shift in the colimitation temperature of A_r and A_c. Furthermore, recent studies have shown that plasticity in this balance differs among species or ecotypes (Onoda et al., 2005b; Atkin et al., 2006; Ishikawa et al., 2007). Plasticity in this balance could explain interspecific variation in the plasticity of photosynthetic temperature dependence (Farquhar and von Caemmerer, 1982; Hikosaka et al., 2006), although there has been no evidence in the previous studies that the optimum temperature for photosynthesis occurs at the colimitation point of A_r and A_c.Temperature tolerance differs between species and, with growth temperature, even within species from the same functional group (Long and Woodward, 1989). Bunce (2000) indicated that the temperature dependences of A_r and A_c to growth temperature were different between species from cool and warm climates and that the balance between A_r and A_c was independent of growth temperature for a given plant species. However, it was not clarified what limited the photosynthetic rate or what parameters were important in temperature acclimation of photosynthesis. Recently, we reported that the extent of temperature homeostasis of leaf respiration and photosynthesis, which is assessed as a ratio of rates measured at their respective growth temperatures, differed depending on the extent of the cold tolerance of the species (Yamori et al., 2009b). Therefore, comparisons of several species with different cold tolerances would provide a new insight into interspecific variation of photosynthetic temperature acclimation and their underlying mechanisms. In this study, we selected 11 herbaceous crop species that differ in their cold tolerance (Yamori et al., 2009b) and grew them at two contrasting temperatures, conducting gas-exchange analyses based on the C₃ photosynthesis model (Farquhar et al., 1980). Based on these results, we addressed the following key questions. (1) Does the plasticity in photosynthetic temperature acclimation differ between cold-sensitive and cold-tolerant species? (2) Does the limiting step of photosynthesis at several leaf temperatures differ between plant species and with growth temperature? (3) What determines the optimum temperature for the photosynthetic rate among A_c, A_r, and the intersection of the temperature dependences of A_c and A_r?     

An efficient lipase-catalyzed enantioselective hydrolysis of (R,S)-azolides derived from N-protected proline, pipecolic acid, and nipecotic acid

In the Candida antarctica lipase B-catalyzed hydrolysis of (R,S)-azolides derived from (R,S)-N-protected proline in water-saturated methyl tert-butyl ether (MTBE), high enzyme activity with excellent enantioselectivity (V _S V _R ^?1 ?>?100) for (R,S)-N-Cbz-proline 1,2,4-triazolide (1) and (R,S)-N-Cbz-proline 4-bromopyrazolide (2) was exploited in comparison with their corresponding methyl ester analog (3). Changing of the substrate structure, water content, solvent, and temperature was found to have profound influences on the lipase performance. On the basis of enzyme activity and enantioselectivity and solvent boiling point, the best reaction condition of using 1 as the substrate in water-saturated MTBE at 45 °C was selected and further employed for the successful resolution of (R,S)-N-Cbz-pipecolic 1,2,4-triazolide (5) and (R,S)-N-Boc-nipecotic 1,2,4-triazolide (9). Moreover, more than 89.1 % recovery of remained (R)-1 is obtainable in five cycles of enzyme reusage, when pH 7 phosphate buffers were employed as the extract at 4 °C.     

The Genome Sequence of Herpes Simplex Virus Type 2

The genomic DNA sequence of herpes simplex virus type 2 (HSV-2) strain HG52 was determined as 154,746 bp with a G+C content of 70.4%. A total of 74 genes encoding distinct proteins was identified; three of these were each present in two copies, within major repeat elements of the genome. The HSV-2 gene set corresponds closely with that of HSV-1, and the HSV-2 sequence prompted several local revisions to the published HSV-1 sequence (D. J. McGeoch, M. A. Dalrymple, A. J. Davison, A. Dolan, M. C. Frame, D. McNab, L. J. Perry, J. E. Scott, and P. Taylor, J. Gen. Virol. 69:1531–1574, 1988). No compelling evidence for the existence of any additional protein-coding genes in HSV-2 was identified.The complete 152-kbp genomic DNA sequence of herpes simplex virus type 1 (HSV-1) was published in 1988 (56) and since then has been very widely employed in a great range of research on HSV-1. Additionally, results from this most studied member of the family Herpesviridae have fed powerfully into research on other herpesviruses. In contrast, although a substantial number of individual gene sequences have been determined for the other HSV serotype, HSV-2, the complete genome sequence for this virus has not been available hitherto. In this paper we report the sequence of the genome of HSV-2, strain HG52.At a gross level the 155-kbp genome of HSV-2 is viewed as consisting of two extended regions of unique sequence (U_L and U_S), each of which is bounded by a pair of inverted repeat elements (TR_L-IR_L and IR_S-TR_S) (17, 66) (Fig. ​(Fig.1).1). There is a directly repeated sequence of some 254 bp at the genome termini (the a sequence), with one or more copies in the opposing orientation (the a′ sequence) at the internal joint between IR_L and IR_S (21). U_L plus its flanking repeats is termed the long (L) region, and U_S with its flanking repeats is termed the short (S) region. In individual molecules of HSV-2 DNA, the L and S components may be linked with each in either orientation, so that DNA preparations contain four sequence-orientation isomers, one of which is defined as the prototype (66). The sequences of the terminal and internal copies of R_L and of R_S are considered to be indistinguishable. Open in a separate windowFIG. 1Overall organization of the genome of HSV-2. The linear double-stranded DNA is represented, with the scale at the top. The unique portions of the genome (U_L and U_S) are shown as heavy solid lines, and the major repeat elements (TR_L, IR_L, IR_S, and TR_S) are shown as open boxes. For each pair of repeats the two copies are in opposing orientations. As indicated, TR_L, U_L, and IR_L are regarded as comprising the L region, and IR_S, U_S, and TR_S are regarded as comprising the S region. Plasmid-cloned fragments used for sequence determination are indicated at the bottom: BamHI and HindIII fragments are indicated by B and H, respectively, followed by individual fragment designations in lowercase; KH and HK indicate KpnI/HindIII fragments as described in the text.This paper presents properties of the HSV-2 DNA sequence and our present understanding of its content of protein-coding genes and other elements. We are also interested in comparative analysis of the HSV-1 and HSV-2 genomes to examine processes of molecular evolution which have occurred since the two species diverged, and we intend to pursue this topic in a separate paper.     

A unique immuno-stimulant steroidal sapogenin acid from the roots of Asparagus racemosus

A new steroidal sapogenin molecule 1 having unique characteristics, 21-nor and unusual C19 carboxylic acid has been isolated from the roots of Asparagus racemosus. On the basis of chemical evidence, extensive spectroscopic analysis including two dimensional (2D) NMR and X-ray studies of single crystal, the structure of 1 was determined as (1S,2R,3S,8S,9S,10S,13S,14S,16S,17R,22R,25R)-21-nor-18β,27α-dimethyl-1β,2β,3β-trihydroxy-25-spirost-4-en-19β-oic acid. 1 crystallizes in monoclinic space group P2₁ with a = 9.295(2), b = 11.238(2), c = 11.376(2) Å; β = 91.993(4)°, Z = 2, D_cal = 1.344 Mg/m³. The structure was solved by direct methods and refined by full-matrix least-squares procedure to a final R-value of 0.0561 for 4064 observed reflections. 1 was tested against the type of immune responses generated during treatment in normal and immune-suppressed animals and detailed biological activity evaluation suggests it to be a potent immunostimulator.     

Anaerobic Respiration of Elemental Sulfur and Thiosulfate by Shewanella oneidensis MR-1 Requires psrA,a Homolog of the phsA Gene of Salmonella enterica Serovar Typhimurium LT2

Shewanella oneidensis MR-1, a facultatively anaerobic gammaproteobacterium, respires a variety of anaerobic terminal electron acceptors, including the inorganic sulfur compounds sulfite (SO₃²⁻), thiosulfate (S₂O₃²⁻), tetrathionate (S₄O₆²⁻), and elemental sulfur (S⁰). The molecular mechanism of anaerobic respiration of inorganic sulfur compounds by S. oneidensis, however, is poorly understood. In the present study, we identified a three-gene cluster in the S. oneidensis genome whose translated products displayed 59 to 73% amino acid similarity to the products of phsABC, a gene cluster required for S⁰ and S₂O₃²⁻ respiration by Salmonella enterica serovar Typhimurium LT2. Homologs of phsA (annotated as psrA) were identified in the genomes of Shewanella strains that reduce S⁰ and S₂O₃²⁻ yet were missing from the genomes of Shewanella strains unable to reduce these electron acceptors. A new suicide vector was constructed and used to generate a markerless, in-frame deletion of psrA, the gene encoding the putative thiosulfate reductase. The psrA deletion mutant (PSRA1) retained expression of downstream genes psrB and psrC but was unable to respire S⁰ or S₂O₃²⁻ as the terminal electron acceptor. Based on these results, we postulate that PsrA functions as the main subunit of the S. oneidensis S₂O₃²⁻ terminal reductase whose end products (sulfide [HS⁻] or SO₃²⁻) participate in an intraspecies sulfur cycle that drives S⁰ respiration.Microbial reduction of inorganic sulfur compounds is central to the biogeochemical cycling of sulfur and other elements such as carbon and metals (29). The ability to reduce elemental sulfur (S⁰) is found in members of both prokaryotic domains (20), including mesophilic deltaproteobacteria (Desulfovibrio vulgaris, Pelobacter carbinolicus, Geobacter sulfurreducens) (6, 9, 36, 51), thermophilic deltaproteobacteria (Desulfurella acetivorans) (39), gammaproteobacteria (Shewanella putrefaciens) (41), epsilonproteobacteria (Wolinella succinogenes) (49), cyanobacteria (“Oscillatoria limnetica”) (45), and hyperthermophilic archaea (1, 53). Partially reduced inorganic sulfur compounds such as tetrathionate (S₄O₆²⁻), thiosulfate (S₂O₃²⁻), and sulfite (SO₃²⁻) are also important electron acceptors in the biogeochemical cycling of sulfur (29, 51). S₄O₆²⁻-reducing bacteria, for example, may produce S₂O₃²⁻ as a metabolic end product of S₄O₆²⁻ reduction, while S₂O₃²⁻ disproportionation is a key reaction catalyzed by sulfate-reducing bacteria, resulting in the formation of sulfate (SO₄²⁻) and sulfide (S²⁻) (26).Shewanella oneidensis MR-1, a facultatively anaerobic gammaproteobacterium, respires a variety of compounds as an anaerobic electron acceptor, including the inorganic sulfur compounds S⁰, SO₃²⁻, S₂O₃²⁻, and S₄O₆²⁻; transition metals [e.g., Fe(III) and Mn(IV)]; and radionuclides [e.g., U(VI) and Tc(VII)] (8, 21, 41, 44, 50, 55, 56). The majority of studies of anaerobic respiration by S. oneidensis have focused on the mechanism of electron transport to transition metals and radionuclides (11, 14, 34, 46, 58, 59), while the mechanism of electron transport to inorganic sulfur compounds has not been thoroughly examined.Microbial S⁰ respiration is postulated to occur via two pathways, both of which are based on an intraspecies sulfur cycle. In the first pathway (catalyzed by members of the genus Salmonella [20]), S₂O₃²⁻ is reduced, yielding HS⁻ and SO₃²⁻ (24). SO₃²⁻ diffuses from the cell and reacts chemically with extracellular S⁰ to form S₂O₃²⁻, which reenters the periplasm and is rereduced, thereby sustaining an intraspecies sulfur cycle. In the second pathway (catalyzed by W. succinogenes [24]), water-soluble polysulfides (S_n²⁻; n > 2), formed by chemical interactions of S⁰ at pHs >7 (52), are reduced stepwise in the periplasm to S_{n − 1}²⁻ and HS⁻. Similarly to what occurs with the first pathway, microbially produced HS⁻ diffuses from the cell and reacts chemically with S⁰ to produce additional S_n²⁻, which reenters the periplasm and is rereduced to sustain an analogous intraspecies sulfur cycle (24).Genetic analyses of S₂O₃²⁻ reduction-deficient mutants of Salmonella enterica serovar Typhimurium have demonstrated that phsA (denoting production of hydrogen sulfide) is required for HS⁻ production during S₂O₃²⁻ respiration (10, 17, 22). In addition, phsA-deficient mutants are unable to reduce S⁰ as an electron acceptor (24). The phsA homolog of W. succinogenes (annotated as psrA, for polysulfide reduction) is required for S⁰ respiration (32, 37). W. succinogenes psrA is the first gene of a three-gene cluster (including psrA, psrB, and psrC) whose products encode a polysulfide reductase, a quinol oxidase, and a membrane anchor, respectively (15). In addition, the structure of the polysulfide reductase complex (PsrABC) from Thermus thermophilus has recently been solved, and results indicate that PsrC acts as a quinol oxidase that transfers electrons stepwise via PsrB and PsrA to S_n²⁻ during anaerobic S⁰ respiration (27). The main objectives of the present study were to (i) identify the S. Typhimurium phsA homolog in the S. oneidensis genome, (ii) employ a newly constructed suicide cloning vector for in-frame gene deletion mutagenesis in S. oneidensis to delete the S. Typhimurium phsA homolog of S. oneidensis, and (iii) test the S. oneidensis psrA deletion mutant for respiratory activity on a combination of two electron donors and 11 electron acceptors, including the inorganic sulfur compounds S₄O₆²⁻, S₂O₃²⁻, and S⁰.