Evolutionary processes driving spatial patterns of intraspecific genetic diversity in river ecosystems

Describing, understanding and predicting the spatial distribution of genetic diversity is a central issue in biological sciences. In river landscapes, it is generally predicted that neutral genetic diversity should increase downstream, but there have been few attempts to test and validate this assumption across taxonomic groups. Moreover, it is still unclear what are the evolutionary processes that may generate this apparent spatial pattern of diversity. Here, we quantitatively synthesized published results from diverse taxa living in river ecosystems, and we performed a meta‐analysis to show that a downstream increase in intraspecific genetic diversity (DIGD) actually constitutes a general spatial pattern of biodiversity that is repeatable across taxa. We further demonstrated that DIGD was stronger for strictly waterborne dispersing than for overland dispersing species. However, for a restricted data set focusing on fishes, there was no evidence that DIGD was related to particular species traits. We then searched for general processes underlying DIGD by simulating genetic data in dendritic‐like river systems. Simulations revealed that the three processes we considered (downstream‐biased dispersal, increase in habitat availability downstream and upstream‐directed colonization) might generate DIGD. Using random forest models, we identified from simulations a set of highly informative summary statistics allowing discriminating among the processes causing DIGD. Finally, combining these discriminant statistics and approximate Bayesian computations on a set of twelve empirical case studies, we hypothesized that DIGD were most likely due to the interaction of two of these three processes and that contrary to expectation, they were not solely caused by downstream‐biased dispersal.     

Canopy height variation and environmental heterogeneity in the tropical dry forests of coastal Oaxaca,Mexico

Despite its importance for carbon storage and other ecosystem functions, the variation in vegetation canopy height is not yet well understood. We examined the relationship between this community attribute and environmental heterogeneity in a tropical dry forest of southern Mexico. We sampled vegetation in 15 sites along a 100‐km coastal stretch of Oaxaca State, and measured the heights of all woody plants (excluding lianas). The majority of the ca. 4000 individuals recorded concentrated in the 4–8 m height range. We defined three plant sets to describe overall community canopy height at each site: a set including all plants, a set made up by the tallest plants representing 10 percent of all individuals, and a set comprising the 10 tallest plants. For each site we computed maximum height and the mean and median heights of the three sets. Significant collinearity was observed between the seven resulting height variables, but null distributions constructed through bootstrap revealed their different behaviors as functions of species richness and density of individuals. Through linear modeling and a model selection procedure, we identified 21 models that best described the variation in canopy height variables. These models pointed out to soil (measured as PC1 of a principal component analysis performed on 10 soil variables), water stress, and elevation as the main drivers of canopy height variation in the region. In the event of increasing water stress resulting from global climate change, the studied tropical dry forests could become shorter and thus decrease their carbon storage potential.     

Who Is the King? The α‐Hydroxy‐β‐oxo‐α,β‐enone Moiety or the Catechol B Ring: Relationship between the Structure of Quercetin Derivatives and Their Pro‐Oxidative Abilities

Quercetin and other flavonoids have been reported to exhibit both antioxidant and pro‐oxidant properties. Most studies about the pro‐oxidative ability were conducted in the presence of metal ions, and the essential functional moiety of quercetin responsible for the pro‐oxidative effect is still unclear. In this study, we evaluated the pro‐oxidative abilities in the absence of metal ions of two quercetin derivatives, i.e., quercetin‐3′‐O‐β‐D ‐glucoside ( 1 ) and quercetin‐3‐O‐β‐D ‐glucoside ( 2 ), by assessing DNA cleavage and HO^.‐radical production. The binding mode between these compounds and DNA was studied by fluorescence and viscometric titrations. The results showed that 1 can efficiently induce oxidative damage to plasmid DNA, while 2 shows poor activity. Both 1 and 2 bind to DNA via groove‐binding. These results proved that the α‐hydroxy‐β‐oxo‐α,β‐enone moiety contributes to the pro‐oxidative activity of quercetin.     

Methane emissions reduce the radiative cooling effect of a subtropical estuarine mangrove wetland by half

The role of coastal mangrove wetlands in sequestering atmospheric carbon dioxide (CO₂) and mitigating climate change has received increasing attention in recent years. While recent studies have shown that methane (CH₄) emissions can potentially offset the carbon burial rates in low‐salinity coastal wetlands, there is hitherto a paucity of direct and year‐round measurements of ecosystem‐scale CH₄ flux (F_CH4) from mangrove ecosystems. In this study, we examined the temporal variations and biophysical drivers of ecosystem‐scale F_CH4 in a subtropical estuarine mangrove wetland based on 3 years of eddy covariance measurements. Our results showed that daily mangrove F_CH4 reached a peak of over 0.1 g CH₄‐C m^?2 day^?1 during the summertime owing to a combination of high temperature and low salinity, while the wintertime F_CH4 was negligible. In this mangrove, the mean annual CH₄ emission was 11.7 ± 0.4 g CH₄‐C m^–2 year^?1 while the annual net ecosystem CO₂ exchange ranged between ?891 and ?690 g CO₂‐C m^?2 year^?1, indicating a net cooling effect on climate over decadal to centurial timescales. Meanwhile, we showed that mangrove F_CH4 could offset the negative radiative forcing caused by CO₂ uptake by 52% and 24% over a time horizon of 20 and 100 years, respectively, based on the corresponding sustained‐flux global warming potentials. Moreover, we found that 87% and 69% of the total variance of daily F_CH4 could be explained by the random forest machine learning algorithm and traditional linear regression model, respectively, with soil temperature and salinity being the most dominant controls. This study was the first of its kind to characterize ecosystem‐scale F_CH4 in a mangrove wetland with long‐term eddy covariance measurements. Our findings implied that future environmental changes such as climate warming and increasing river discharge might increase CH₄ emissions and hence reduce the net radiative cooling effect of estuarine mangrove forests.     

Pressurized Pepsin Digestion in Proteomics: AN AUTOMATABLE ALTERNATIVE TO TRYPSIN FOR INTEGRATED TOP-DOWN BOTTOM-UP PROTEOMICS*

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome.In-depth characterization and quantitation of protein isoforms, including post-translationally modified proteins, are challenging goals of contemporary proteomics. Traditionally, top-down (1, 2) and bottom-up (3, 4) proteomics have been two distinct analytical paths for liquid-based proteomics analysis. Top-down proteomics is the mass spectrometry (MS)-based characterization of intact proteins, whereas bottom-up proteomics requires a chemical or enzymatic proteolytic digestion of all proteins into peptides prior to MS analysis. Both strategies have their own strengths and challenges and can be thought of as complementary rather than competing analytical techniques.In a top-down proteomics approach, proteins are usually separated by one- or two-dimensional liquid chromatography (LC) and identified using high performance MS (5, 6). This approach is very attractive because it allows the identification of protein isoforms arising from various amino acid modifications, genetic variants (e.g. single nucleotide polymorphisms), mRNA splice variants, and multisite modifications (7) (e.g. specific histone modifications) as well as characterization of proteolytic processing events. However, there are several challenges that have limited the broad application of the approach. Typically, intact proteins are less soluble than their peptide complement, which effectively results in greater losses during various stages of sample handling (i.e. limited sensitivity). Similarly, proteins above ∼40–50 kDa in size are more difficult to ionize, detect, and dissociate in most high throughput MS work flows. Additionally, major challenges associated with MS data interpretation and sensitivity, especially for higher molecular mass proteins (>100 kDa) and highly hydrophobic proteins (e.g. integral membrane proteins), remain largely unsolved, thus limiting the applicability of top-down proteomics on a large scale.Bottom-up proteomics approaches have broad application because peptides are easier to separate and analyze via LC coupled with tandem mass spectrometry (MS/MS), offering a basis for more comprehensive protein identification. As this method relies on protein digestion (which produces multiple peptides for each protein), the sample complexity can become exceedingly large, requiring several dimensions of chromatographic separations (e.g. strong cation exchange and/or high pH reversed phase) prior to the final LC separation (typically reversed phase (RP)¹ C₁₈), which is oftentimes directly coupled with the mass spectrometer (3, 8). In general, the bottom-up analysis rarely achieves 100% sequence coverage of the original proteins, which can result in an incorrect/incomplete assessment of protein isoforms and combinatorial PTMs. Additionally, the digested peptides are not detected with uniform efficiency, which challenges and distorts protein quantification efforts.Because the data obtained from top-down and bottom-up work flows are complementary, several attempts have been made to integrate the two strategies (9, 10). Typically, these efforts have utilized extensive fractionation of the intact protein separation followed by bottom-up analysis of the collected fractions. Results so far have encouraged us to consider on-line digestion methods for integrating top-down and bottom-up proteomics in a higher throughput fashion. Such an on-line digestion approach would not only benefit in terms of higher sample throughput and improved overall sensitivity but would also allow a better correlation between the observed intact protein and its peptide digestion products, greatly aiding data analysis and protein characterization efforts.So far, however, none of the on-line integrated methods have proven robust enough for routine high throughput analyses. One of the reasons for this limited success relates to the choice of the proteolytic enzyme used for the bottom-up segment. Trypsin is by far the most widely used enzyme for proteome analyses because it is affordable (relative to other proteases), it has been well characterized for proteome research, and it offers a nice array of detectable peptides due to a fairly even distribution of lysines and arginines across most proteins. However, protein/peptide RPLC separations (optimal at low pH) are fundamentally incompatible with on-line trypsin digestion (optimal at pH ∼ 8) (11, 12). Therefore, on-line coupling of trypsin digestion and RPLC separations is fraught with technological challenges, and proposed solutions (12) have not proven to be robust enough for integration into demanding high throughput platforms.Our approach to this challenge was to investigate alternative proteases that may be more compatible with automated on-line digestion, peptide separation, and MS detection. Pepsin, which is acid-compatible (i.e. it acts in the stomach to initially aid in the digestion of food) (13), is a particularly promising candidate. This protease has previously been successfully used for the targeted analyses of protein complexes, hydrogen/deuterium exchange experiments (14, 15), and characterization of biopharmaceuticals (16, 17). Generally, pepsin preferentially cleaves the peptide bond located on the N-terminal side of hydrophobic amino acids, such as leucine and phenylalanine, although with less specificity than the preferential cleavage observed for trypsin at arginine and lysine. The compatibility of pepsin with typical LC-MS operation makes it an ideal choice for the development of novel approaches combining protein digestion, protein/peptide separation, and MS-based protein/peptide identification.To develop an automated system capable of simultaneously capturing top-down and bottom-up data, enzyme kinetics of the chosen protease must be extremely fast (because one cannot wait hours as is typical when performing off-line proteolysis). Another requirement is the use of immobilized enzyme or a low enough concentration of the enzyme such that autolysis products do not obscure the detection of substrate peptides. The latter was a concern when using pepsin because prior hydrogen/deuterium exchange experiments used enzyme:substrate ratios up to 1:2 (18, 19). To test whether or not such a large concentration of pepsin was necessary, we performed pepsin digestion at ratios of 1:20. Many alternative energy inputs into the system were considered for speeding up the digestion. For instance, it has been shown that an input of ultrasonic energy could accelerate the reaction rate of a typical trypsin digestion while using small amounts of a protease (20). Because ultrasonic energy results in an increase of temperature and microenvironments of high pressure, it has been hypothesized that the higher temperature was the component responsible for the enhanced enzyme activity (21). López-Ferrer et al. (22, 23), however, have demonstrated that application of higher pressure with incorporation of a Barocycler alone can make trypsin display faster enzyme kinetics. This phenomenon can easily be integrated with an LC separation (which already operates at elevated pressure) to enable an automatable ultrarapid on-line digestion LC-MS proteomics platform. Herein, we refer to this platform as the fast on-line digestion system (FOLDS) (23). Although FOLDS has been described before using trypsin, here the system is characterized with pepsin, and the results obtained are compared with results attainable with trypsin. Like trypsin, pepsin produced efficient protein digestion in just a few minutes when placed under pressure. Because of the natural maximal activity of pepsin at low pH, the FOLDS can be incorporated with a RePlay (Advion Biosciences, Ithaca, NY) system, and this powerful combination is what ultimately makes the integration of top-down and bottom-up proteomics analyses possible. The integrated analysis begins with a chromatographic separation of intact proteins. The separated proteins are then split into two streams. One stream proceeds directly to the mass spectrometer for MS and/or tandem MS analysis. The second stream is split into a long capillary where the chromatographic separation of the proteins is maintained, but their arrival to the mass spectrometer for detection is delayed. This is in essence the concept of RePlay (24, 25). Herein, we have taken the RePlay a step further by implementing our FOLDS technology into the second split delayed stream of proteins. While these delayed proteins travel down the long and narrow capillary, we exposed them to pepsin where, in combination with the pressure, the proteins are quickly and reproducibly digested. These peptide fragments are subsequently subjected to MS and/or tandem MS analysis. The FOLDS RePlay system allows the rapid and robust incorporation of the integrated top-down bottom-up proteomics work flow with the ability to not only identify proteins but also to sequence multisite/combinatorial PTMs because all detected peptides (from the FOLDS analysis) are confined to the original chromatographic peak of the protein they were derived from. The analysis of protein mixtures using this integrated strategy reduces the total amount of samples required to obtain both the top-down and bottom-up data, increases throughput, and improves protein sequence coverage.     

incR: a new R package to analyse incubation behaviour

Incubation represents a life stage of crucial importance for the optimal development of avian embryos. For most birds, incubation poses a trade‐off between investing in self‐maintenance and offspring care. Furthermore, incubation is affected by environmental temperatures and, therefore, will be likely impacted by climate change. Despite its relevance and readily available temperature logging methods, avian incubation research is hindered by recognised limitations in available software. In this paper, a new quantitative approach to analyse incubation behaviour is presented. This new approach is embedded in a free R package, incR. The flexibility of the R environment eases the analysis, validation and visualisation of incubation temperature data. The core algorithm in incR is validated here and it is shown that the method extracts accurate metrics of incubation behaviour (e.g. number and duration of incubation bouts). This paper also presents a suggested workflow along with detailed R code to aid the practical implementation of incR.     

Multispecies coexistence of trees in tropical forests: spatial signals of topographic niche differentiation increase with environmental heterogeneity

Neutral and niche theories give contrasting explanations for the maintenance of tropical tree species diversity. Both have some empirical support, but methods to disentangle their effects have not yet been developed. We applied a statistical measure of spatial structure to data from 14 large tropical forest plots to test a prediction of niche theory that is incompatible with neutral theory: that species in heterogeneous environments should separate out in space according to their niche preferences. We chose plots across a range of topographic heterogeneity, and tested whether pairwise spatial associations among species were more variable in more heterogeneous sites. We found strong support for this prediction, based on a strong positive relationship between variance in the spatial structure of species pairs and topographic heterogeneity across sites. We interpret this pattern as evidence of pervasive niche differentiation, which increases in importance with increasing environmental heterogeneity.     

Assessing facilitative responses to a nurse shrub at the community level: the example of Potentilla fruticosa in a sub‐alpine grassland of northwest China

Biotic interaction studies have revealed a large discrepancy among experiments in target responses to the effects of neighbours, which may in part be due to both high species‐specificity of plant responses and low number of target species used in experiments. Our aim was to assess facilitative responses at the community level and the role of both functional groups and ecological attributes of target species. In a sub‐alpine grassland on the eastern Tibet plateau, we assessed growth responses of all species in the community to removal of a dominant shrub. We also measured changes in the main environmental variables. Species responses were analysed by functional group and in relation to their mean regional altitudinal distribution. All significant interactions were positive and affected one‐third of the total species richness of the community. All functional groups were facilitated but forbs were less strongly facilitated than in the two other groups. High‐alpine species were less strongly facilitated than low‐sub‐alpine species, but the strength of this relationship was weaker than that reported in previous work. There was evidence of a decrease in extreme temperatures below the canopy of the shrub but no variations in soil moisture. We conclude that the highly stressful conditions induced by the dry continental climate of the eastern Tibet plateau are a main driver of the exclusive dominance of positive interactions. Assessing interactive responses at the community level is likely to provide a useful tool to better understand the role of biotic interactions in community responses to environmental changes.