A multidisciplinary approach to understanding the recent and historical occurrence of the freshwater plant, Littorella uniflora

1. The vulnerability of softwater, oligotrophic lakes to eutrophication has caused the disappearance of many, if not most, of the unique isoetid plant communities. We tested whether the presence or disappearance of the isoetid Littorella uniflora (L.) could be predicted from environmental parameters, soil types and land use in the catchment area, and atmospheric nitrogen deposition. 2. We found that the topographic catchment area of a lake was an irrelevant unit to study effects of soil type and land use. Instead, using a GIS‐generated buffer zone around the lakes it proved feasible to classify 472 lakes into historical (if L. uniflora had disappeared) or recent (if L. uniflora was still present) Littorella lakes, based on soil type and land use. Our analysis showed that aeolian sand deposits and heath in the buffer zone favoured the presence of L. uniflora, whereas moraine clay and agriculture were strongly linked to the disappearance of L. uniflora. 3. However, in order to understand fully the presence or disappearance of L. uniflora, environmental data were needed in addition to soil types, land use and nitrogen deposition, and the use of discriminant analysis allowed us to classify 96% of the investigated lakes correctly into recent or historical sites. Alkalinity, total phosphorus, total nitrogen, aeolian sand deposits and heath were the most important parameters explaining the presence or disappearance of L. uniflora. Our analysis also indicated that eutrophication, rather than acidification, has likely caused the disappearance of L. uniflora from 218 of the 472 lakes investigated. 4. Our findings have widespread implications for the conservation or restoration of isoetid habitats and we recommend applying a wide buffer zone around lakes, with restrictions on farming and traditional forestry activities. In addition, our buffering concept may prove a useful tool for aquatic ecologists to investigate relationships between catchment features and organisms (plants, insects and amphibians) with aquatic as well as terrestrial life forms.     

Assessment of unanticipated unintended effects of genetically modified plants on non‐target organisms: a controversy worthy of pursuit?

A typical risk hypothesis addressed during the environmental risk assessment (ERA) of genetically modified (GM) plants for cultivation is that the novel traits intentionally introduced into GM plants do not adversely affect non‐target organisms (NTOs). However, genetic modification may potentially also lead to unintended changes in the GM plant which could raise safety concerns. Therefore, the European Food Safety Authority (EFSA) advocates the characterization of ecological interactions between the GM plant and representative NTOs as part of the ERA of GM plants for cultivation in the European Union. Yet, this requirement is not unanimously accepted by stakeholders. Here, we present EFSA's approach to assess potential adverse effects on NTOs and summarize some of the stakeholders' views, mostly opposing EFSA's position on scientific grounds.     

Molecular dynamics simulations of apo,holo, and inactivator bound GABA‐at reveal the role of active site residues in PLP dependent enzymes

The pyridoxal 5‐phosphate (PLP) cofactor is a significant organic molecule in medicinal chemistry. It is often found covalently bound to lysine residues in proteins to form PLP dependent enzymes. An example of this family of PLP dependent enzymes is γ‐aminobutyric acid aminotransferase (GABA‐AT) which is responsible for the degradation of the neurotransmitter GABA. Its inhibition or inactivation can be used to prevent the reduction of GABA concentration in brain which is the source of several neurological disorders. As a test case for PLP dependent enzymes, we have performed molecular dynamics simulations of GABA‐AT to reveal the roles of the protein residues and its cofactor. Three different states have been considered: the apoenzyme, the holoenzyme, and the inactive state obtained after the suicide inhibition by vigabatrin. Different protonation states have also been considered for PLP and two key active site residues: Asp298 and His190. Together, 24 independent molecular dynamics trajectories have been simulated for a cumulative total of 2.88 µs. Our results indicate that, unlike in aqueous solution, the PLP pyridine moiety is protonated in GABA‐AT. This is a consequence of a pK_a shift triggered by a strong charge–charge interaction with an ionic “diad” formed by Asp298 and His190 that would help the activation of the first half‐reaction of the catalytic mechanism in GABA‐AT: the conversion of PLP to free pyridoxamine phosphate (PMP). In addition, our MD simulations exhibit additional strong hydrogen bond networks between the protein and PLP: the phosphate group is held in place by the donation of at least three hydrogen bonds while the carbonyl oxygen of the pyridine ring interacts with Gln301; Phe181 forms a π–π stacking interaction with the pyridine ring and works as a gate keeper with the assistance of Val300. All these interactions are hypothesized to help maintain free PMP in place inside the protein active site to facilitate the second half‐reaction in GABA‐AT: the regeneration of PLP‐bound GABA‐AT (i.e., the holoenzyme). Proteins 2016; 84:875–891. © 2016 Wiley Periodicals, Inc.     

Statistical analysis of structural determinants for protein–DNA‐binding specificity

DNA‐binding proteins play critical roles in biological processes including gene expression, DNA packaging and DNA repair. They bind to DNA target sequences with different degrees of binding specificity, ranging from highly specific (HS) to nonspecific (NS). Alterations of DNA‐binding specificity, due to either genetic variation or somatic mutations, can lead to various diseases. In this study, a comparative analysis of protein–DNA complex structures was carried out to investigate the structural features that contribute to binding specificity. Protein–DNA complexes were grouped into three general classes based on degrees of binding specificity: HS, multispecific (MS), and NS. Our results show a clear trend of structural features among the three classes, including amino acid binding propensities, simple and complex hydrogen bonds, major/minor groove and base contacts, and DNA shape. We found that aspartate is enriched in HS DNA binding proteins and predominately binds to a cytosine through a single hydrogen bond or two consecutive cytosines through bidentate hydrogen bonds. Aromatic residues, histidine and tyrosine, are highly enriched in the HS and MS groups and may contribute to specific binding through different mechanisms. To further investigate the role of protein flexibility in specific protein–DNA recognition, we analyzed the conformational changes between the bound and unbound states of DNA‐binding proteins and structural variations. The results indicate that HS and MS DNA‐binding domains have larger conformational changes upon DNA‐binding and larger degree of flexibility in both bound and unbound states. Proteins 2016; 84:1147–1161. © 2016 Wiley Periodicals, Inc.     

Effect of methylation on the side‐chain pKa value of arginine

Arginine methylation is important in biological systems. Recent studies link the deregulation of protein arginine methyltransferases with certain cancers. To assess the impact of methylation on interaction with other biomolecules, the pK_a values of methylated arginine variants were determined using NMR data. The pK_a values of monomethylated, symmetrically dimethylated, and asymmetrically dimethylated arginine are similar to the unmodified arginine (14.2 ± 0.4). Although the pK_a value has not been significantly affected by methylation, consequences of methylation include changes in charge distribution and steric effects, suggesting alternative mechanisms for recognition.     

Recent changes in mountain grasslands: a vegetation resampling study

Understanding how land‐use changes affect different facets of plant biodiversity in seminatural European grasslands is of particular importance for biodiversity conservation. As conclusions of previous experimental or synchronic observational studies did not converge toward a general agreement, assessing the recent trends in vegetation change in various grassland systems using a diachronic approach is needed. In this resurvey study, we investigated the recent changes in grassland vegetation of the French Jura Mountains, a region with a long tradition of pastoralism. We compared the floristic composition of 150 grassland plots recorded between 1990 and 2000 with new relevés made in 2012 on the same plots. We considered taxonomic, phylogenetic and functional diversity as well as ecological characteristics of the plant communities derived from ecological indicator values and life strategies of the species. PCA of the floristic composition revealed a significant general trend linked to the sampling year. Wilcoxon paired tests showed that contemporary communities were generally more dominated by grass species and presented a higher tolerance to defoliation, a higher pastoral value, and a higher nutrient indicator value. Comparisons revealed a decrease in phylogenetic and functional diversity. By contrast, local species richness has slightly increased. The intensity of change in species composition, measured by Hellinger distance between pairs of relevés, was dependent on neither the time lag between the two surveys, the author of the first relevé nor its location or elevation. The most important changes were observed in grasslands that previously presented low pastoral value, low grass cover, low tolerance to defoliation, and high proportion of stress‐tolerant species. This trend was likely linked to the intensification of grassland management reported in the region, with a parallel increase in mowing frequency, grazing pressure, and fertilization level. More restrictive specifications should be applied to agricultural practices to avoid overexploitation of mountain species‐rich grasslands and its negative consequences on their biodiversity and resilience.     

Snowbeds are more affected than other subalpine–alpine plant communities by climate change in the Swiss Alps

While the upward shift of plant species has been observed on many alpine and nival summits, the reaction of the subalpine and lower alpine plant communities to the current warming and lower snow precipitation has been little investigated so far. To this aim, 63 old, exhaustive plant inventories, distributed along a subalpine–alpine elevation gradient of the Swiss Alps and covering different plant community types (acidic and calcareous grasslands; windy ridges; snowbeds), were revisited after 25–50 years. Old and recent inventories were compared in terms of species diversity with Simpson diversity and Bray–Curtis dissimilarity indices, and in terms of community composition with principal component analysis. Changes in ecological conditions were inferred from the ecological indicator values. The alpha‐diversity increased in every plant community, likely because of the arrival of new species. As observed on mountain summits, the new species led to a homogenization of community compositions. The grasslands were quite stable in terms of species composition, whatever the bedrock type. Indeed, the newly arrived species were part of the typical species pool of the colonized community. In contrast, snowbed communities showed pronounced vegetation changes and a clear shift toward dryer conditions and shorter snow cover, evidenced by their colonization by species from surrounding grasslands. Longer growing seasons allow alpine grassland species, which are taller and hence more competitive, to colonize the snowbeds. This study showed that subalpine–alpine plant communities reacted differently to the ongoing climate changes. Lower snow/rain ratio and longer growing seasons seem to have a higher impact than warming, at least on plant communities dependent on long snow cover. Consequently, they are the most vulnerable to climate change and their persistence in the near future is seriously threatened. Subalpine and alpine grasslands are more stable, and, until now, they do not seem to be affected by a warmer climate.     

Function and conformation analyses of an aspartate substitution of the invariant glycine in the integrin βI domain α1-α1′ helix

We showed that the αLβ2 integrin with the non-functional mutation G150D cannot be induced with Mg/EGTA to express the mAb KIM127 epitope, which reports the leg-extended conformation. We extended the study to the αIIbβ3, an integrin without an αI domain. The equivalent mutation, i.e. G161D, also resulted in an expressible, but non-adhesive αIIbβ3 integrin. An NMR study of synthetic peptides spanning the α1-α1′ helix of the β3 I domain shows that both wild-type and mutant peptides are α-helical. However, whereas in the wild-type peptide this helix is continuous, the mutant presents a discontinuity, or kink, precisely at the site of mutation G161D. Our results suggest that the mutation may lock integrin heterodimers in a bent conformation that prevents integrin activation via conformational extension.     

High interannual variation in the diet of a tropical forest frugivore (Hylobates lar)

Frugivores must deal with seasonal changes in fruit availability and changes from year to year, as most species of tropical forest fruiting trees have considerable interannual variation in phenology and many are mast fruiters. We quantified seasonal and interannual changes in the fruit diet in a frugivore and important seed disperser, the white‐handed gibbon, Hylobates lar, in Thailand. We used 40‐d following data during April and May replicated in six consecutive years to study interannual variability in the diet and compared it with seasonal changes measured in monthly samples of the same size collected in three successive years. The 40‐d periods of following also allowed us to measure the decline in dietary similarity with time over a finer scale. We measured fruit diet similarity between replicated 5‐d periods using the percentage overlap (Renkonen's) index and Jaccard's similarity index. Seasonally, average dietary overlap between adjacent months was low, and similarity approached zero after four months. Average rate of decline in similarity exceeded 20 percent per 5‐d period. Variation in fruit species in the diet between years was high and was correlated with interannual variation in fruiting phenology. The strongest correlation occurred in the case of Nephelium melliferum, a highly preferred species that dominated the diet in good fruiting years. It is difficult to separate changes in food species preference from changes in availability from year to year. We devised a relative measure of preference that depends on the degree to which the gibbons rely on prior knowledge to find sources.     

Advances in the computational and molecular understanding of the prostate cancer cell nucleus

Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that may not be visually perceptible to a pathologist, to the nucleus and its ultrastructural components can precede visual histopathological recognition of cancer. Alterations to nuclear features, such as nuclear size and shape, texture, and spatial architecture, reflect the complex molecular‐level changes that occur during oncogenesis. Quantitative nuclear morphometry, a field that uses computational approaches to identify and quantify malignancy‐induced nuclear changes, can enable a detailed and objective analysis of the PCa cell nucleus. Recent advances in machine learning–based approaches can now automatically mine data related to these changes to aid in the diagnosis, decision making, and prediction of PCa prognoses. In this review, we use PCa as a case study to connect the molecular‐level mechanisms that underlie these nuclear changes to the machine learning computational approaches, bridging the gap between the clinical and computational understanding of PCa. First, we will discuss recent developments to our understanding of the molecular events that drive nuclear alterations in the context of PCa: the role of the nuclear matrix and lamina in size and shape changes, the role of 3‐dimensional chromatin organization and epigenetic modifications in textural changes, and the role of the tumor microenvironment in altering nuclear spatial topology. We will then discuss the advances in the applications of machine learning algorithms to automatically segment nuclei in prostate histopathological images, extract nuclear features to aid in diagnostic decision making, and predict potential outcomes, such as biochemical recurrence and survival. Finally, we will discuss the challenges and opportunities associated with translation of the quantitative nuclear morphometry methodology into the clinical space. Ultimately, accurate identification and quantification of nuclear alterations can contribute to the field of nucleomics and has applications for computationally driven precision oncologic patient care.