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Starch is a complex carbohydrate polymer produced by plants and especially by crops in huge amounts. It consists of amylose and amylopectin, which have alpha-1,4-and alpha-1,6-linked glucose units. Despite this simple chemistry, the entire starch metabolism is complex, containing various (iso)enzymes/proteins. However, whose interplay is still not yet fully understood. Starch is essential for humans and animals as a source of nutrition and energy. Nowadays, starch is also commonly used in non-food industrial sectors for a variety of purposes. However, native starches do not always satisfy the needs of a wide range of (industrial) applications. This review summarizes the structural properties of starch, analytical methods for starch characterization, and in planta starch modifications.
Physically interacting proteins form macromolecule complexes that drive diverse cellular processes. Advances in experimental techniques that capture interactions between proteins provide us with protein-protein interaction (PPI) networks from several model organisms. These datasets have enabled the prediction and other computational analyses of protein complexes. Here we provide a systematic review of the state-of-the-art algorithms for protein complex prediction from PPI networks proposed in the past two decades. The existing approaches that solve this problem are categorized into three groups, including: cluster-quality-based, node affinity-based, and network embedding-based approaches, and we compare and contrast the advantages and disadvantages. We further include a comparative analysis by computing the performance of eighteen methods based on twelve well-established performance measures on four widely used benchmark protein-protein interaction networks. Finally, the limitations and drawbacks of both, current data and approaches, along with the potential solutions in this field are discussed, with emphasis on the points that pave the way for future research efforts in this field. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
Electrochemical methods offer the simple characterization of the synthesis of molecularly imprinted polymers (MIPs) and the readouts of target binding. The binding of electroinactive analytes can be detected indirectly by their modulating effect on the diffusional permeability of a redox marker through thin MIP films. However, this process generates an overall signal, which may include nonspecific interactions with the nonimprinted surface and adsorption at the electrode surface in addition to (specific) binding to the cavities. Redox-active low-molecular-weight targets and metalloproteins enable a more specific direct quantification of their binding to MIPs by measuring the faradaic current. The in situ characterization of enzymes, MIP-based mimics of redox enzymes or enzyme-labeled targets, is based on the indication of an electroactive product. This approach allows the determination of both the activity of the bio(mimetic) catalyst and of the substrate concentration.
The biosynthesis of the molybdenum cofactor (Moco) is highly conserved among all kingdoms of life. In all molybdoenzymes containing Moco, the molybdenum atom is coordinated to a dithiolene group present in the pterin-based 6-alkyl side chain of molybdopterin (MPT). In general, the biosynthesis of Moco can be divided into four steps in in bacteria: (i) the starting point is the formation of the cyclic pyranopterin monophosphate (cPMP) from 5 '-GTP, (ii) in the second step the two sulfur atoms are inserted into cPMP leading to the formation of MPT, (iii) in the third step the molybdenum atom is inserted into MPT to form Moco and (iv) in the fourth step bis-Mo-MPT is formed and an additional modification of Moco is possible with the attachment of a nucleotide (CMP or GMP) to the phosphate group of MPT, forming the dinucleotide variants of Moco. This review presents an update on the well-characterized Moco biosynthesis in the model organism Escherichia coli including novel discoveries from the recent years.
Plans are currently being drafted for the next decade of action on biodiversity-both the post-2020 Global Biodiversity Framework of the Convention on Biological Diversity (CBD) and Biodiversity Strategy of the European Union (EU). Freshwater biodiversity is disproportionately threatened and underprioritized relative to the marine and terrestrial biota, despite supporting a richness of species and ecosystems with their own intrinsic value and providing multiple essential ecosystem services. Future policies and strategies must have a greater focus on the unique ecology of freshwater life and its multiple threats, and now is a critical time to reflect on how this may be achieved. We identify priority topics including environmental flows, water quality, invasive species, integrated water resources management, strategic conservation planning, and emerging technologies for freshwater ecosystem monitoring. We synthesize these topics with decades of first-hand experience and recent literature into 14 special recommendations for global freshwater biodiversity conservation based on the successes and setbacks of European policy, management, and research. Applying and following these recommendations will inform and enhance the ability of global and European post-2020 biodiversity agreements to halt and reverse the rapid global decline of freshwater biodiversity.
Bacterial molybdoenzymes are key enzymes involved in the global sulphur, nitrogen and carbon cycles. These enzymes require the insertion of the molybdenum cofactor (Moco) into their active sites and are able to catalyse a large range of redox-reactions. Escherichia coli harbours nineteen different molybdoenzymes that require a tight regulation of their synthesis according to substrate availability, oxygen availability and the cellular concentration of molybdenum and iron. The synthesis and assembly of active molybdoenzymes are regulated at the level of transcription of the structural genes and of translation in addition to the genes involved in Moco biosynthesis. The action of global transcriptional regulators like FNR, NarXL/QP, Fur and ArcA and their roles on the expression of these genes is described in detail. In this review we focus on what is known about the molybdenum- and iron-dependent regulation of molybdoenzyme and Moco biosynthesis genes in the model organism E. coli. The gene regulation in E. coli is compared to two other well studied model organisms Rhodobacter capsulatus and Shewanella oneidensis.
Electrochemical synthesis and signal generation dominate among the almost 1200 articles published annually on protein-imprinted polymers. Such polymers can be easily prepared directly on the electrode surface, and the polymer thickness can be precisely adjusted to the size of the target to enable its free exchange. In this architecture, the molecularly imprinted polymer (MIP) layer represents only one ‘separation plate’; thus, the selectivity does not reach the values of ‘bulk’ measurements. The binding of target proteins can be detected straightforwardly by their modulating effect on the diffusional permeability of a redox marker through the thin MIP films. However, this generates an ‘overall apparent’ signal, which may include nonspecific interactions in the polymer layer and at the electrode surface. Certain targets, such as enzymes or redox active proteins, enables a more specific direct quantification of their binding to MIPs by in situ determination of the enzyme activity or direct electron transfer, respectively.
Inducible defences against predation are widespread in the natural world, allowing prey to economise on the costs of defence when predation risk varies over time or is spatially structured. Through interspecific interactions, inducible defences have major impacts on ecological dynamics, particularly predator-prey stability and phase lag. Researchers have developed multiple distinct approaches, each reflecting assumptions appropriate for particular ecological communities. Yet, the impact of inducible defences on ecological dynamics can be highly sensitive to the modelling approach used, making the choice of model a critical decision that affects interpretation of the dynamical consequences of inducible defences. Here, we review three existing approaches to modelling inducible defences: Switching Function, Fitness Gradient and Optimal Trait. We assess when and how the dynamical outcomes of these approaches differ from each other, from classic predator-prey dynamics and from commonly observed eco-evolutionary dynamics with evolving, but non-inducible, prey defences. We point out that the Switching Function models tend to stabilise population dynamics, and the Fitness Gradient models should be carefully used, as the difference with evolutionary dynamics is important. We discuss advantages of each approach for applications to ecological systems with particular features, with the goal of providing guidelines for future researchers to build on.
Ecological effects of alien species can be dramatic, but management and prevention of negative impacts are often hindered by crypticity of the species or their ecological functions. Ecological functions can change dramatically over time, or manifest after long periods of an innocuous presence. Such cryptic processes may lead to an underestimation of long-term impacts and constrain management effectiveness. Here, we present a conceptual framework of crypticity in biological invasions. We identify the underlying mechanisms, provide evidence of their importance, and illustrate this phenomenon with case studies. This framework has potential to improve the recognition of the full risks and impacts of invasive species.
There is an increasing need for an assessment of the impacts of land use and land use change (LUCC). In this context, simulation models are valuable tools for investigating the impacts of stakeholder actions or policy decisions. Agricultural landscape generators (ALGs), which systematically and automatically generate realistic but simplified representations of land cover in agricultural landscapes, can provide the input for LUCC models. We reviewed existing ALGs in terms of their objectives, design and scope. We found eight ALGs that met our definition. They were based either on generic mathematical algorithms (pattern-based) or on representations of ecological or land use processes (process-based). Most ALGs integrate only a few landscape metrics, which limits the design of the landscape pattern and thus the range of applications. For example, only a few specific farming systems have been implemented. We conclude that existing ALGs contain useful approaches that can be used for specific purposes, but ideally generic modular ALGs are developed that can be used for a wide range of scenarios, regions and model types. We have compiled features of such generic ALGs and propose a possible software architecture. Considerable joint efforts are required to develop such generic ALGs, but the benefits in terms of a better understanding and development of more efficient agricultural policies would be high.
Winter is an important season for many limnological processes, which can range from biogeochemical transformations to ecological interactions. Interest in the structure and function of lake ecosystems under ice is on the rise. Although limnologists working at polar latitudes have a long history of winter work, the required knowledge to successfully sample under winter conditions is not widely available and relatively few limnologists receive formal training. In particular, the deployment and operation of equipment in below 0 degrees C temperatures pose considerable logistical and methodological challenges, as do the safety risks of sampling during the ice-covered period. Here, we consolidate information on winter lake sampling and describe effective methods to measure physical, chemical, and biological variables in and under ice. We describe variation in snow and ice conditions and discuss implications for sampling logistics and safety. We outline commonly encountered methodological challenges and make recommendations for best practices to maximize safety and efficiency when sampling through ice or deploying instruments in ice-covered lakes. Application of such practices over a broad range of ice-covered lakes will contribute to a better understanding of the factors that regulate lakes during winter and how winter conditions affect the subsequent ice-free period.
Fungi in aquatic ecosystems
(2019)
Fungi are phylogenetically and functionally diverse ubiquitous components of almost all ecosystems on Earth, including aquatic environments stretching from high montane lakes down to the deep ocean. Aquatic ecosystems, however, remain frequently overlooked as fungal habitats, although fungi potentially hold important roles for organic matter cycling and food web dynamics. Recent methodological improvements have facilitated a greater appreciation of the importance of fungi in many aquatic systems, yet a conceptual framework is still missing. In this Review, we conceptualize the spatiotemporal dimensions, diversity, functions and organismic interactions of fungi in structuring aquatic food webs. We focus on currently unexplored fungal diversity, highlighting poorly understood ecosystems, including emerging artificial aquatic habitats.
The primary function of leaves is to provide an interface between plants and their environment for gas exchange, light exposure and thermoregulation. Leaves have, therefore a central contribution to plant fitness by allowing an efficient absorption of sunlight energy through photosynthesis to ensure an optimal growth. Their final geometry will result from a balance between the need to maximize energy uptake while minimizing the damage caused by environmental stresses. This intimate relationship between leaf and its surroundings has led to an enormous diversification in leaf forms. Leaf shape varies between species, populations, individuals or even within identical genotypes when those are subjected to different environmental conditions. For instance, the extent of leaf margin dissection has, for long, been found to inversely correlate with the mean annual temperature, such that Paleobotanists have used models based on leaf shape to predict the paleoclimate from fossil flora. Leaf growth is not only dependent on temperature but is also regulated by many other environmental factors such as light quality and intensity or ambient humidity. This raises the question of how the different signals can be integrated at the molecular level and converted into clear developmental decisions. Several recent studies have started to shed the light on the molecular mechanisms that connect the environmental sensing with organ-growth and patterning. In this review, we discuss the current knowledge on the influence of different environmental signals on leaf size and shape, their integration as well as their importance for plant adaptation.
Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.
Children’s motor competence is known to have a determinant role in learning and engaging later in complex motor skills and, thus, in physical activity. The development of adequate motor competence is a central aim of physical education, and assuring that pupils are learning and developing motor competence depends on accurate assessment protocols. The MOBAK 1 test battery is a recent instrument developed to assess motor competence in primary physical education. This study used the MOBAK 1 to explore motor competence levels and gender differences among 249 (Mage = 6.3, SD = 0.5 years; 127 girls and 122 boys) Grade 1 primary school Portuguese children. On independent sample t tests, boys presented higher object movement motor competence than girls (boys: M = 5.8, SD = 1.7; girls: M = 4.0, SD = 1.7; p < .001), while girls were more proficient among self-movement skills (girls: M = 5.1, SD = 1.8; boys: M = 4.3, SD = 1.7; p < .01). On “total motor competence,” boys (M = 10.3, SD = 2.6) averaged one point ahead of girls (M = 9.1, SD = 2.9). The percentage of girls in the first quartile of object movement was 18.9%, while, for “self movement,” the percentage of boys in the first quartile was almost double that of girls (30.3% and 17.3%, respectively). The confirmatory model to test for construct validity confirmed the assumed theoretical two-factor structure of MOBAK 1 test items in this Portuguese sample. These results support the MOBAK 1 instrument for assessing motor competence and highlighted gender differences, of relevance to intervention efforts.
Plant roots control uptake of water and nutrients and cope with environmental challenges. The root epidermis provides the first selective interface for nutrient absorption, while the endodermis produces the main apoplastic diffusion barrier in the form of a structure called the Casparian strip. The positioning of root hairs on epidermal cells, and of the Casparian strip around endodermal cells, requires asymmetries along cellular axes (cell polarity). Cell polarity is termed planar polarity, when coordinated within the plane of a given tissue layer. Here, we review recent molecular advances towards understanding both the polar positioning of the proteo-lipid membrane domain instructing root hair initiation, and the cytoskeletal, trafficking and polar tethering requirements of proteins at outer or inner plasma membrane domains. Finally, we highlight progress towards understanding mechanisms of Casparian strip formation and underlying endodermal cell polarity.
A challenge for eco-evolutionary research is to better understand the effect of climate and landscape changes on species and their distribution. Populations of species can respond to changes in their environment through local genetic adaptation or plasticity, dispersal, or local extinction. The individual-based modeling (IBM) approach has been repeatedly applied to assess organismic responses to environmental changes. IBMs simulate emerging adaptive behaviors from the basic entities upon which both ecological and evolutionary mechanisms act. The objective of this review is to summarize the state of the art of eco-evolutionary IBMs and to explore to what degree they already address the key responses of organisms to environmental change. In this, we identify promising approaches and potential knowledge gaps in the implementation of eco-evolutionary mechanisms to motivate future research. Using mainly the ISI Web of Science, we reveal that most of the progress in eco-evolutionary IBMs in the last decades was achieved for genetic adaptation to novel local environmental conditions. There is, however, not a single eco-evolutionary IBM addressing the three potential adaptive responses simultaneously. Additionally, IBMs implementing adaptive phenotypic plasticity are rare. Most commonly, plasticity was implemented as random noise or reaction norms. Our review further identifies a current lack of models where plasticity is an evolving trait. Future eco-evolutionary models should consider dispersal and plasticity as evolving traits with their associated costs and benefits. Such an integrated approach could help to identify conditions promoting population persistence depending on the life history strategy of organisms and the environment they experience.
Flowers represent a key innovation during plant evolution. Driven by reproductive optimization, evolution of flower morphology has been central in boosting species diversification. In most cases, this has happened through specialized interactions with animal pollinators and subsequent reduction of gene flow between specialized morphs. While radiation has led to an enormous variability in flower forms and sizes, recurrent evolutionary patterns can be observed. Here, we discuss the targets of selection involved in major trends of pollinator-driven flower evolution. We review recent findings on their adaptive values, developmental grounds and genetic bases, in an attempt to better understand the repeated nature of pollinator-driven flower evolution. This analysis highlights how structural innovation can provide flexibility in phenotypic evolution, adaptation and speciation. (C) 2017 Elsevier Ltd. All rights reserved.
Numerical knowledge, including number concepts and arithmetic procedures, seems to be a clear-cut case for abstract symbol manipulation. Yet, evidence from perceptual and motor behaviour reveals that natural number knowledge and simple arithmetic also remain closely associated with modal experiences. Following a review of behavioural, animal and neuroscience studies of number processing, we propose a revised understanding of psychological number concepts as grounded in physical constraints, embodied in experience and situated through task-specific intentions. The idea that number concepts occupy a range of positions on the continuum between abstract and modal conceptual knowledge also accounts for systematic heuristics and biases in mental arithmetic, thus inviting psycho-logical approaches to the study of the mathematical mind.
Cardiogenesis is a complex developmental process involving multiple overlapping stages of cell fate specification, proliferation, differentiation, and morphogenesis. Precise spatiotemporal coordination between the different cardiogenic processes is ensured by intercellular signalling crosstalk and tissue-tissue interactions. Notch is an intercellular signalling pathway crucial for cell fate decisions during multicellular organismal development and is aptly positioned to coordinate the complex signalling crosstalk required for progressive cell lineage restriction during cardiogenesis. In this Review, we describe the role of Notch signalling and the crosstalk with other signalling pathways during the differentiation and patterning of the different cardiac tissues and in cardiac valve and ventricular chamber development. We examine how perturbation of Notch signalling activity is linked to congenital heart diseases affecting the neonate and adult, and discuss studies that shed light on the role of Notch signalling in heart regeneration and repair after injury.