570 Biowissenschaften; Biologie
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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.
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.
The relevance for in vitro three-dimensional (3D) tissue culture of skin has been present for almost a century. From using skin biopsies in organ culture, to vascularized organotypic full-thickness reconstructed human skin equivalents, in vitro tissue regeneration of 3D skin has reached a golden era. However, the reconstruction of 3D skin still has room to grow and develop. The need for reproducible methodology, physiological structures and tissue architecture, and perfusable vasculature are only recently becoming a reality, though the addition of more complex structures such as glands and tactile corpuscles require advanced technologies. In this review, we will discuss the current methodology for biofabrication of 3D skin models and highlight the advantages and disadvantages of the existing systems as well as emphasize how new techniques can aid in the production of a truly physiologically relevant skin construct for preclinical innovation.
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.
Can't remember to forget you
(2017)
In nature plants are exposed to frequent changes in their abiotic and biotic environment. While some environmental cues are used to gauge the environment and align growth and development, others are beyond the regularly encountered spectrum of a species and trigger stress responses. Such stressful conditions provide a potential threat to survival and integrity. Plants adapt to extreme environmental conditions through physiological adaptations that are usually transient and are maintained until stressful environments subside. It is increasingly appreciated that in some cases environmental cues activate a stress memory that persists for some time after the extreme condition has subsided. Recent research has shown that this stress-induced environmental memory is mediated by epigenetic and chromatin-based mechanisms and both histone methylation and nucleosome occupancy are associated with it.
For successful growth and development, plants constantly have to gauge their environment. Plants are capable to monitor their current environmental conditions, and they are also able to integrate environmental conditions over time and store the information induced by the cues. In a developmental context, such an environmental memory is used to align developmental transitions with favourable environmental conditions. One temperature-related example of this is the transition to flowering after experiencing winter conditions, that is, vernalization. In the context of adaptation to stress, such an environmental memory is used to improve stress adaptation even when the stress cues are intermittent. A somatic stress memory has now been described for various stresses, including extreme temperatures, drought, and pathogen infection. At the molecular level, such a memory of the environment is often mediated by epigenetic and chromatin modifications. Histone modifications in particular play an important role. In this review, we will discuss and compare different types of temperature memory and the histone modifications, as well as the reader, writer, and eraser proteins involved.
Microplastics (MP) provide a unique and extensive surface for microbial colonization in aquatic ecosystems. The formation of microorganism-microplastic complexes, such as biofilms, maximizes the degradation of organic matter and horizontal gene transfer. In this context, MP affect the structure and function of microbial communities, which in turn render the physical and chemical fate of MP. This new paradigm generates challenges for microbiology, ecology, and ecotoxicology. Dispersal of MP is concomitant with that of their associated microorganisms and their mobile genetic elements, including antibiotic resistance genes, islands of pathogenicity, and diverse metabolic pathways. Functional changes in aquatic microbiomes can alter carbon metabolism and food webs, with unknown consequences on higher organisms or human microbiomes and hence health. Here, we examine a variety of effects of MP pollution from the microbial ecology perspective, whose repercussions on aquatic ecosystems begin to be unraveled. (C) 2018 Elsevier B.V. All rights reserved.
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/).
Terrestrial environmental systems are characterised by numerous feedback links between their different compartments. However, scientific research is organized into disciplines that focus on processes within the respective compartments rather than on interdisciplinary links. Major feedback mechanisms between compartments might therefore have been systematically overlooked so far. Without identifying these gaps, initiatives on future comprehensive environmental monitoring schemes and experimental platforms might fail. We performed a comprehensive overview of feedbacks between compartments currently represented in environmental sciences and explores to what degree missing links have already been acknowledged in the literature. We focused on process models as they can be regarded as repositories of scientific knowledge that compile findings of numerous single studies. In total, 118 simulation models from 23 model types were analysed. Missing processes linking different environmental compartments were identified based on a meta-review of 346 published reviews, model inter-comparison studies, and model descriptions. Eight disciplines of environmental sciences were considered and 396 linking processes were identified and ascribed to the physical, chemical or biological domain. There were significant differences between model types and scientific disciplines regarding implemented interdisciplinary links. The most wide-spread interdisciplinary links were between physical processes in meteorology, hydrology and soil science that drive or set the boundary conditions for other processes (e.g., ecological processes). In contrast, most chemical and biological processes were restricted to links within the same compartment. Integration of multiple environmental compartments and interdisciplinary knowledge was scarce in most model types. There was a strong bias of suggested future research foci and model extensions towards reinforcing existing interdisciplinary knowledge rather than to open up new interdisciplinary pathways. No clear pattern across disciplines exists with respect to suggested future research efforts. There is no evidence that environmental research would clearly converge towards more integrated approaches or towards an overarching environmental systems theory. (c) 2017 Elsevier B.V. All rights reserved.
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.
Employing electric phenomena for the spatial manipulation of bioparticles from whole cells down to dissolved molecules has become a useful tool in biotechnology and analytics. AC electrokinetic effects like dielectrophoresis and AC electroosmosis are increasingly used to concentrate, separate and immobilize DNA and proteins. With the advance of photolithographical micro- and nanofabrication methods, novel or improved bioanalytical applications benefit from concentrating analytes, signal enhancement and locally controlled immobilization by AC electrokinetic effects. In this review of AC electrokinetics of proteins, the respective studies are classified according to their different electrode geometries: individual electrode pairs, interdigitated electrodes, quadrupole electrodes, and 3D configurations of electrode arrays. Known advantages and disadvantages of each layout are discussed.
Ecological communities change in time and space, but long-term dynamics at the century-to-millennia scale are poorly documented due to lack of relevant data sets. Nevertheless, understanding long-term dynamics is important for explaining present-day biodiversity patterns and placing conservation goals in a historical context. Here, we use recent examples and new perspectives to highlight how environmental DNA (eDNA) is starting to provide a powerful new source of temporal data for research questions that have so far been overlooked, by helping to resolve the ecological dynamics of populations, communities, and ecosystems over hundreds to thousands of years. We give examples of hypotheses that may be addressed by temporal eDNA biodiversity data, discuss possible research directions, and outline related challenges.
Several meta-analyses have been published summarizing the associations of the Mediterranean diet (MedDiet) with chronic diseases. We evaluated the quality and credibility of evidence from these meta-analyses as well as characterized the different indices used to define MedDiet and re-calculated the associations with the different indices identified. We conducted an umbrella review of meta-analyses on cohort studies evaluating the association of the MedDiet with type 2 diabetes, cardiovascular disease, cancer and cognitive-related diseases. We used the AMSTAR (A MeaSurement Tool to Assess systematic Reviews) checklist to evaluate the methodological quality of the meta-analyses, and the NutriGrade scoring system to evaluate the credibility of evidence. We also identified different indices used to define MedDiet; tests for subgroup differences were performed to compare the associations with the different indices when at least 2 studies were available for different definitions. Fourteen publications were identified and within them 27 meta-analyses which were based on 70 primary studies. Almost all meta-analyses reported inverse associations between MedDiet and risk of chronic disease, but the credibility of evidence was rated low to moderate. Moreover, substantial heterogeneity was observed on the use of the indices assessing adherence to the MedDiet, but two indices were the most used ones [Trichopoulou MedDiet (tMedDiet) and alternative MedDiet (aMedDiet)]. Overall, we observed little difference in risk associations comparing different MedDiet indices in the subgroup meta-analyses. Future prospective cohort studies are advised to use more homogenous definitions of the MedDiet to improve the comparability across meta-analyses.
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.
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.
Single molecule RNA fluorescent in situ hybridization (smFISH) enables gene transcription to be assessed at the cellular level. In this point of view article, we describe our recent smFISH research in the model plant Arabidopsis thaliana and discuss how this technique could further knowledge of plant gene transcription in the future.
The pathophysiological influence of gene-lifestyle interactions on the risk to develop type 2 diabetes (T2D) is currently under intensive research. This systematic review summarizes the evidence for gene-lifestyle interactions regarding T2D incidence. MEDLINE, EMBASE, and Web of Science were systematically searched until 31 January 2019 to identify publication with (a) prospective study design; (b) T2D incidence; (c) gene-diet, gene-physical activity, and gene-weight loss intervention interaction; and (d) population who are healthy or prediabetic. Of 66 eligible publications, 28 reported significant interactions. A variety of different genetic variants and dietary factors were studied. Variants at TCF7L2 were most frequently investigated and showed interactions with fiber and whole grain on T2D incidence. Further gene-diet interactions were reported for, eg, a western dietary pattern with a T2D-GRS, fat and carbohydrate with IRS1 rs2943641, and heme iron with variants of HFE. Physical activity showed interaction with HNF1B, IRS1, PPAR gamma, ADRA2B, SLC2A2, and ABCC8 variants and weight loss interventions with ENPP1, PPAR gamma, ADIPOR2, ADRA2B, TNF alpha, and LIPC variants. However, most findings represent single study findings obtained in European ethnicities. Although some interactions have been reported, their conclusiveness is still low, as most findings were not yet replicated across multiple study populations.
The ability of an organism to change its phenotype in response to different environments, termed plasticity, is a particularly important characteristic to enable sessile plants to adapt to rapid changes in their surroundings. Plasticity is a quantitative trait that can provide a fitness advantage and mitigate negative effects due to environmental perturbations. Yet, its genetic basis is not fully understood. Alongside technological limitations, the main challenge in studying plasticity has been the selection of suitable approaches for quantification of phenotypic plasticity. Here, we propose a categorization of the existing quantitative measures of phenotypic plasticity into nominal and relative approaches. Moreover, we highlight the recent advances in the understanding of the genetic architecture underlying phenotypic plasticity in plants. We identify four pillars for future research to uncover the genetic basis of phenotypic plasticity, with emphasis on development of computational approaches and theories. These developments will allow us to perform specific experiments to validate the causal genes for plasticity and to discover their role in plant fitness and evolution.
The short- and long-term thrombogenicity of implant materials is still unpredictable, which is a significant challenge for the treatment of cardiovascular diseases. A knowledge-based approach for implementing biofunctions in materials requires a detailed understanding of the medical device in the biological system. In particular, the interplay between material and blood components/cells as well as standardized and commonly acknowledged in vitro test methods allowing a reproducible categorization of the material thrombogenicity requires further attention. Here, the status of in vitro thrombogenicity testing methods for biomaterials is reviewed, particularly taking in view the preparation of test materials and references, the selection and characterization of donors and blood samples, the prerequisites for reproducible approaches and applied test systems. Recent joint approaches in finding common standards for a reproducible testing are summarized and perspectives for a more disease oriented in vitro thrombogenicity testing are discussed.
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.