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The nutrition of animal consumers is an important regulator of ecological processes due to its effects on their physiology, life-history and behaviour. Understanding the ecological effects of poor nutrition depends on correctly diagnosing the nature and strength of nutritional limitation. Despite the need to assess nutritional limitation, current approaches to delineating nutritional constraints can be non-specific and imprecise. Here, we consider the need and potential to develop new complementary approaches to the study of nutritional constraints on animal consumers by studying and using a suite of established and emerging biochemical and molecular responses. These nutritional indicators include gene expression, transcript regulators, protein profiling and activity, and gross biochemical and elemental composition. The potential applications of nutritional indicators to ecological studies are highlighted to demonstrate the value that this approach would have to future studies in community and ecosystem ecology.
Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests.
Potassium (K+) is inevitable for plant growth and development. It plays a crucial role in the regulation of enzyme activities, in adjusting the electrical membrane potential and the cellular turgor, in regulating cellular homeostasis and in the stabilization of protein synthesis. Uptake of K+ from the soil and its transport to growing organs is essential for a healthy plant development. Uptake and allocation of K+ are performed by K+ channels and transporters belonging to different protein families. In this review we summarize the knowledge on the versatile physiological roles of plant K+ channels and their behavior under stress conditions in the model plant Arabidopsis thaliana.
Antibiotics are chemotherapeutic agents, which have been a very powerful tool in the clinical management of bacterial diseases since the 1940s. However, benefits offered by these magic bullets have been substantially lost in subsequent days following the widespread emergence and dissemination of antibiotic-resistant strains. While it is obvious that excessive and imprudent use of antibiotics significantly contributes to the emergence of resistant strains, antibiotic resistance is also observed in natural bacteria of remote places unlikely to be impacted by human intervention. Both antibiotic biosynthetic genes and resistance-conferring genes have been known to evolve billions of years ago, long before clinical use of antibiotics. Hence it appears that antibiotics and antibiotics resistance determinants have some other roles in nature, which often elude our attention because of overemphasis on the therapeutic importance of antibiotics and the crisis imposed by the antibiotic resistance in pathogens. In the natural milieu, antibiotics are often found to be present in sub-inhibitory concentrations acting as signaling molecules supporting the process of quorum sensing and biofilm formation. They also play an important role in the production of virulence factors and influence host-parasite interactions (e.g., phagocytosis, adherence to the target cell, and so on). The evolutionary and ecological aspects of antibiotics and antibiotic resistance in the naturally occurring microbial community are little understood. Therefore, the actual role of antibiotics in nature warrants in-depth investigations. Studies on such an intriguing behavior of the microorganisms promise insight into the intricacies of the microbial physiology and are likely to provide some lead in controlling the emergence and subsequent dissemination of antibiotic resistance. This article highlights some of the recent findings on the role of antibiotics and the genes that confer resistance to antibiotics in nature.
In this BEEBOOK paper we present a set of established methods for quantifying honey bee behaviour. We start with general methods for preparing bees for behavioural assays. Then we introduce assays for quantifying sensory responsiveness to gustatory, visual and olfactory stimuli. Presentation of more complex behaviours like appetitive and aversive learning under controlled laboratory conditions and learning paradigms under free-flying conditions will allow the reader to investigate a large range of cognitive skills in honey bees. Honey bees are very sensitive to changing temperatures. We therefore present experiments which aim at analysing honey bee locomotion in temperature gradients. The complex flight behaviour of honey bees can be investigated under controlled conditions in the laboratory or with sophisticated technologies like harmonic radar or RFID in the field. These methods will be explained in detail in different sections. Honey bees are model organisms in behavioural biology for their complex yet plastic division of labour. To observe the daily behaviour of individual bees in a colony, classical observation hives are very useful. The setting up and use of typical observation hives will be the focus of another section. The honey bee dance language has important characteristics of a real language and has been the focus of numerous studies. We here discuss the background of the honey bee dance language and describe how it can be studied. Finally, the mating of a honey bee queen with drones is essential to survival of the entire colony. We here give detailed and structured information how the mating behaviour of drones and queens can be observed and experimentally manipulated.
The ultimate goal of this chapter is to provide the reader with a comprehensive set of experimental protocols for detailed studies on all aspects of honey bee behaviour including investigation of pesticide and insecticide effects.
Over the past 15 years, the genetic basis for production of many cyanobacterial bioactive compounds has been described. This knowledge has enabled investigations into the environmental factors that regulate the production of these toxins at the molecular level. Such molecular or systems level studies are also likely to reveal the physiological role of the toxin and contribute to effective water resource management. This review focuses on the environmental regulation of some of the most relevant cyanotoxins, namely the microcystins, nodularin, cylindrospermopsin, saxitoxins, anatoxins and jamaicamides.
Molybdenum enzymes, their maturation and molybdenum cofactor biosynthesis in Escherichia coli
(2013)
Molybdenum cofactor (Moco) biosynthesis is an ancient, ubiquitous, and highly conserved pathway leading to the biochemical activation of molybdenum. Moco is the essential component of a group of redox enzymes, which are diverse in terms of their phylogenetic distribution and their architectures, both at the overall level and in their catalytic geometry. A wide variety of transformations are catalyzed by these enzymes at carbon, sulfur and nitrogen atoms, which include the transfer of an oxo group or two electrons to or from the substrate. More than 50 molybdoenzymes were identified in bacteria to date. In molybdoenzymes Mo is coordinated to a dithiolene group on the 6-alkyl side chain of a pterin called molybdopterin (MPT). The biosynthesis of Moco can be divided into four general steps in bacteria: I) formation of the cyclic pyranopterin monophosphate, 2) formation of MPT, 3) insertion of molybdenum into molybdopterin to form Moco, and 4) additional modification of Moco with the attachment of GMP or CMP to the phosphate group of MPT, forming the dinucleotide variant of Moco. This review will focus on molybdoenzymes, the biosynthesis of Moco, and its incorporation into specific target proteins focusing on Escherichia coli. This article is part of a Special Issue entitled: Metals in Bioenergetics and Biomimetics Systems.
Cyanobacteria produce an unparalleled variety of toxins that can cause severe health problems or even death in humans, and wild or domestic animals. In the last decade, biosynthetic pathways have been assigned to the majority of the known toxin families. This review summarizes current knowledge about the enzymatic basis for the production of the hepatotoxins microcystin and nodularin, the cytotoxin cylindrospermopsin, the neurotoxins anatoxin and saxitoxin, and the dermatotoxin lyngbyatoxin. Elucidation of the biosynthetic pathways of the toxins has paved the way for the development of molecular techniques for the detection and quantification of the producing cyanobacteria in different environments. Phylogenetic analyses of related clusters from a large number of strains has also allowed for the reconstruction of the evolutionary scenarios that have led to the emergence, diversification, and loss of such gene clusters in different strains and genera of cyanobacteria. Advances in the understanding of toxin biosynthesis and evolution have provided new methods for drinking-water quality control and may inspire the development of techniques for the management of bloom formation in the future.
Compared to the well-studied open water of the "growing" season, under-ice conditions in lakes are characterized by low and rather constant temperature, slow water movements, limited light availability, and reduced exchange with the surrounding landscape. These conditions interact with ice-cover duration to shape microbial processes in temperate lakes and ultimately influence the phenology of community and ecosystem processes. We review the current knowledge on microorganisms in seasonally frozen lakes. Specifically, we highlight how under-ice conditions alter lake physics and the ways that this can affect the distribution and metabolism of auto-and heterotrophic microorganisms. We identify functional traits that we hypothesize are important for understanding under-ice dynamics and discuss how these traits influence species interactions. As ice coverage duration has already been seen to reduce as air temperatures have warmed, the dynamics of the under-ice microbiome are important for understanding and predicting the dynamics and functioning of seasonally frozen lakes in the near future.
1. The health of managed and wild honeybee colonies appears to have declined substantially in Europe and the United States over the last decade. Sustainability of honeybee colonies is important not only for honey production, but also for pollination of crops and wild plants alongside other insect pollinators. A combination of causal factors, including parasites, pathogens, land use changes and pesticide usage, are cited as responsible for the increased colony mortality. 2. However, despite detailed knowledge of the behaviour of honeybees and their colonies, there are no suitable tools to explore the resilience mechanisms of this complex system under stress. Empirically testing all combinations of stressors in a systematic fashion is not feasible. We therefore suggest a cross-level systems approach, based on mechanistic modelling, to investigate the impacts of (and interactions between) colony and land management. 3. We review existing honeybee models that are relevant to examining the effects of different stressors on colony growth and survival. Most of these models describe honeybee colony dynamics, foraging behaviour or honeybee - varroa mite - virus interactions. 4. We found that many, but not all, processes within honeybee colonies, epidemiology and foraging are well understood and described in the models, but there is no model that couples in-hive dynamics and pathology with foraging dynamics in realistic landscapes. 5. Synthesis and applications. We describe how a new integrated model could be built to simulate multifactorial impacts on the honeybee colony system, using building blocks from the reviewed models. The development of such a tool would not only highlight empirical research priorities but also provide an important forecasting tool for policy makers and beekeepers, and we list examples of relevant applications to bee disease and landscape management decisions.