Leptin in farm animals: where are we and where can we go?

Fat affects meat quality, value and production efficiency as well as providing energy reserves for pregnancy and lactation in farm livestock. Leptin, the adipocyte product of the obese (ob) gene, was quickly seen as a predictor of body fat content in animals approaching slaughter and an aid to assessing reproductive readiness in females. Its participation in inflammation and immune responses that help animals survive infection and trauma has clear additional relevance to meat and milk production. Furthermore, almost a decade of discoveries of nucleotide polymorphisms in the leptin and leptin receptor genes has suggested useful applications relating to feed intake regulation, the efficiency of feed use, the composition of growth, the timing of puberty, mammogenesis and mammary gland function and fertility in cattle, pigs and poultry. The current review attempts to summarise where research has taken us in each of these aspects and speculates on where future research might lead.     

Prediction and prevention of schizophrenia: what has been achieved and where to go next?

In modern medicine, vigorous efforts are being made in the prediction and prevention of diseases. Mental disorders are suitable candidates for the application of this program. The currently known neurobiological and psychosocial risk indicators for schizophrenia do not have a predictive power sufficient for selective prevention in asymptomatic patients at risk. However, once predictive basic and later pre-psychotic high risk symptoms of psychosis develop into the five-year initial prodrome, the impending outbreak of the disease can be predicted with high accuracy. Research findings suggest a differential strategy of indicated prevention with cognitive behavioral therapy in early initial prodromal states and low dosage atypical antipsychotics in late initial prodromal states. The most important future tasks are the improvement of the predictive power by risk enrichment and stratification, as well as the confirmation of the existing and the development of new prevention strategies, with a stronger focus on the etiology of the disorder. In addition, the prediction and prevention approach would benefit from the inclusion of risk symptoms in the DSM-5 criteria.     

Genetic research in osteoporosis: Where are we? Where should we go next?

Fractures resulting from low bone mass and excessive skeletal fragility (osteoporosis) are common worldwide both in males and females, particularly in later years of life. Both fractures, and the most important predictor of fractures, bone mass, are now known to be strongly heritable. This fact, plus the current growth in genetic science, has led to a surge of genetic research in osteoporosis, mostly in the search for genes and their polymorphisms that are responsible for variation in bone mass. Finding the genetic basis underlying variation in bone mass will lead us to deeper understanding of the biology of bone mass accumulation, maintenance and adaptation to load. This, plus finding the genetic basis for overall variation in fracture risk per se, will facilitate the development of interventions, both pharmaceutical and non-pharmaceutical, to prevent and/or treat osteoporosis successfully. This research has produced a rather large number of gene loci that seem to influence bone mass. The challenge now is to refine the statistical genetics and the phenotypes involved so that we can confidently identify those gene loci that truly influence bone mass, and to find ways to study the genetic basis for the most direct disease outcome of interest, fracture.     

Utilizing proteomics to understand and define hypertension: where are we and where do we go?

Introduction: Hypertension is a complex and multifactorial cardiovascular disorder. With different mechanisms contributing to a different extent to an individual’s blood pressure, the discovery of novel pathogenetic principles of hypertension is challenging. However, there is an urgent and unmet clinical need to improve prevention, detection, and therapy of hypertension in order to reduce the global burden associated with hypertension-related cardiovascular diseases.

Areas covered: Proteomic techniques have been applied in reductionist experimental models including angiotensin II infusion models in rodents and the spontaneously hypertensive rat in order to unravel mechanisms involved in blood pressure control and end organ damage. In humans proteomic studies mainly focus on prediction and detection of organ damage, particularly of heart failure and renal disease. While there are only few proteomic studies specifically addressing human primary hypertension, there are more data available in hypertensive disorders in pregnancy, such as preeclampsia. We will review these studies and discuss implications of proteomics on precision medicine approaches.

Expert commentary: Despite the potential of proteomic studies in hypertension there has been moderate progress in this area of research. Standardized large-scale studies are required in order to make best use of the potential that proteomics offers in hypertension and other cardiovascular diseases.     

Shift-work research: Where do we stand,where should we go?

Sleep and Biological Rhythms - Shift-work seriously affects the health and well-being of millions of people worldwide, and the number of shift workers is constantly rising (currently approximately...     

The restoration of biodiversity: where has research been and where does it need to go?

The practice of ecological restoration is a primary option for increasing levels of biodiversity by modifying human-altered ecosystems. The scientific discipline of restoration ecology provides conceptual guidance and tests of restoration strategies, with the ultimate goal of predictive landscape restoration. I construct a conceptual model for restoration of biodiversity, based on site-level (e.g., biotic and abiotic) conditions, landscape (e.g, interpatch connectivity and patch geometry), and historical factors (e.g., species arrival order and land-use legacies). I then ask how well restoration ecology has addressed the various components of this model. During the past decade, restoration research has focused largely on how the restoration of site-level factors promotes species diversity-primarily of plants. Relatively little attention has been paid to how landscape or historical factors interplay with restoration, how restoration influences functional and genetic components of biodiversity, or how a suite of less-studied taxa might be restored. I suggest that the high level of variation seen in restoration outcomes might be explained, at least in part, by the contingencies placed on site-level restoration by landscape and historical factors and then present a number of avenues for future research to address these often ignored linkages in the biodiversity restoration model. Such work will require carefully conducted restoration experiments set across multiple sites and many years. It is my hope that by considering how space and time influence restoration, we might move restoration ecology in a direction of stronger prediction, conducted across landscapes, thus providing feasible restoration strategies that work at scales over which biodiversity conservation occurs.     

Advancing global change biology through experimental manipulations: Where have we been and where might we go?

This commentary summarizes the publication history of Global Change Biology for works on experimental manipulations over the past 25 years and highlights a number of key publications. The retrospective summary is then followed by some thoughts on the future of experimental work as it relates to mechanistic understanding and methodological needs. Experiments for elevated CO₂ atmospheres and anticipated warming scenarios which take us beyond historical analogs are suggested as future priorities. Disturbance is also highlighted as a key agent of global change. Because experiments are demanding of both personnel effort and limited fiscal resources, the allocation of experimental investments across Earth's biomes should be done in ecosystems of key importance. Uncertainty analysis and broad community consultation should be used to identify research questions and target biomes that will yield substantial gains in predictive confidence and societal relevance. A full range of methodological approaches covering small to large spatial scales will continue to be justified as a source of mechanistic understanding. Nevertheless, experiments operating at larger spatial scales encompassing organismal, edaphic, and environmental diversity of target ecosystems are favored, as they allow for the assessment of long‐term biogeochemical feedbacks enabling a full range of questions to be addressed. Such studies must also include adequate investment in measurements of key interacting variables (e.g., water and nutrient availability and budgets) to enable mechanistic understanding of responses and to interpret context dependency. Integration of ecosystem‐scale manipulations with focused process‐based manipulations, networks, and large‐scale observations will aid more complete understanding of ecosystem responses, context dependence, and the extrapolation of results. From the outset, these studies must be informed by and integrated with ecosystem models that provide quantitative predictions from their embedded mechanistic hypotheses. A true two‐way interaction between experiments and models will simultaneously increase the rate and robustness of Global Change research.     

Joint analysis of demography and selection in population genetics: where do we stand and where could we go?

Teasing apart the effects of selection and demography on genetic polymorphism remains one of the major challenges in the analysis of population genomic data. The traditional approach has been to assume that demography would leave a genome-wide signature, whereas the effect of selection would be local. In the light of recent genomic surveys of sequence polymorphism, several authors have argued that this approach is questionable based on the evidence of the pervasive role of positive selection and that new approaches are needed. In the first part of this review, we give a few empirical and theoretical examples illustrating the difficulty in teasing apart the effects of selection and demography on genomic polymorphism patterns. In the second part, we review recent efforts to detect recent positive selection. Most available methods still rely on an a priori classification of sites in the genome but there are many promising new approaches. These new methods make use of the latest developments in statistics, explore aspects of the data that had been neglected hitherto or take advantage of the emerging population genomic data. A current and promising approach is based on first estimating demographic and genetic parameters, using, e.g., a likelihood or approximate Bayesian computation framework, focusing on extreme outlier regions, and then using an independent method to confirm these. Finally, especially for species where evidence of natural selection has been limited, more experimental and versatile approaches that contrast populations under varied environmental constraints might be more successful compared with species-wide genome scans in search of specific signatures.     

Marine biodiversity and ecosystem functioning: what's known and what's next?

Marine ecosystems are experiencing rapid and pervasive changes in biodiversity and species composition. Understanding the ecosystem consequences of these changes is critical to effectively managing these systems. Over the last several years, numerous experimental manipulations of species richness have been performed, yet existing quantitative syntheses have focused on a just a subset of processes measured in experiments and, as such, have not summarized the full data available from marine systems. Here, we present the results of a meta‐analysis of 110 marine experiments from 42 studies that manipulated the species richness of organisms across a range of taxa and trophic levels and analysed the consequences for various ecosystem processes (categorised as production, consumption or biogeochemical fluxes). Our results show that, generally, mixtures of species tend to enhance levels of ecosystem function relative to the average component species in monoculture, but have no effect or a negative effect on functioning relative to the ‘highest‐ performing’ species. These results are largely consistent with those from other syntheses, and extend conclusions to ecological functions that are commonly measured in the marine realm (e.g. nutrient release from sediment bioturbation). For experiments that manipulated three or more levels of richness, we attempted to discern the functional form of the biodiversity–ecosystem functioning relationship. We found that, for response variables related to consumption, a power‐function best described the relationship, which is also consistent with previous findings. However, we identified a linear relationship between richness and production. Combined, our results suggest that changes in the number of species will, on average, tend to alter the functioning of marine ecosystems. We outline several research frontiers that will allow us to more fully understand how, why, and when diversity may drive the functioning of marine ecosystems. Synthesis The oceans host an incredible number and variety of species. However, human activities are driving rapid changes in the marine environment. It is imperative we understand ecosystem consequences of any associated loss of species. We summarized data from 110 experiments that manipulated species diversity and evaluated resulting changes to a range of ecosystem responses. We show that losing species, on average, decreases productivity, growth, and a myriad of other processes related to how marine organisms capture and utilize resources. Finally, we suggest that the loss of species may have stronger consequences for some processes than others.     

NMR-based plant metabolomics: where do we stand, where do we go?

NMR-based metabolomics is an important tool for studying biological systems and has been applied in various organisms, including animals, plants and microbes. NMR is able to provide a 'holistic view' of the metabolites under certain conditions, and thus is advantageous for metabolomic studies. To maximize the use of the information obtained, it is also important to create a platform to measure, store and share data. Public databases for storing and sharing information are still lacking for NMR-based metabolomic analysis in plants. Such databases are urgently needed to make metabolic profiling a real omics technology. In addition, to understand metabolic processes in depth, single-cell analysis and the turnover of metabolites in pathways (fluxomics) should be measured.     

No Nogo: now where to go?

Nogo-A, a reticulon protein expressed by oligodendrocytes, contributes to the axonal growth inhibitory action of central myelin in growth cone collapse and neurite outgrowth in vitro assays, and antibody and inhibitor studies have implicated a role for Nogo in regeneration in the adult CNS in vivo. Three independent labs have now produced Nogo knockout mice with, quite unexpectedly, three different regeneration phenotypes.