Native drivers of fish life history traits are lost during the invasion process

Rapid adaptation to global change can counter vulnerability of species to population declines and extinction. Theoretically, under such circumstances both genetic variation and phenotypic plasticity can maintain population fitness, but empirical support for this is currently limited. Here, we aim to characterize the role of environmental and genetic diversity, and their prior evolutionary history (via haplogroup profiles) in shaping patterns of life history traits during biological invasion. Data were derived from both genetic and life history traits including a morphological analysis of 29 native and invasive populations of topmouth gudgeon Pseudorasbora parva coupled with climatic variables from each location. General additive models were constructed to explain distribution of somatic growth rate (SGR) data across native and invasive ranges, with model selection performed using Akaike's information criteria. Genetic and environmental drivers that structured the life history of populations in their native range were less influential in their invasive populations. For some vertebrates at least, fitness‐related trait shifts do not seem to be dependent on the level of genetic diversity or haplogroup makeup of the initial introduced propagule, nor of the availability of local environmental conditions being similar to those experienced in their native range. As long as local conditions are not beyond the species physiological threshold, its local establishment and invasive potential are likely to be determined by local drivers, such as density‐dependent effects linked to resource availability or to local biotic resistance.     

Variability of qualitative and quantitative secondary metabolites traits among wild genetic resources of Lavandula stoechas L.

Lavandula stoechas L. (Lamiaceae) is an attractive shrub native to the Mediterranean regions used for ornamental, melliferous, aromatic and medicinal purposes. Furthermore, this species presents an increasing interest in cosmetics, perfumery and pharmaceutical industries. The variability of qualitative and quantitative metabolic traits among nine wild germplasms representing the distribution area of this species in Tunisia was undertaken. A total of 45 essential oil components were identified in the aerial parts of the studied germplasms. The main essential oil components were camphor (15.32–50.63%), fenchone (6.57–34.70%), 1,8-cineole (0.05–13.45%) and γ-gurjunene (1.10–12.15%). In addition to the well known chemotypes camphor/fenchone and camphor/1.8-cineole, a new chemotype camphor/γ-gurjunene was detected in Tunisian L. stoechas L. Six phenolic acids (quinic acid, gallic acid, p-coumaric acid, 4,5-di-O-caffeoyquinic acid, salviolinic acid and trans cinnamic acid) and five flavonoids (luteolin-7-o-glucoside, naringin, apegenin-7-o-glucoside, quercetin and kampherol) were identified in the ethanolic extracts. Salviolinic acid (46.30–615.18 μg/g) and luteolin-7-o-glucoside (5.98–38.54 μg/g) were the most abundant phenolic compounds. A high significant phytochemical variability (p ˂ 0.01) in the accumulation of volatile and phenolic secondary metabolites among the studied germplasms was recorded. The conducted multivariate (PCA) and clustering (HCA) analyses revealed different classification pattern for essential oil and phenolic compounds. The detected phytochemical polymorphism among the investigated lavender ecotypes didn't show accordance with bioclimatic and geographical areas which suggests genetic background as the main explaining factor. The detected secondary metabolites polymorphism valorises Tunisian L. stoechas L. genetic resources as valuable plant material in further breeding programs. Moreover, an urgent in situ and ex situ conservation measures are required for these wild germplasms threatened by human over-harvesting practices and the occurring dramatic changes in climatic conditions.     

Metabolic syndrome during gestation and lactation: An important renal problem in dams. selenium renal clearance

BackgroundMetabolic syndrome (MS) in lactating dams leads to several cardiometabolic changes related to selenium (Se) status and selenoproteins expression which produce hypertension. However, little is known about the state of these dams’ kidney functions and their Se deposits.MethodsTwo experimental groups of dam rats were used: control (Se: 0.1 ppm) and MS (Fructose 65 % and Se: 0.1 ppm). At the end of lactation (21d postpartum) kidney weight and protein content, Se deposits, and the activity of the antioxidant selenoprotein glutathione peroxidase (GPx) were measured in dams. Kidney functional parameters: albuminuria, creatinine clearance, serum aldosterone and uric acid levels and water and electrolyte (Na⁺ and K⁺) balance were also evaluated. Systolic blood pressure (SBP) was measured.ResultsIn MS dams at the end of lactation Se deposits and GPx activity are higher in the kidney; however, lipid renal peroxidation appears, relative Se clearance increases, and the dams have lost Se by urine. MS dams have polyuria and polydipsia, high uric acid serum levels, albuminuria and high creatinine clearance, implying glomerular renal malfunction with protein loss. They also present hypernatremia, hypokalemia and hyperaldosteronemia, leading to high SBP; however, a natriuretic process is taking place.ConclusionSince these alterations appear, at least in part, to be related to oxidative stress in renal cells, Se supplementation could be beneficial to avoiding greater lipid renal oxidation during lactation.     

A comprehensive landscape genomics approach for seed sourcing strategies in landscapes under varying degrees of habitat disturbance

As most ecosystems around the world are threatened by anthropogenic degradation and climate change, there is an increasing urgency to implement restoration strategies aiming at ensuring ecosystem self‐sustainability and resilience. An initial step towards that goal relies on selecting the most suitable seed sources for a successful revegetation, which can be extremely challenging in highly degraded landscapes. The most common seed sourcing strategy is to select local seeds because it is assumed that plants experience strong adaptations to their natal sites. An alternative strategy is the selection of climate‐adapted genotypes to future conditions. While considering future climatic projections is important to account for spatial shifts in climate to inform assisted gene flow and translocations, to restore highly degraded landscapes we need a comprehensive approach that first accounts for species adaptations to current at‐site environmental conditions. In this issue of Molecular Ecology Resources, Carvalho et al. present a novel landscape genomics framework to identify the most appropriate seed sourcing strategy for moderately and highly degraded sites by integrating genotype, phenotype and environmental data in a spatially explicit context for two native plant species with potential to help restore iron‐rich Amazonian savannas. This framework is amenable to be applicable and adapted to a broad range of restoration initiatives, as the dichotomy between focusing on the current or future climatic conditions should depend on the goals and environmental circumstances of each restoration site.     

A guide to metabolic flux analysis in metabolic engineering: Methods,tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, “Metabolic fluxes and metabolic engineering” (Metabolic Engineering, 1: 1–11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.     

Active and machine learning-based approaches to rapidly enhance microbial chemical production

In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism)—requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity in Escherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.     

Preferred step frequency during downhill running may be determined by muscle activity

It is well established that metabolic cost is minimized at an individual’s running preferred step frequency (PSF). It has been proposed that the metabolic minimum at PSF is due to a tradeoff between mechanical factors, however, this ignores muscle activity, the primary consumer of energy. Thus, we hypothesized that during downhill running, total muscle activity would be greater with deviations from PSF. Specifically, we predicted that slow step frequencies would have greater stance activity while fast step frequencies would have greater swing activity. We collected metabolic cost and leg muscle activity data while 10 healthy young adults ran at 3.0 m/s for 5 min at level and downhill at PSF and ±15% PSF. In support of our hypothesis, there was a significant main effect for step frequency for both metabolic cost and total muscle activity. In addition, there was greater muscle activity in the stance phase during the slower step frequency while muscle activity was greater in the swing phase during the fast step frequency. This suggests that PSF is partially determined by the tradeoff between the greater cost of muscle activity in the swing phase and lower cost in the stance phase with faster step frequency.     

Characterization of two geraniol synthases from Valeriana officinalis and Lippia dulcis: Similar activity but difference in subcellular localization

Two geraniol synthases (GES), from Valeriana officinalis (VoGES) and Lippia dulcis (LdGES), were isolated and were shown to have geraniol biosynthetic activity with K_m values of 32 µM and 51 µM for GPP, respectively, upon expression in Escherichia coli. The in planta enzymatic activity and sub-cellular localization of VoGES and LdGES were characterized in stable transformed tobacco and using transient expression in Nicotiana benthamiana. Transgenic tobacco expressing VoGES or LdGES accumulate geraniol, oxidized geraniol compounds like geranial, geranic acid and hexose conjugates of these compounds to similar levels. Geraniol emission of leaves was lower than that of flowers, which could be related to higher levels of competing geraniol-conjugating activities in leaves. GFP-fusions of the two GES proteins show that VoGES resides (as expected) predominantly in the plastids, while LdGES import into to the plastid is clearly impaired compared to that of VoGES, resulting in both cytosolic and plastidic localization. Geraniol production by VoGES and LdGES in N. benthamiana was nonetheless very similar. Expression of a truncated version of VoGES or LdGES (cytosolic targeting) resulted in the accumulation of 30% less geraniol glycosides than with the plastid targeted VoGES and LdGES, suggesting that the substrate geranyl diphosphate is readily available, both in the plastids as well as in the cytosol. The potential role of GES in the engineering of the TIA pathway in heterologous hosts is discussed.     

Experimental and modelling studies of drought‐adaptive root architectural traits in wheat (Triticum aestivum L.)

Abstract

This paper presents an interdisciplinary approach to crop improvement that links physiology with plant breeding and simulation modelling to enhance the selection of high‐yielding, drought‐tolerant varieties. In a series of field experiments in Queensland, Australia, we found that the yield of CIMMYT wheat line SeriM82 ranged from 6% to 28% greater than the current cultivar Hartog. Physiological studies on the adaptive traits revealed that SeriM82 had a narrower root architecture and extracted more soil moisture, particularly deep in the profile. Results of a simulation analysis of these adaptive root traits with the cropping system model APSIM for a range of rain‐fed environments in southern Queensland indicated a mean relative yield benefit of 14.5% in water‐deficit seasons. Furthermore, each additional millimetre of water extracted during grain filling generated an extra 55 kg ha^?1 of grain yield. Further root studies of a large number of wheat genotypes revealed that wheat root architecture is closely linked to the angle of seminal roots at the seedling stage – a trait which is suitable for large‐scale and cost‐effective screening programmes. Overall, our results suggest that an interdisciplinary approach to crop improvement is likely to enhance the rate of yield improvement in rain‐fed crops.