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Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel patterns and the source of controversy in a general hypothesis. We apply a decision tree algorithm, assuming that evidence from various contexts can be adequately integrated in a hierarchically nested structure. As a case study, we analyzed 163 articles that studied a prominent hypothesis in invasion biology, the enemy release hypothesis. We explored if any of the nine attributes that classify each study can differentiate conclusions as classification problem. Results corroborated that machine learning can be useful for research synthesis, as the algorithm could detect patterns that had been already focused in previous narrative reviews. Compared with the previous synthesis study that assessed the same evidence collection based on experts' judgement, the algorithm has newly proposed that the studies focusing on Asian regions mostly supported the hypothesis, suggesting that more detailed investigations in these regions can enhance our understanding of the hypothesis. We suggest that machine learning algorithms can be a promising synthesis tool especially where studies (a) reformulate a general hypothesis from different perspectives, (b) use different methods or variables, or (c) report insufficient information for conducting meta-analyses.
Flight behaviour characteristics such as flight altitude and avoidance behaviour determine the species-specific collision risk of birds with wind turbines. However, traditional observational methods exhibit limited positional accuracy. High-resolution GPS telemetry represents a promising method to overcome this drawback. In this study, we used three-dimensional GPS tracking data including high-accuracy tracks recorded at 3-s intervals to investigate the collision risk of breeding male Montagu's Harriers Circus pygargus in the Dutch–German border region. Avoidance of wind turbines was quantified by a novel approach comparing observed flights to a null model of random flight behaviour. On average, Montagu's Harriers spent as much as 8.2 h per day in flight. Most flights were at low altitude, with only 7.1% within the average rotor height range (RHR; 45–125 m). Montagu's Harriers showed significant avoidance behaviour, approaching turbines less often than expected, particularly when flying within the RHR (avoidance rate of 93.5%). For the present state, with wind farms situated on the fringes of the regional nesting range, collision risk models based on our new insights on flight behaviour indicated 0.6–2.0 yearly collisions of adult males (as compared with a population size of c. 40 pairs). However, the erection of a new wind farm inside the core breeding area could markedly increase mortality (up to 9.7 yearly collisions). If repowering of the wind farms was carried out using low-reaching modern turbines (RHR 36–150 m), mortality would more than double, whereas it would stay approximately constant if higher turbines (RHR 86–200 m) were used. Our study demonstrates the great potential of high-resolution GPS tracking for collision risk assessments. The resulting information on collision-related flight behaviour allows for performing detailed scenario analyses on wind farm siting and turbine design, in contrast to current environmental assessment practices. With regard to Montagu's Harriers, we conclude that although the deployment of higher wind turbines represents an opportunity to reduce collision risk for this species, precluding wind energy developments in core breeding areas remains the most important mitigation measure.
Context Cities are a challenging habitat for obligate nocturnal mammals because of the ubiquitous use of artificial light at night (ALAN). How nocturnal animals move in an urban landscape, particularly in response to ALAN is largely unknown. Objectives We studied the movement responses, foraging and commuting, of common noctules (Nyctalus noctula) to urban landscape features in general and ALAN in particular. Methods We equipped 20 bats with miniaturized GPS loggers in the Berlin metropolitan area and related spatial positions of bats to anthropogenic and natural landscape features and levels of ALAN. Results Common noctules foraged close to ALAN only next to bodies of water or well vegetated areas, probably to exploit swarms of insects lured by street lights. In contrast, they avoided illuminated roads, irrespective of vegetation cover nearby. Predictive maps identified most of the metropolitan area as non-favoured by this species because of high levels of impervious surfaces and ALAN. Dark corridors were used by common noctules for commuting and thus likely improved the permeability of the city landscape. Conclusions We conclude that the spatial use of common noctules, previously considered to be more tolerant to light than other bats, is largely constrained by ALAN. Our study is the first individual-based GPS tracking study to show sensitive responses of nocturnal wildlife to light pollution. Approaches to protect urban biodiversity need to include ALAN to safeguard the larger network of dark habitats for bats and other nocturnal species in cities.
Wind influences the development, architecture and morphology of plant roots and may modify subsequent interactions between plants and soil (plant–soil feedbacks—PSFs). However, information on wind effects on fine root morphology is scarce and the extent to which wind changes plant–soil interactions remains unclear. Therefore, we investigated the effects of two wind intensity levels by manipulating surrounding vegetation height in a grassland PSF field experiment. We grew four common plant species (two grasses and two non-leguminous forbs) with soil biota either previously conditioned by these or other species and tested the effect of wind on root:shoot ratio, fine root morphological traits as well as the outcome for PSFs. Wind intensity did not affect biomass allocation (i.e. root:shoot ratio) in any species. However, fine-root morphology of all species changed under high wind intensity. High wind intensity increased specific root length and surface area and decreased root tissue density, especially in the two grasses. Similarly, the direction of PSFs changed under high wind intensity in all four species, but differences in biomass production on the different soils between high and low wind intensity were marginal and most pronounced when comparing grasses with forbs. Because soils did not differ in plant-available nor total nutrient content, the results suggest that wind-induced changes in root morphology have the potential to influence plant–soil interactions. Linking wind-induced changes in fine-root morphology to effects on PSF improves our understanding of plant–soil interactions under changing environmental conditions.
Engineering biotechnological microorganisms to use methanol as a feedstock for bioproduction is a major goal for the synthetic metabolism community. Here, we aim to redesign the natural serine cycle for implementation in E. coli. We propose the homoserine cycle, relying on two promiscuous formaldehyde aldolase reactions, as a superior pathway design. The homoserine cycle is expected to outperform the serine cycle and its variants with respect to biomass yield, thermodynamic favorability, and integration with host endogenous metabolism. Even as compared to the RuMP cycle, the most efficient naturally occurring methanol assimilation route, the homoserine cycle is expected to support higher yields of a wide array of products. We test the in vivo feasibility of the homoserine cycle by constructing several E. coli gene deletion strains whose growth is coupled to the activity of different pathway segments. Using this approach, we demonstrate that all required promiscuous enzymes are active enough to enable growth of the auxotrophic strains. Our findings thus identify a novel metabolic solution that opens the way to an optimized methylotrophic platform.
Formaldehyde is a highly reactive compound that participates in multiple spontaneous reactions, but these are mostly deleterious and damage cellular components. In contrast, the spontaneous condensation of formaldehyde with tetrahydrofolate (THF) has been proposed to contribute to the assimilation of this intermediate during growth on C1 carbon sources such as methanol. However, the in vivo rate of this condensation reaction is unknown and its possible contribution to growth remains elusive. Here, we used microbial platforms to assess the rate of this condensation in the cellular environment. We constructed Escherichia coli strains lacking the enzymes that naturally produce 5,10-methylene-THF. These strains were able to grow on minimal medium only when equipped with a sarcosine (N-methyl-glycine) oxidation pathway that sustained a high cellular concentration of formaldehyde, which spontaneously reacts with THF to produce 5,10-methylene-THF. We used flux balance analysis to derive the rate of the spontaneous condensation from the observed growth rate. According to this, we calculated that a microorganism obtaining its entire biomass via the spontaneous condensation of formaldehyde with THF would have a doubling time of more than three weeks. Hence, this spontaneous reaction is unlikely to serve as an effective route for formaldehyde assimilation.
Starch and Glycogen Analyses
(2020)
For complex carbohydrates, such as glycogen and starch, various analytical methods and techniques exist allowing the detailed characterization of these storage carbohydrates. In this article, we give a brief overview of the most frequently used methods, techniques, and results. Furthermore, we give insights in the isolation, purification, and fragmentation of both starch and glycogen. An overview of the different structural levels of the glucans is given and the corresponding analytical techniques are discussed. Moreover, future perspectives of the analytical needs and the challenges of the currently developing scientific questions are included
In recent years, increasing concerns have been raised about the environmental risk of microplastics in freshwater ecosystems. Small microplastics enter the water either directly or accumulate through disintegration of larger plastic particles. These particles might then be ingested by filter-feeding zooplankton, such as rotifers. Particles released into the water may also interact with the biota through the formation of aggregates, which might alter the uptake by zooplankton. In this study, we tested for size-specific aggregation of polystyrene microspheres and their ingestion by a common freshwater rotifer Brachionus calyciflorus. The ingestion of three sizes of polystyrene microspheres (MS) 1-, 3-, and 6-mu m was investigated. Each MS size was tested in combination with three different treatments: MS as the sole food intake, MS in association with food algae and MS aggregated with biogenic matter. After 72 h incubation in pre-filtered natural river water, the majority of the 1-mu m spheres occurred as aggregates. The larger the particles, the higher the relative number of single particles and the larger the aggregates. All particles were ingested by the rotifer following a Type-II functional response. The presence of algae did not influence the ingestion of the MS for all three sizes. The biogenic aggregation of microspheres led to a significant size-dependent alteration in their ingestion. Rotifers ingested more microspheres (MS) when exposed to aggregated 1- and 3-mu m MS as compared to single spheres, whereas fewer aggregated 6-mu m spheres were ingested. This indicates that the small particles when aggregated were in an effective size range for Brachionus, while the aggregated larger spheres became too large to be efficiently ingested. These observations provide the first evidence of a size- and aggregation-dependent feeding interaction between microplastics and rotifers. Microplastics when aggregated with biogenic particles in a natural environment can rapidly change their size-dependent availability. The aggregation properties of microplastics should be taken into account when performing experiments mimicking the natural environment.
Although the use of stable transformation technology has led to great insight into gene function, its application in high-throughput studies remains arduous. Agro-infiltration have been widely used in species such as Nicotiana benthamiana for the rapid detection of gene expression and protein interaction analysis, but this technique does not work efficiently in other plant species, including Arabidopsis thaliana. As an efficient high-throughput transient expression system is currently lacking in the model plant species A. thaliana, we developed a method that is characterized by high efficiency, reproducibility, and suitability for transient expression of a variety of functional proteins in A. thaliana and 7 other plant species, including Brassica oleracea, Capsella rubella, Thellungiella salsuginea, Thellungiella halophila, Solanum tuberosum, Capsicum annuum, and N. benthamiana. Efficiency of this method was independently verified in three independent research facilities, pointing to the robustness of this technique. Furthermore, in addition to demonstrating the utility of this technique in a range of species, we also present a case study employing this method to assess protein-protein interactions in the sucrose biosynthesis pathway in Arabidopsis.
A shelter for the future
(2020)
Plant development in its majority occurs post-embryonically
through the activity of local meristems that provide daughter cells
for the development of new organs. It has long been acknowledged
that the shoot apical meristem (SAM), which holds the stem cells
that will form above-ground organs, is recalcitrant to infection by
multiple pathogens, a crucial strategy to safeguard normal devel-
opment and subsequent generations. However, the molecular
mechanisms underlying SAM immunity remain largely unknown.