5,261 research outputs found
Metabolic Heat in Microbial Conflict and Cooperation
Many microbes live in habitats below their optimum temperature. Retention of
metabolic heat by aggregation or insulation would boost growth. Generation of
excess metabolic heat may also provide benefit. A cell that makes excess
metabolic heat pays the cost of production, whereas the benefit may be shared
by neighbors within a zone of local heat capture. Metabolic heat as a shareable
public good raises interesting questions about conflict and cooperation of heat
production and capture. Metabolic heat may also be deployed as a weapon.
Species with greater thermotolerance gain by raising local temperature to
outcompete less thermotolerant taxa. Metabolic heat may provide defense against
bacteriophage attack, by analogy with fever in vertebrates. This article
outlines the theory of metabolic heat in microbial conflict and cooperation,
presenting several predictions for future study
The generalized Price equation: Forces that change population statistics
The Price equation partitions the change in the expected value of a population measure. The first component describes the partial change caused by altered frequencies. The second component describes the partial change caused by altered measurements. In biology, frequency changes often associate with the direct effect of natural selection. Measure changes reflect processes during transmission that alter trait values. More broadly, the two components describe the direct forces that change population composition and the altered frame of reference that changes measured values. The classic Price equation is limited to population statistics that can be expressed as the expected value of a measure. Many statistics cannot be expressed as expected values, such as the harmonic mean and the family of rescaled diversity measures. We generalize the Price equation to any population statistic that can be expressed as a function of frequencies and measurements. We obtain the generalized partition between the direct forces that cause frequency change and the altered frame of reference that changes measurements
Maladaptation and the paradox of robustness in evolution
Background. Organisms use a variety of mechanisms to protect themselves
against perturbations. For example, repair mechanisms fix damage, feedback
loops keep homeostatic systems at their setpoints, and biochemical filters
distinguish signal from noise. Such buffering mechanisms are often discussed in
terms of robustness, which may be measured by reduced sensitivity of
performance to perturbations. Methodology/Principal Findings. I use a
mathematical model to analyze the evolutionary dynamics of robustness in order
to understand aspects of organismal design by natural selection. I focus on two
characters: one character performs an adaptive task; the other character
buffers the performance of the first character against perturbations. Increased
perturbations favor enhanced buffering and robustness, which in turn decreases
sensitivity and reduces the intensity of natural selection on the adaptive
character. Reduced selective pressure on the adaptive character often leads to
a less costly, lower performance trait. Conclusions/Significance. The paradox
of robustness arises from evolutionary dynamics: enhanced robustness causes an
evolutionary reduction in the adaptive performance of the target character,
leading to a degree of maladaptation compared to what could be achieved by
natural selection in the absence of robustness mechanisms. Over evolutionary
time, buffering traits may become layered on top of each other, while the
underlying adaptive traits become replaced by cheaper, lower performance
components. The paradox of robustness has widespread implications for
understanding organismal design
Kinetics of cancer: a method to test hypotheses of genetic causation
BACKGROUND: Mouse studies have recently compared the age-onset patterns of cancer between different genotypes. Genes associated with earlier onset are tentatively assigned a causal role in carcinogenesis. These standard analyses ignore the great amount of information about kinetics contained in age-onset curves. We present a method for analyzing kinetics that measures quantitatively the causal role of candidate genes in cancer progression. We use our method to demonstrate a clear association between somatic mutation rates of different DNA mismatch repair (MMR) genotypes and the kinetics of cancer progression. METHODS: Most experimental studies report age-onset curves as the fraction diagnosed with tumors at each age for each group. We use such data to estimate smoothed survival curves, then measure incidence rates at each age by the slope of the fitted curve divided by the fraction of mice that remain undiagnosed for tumors at that age. With the estimated incidence curves, we compare between different genotypes the median age of cancer onset and the acceleration of cancer, which is the rate of increase in incidence with age. RESULTS: The direction of change in somatic mutation rate between MMR genotypes predicts the direction of change in the acceleration of cancer onset in all 7 cases (p ˜ 0.008), with the same result for the association between mutation rate and the median age of onset. CONCLUSION: Many animal experiments compare qualitatively the onset curves for different genotypes. If such experiments were designed to analyze kinetics, the research could move to the next stage in which the mechanistic consequences of particular genetic pathways are related to the dynamics of carcinogenesis. The data we analyzed here were not collected to test mechanistic and quantitative hypotheses about kinetics. Even so, a simple reanalysis revealed significant insights about how DNA repair genotypes affect separately the age of onset and the acceleration of cancer. Our method of comparing genotypes provides good statistical tests even with small samples for each genotype
Variable sex ratio among colonies of ants
Small colonies of ants often produce mostly male alates, while large colonies produce mostly female alates. I present a simple model consistent with this pattern in which males that compete for mates are related (Local Mate Competition). The model explains the observed trend even when relatedness among competing males is low, so that there is only a negligible effect on the predicted sex allocation ratio in the population. The reverse trend is expected when there is competition among related females for a limited resource, such as nest sites (Local Resource Competition); small broods are predicted to be mostly female and large broods are predicted to be mostly male.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46877/1/265_2004_Article_BF00299733.pd
Cooperation and virulence in acute Pseudomonas aeruginosa infections
BACKGROUND: Efficient host exploitation by parasites is frequently likely to depend on cooperative behaviour. Under these conditions, mixed-strain infections are predicted to show lower virulence (host mortality) than are single-clone infections, due to competition favouring non-contributing social 'cheats' whose presence will reduce within-host growth. We tested this hypothesis using the cooperative production of iron-scavenging siderophores by the pathogenic bacterium Pseudomonas aeruginosa in an insect host. RESULTS: We found that infection by siderophore-producing bacteria (cooperators) results in more rapid host death than does infection by non-producers (cheats), and that mixtures of both result in intermediate levels of virulence. Within-host bacterial growth rates exhibited the same pattern. Crucially, cheats were more successful in mixed infections compared with single-clone infections, while the opposite was true of cooperators. CONCLUSION: These data demonstrate that mixed clone infections can favour the evolution of social cheats, and thus decrease virulence when parasite growth is dependent on cooperative behaviours
Competition between species can stabilize public-goods cooperation within a species
Competition between species is a major ecological force that can drive evolution. Here, we test the effect of this force on the evolution of cooperation within a species. We use sucrose metabolism of budding yeast, Saccharomyces cerevisiae, as a model cooperative system that is subject to social parasitism by cheater strategies. We find that when cocultured with a bacterial competitor, Escherichia coli, the frequency of cooperator phenotypes in yeast populations increases dramatically as compared with isolated yeast populations. Bacterial competition stabilizes cooperation within yeast by limiting the yeast population density and also by depleting the public goods produced by cooperating yeast cells. Both of these changes induced by bacterial competition increase the cooperator frequency because cooperator yeast cells have a small preferential access to the public goods they produce; this preferential access becomes more important when the public good is scarce. Our results indicate that a thorough understanding of species interactions is crucial for explaining the maintenance and evolution of cooperation in nature.United States. National Institutes of Health (GM085279‐02)National Science Foundation (U.S.) (PHY‐1055154)Alfred P. Sloan Foundation (BR2011‐066
WeedMap: A large-scale semantic weed mapping framework using aerial multispectral imaging and deep neural network for precision farming
We present a novel weed segmentation and mapping framework that processes
multispectral images obtained from an unmanned aerial vehicle (UAV) using a
deep neural network (DNN). Most studies on crop/weed semantic segmentation only
consider single images for processing and classification. Images taken by UAVs
often cover only a few hundred square meters with either color only or color
and near-infrared (NIR) channels. Computing a single large and accurate
vegetation map (e.g., crop/weed) using a DNN is non-trivial due to difficulties
arising from: (1) limited ground sample distances (GSDs) in high-altitude
datasets, (2) sacrificed resolution resulting from downsampling high-fidelity
images, and (3) multispectral image alignment. To address these issues, we
adopt a stand sliding window approach that operates on only small portions of
multispectral orthomosaic maps (tiles), which are channel-wise aligned and
calibrated radiometrically across the entire map. We define the tile size to be
the same as that of the DNN input to avoid resolution loss. Compared to our
baseline model (i.e., SegNet with 3 channel RGB inputs) yielding an area under
the curve (AUC) of [background=0.607, crop=0.681, weed=0.576], our proposed
model with 9 input channels achieves [0.839, 0.863, 0.782]. Additionally, we
provide an extensive analysis of 20 trained models, both qualitatively and
quantitatively, in order to evaluate the effects of varying input channels and
tunable network hyperparameters. Furthermore, we release a large sugar
beet/weed aerial dataset with expertly guided annotations for further research
in the fields of remote sensing, precision agriculture, and agricultural
robotics.Comment: 25 pages, 14 figures, MDPI Remote Sensin
Dynein structure and power stroke
Dynein ATPases are microtubule motors that are critical to diverse processes such as vesicle transport and the beating of sperm tails; however, their mechanism of force generation is unknown. Each dynein comprises a head, from which a stalk and a stem emerge. Here we use electron microscopy and image processing to reveal new structural details of dynein c, an isoform from Chlamydomonas reinhardtii flagella, at the start and end of its power stroke. Both stem and stalk are flexible, and the stem connects to the head by means of a linker approximately 10 nm long that we propose lies across the head. With both ADP and vanadate bound, the stem and stalk emerge from the head 10 nm apart. However, without nucleotide they emerge much closer together owing to a change in linker orientation, and the coiled-coil stalk becomes stiffer. The net result is a shortening of the molecule coupled to an approximately 15-nm displacement of the tip of the stalk. These changes indicate a mechanism for the dynein power stroke
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