433 research outputs found
Coexistence via Resource Partitioning Fails to Generate an Increase in Community Function
Classic ecological theory suggests that resource partitioning facilitates the coexistence of species by reducing inter-specific competition. A byproduct of this process is an increase in overall community function, because a greater spectrum of resources can be used. In contrast, coexistence facilitated by neutral mechanisms is not expected to increase function. We studied coexistence in laboratory microcosms of the bactivorous ciliates Paramecium aurelia and Colpidium striatum to understand the relationship between function and coexistence mechanism. We quantified population and community-level function (biomass and oxygen consumption), competitive interactions, and resource partitioning. The two ciliates partitioned their bacterial resource along a size axis, with the larger ciliate consuming larger bacteria than the smaller ciliate. Despite this, there was no gain in function at the community level for either biomass or oxygen consumption, and competitive effects were symmetrical within and between species. Because other potential coexistence mechanisms can be ruled out, it is likely that inter-specific interference competition diminished the expected gain in function generated by resource partitioning, leading to a system that appeared competitively neutral even when structured by niche partitioning. We also analyzed several previous studies where two species of protists coexisted and found that the two-species communities showed a broad range of biomass levels relative to the single-species states
Industrial energy use and the human life history
The demographic rates of most organisms are supported by the consumption of food energy, which is used to produce new biomass and fuel physiological processes. Unlike other species, modern humans use ‘extra-metabolic' energy sources acquired independent of physiology, which also influence demographics. We ask whether the amount of extra-metabolic energy added to the energy budget affects demographic and life history traits in a predictable way. Currently it is not known how human demographics respond to energy use, and we characterize this response using an allometric approach. All of the human life history traits we examine are significant functions of per capita energy use across industrialized populations. We find a continuum of traits from those that respond strongly to the amount of extra-metabolic energy used, to those that respond with shallow slopes. We also show that the differences in plasticity across traits can drive the net reproductive rate to below-replacement levels
Analysis of a viral metagenomic library from 200 m depth in Monterey Bay, California constructed by direct shotgun cloning
<p>Abstract</p> <p>Background</p> <p>Viruses have a profound influence on both the ecology and evolution of marine plankton, but the genetic diversity of viral assemblages, particularly those in deeper ocean waters, remains poorly described. Here we report on the construction and analysis of a viral metagenome prepared from below the euphotic zone in a temperate, eutrophic bay of coastal California.</p> <p>Methods</p> <p>We purified viruses from approximately one cubic meter of seawater collected from 200m depth in Monterey Bay, CA. DNA was extracted from the virus fraction, sheared, and cloned with no prior amplification into a plasmid vector and propagated in <it>E. coli </it>to produce the MBv200m library. Random clones were sequenced by the Sanger method. Sequences were assembled then compared to sequences in GenBank and to other viral metagenomic libraries using BLAST analyses.</p> <p>Results</p> <p>Only 26% of the 881 sequences remaining after assembly had significant (E ≤ 0.001) BLAST hits to sequences in the GenBank nr database, with most being matches to bacteria (15%) and viruses (8%). When BLAST analysis included environmental sequences, 74% of sequences in the MBv200m library had a significant match. Most of these hits (70%) were to microbial metagenome sequences and only 0.7% were to sequences from viral metagenomes. Of the 121 sequences with a significant hit to a known virus, 94% matched bacteriophages (Families <it>Podo</it>-, <it>Sipho</it>-, and <it>Myoviridae</it>) and 6% matched viruses of eukaryotes in the Family <it>Phycodnaviridae </it>(5 sequences) or the Mimivirus (2 sequences). The largest percentages of hits to viral genes of known function were to those involved in DNA modification (25%) or structural genes (17%). Based on reciprocal BLAST analyses, the MBv200m library appeared to be most similar to viral metagenomes from two other bays and least similar to a viral metagenome from the Arctic Ocean.</p> <p>Conclusions</p> <p>Direct cloning of DNA from diverse marine viruses was feasible and resulted in a distribution of virus types and functional genes at depth that differed in detail, but were broadly similar to those found in surface marine waters. Targeted viral analyses are useful for identifying those components of the greater marine metagenome that circulate in the subcellular size fraction.</p
A panel of kallikrein markers can predict outcome of prostate biopsy following clinical work-up: an independent validation study from the European Randomized Study of Prostate Cancer screening, France
<p>Abstract</p> <p>Background</p> <p>We have previously shown that a panel of kallikrein markers - total prostate-specific antigen (PSA), free PSA, intact PSA and human kallikrein-related peptidase 2 (hK2) - can predict the outcome of prostate biopsy in men with elevated PSA. Here we investigate the properties of our panel in men subject to clinical work-up before biopsy.</p> <p>Methods</p> <p>We applied a previously published predictive model based on the kallikrein panel to 262 men undergoing prostate biopsy following an elevated PSA (≥ 3 ng/ml) and further clinical work-up during the European Randomized Study of Prostate Cancer screening, France. The predictive accuracy of the model was compared to a "base" model of PSA, age and digital rectal exam (DRE).</p> <p>Results</p> <p>83 (32%) men had prostate cancer on biopsy of whom 45 (54%) had high grade disease (Gleason score 7 or higher). Our model had significantly higher accuracy than the base model in predicting cancer (area-under-the-curve [AUC] improved from 0.63 to 0.78) or high-grade cancer (AUC increased from 0.77 to 0.87). Using a decision rule to biopsy those with a 20% or higher risk of cancer from the model would reduce the number of biopsies by nearly half. For every 1000 men with elevated PSA and clinical indication for biopsy, the model would recommend against biopsy in 61 men with cancer, the majority (≈80%) of whom would have low stage <it>and </it>low grade disease at diagnosis.</p> <p>Conclusions</p> <p>In this independent validation study, the model was highly predictive of prostate cancer in men for whom the decision to biopsy is based on both elevated PSA and clinical work-up. Use of this model would reduce a large number of biopsies while missing few cancers.</p
Design effect in multicenter studies: gain or loss of power?
<p>Abstract</p> <p>Background</p> <p>In a multicenter trial, responses for subjects belonging to a common center are correlated. Such a clustering is usually assessed through the design effect, defined as a ratio of two variances. The aim of this work was to describe and understand situations where the design effect involves a gain or a loss of power.</p> <p>Methods</p> <p>We developed a design effect formula for a multicenter study aimed at testing the effect of a binary factor (which thus defines two groups) on a continuous outcome, and explored this design effect for several designs (from individually stratified randomized trials to cluster randomized trials, and for other designs such as matched pair designs or observational multicenter studies).</p> <p>Results</p> <p>The design effect depends on the intraclass correlation coefficient (ICC) (which assesses the correlation between data for two subjects from the same center) but also on a statistic <it>S</it>, which quantifies the heterogeneity of the group distributions among centers (thus the level of association between the binary factor and the center) and on the degree of global imbalance (the number of subjects are then different) between the two groups. This design effect may induce either a loss or a gain in power, depending on whether the <it>S </it>statistic is respectively higher or lower than 1.</p> <p>Conclusion</p> <p>We provided a global design effect formula applying for any multicenter study and allowing identifying factors – the ICC and the distribution of the group proportions among centers – that are associated with a gain or a loss of power in such studies.</p
A cortical motor nucleus drives the basal ganglia-recipient thalamus in singing birds
The pallido-recipient thalamus transmits information from the basal ganglia to the cortex and is critical for motor initiation and learning. Thalamic activity is strongly inhibited by pallidal inputs from the basal ganglia, but the role of nonpallidal inputs, such as excitatory inputs from cortex, remains unclear. We simultaneously recorded from presynaptic pallidal axon terminals and postsynaptic thalamocortical neurons in a basal ganglia–recipient thalamic nucleus that is necessary for vocal variability and learning in zebra finches. We found that song-locked rate modulations in the thalamus could not be explained by pallidal inputs alone and persisted following pallidal lesion. Instead, thalamic activity was likely driven by inputs from a motor cortical nucleus that is also necessary for singing. These findings suggest a role for cortical inputs to the pallido-recipient thalamus in driving premotor signals that are important for exploratory behavior and learning.National Institutes of Health (U.S.) (Grant R01DC009183)National Institutes of Health (U.S.) (Grant K99NS067062)Damon Runyon Cancer Research Foundation (Postdoctoral Fellowship)Charles A. King Trust (Postdoctoral Fellowship
Numerical magnitude affects temporal memories but not time encoding
Previous research has suggested that the perception of time is influenced by concurrent magnitude information (e.g., numerical magnitude in digits, spatial distance), but the locus of the effect is unclear, with some findings suggesting that concurrent magnitudes such as space affect temporal memories and others suggesting that numerical magnitudes in digits affect the clock speed during time encoding. The current paper reports 6 experiments in which participants perceived a stimulus duration and then reproduced it. We showed that though a digit of a large magnitude (e.g., 9), relative to a digit of a small magnitude (e.g., 2), led to a longer reproduced duration when the digits were presented during the perception of the stimulus duration, such a magnitude effect disappeared when the digits were presented during the reproduction of the stimulus duration. These findings disconfirm the account that large numerical magnitudes accelerate the speed of an internal clock during time encoding, as such an account incorrectly predicts that a large numerical magnitude should lead to a shorter reproduced duration when presented during reproduction. Instead, the findings suggest that numerical magnitudes, like other magnitudes such as space, affect temporal memories when numerical magnitudes and temporal durations are concurrently held in memory. Under this account, concurrent numerical magnitudes have the chance to influence the memory of the perceived duration when they are presented during perception but not when they are presented at the reproduction stage
Experimental Incubations Elicit Profound Changes in Community Transcription in OMZ Bacterioplankton
Sequencing of microbial community RNA (metatranscriptome) is a useful approach for assessing gene expression in microorganisms from the natural environment. This method has revealed transcriptional patterns in situ, but can also be used to detect transcriptional cascades in microcosms following experimental perturbation. Unambiguously identifying differential transcription between control and experimental treatments requires constraining effects that are simply due to sampling and bottle enclosure. These effects remain largely uncharacterized for “challenging” microbial samples, such as those from anoxic regions that require special handling to maintain in situ conditions. Here, we demonstrate substantial changes in microbial transcription induced by sample collection and incubation in experimental bioreactors. Microbial communities were sampled from the water column of a marine oxygen minimum zone by a pump system that introduced minimal oxygen contamination and subsequently incubated in bioreactors under near in situ oxygen and temperature conditions. Relative to the source water, experimental samples became dominated by transcripts suggestive of cell stress, including chaperone, protease, and RNA degradation genes from diverse taxa, with strong representation from SAR11-like alphaproteobacteria. In tandem, transcripts matching facultative anaerobic gammaproteobacteria of the Alteromonadales (e.g., Colwellia) increased 4–13 fold up to 43% of coding transcripts, and encoded a diverse gene set suggestive of protein synthesis and cell growth. We interpret these patterns as taxon-specific responses to combined environmental changes in the bioreactors, including shifts in substrate or oxygen availability, and minor temperature and pressure changes during sampling with the pump system. Whether such changes confound analysis of transcriptional patterns may vary based on the design of the experiment, the taxonomic composition of the source community, and on the metabolic linkages between community members. These data highlight the impressive capacity for transcriptional changes within complex microbial communities, underscoring the need for caution when inferring in situ metabolism based on transcript abundances in experimental incubations
Protein Phosphatase 2A Controls Ethylene Biosynthesis by Differentially Regulating the Turnover of ACC Synthase Isoforms
The gaseous hormone ethylene is one of the master regulators of development and physiology throughout the plant life cycle. Ethylene biosynthesis is stringently regulated to permit maintenance of low levels during most phases of vegetative growth but to allow for rapid peaks of high production at developmental transitions and under stress conditions. In most tissues ethylene is a negative regulator of cell expansion, thus low basal levels of ethylene biosynthesis in dark-grown seedlings are critical for optimal cell expansion during early seedling development. The committed steps in ethylene biosynthesis are performed by the enzymes 1-aminocyclopropane 1-carboxylate synthase (ACS) and 1-aminocyclopropane 1-carboxylate oxidase (ACO). The abundance of different ACS enzymes is tightly regulated both by transcriptional control and by post-translational modifications and proteasome-mediated degradation. Here we show that specific ACS isozymes are targets for regulation by protein phosphatase 2A (PP2A) during Arabidopsis thaliana seedling growth and that reduced PP2A function causes increased ACS activity in the roots curl in 1-N-naphthylphthalamic acid 1 (rcn1) mutant. Genetic analysis reveals that ethylene overproduction in PP2A-deficient plants requires ACS2 and ACS6, genes that encode ACS proteins known to be stabilized by phosphorylation, and proteolytic turnover of the ACS6 protein is retarded when PP2A activity is reduced. We find that PP2A and ACS6 proteins associate in seedlings and that RCN1-containing PP2A complexes specifically dephosphorylate a C-terminal ACS6 phosphopeptide. These results suggest that PP2A-dependent destabilization requires RCN1-dependent dephosphorylation of the ACS6 C-terminus. Surprisingly, rcn1 plants exhibit decreased accumulation of the ACS5 protein, suggesting that a regulatory phosphorylation event leads to ACS5 destabilization. Our data provide new insight into the circuitry that ensures dynamic control of ethylene synthesis during plant development, showing that PP2A mediates a finely tuned regulation of overall ethylene production by differentially affecting the stability of specific classes of ACS enzymes
Evolutionary tradeoffs in cellular composition across diverse bacteria
One of the most important classic and contemporary interests in biology is the connection between cellular composition and physiological function. Decades of research have allowed us to understand the detailed relationship between various cellular components and processes for individual species, and have uncovered common functionality across diverse species. However, there still remains the need for frameworks that can mechanistically predict the tradeoffs between cellular functions and elucidate and interpret average trends across species. Here we provide a comprehensive analysis of how cellular composition changes across the diversity of bacteria as connected with physiological function and metabolism, spanning five orders of magnitude in body size. We present an analysis of the trends with cell volume that covers shifts in genomic, protein, cellular envelope, RNA and ribosomal content. We show that trends in protein content are more complex than a simple proportionality with the overall genome size, and that the number of ribosomes is simply explained by cross-species shifts in biosynthesis requirements. Furthermore, we show that the largest and smallest bacteria are limited by physical space requirements. At the lower end of size, cell volume is dominated by DNA and protein content—the requirement for which predicts a lower limit on cell size that is in good agreement with the smallest observed bacteria. At the upper end of bacterial size, we have identified a point at which the number of ribosomes required for biosynthesis exceeds available cell volume. Between these limits we are able to discuss systematic and dramatic shifts in cellular composition. Much of our analysis is connected with the basic energetics of cells where we show that the scaling of metabolic rate is surprisingly superlinear with all cellular components
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